Sample records for robust synthetic gene
-
Chen, Bor-Sen; Lin, Ying-Po
2013-01-01
Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental
-
Robust synthetic biology design: stochastic game theory approach.
Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching
2009-07-15
Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.
-
A systematic design method for robust synthetic biology to satisfy design specifications.
Chen, Bor-Sen; Wu, Chih-Hung
2009-06-30
Synthetic biology is foreseen to have important applications in biotechnology and medicine, and is expected to contribute significantly to a better understanding of the functioning of complex biological systems. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to intrinsic parameter uncertainties, external disturbances and functional variations of intra- and extra-cellular environments. The design method for a robust synthetic gene network that works properly in a host cell under these intrinsic parameter uncertainties and external disturbances is the most important topic in synthetic biology. In this study, we propose a stochastic model that includes parameter fluctuations and external disturbances to mimic the dynamic behaviors of a synthetic gene network in the host cell. Then, based on this stochastic model, four design specifications are introduced to guarantee that a synthetic gene network can achieve its desired steady state behavior in spite of parameter fluctuations, external disturbances and functional variations in the host cell. We propose a systematic method to select a set of appropriate design parameters for a synthetic gene network that will satisfy these design specifications so that the intrinsic parameter fluctuations can be tolerated, the external disturbances can be efficiently filtered, and most importantly, the desired steady states can be achieved. Thus the synthetic gene network can work properly in a host cell under intrinsic parameter uncertainties, external disturbances and functional variations. Finally, a design procedure for the robust synthetic gene network is developed and a design example is given in silico to confirm the performance of the proposed method. Based on four design specifications, a systematic design procedure is developed for designers to engineer a robust synthetic biology network that can achieve its desired steady state behavior
-
On the Interplay between Entropy and Robustness of Gene Regulatory Networks
Directory of Open Access Journals (Sweden)
Bor-Sen Chen
2010-05-01
Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.
-
Queueing-Based Synchronization and Entrainment for Synthetic Gene Oscillators
Mather, William; Butzin, Nicholas; Hochendoner, Philip; Ogle, Curtis
Synthetic gene oscillators have been a major focus of synthetic biology research since the beginning of the field 15 years ago. They have proven to be useful both for biotechnological applications as well as a testing ground to significantly develop our understanding of the design principles behind synthetic and native gene oscillators. In particular, the principles governing synchronization and entrainment of biological oscillators have been explored using a synthetic biology approach. Our work combines experimental and theoretical approaches to specifically investigate how a bottleneck for protein degradation, which is present in most if not all existing synthetic oscillators, can be leveraged to robustly synchronize and entrain biological oscillators. We use both the terminology and mathematical tools of queueing theory to intuitively explain the role of this bottleneck in both synchronization and entrainment, which extends prior work demonstrating the usefulness of queueing theory in synthetic and native gene circuits. We conclude with an investigation of how synchronization and entrainment may be sensitive to the presence of multiple proteolytic pathways in a cell that couple weakly through crosstalk. This work was supported by NSF Grant #1330180.
-
Directory of Open Access Journals (Sweden)
Miles Miller
Full Text Available Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for 'synthetic cellular heterogeneity' that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism, demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a 'phenotypic sensitivity analysis' method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in
-
Miller, Miles; Hafner, Marc; Sontag, Eduardo; Davidsohn, Noah; Subramanian, Sairam; Purnick, Priscilla E M; Lauffenburger, Douglas; Weiss, Ron
2012-01-01
Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation) are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for 'synthetic cellular heterogeneity' that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism), demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a 'phenotypic sensitivity analysis' method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in isolation, and
-
Accurate, model-based tuning of synthetic gene expression using introns in S. cerevisiae.
Directory of Open Access Journals (Sweden)
Ido Yofe
2014-06-01
Full Text Available Introns are key regulators of eukaryotic gene expression and present a potentially powerful tool for the design of synthetic eukaryotic gene expression systems. However, intronic control over gene expression is governed by a multitude of complex, incompletely understood, regulatory mechanisms. Despite this lack of detailed mechanistic understanding, here we show how a relatively simple model enables accurate and predictable tuning of synthetic gene expression system in yeast using several predictive intron features such as transcript folding and sequence motifs. Using only natural Saccharomyces cerevisiae introns as regulators, we demonstrate fine and accurate control over gene expression spanning a 100 fold expression range. These results broaden the engineering toolbox of synthetic gene expression systems and provide a framework in which precise and robust tuning of gene expression is accomplished.
-
Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.
Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S
2016-01-01
Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for
-
Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.
Directory of Open Access Journals (Sweden)
Arno Steinacher
Full Text Available Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest
-
Chen, Bor-Sen; Hsu, Chih-Yuan
2012-10-26
Collective rhythms of gene regulatory networks have been a subject of considerable interest for biologists and theoreticians, in particular the synchronization of dynamic cells mediated by intercellular communication. Synchronization of a population of synthetic genetic oscillators is an important design in practical applications, because such a population distributed over different host cells needs to exploit molecular phenomena simultaneously in order to emerge a biological phenomenon. However, this synchronization may be corrupted by intrinsic kinetic parameter fluctuations and extrinsic environmental molecular noise. Therefore, robust synchronization is an important design topic in nonlinear stochastic coupled synthetic genetic oscillators with intrinsic kinetic parameter fluctuations and extrinsic molecular noise. Initially, the condition for robust synchronization of synthetic genetic oscillators was derived based on Hamilton Jacobi inequality (HJI). We found that if the synchronization robustness can confer enough intrinsic robustness to tolerate intrinsic parameter fluctuation and extrinsic robustness to filter the environmental noise, then robust synchronization of coupled synthetic genetic oscillators is guaranteed. If the synchronization robustness of a population of nonlinear stochastic coupled synthetic genetic oscillators distributed over different host cells could not be maintained, then robust synchronization could be enhanced by external control input through quorum sensing molecules. In order to simplify the analysis and design of robust synchronization of nonlinear stochastic synthetic genetic oscillators, the fuzzy interpolation method was employed to interpolate several local linear stochastic coupled systems to approximate the nonlinear stochastic coupled system so that the HJI-based synchronization design problem could be replaced by a simple linear matrix inequality (LMI)-based design problem, which could be solved with the help of LMI
-
Automatic Design of Synthetic Gene Circuits through Mixed Integer Non-linear Programming
Huynh, Linh; Kececioglu, John; Köppe, Matthias; Tagkopoulos, Ilias
2012-01-01
Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits. PMID:22536398
-
Paper-based synthetic gene networks.
Pardee, Keith; Green, Alexander A; Ferrante, Tom; Cameron, D Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J
2014-11-06
Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides an alternate, versatile venue for synthetic biologists to operate and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze dried onto paper, enabling the inexpensive, sterile, and abiotic distribution of synthetic-biology-based technologies for the clinic, global health, industry, research, and education. For field use, we create circuits with colorimetric outputs for detection by eye and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small-molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors.
-
Paper-based Synthetic Gene Networks
Pardee, Keith; Green, Alexander A.; Ferrante, Tom; Cameron, D. Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J.
2014-01-01
Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides a new venue for synthetic biologists to operate, and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze-dried onto paper, enabling the inexpensive, sterile and abiotic distribution of synthetic biology-based technologies for the clinic, global health, industry, research and education. For field use, we create circuits with colorimetric outputs for detection by eye, and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors. PMID:25417167
-
Precision control of recombinant gene transcription for CHO cell synthetic biology.
Brown, Adam J; James, David C
2016-01-01
The next generation of mammalian cell factories for biopharmaceutical production will be genetically engineered to possess both generic and product-specific manufacturing capabilities that may not exist naturally. Introduction of entirely new combinations of synthetic functions (e.g. novel metabolic or stress-response pathways), and retro-engineering of existing functional cell modules will drive disruptive change in cellular manufacturing performance. However, before we can apply the core concepts underpinning synthetic biology (design, build, test) to CHO cell engineering we must first develop practical and robust enabling technologies. Fundamentally, we will require the ability to precisely control the relative stoichiometry of numerous functional components we simultaneously introduce into the host cell factory. In this review we discuss how this can be achieved by design of engineered promoters that enable concerted control of recombinant gene transcription. We describe the specific mechanisms of transcriptional regulation that affect promoter function during bioproduction processes, and detail the highly-specific promoter design criteria that are required in the context of CHO cell engineering. The relative applicability of diverse promoter development strategies are discussed, including re-engineering of natural sequences, design of synthetic transcription factor-based systems, and construction of synthetic promoters. This review highlights the potential of promoter engineering to achieve precision transcriptional control for CHO cell synthetic biology. Copyright © 2015. Published by Elsevier Inc.
-
Robust gene selection methods using weighting schemes for microarray data analysis.
Kang, Suyeon; Song, Jongwoo
2017-09-02
A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.
-
[Smart therapeutics based on synthetic gene circuits].
Peng, Shuguang; Xie, Zhen
2017-03-25
Synthetic biology has an important impact on biology research since its birth. Applying the thought and methods that reference from electrical engineering, synthetic biology uncovers many regulatory mechanisms of life systems, transforms and expands a series of biological components. Therefore, it brings a wide range of biomedical applications, including providing new ideas for disease diagnosis and treatment. This review describes the latest advances in the field of disease diagnosis and therapy based on mammalian cell or bacterial synthetic gene circuits, and provides new ideas for future smart therapy design.
-
Annotating novel genes by integrating synthetic lethals and genomic information
Directory of Open Access Journals (Sweden)
Faty Mahamadou
2008-01-01
Full Text Available Abstract Background Large scale screening for synthetic lethality serves as a common tool in yeast genetics to systematically search for genes that play a role in specific biological processes. Often the amounts of data resulting from a single large scale screen far exceed the capacities of experimental characterization of every identified target. Thus, there is need for computational tools that select promising candidate genes in order to reduce the number of follow-up experiments to a manageable size. Results We analyze synthetic lethality data for arp1 and jnm1, two spindle migration genes, in order to identify novel members in this process. To this end, we use an unsupervised statistical method that integrates additional information from biological data sources, such as gene expression, phenotypic profiling, RNA degradation and sequence similarity. Different from existing methods that require large amounts of synthetic lethal data, our method merely relies on synthetic lethality information from two single screens. Using a Multivariate Gaussian Mixture Model, we determine the best subset of features that assign the target genes to two groups. The approach identifies a small group of genes as candidates involved in spindle migration. Experimental testing confirms the majority of our candidates and we present she1 (YBL031W as a novel gene involved in spindle migration. We applied the statistical methodology also to TOR2 signaling as another example. Conclusion We demonstrate the general use of Multivariate Gaussian Mixture Modeling for selecting candidate genes for experimental characterization from synthetic lethality data sets. For the given example, integration of different data sources contributes to the identification of genetic interaction partners of arp1 and jnm1 that play a role in the same biological process.
-
Synchronous long-term oscillations in a synthetic gene circuit.
Potvin-Trottier, Laurent; Lord, Nathan D; Vinnicombe, Glenn; Paulsson, Johan
2016-10-27
Synthetically engineered genetic circuits can perform a wide variety of tasks but are generally less accurate than natural systems. Here we revisit the first synthetic genetic oscillator, the repressilator, and modify it using principles from stochastic chemistry in single cells. Specifically, we sought to reduce error propagation and information losses, not by adding control loops, but by simply removing existing features. We show that this modification created highly regular and robust oscillations. Furthermore, some streamlined circuits kept 14 generation periods over a range of growth conditions and kept phase for hundreds of generations in single cells, allowing cells in flasks and colonies to oscillate synchronously without any coupling between them. Our results suggest that even the simplest synthetic genetic networks can achieve a precision that rivals natural systems, and emphasize the importance of noise analyses for circuit design in synthetic biology.
-
Mutational robustness of gene regulatory networks.
Directory of Open Access Journals (Sweden)
Aalt D J van Dijk
Full Text Available Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor-target gene interactions but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive. In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence.
-
Robust Nonlinear Regulation of Limit Cycle Oscillations in UAVs Using Synthetic Jet Actuators
Directory of Open Access Journals (Sweden)
Natalie Ramos Pedroza
2014-09-01
Full Text Available In this paper, a synthetic jet actuators (SJA-based nonlinear robust controller is developed, which is capable of completely suppressing limit cycle oscillations (LCO in UAV systems with parametric uncertainty in the SJA dynamics and unmodeled external disturbances. Specifically, the control law compensates for uncertainty in an input gain matrix, which results from the unknown airflow dynamics generated by the SJA. Challenges in the control design include compensation for input-multiplicative parametric uncertainty in the actuator dynamic model. The result was achieved via innovative algebraic manipulation in the error system development, along with a Lyapunov-based robust control law. A rigorous Lyapunov-based stability analysis is utilized to prove asymptotic LCO suppression, considering a detailed dynamic model of the pitching and plunging dynamics. Numerical simulation results are provided to demonstrate the robustness and practical performance of the proposed control law.
-
Synthetic sustained gene delivery systems.
Agarwal, Ankit; Mallapragada, Surya K
2008-01-01
Gene therapy today is hampered by the need of a safe and efficient gene delivery system that can provide a sustained therapeutic effect without cytotoxicity or unwanted immune responses. Bolus gene delivery in solution results in the loss of delivered factors via lymphatic system and may cause undesired effects by the escape of bioactive molecules to distant sites. Controlled gene delivery systems, acting as localized depot of genes, provide an extended sustained release of genes, giving prolonged maintenance of the therapeutic level of encoded proteins. They also limit the DNA degradation in the nuclease rich extra-cellular environment. While attempts have been made to adapt existing controlled drug delivery technologies, more novel approaches are being investigated for controlled gene delivery. DNA encapsulated in nano/micro spheres of polymers have been administered systemically/orally to be taken up by the targeted tissues and provide sustained release once internalized. Alternatively, DNA entrapped in hydrogels or scaffolds have been injected/implanted in tissues/cavities as platforms for gene delivery. The present review examines these different modalities for sustained delivery of viral and non-viral gene-delivery vectors. Design parameters and release mechanisms of different systems made with synthetic or natural polymers are presented along with their prospective applications and opportunities for continuous development.
-
Reverse engineering validation using a benchmark synthetic gene circuit in human cells.
Kang, Taek; White, Jacob T; Xie, Zhen; Benenson, Yaakov; Sontag, Eduardo; Bleris, Leonidas
2013-05-17
Multicomponent biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network.
-
Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks.
Yeung, Enoch; Dy, Aaron J; Martin, Kyle B; Ng, Andrew H; Del Vecchio, Domitilla; Beck, James L; Collins, James J; Murray, Richard M
2017-07-26
Synthetic gene expression is highly sensitive to intragenic compositional context (promoter structure, spacing regions between promoter and coding sequences, and ribosome binding sites). However, much less is known about the effects of intergenic compositional context (spatial arrangement and orientation of entire genes on DNA) on expression levels in synthetic gene networks. We compare expression of induced genes arranged in convergent, divergent, or tandem orientations. Induction of convergent genes yielded up to 400% higher expression, greater ultrasensitivity, and dynamic range than divergent- or tandem-oriented genes. Orientation affects gene expression whether one or both genes are induced. We postulate that transcriptional interference in divergent and tandem genes, mediated by supercoiling, can explain differences in expression and validate this hypothesis through modeling and in vitro supercoiling relaxation experiments. Treatment with gyrase abrogated intergenic context effects, bringing expression levels within 30% of each other. We rebuilt the toggle switch with convergent genes, taking advantage of supercoiling effects to improve threshold detection and switch stability. Copyright © 2017 Elsevier Inc. All rights reserved.
-
Modeling stochasticity and robustness in gene regulatory networks.
Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis
2009-06-15
Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.
-
Directory of Open Access Journals (Sweden)
Walchli John
2009-04-01
Full Text Available Abstract Background With the goal of improving yield and success rates of heterologous protein production for structural studies we have developed the database and algorithm software package Gene Composer. This freely available electronic tool facilitates the information-rich design of protein constructs and their engineered synthetic gene sequences, as detailed in the accompanying manuscript. Results In this report, we compare heterologous protein expression levels from native sequences to that of codon engineered synthetic gene constructs designed by Gene Composer. A test set of proteins including a human kinase (P38α, viral polymerase (HCV NS5B, and bacterial structural protein (FtsZ were expressed in both E. coli and a cell-free wheat germ translation system. We also compare the protein expression levels in E. coli for a set of 11 different proteins with greatly varied G:C content and codon bias. Conclusion The results consistently demonstrate that protein yields from codon engineered Gene Composer designs are as good as or better than those achieved from the synonymous native genes. Moreover, structure guided N- and C-terminal deletion constructs designed with the aid of Gene Composer can lead to greater success in gene to structure work as exemplified by the X-ray crystallographic structure determination of FtsZ from Bacillus subtilis. These results validate the Gene Composer algorithms, and suggest that using a combination of synthetic gene and protein construct engineering tools can improve the economics of gene to structure research.
-
Effect of Duplicate Genes on Mouse Genetic Robustness: An Update
Directory of Open Access Journals (Sweden)
Zhixi Su
2014-01-01
Full Text Available In contrast to S. cerevisiae and C. elegans, analyses based on the current knockout (KO mouse phenotypes led to the conclusion that duplicate genes had almost no role in mouse genetic robustness. It has been suggested that the bias of mouse KO database toward ancient duplicates may possibly cause this knockout duplicate puzzle, that is, a very similar proportion of essential genes (PE between duplicate genes and singletons. In this paper, we conducted an extensive and careful analysis for the mouse KO phenotype data and corroborated a strong effect of duplicate genes on mouse genetics robustness. Moreover, the effect of duplicate genes on mouse genetic robustness is duplication-age dependent, which holds after ruling out the potential confounding effect from coding-sequence conservation, protein-protein connectivity, functional bias, or the bias of duplicates generated by whole genome duplication (WGD. Our findings suggest that two factors, the sampling bias toward ancient duplicates and very ancient duplicates with a proportion of essential genes higher than that of singletons, have caused the mouse knockout duplicate puzzle; meanwhile, the effect of genetic buffering may be correlated with sequence conservation as well as protein-protein interactivity.
-
Robust multi-tissue gene panel for cancer detection
Directory of Open Access Journals (Sweden)
Talantov Dmitri
2010-06-01
Full Text Available Abstract Background We have identified a set of genes whose relative mRNA expression levels in various solid tumors can be used to robustly distinguish cancer from matching normal tissue. Our current feature set consists of 113 gene probes for 104 unique genes, originally identified as differentially expressed in solid primary tumors in microarray data on Affymetrix HG-U133A platform in five tissue types: breast, colon, lung, prostate and ovary. For each dataset, we first identified a set of genes significantly differentially expressed in tumor vs. normal tissue at p-value = 0.05 using an experimentally derived error model. Our common cancer gene panel is the intersection of these sets of significantly dysregulated genes and can distinguish tumors from normal tissue on all these five tissue types. Methods Frozen tumor specimens were obtained from two commercial vendors Clinomics (Pittsfield, MA and Asterand (Detroit, MI. Biotinylated targets were prepared using published methods (Affymetrix, CA and hybridized to Affymetrix U133A GeneChips (Affymetrix, CA. Expression values for each gene were calculated using Affymetrix GeneChip analysis software MAS 5.0. We then used a software package called Genes@Work for differential expression discovery, and SVM light linear kernel for building classification models. Results We validate the predictability of this gene list on several publicly available data sets generated on the same platform. Of note, when analysing the lung cancer data set of Spira et al, using an SVM linear kernel classifier, our gene panel had 94.7% leave-one-out accuracy compared to 87.8% using the gene panel in the original paper. In addition, we performed high-throughput validation on the Dana Farber Cancer Institute GCOD database and several GEO datasets. Conclusions Our result showed the potential for this panel as a robust classification tool for multiple tumor types on the Affymetrix platform, as well as other whole genome arrays
-
Computational Tools and Algorithms for Designing Customized Synthetic Genes
Energy Technology Data Exchange (ETDEWEB)
Gould, Nathan [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States); Hendy, Oliver [Department of Biology, The College of New Jersey, Ewing, NJ (United States); Papamichail, Dimitris, E-mail: papamicd@tcnj.edu [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States)
2014-10-06
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
-
Computational Tools and Algorithms for Designing Customized Synthetic Genes
International Nuclear Information System (INIS)
Gould, Nathan; Hendy, Oliver; Papamichail, Dimitris
2014-01-01
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
-
Automatic design of digital synthetic gene circuits.
Directory of Open Access Journals (Sweden)
Mario A Marchisio
2011-02-01
Full Text Available De novo computational design of synthetic gene circuits that achieve well-defined target functions is a hard task. Existing, brute-force approaches run optimization algorithms on the structure and on the kinetic parameter values of the network. However, more direct rational methods for automatic circuit design are lacking. Focusing on digital synthetic gene circuits, we developed a methodology and a corresponding tool for in silico automatic design. For a given truth table that specifies a circuit's input-output relations, our algorithm generates and ranks several possible circuit schemes without the need for any optimization. Logic behavior is reproduced by the action of regulatory factors and chemicals on the promoters and on the ribosome binding sites of biological Boolean gates. Simulations of circuits with up to four inputs show a faithful and unequivocal truth table representation, even under parametric perturbations and stochastic noise. A comparison with already implemented circuits, in addition, reveals the potential for simpler designs with the same function. Therefore, we expect the method to help both in devising new circuits and in simplifying existing solutions.
-
Engineering synthetic TALE and CRISPR/Cas9 transcription factors for regulating gene expression.
Kabadi, Ami M; Gersbach, Charles A
2014-09-01
Engineered DNA-binding proteins that can be targeted to specific sites in the genome to manipulate gene expression have enabled many advances in biomedical research. This includes generating tools to study fundamental aspects of gene regulation and the development of a new class of gene therapies that alter the expression of endogenous genes. Designed transcription factors have entered clinical trials for the treatment of human diseases and others are in preclinical development. High-throughput and user-friendly platforms for designing synthetic DNA-binding proteins present innovative methods for deciphering cell biology and designing custom synthetic gene circuits. We review two platforms for designing synthetic transcription factors for manipulating gene expression: Transcription activator-like effectors (TALEs) and the RNA-guided clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system. We present an overview of each technology and a guide for designing and assembling custom TALE- and CRISPR/Cas9-based transcription factors. We also discuss characteristics of each platform that are best suited for different applications. Copyright © 2014 Elsevier Inc. All rights reserved.
-
Computational Tools and Algorithms for Designing Customized Synthetic Genes
Directory of Open Access Journals (Sweden)
Nathan eGould
2014-10-01
Full Text Available Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de-novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
-
Synthetic Jet Actuator-Based Aircraft Tracking Using a Continuous Robust Nonlinear Control Strategy
Directory of Open Access Journals (Sweden)
N. Ramos-Pedroza
2017-01-01
Full Text Available A robust nonlinear control law that achieves trajectory tracking control for unmanned aerial vehicles (UAVs equipped with synthetic jet actuators (SJAs is presented in this paper. A key challenge in the control design is that the dynamic characteristics of SJAs are nonlinear and contain parametric uncertainty. The challenge resulting from the uncertain SJA actuator parameters is mitigated via innovative algebraic manipulation in the tracking error system derivation along with a robust nonlinear control law employing constant SJA parameter estimates. A key contribution of the paper is a rigorous analysis of the range of SJA actuator parameter uncertainty within which asymptotic UAV trajectory tracking can be achieved. A rigorous stability analysis is carried out to prove semiglobal asymptotic trajectory tracking. Detailed simulation results are included to illustrate the effectiveness of the proposed control law in the presence of wind gusts and varying levels of SJA actuator parameter uncertainty.
-
Bauer, Christopher R; Li, Shuang; Siegal, Mark L
2015-01-01
The concept of robustness in biology has gained much attention recently, but a mechanistic understanding of how genetic networks regulate phenotypic variation has remained elusive. One approach to understand the genetic architecture of variability has been to analyze dispensable gene deletions in model organisms; however, the most important genes cannot be deleted. Here, we have utilized two systems in yeast whereby essential genes have been altered to reduce expression. Using high-throughput microscopy and image analysis, we have characterized a large number of morphological phenotypes, and their associated variation, for the majority of essential genes in yeast. Our results indicate that phenotypic robustness is more highly dependent upon the expression of essential genes than on the presence of dispensable genes. Morphological robustness appears to be a general property of a genotype that is closely related to pleiotropy. While the fitness profile across a range of expression levels is idiosyncratic to each gene, the global pattern indicates that there is a window in which phenotypic variation can be released before fitness effects are observable. PMID:25609648
-
Interrogating the topological robustness of gene regulatory circuits by randomization.
Directory of Open Access Journals (Sweden)
Bin Huang
2017-03-01
Full Text Available One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE, for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT, from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression.
-
Programming Morphogenesis through Systems and Synthetic Biology.
Velazquez, Jeremy J; Su, Emily; Cahan, Patrick; Ebrahimkhani, Mo R
2018-04-01
Mammalian tissue development is an intricate, spatiotemporal process of self-organization that emerges from gene regulatory networks of differentiating stem cells. A major goal in stem cell biology is to gain a sufficient understanding of gene regulatory networks and cell-cell interactions to enable the reliable and robust engineering of morphogenesis. Here, we review advances in synthetic biology, single cell genomics, and multiscale modeling, which, when synthesized, provide a framework to achieve the ambitious goal of programming morphogenesis in complex tissues and organoids. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Directory of Open Access Journals (Sweden)
Ye Ping
2005-12-01
Full Text Available Abstract Background Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership in a single protein complex may be inferred between genes that share synthetic lethal interaction partners than genes that are directly synthetic lethal. Probabilistic algorithms that identify gene modules based on motif discovery are highly appropriate for the analysis of synthetic lethal genetic interaction data and have great potential in integrative analysis of heterogeneous datasets. Results We have developed Genetic Interaction Motif Finding (GIMF, an algorithm for unsupervised motif discovery from synthetic lethal interaction data. Interaction motifs are characterized by position weight matrices and optimized through expectation maximization. Given a seed gene, GIMF performs a nonlinear transform on the input genetic interaction data and automatically assigns genes to the motif or non-motif category. We demonstrate the capacity to extract known and novel pathways for Saccharomyces cerevisiae (budding yeast. Annotations suggested for several uncharacterized genes are supported by recent experimental evidence. GIMF is efficient in computation, requires no training and automatically down-weights promiscuous genes with high degrees. Conclusion GIMF effectively identifies pathways from synthetic lethality data with several unique features. It is mostly suitable for building gene modules around seed genes. Optimal choice of one single model parameter allows construction of gene networks with different levels of confidence. The impact of hub genes the generic probabilistic framework of GIMF may be used to group other types of biological entities such as proteins based on stochastic motifs. Analysis of the strongest motifs discovered by the algorithm indicates that synthetic lethal interactions are depleted between genes within a motif, suggesting that synthetic
-
Zampini, Massimiliano; Mur, Luis A J; Rees Stevens, Pauline; Pachebat, Justin A; Newbold, C James; Hayes, Finbarr; Kingston-Smith, Alison
2016-05-25
Synthetic biology is characterized by the development of novel and powerful DNA fabrication methods and by the application of engineering principles to biology. The current study describes Terminator Operon Reporter (TOR), a new gene assembly technology based on the conditional activation of a reporter gene in response to sequence errors occurring at the assembly stage of the synthetic element. These errors are monitored by a transcription terminator that is placed between the synthetic gene and reporter gene. Switching of this terminator between active and inactive states dictates the transcription status of the downstream reporter gene to provide a rapid and facile readout of the accuracy of synthetic assembly. Designed specifically and uniquely for the synthesis of protein coding genes in bacteria, TOR allows the rapid and cost-effective fabrication of synthetic constructs by employing oligonucleotides at the most basic purification level (desalted) and without the need for costly and time-consuming post-synthesis correction methods. Thus, TOR streamlines gene assembly approaches, which are central to the future development of synthetic biology.
-
A mammalianized synthetic nitroreductase gene for high-level expression
International Nuclear Information System (INIS)
Grohmann, Maik; Paulmann, Nils; Fleischhauer, Sebastian; Vowinckel, Jakob; Priller, Josef; Walther, Diego J
2009-01-01
The nitroreductase/5-(azaridin-1-yl)-2,4-dinitrobenzamide (NTR/CB1954) enzyme/prodrug system is considered as a promising candidate for anti-cancer strategies by gene-directed enzyme prodrug therapy (GDEPT) and has recently entered clinical trials. It requires the genetic modification of tumor cells to express the E. coli enzyme nitroreductase that bioactivates the prodrug CB1954 to a powerful cytotoxin. This metabolite causes apoptotic cell death by DNA interstrand crosslinking. Enhancing the enzymatic NTR activity for CB1954 should improve the therapeutical potential of this enzyme-prodrug combination in cancer gene therapy. We performed de novo synthesis of the bacterial nitroreductase gene adapting codon usage to mammalian preferences. The synthetic gene was investigated for its expression efficacy and ability to sensitize mammalian cells to CB1954 using western blotting analysis and cytotoxicity assays. In our study, we detected cytoplasmic protein aggregates by expressing GFP-tagged NTR in COS-7 cells, suggesting an impaired translation by divergent codon usage between prokaryotes and eukaryotes. Therefore, we generated a synthetic variant of the nitroreductase gene, called ntro, adapted for high-level expression in mammalian cells. A total of 144 silent base substitutions were made within the bacterial ntr gene to change its codon usage to mammalian preferences. The codon-optimized ntro either tagged to gfp or c-myc showed higher expression levels in mammalian cell lines. Furthermore, the ntro rendered several cell lines ten times more sensitive to the prodrug CB1954 and also resulted in an improved bystander effect. Our results show that codon optimization overcomes expression limitations of the bacterial ntr gene in mammalian cells, thereby improving the NTR/CB1954 system at translational level for cancer gene therapy in humans
-
Parts & Pools: A Framework for Modular Design of Synthetic Gene Circuits
Energy Technology Data Exchange (ETDEWEB)
Marchisio, Mario Andrea, E-mail: marchisio@hit.edu.cn [School of Life Science and Technology, Harbin Institute of Technology, Harbin (China)
2014-10-06
Published in 2008, Parts & Pools represents one of the first attempts to conceptualize the modular design of bacterial synthetic gene circuits with Standard Biological Parts (DNA segments) and Pools of molecules referred to as common signal carriers (e.g., RNA polymerases and ribosomes). The original framework for modeling bacterial components and designing prokaryotic circuits evolved over the last years and brought, first, to the development of an algorithm for the automatic design of Boolean gene circuits. This is a remarkable achievement since gene digital circuits have a broad range of applications that goes from biosensors for health and environment care to computational devices. More recently, Parts & Pools was enabled to give a proper formal description of eukaryotic biological circuit components. This was possible by employing a rule-based modeling approach, a technique that permits a faithful calculation of all the species and reactions involved in complex systems such as eukaryotic cells and compartments. In this way, Parts & Pools is currently suitable for the visual and modular design of synthetic gene circuits in yeast and mammalian cells too.
-
Parts & Pools: A Framework for Modular Design of Synthetic Gene Circuits
International Nuclear Information System (INIS)
Marchisio, Mario Andrea
2014-01-01
Published in 2008, Parts & Pools represents one of the first attempts to conceptualize the modular design of bacterial synthetic gene circuits with Standard Biological Parts (DNA segments) and Pools of molecules referred to as common signal carriers (e.g., RNA polymerases and ribosomes). The original framework for modeling bacterial components and designing prokaryotic circuits evolved over the last years and brought, first, to the development of an algorithm for the automatic design of Boolean gene circuits. This is a remarkable achievement since gene digital circuits have a broad range of applications that goes from biosensors for health and environment care to computational devices. More recently, Parts & Pools was enabled to give a proper formal description of eukaryotic biological circuit components. This was possible by employing a rule-based modeling approach, a technique that permits a faithful calculation of all the species and reactions involved in complex systems such as eukaryotic cells and compartments. In this way, Parts & Pools is currently suitable for the visual and modular design of synthetic gene circuits in yeast and mammalian cells too.
-
van Haaften, Gijs; Vastenhouw, Nadine L; Nollen, Ellen A A; Plasterk, Ronald H A; Tijsterman, Marcel
2004-01-01
Here, we describe a systematic search for synthetic gene interactions in a multicellular organism, the nematode Caenorhabditis elegans. We established a high-throughput method to determine synthetic gene interactions by genome-wide RNA interference and identified genes that are required to protect
-
From essential to persistent genes: a functional approach to constructing synthetic life
DEFF Research Database (Denmark)
Acevedo-Rocha, Carlos G.; Fang, Gang; Schmidt, Markus
2013-01-01
A central undertaking in synthetic biology (SB) is the quest for the ‘minimal genome’. However, ‘minimal sets’ of essential genes are strongly context-dependent and, in all prokaryotic genomes sequenced to date, not a single protein-coding gene is entirely conserved. Furthermore, a lack...
-
Adams, Bryn L
2016-12-16
Escherichia coli (E. coli) has played a pivotal role in the development of genetics and molecular biology as scientific fields. It is therefore not surprising that synthetic biology (SB) was built upon E. coli and continues to dominate the field. However, scientific capabilities have advanced from simple gene mutations to the insertion of rationally designed, complex synthetic circuits and creation of entirely synthetic genomes. The point is rapidly approaching where E. coli is no longer an adequate host for the increasingly sophisticated genetic designs of SB. It is time to develop the next generation of SB chassis; robust organisms that can provide the advanced physiology novel synthetic circuits will require to move SB from the laboratory into fieldable technologies. This can be accomplished by developing chassis-specific genetic toolkits that are as extensive as those for E. coli. However, the holy grail of SB would be the development of a universal toolkit that can be ported into any chassis. This viewpoint article underscores the need for new bacterial chassis, as well as discusses some of the important considerations in their selection. It also highlights a few examples of robust, tractable bacterial species that can meet the demands of tomorrow's state-of-the-art in SB. Significant advances have been made in the first 15 years since this field has emerged. However, the advances over the next 15 years will occur not in laboratory organisms, but in fieldable species where the potential of SB can be fully realized in game changing technology.
-
Towards precise classification of cancers based on robust gene functional expression profiles
Directory of Open Access Journals (Sweden)
Zhu Jing
2005-03-01
Full Text Available Abstract Background Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. Results Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. Conclusion This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge
-
Robust network topologies for generating switch-like cellular responses.
Directory of Open Access Journals (Sweden)
Najaf A Shah
2011-06-01
Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.
-
Engineering emergent multicellular behavior through synthetic adhesion
Glass, David; Riedel-Kruse, Ingmar
In over a decade, synthetic biology has developed increasingly robust gene networks within single cells, but constructed very few systems that demonstrate multicellular spatio-temporal dynamics. We are filling this gap in synthetic biology's toolbox by developing an E. coli self-assembly platform based on modular cell-cell adhesion. We developed a system in which adhesive selectivity is provided by a library of outer membrane-displayed peptides with intra-library specificities, while affinity is provided by consistent expression across the entire library. We further provide a biophysical model to help understand the parameter regimes in which this tool can be used to self-assemble into cellular clusters, filaments, or meshes. The combined platform will enable future development of synthetic multicellular systems for use in consortia-based metabolic engineering, in living materials, and in controlled study of minimal multicellular systems. Stanford Bio-X Bowes Fellowship.
-
A robust approach based on Weibull distribution for clustering gene expression data
Directory of Open Access Journals (Sweden)
Gong Binsheng
2011-05-01
Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters
-
Directory of Open Access Journals (Sweden)
Andrei Zinovyev
2013-04-01
Full Text Available Systematic analysis of synthetic lethality (SL constitutes a critical tool for systems biology to decipher molecular pathways. The most accepted mechanistic explanation of SL is that the two genes function in parallel, mutually compensatory pathways, known as between-pathway SL. However, recent genome-wide analyses in yeast identified a significant number of within-pathway negative genetic interactions. The molecular mechanisms leading to within-pathway SL are not fully understood. Here, we propose a novel mechanism leading to within-pathway SL involving two genes functioning in a single non-essential pathway. This type of SL termed within-reversible-pathway SL involves reversible pathway steps, catalyzed by different enzymes in the forward and backward directions, and kinetic trapping of a potentially toxic intermediate. Experimental data with recombinational DNA repair genes validate the concept. Mathematical modeling recapitulates the possibility of kinetic trapping and revealed the potential contributions of synthetic, dosage-lethal interactions in such a genetic system as well as the possibility of within-pathway positive masking interactions. Analysis of yeast gene interaction and pathway data suggests broad applicability of this novel concept. These observations extend the canonical interpretation of synthetic-lethal or synthetic-sick interactions with direct implications to reconstruct molecular pathways and improve therapeutic approaches to diseases such as cancer.
-
A platform for rapid prototyping of synthetic gene networks in mammalian cells
Duportet, Xavier; Wroblewska, Liliana; Guye, Patrick; Li, Yinqing; Eyquem, Justin; Rieders, Julianne; Rimchala, Tharathorn; Batt, Gregory; Weiss, Ron
2014-01-01
Mammalian synthetic biology may provide novel therapeutic strategies, help decipher new paths for drug discovery and facilitate synthesis of valuable molecules. Yet, our capacity to genetically program cells is currently hampered by the lack of efficient approaches to streamline the design, construction and screening of synthetic gene networks. To address this problem, here we present a framework for modular and combinatorial assembly of functional (multi)gene expression vectors and their efficient and specific targeted integration into a well-defined chromosomal context in mammalian cells. We demonstrate the potential of this framework by assembling and integrating different functional mammalian regulatory networks including the largest gene circuit built and chromosomally integrated to date (6 transcription units, 27kb) encoding an inducible memory device. Using a library of 18 different circuits as a proof of concept, we also demonstrate that our method enables one-pot/single-flask chromosomal integration and screening of circuit libraries. This rapid and powerful prototyping platform is well suited for comparative studies of genetic regulatory elements, genes and multi-gene circuits as well as facile development of libraries of isogenic engineered cell lines. PMID:25378321
-
Design parameters to control synthetic gene expression in Escherichia coli.
Directory of Open Access Journals (Sweden)
Mark Welch
Full Text Available BACKGROUND: Production of proteins as therapeutic agents, research reagents and molecular tools frequently depends on expression in heterologous hosts. Synthetic genes are increasingly used for protein production because sequence information is easier to obtain than the corresponding physical DNA. Protein-coding sequences are commonly re-designed to enhance expression, but there are no experimentally supported design principles. PRINCIPAL FINDINGS: To identify sequence features that affect protein expression we synthesized and expressed in E. coli two sets of 40 genes encoding two commercially valuable proteins, a DNA polymerase and a single chain antibody. Genes differing only in synonymous codon usage expressed protein at levels ranging from undetectable to 30% of cellular protein. Using partial least squares regression we tested the correlation of protein production levels with parameters that have been reported to affect expression. We found that the amount of protein produced in E. coli was strongly dependent on the codons used to encode a subset of amino acids. Favorable codons were predominantly those read by tRNAs that are most highly charged during amino acid starvation, not codons that are most abundant in highly expressed E. coli proteins. Finally we confirmed the validity of our models by designing, synthesizing and testing new genes using codon biases predicted to perform well. CONCLUSION: The systematic analysis of gene design parameters shown in this study has allowed us to identify codon usage within a gene as a critical determinant of achievable protein expression levels in E. coli. We propose a biochemical basis for this, as well as design algorithms to ensure high protein production from synthetic genes. Replication of this methodology should allow similar design algorithms to be empirically derived for any expression system.
-
Robustness and accuracy in sea urchin developmental gene regulatory networks
Directory of Open Access Journals (Sweden)
Smadar eBen-Tabou De-Leon
2016-02-01
Full Text Available Developmental gene regulatory networks robustly control the timely activation of regulatory and differentiation genes. The structure of these networks underlies their capacity to buffer intrinsic and extrinsic noise and maintain embryonic morphology. Here I illustrate how the use of specific architectures by the sea urchin developmental regulatory networks enables the robust control of cell fate decisions. The Wnt-βcatenin signaling pathway patterns the primary embryonic axis while the BMP signaling pathway patterns the secondary embryonic axis in the sea urchin embryo and across bilateria. Interestingly, in the sea urchin in both cases, the signaling pathway that defines the axis controls directly the expression of a set of downstream regulatory genes. I propose that this direct activation of a set of regulatory genes enables a uniform regulatory response and a clear cut cell fate decision in the endoderm and in the dorsal ectoderm. The specification of the mesodermal pigment cell lineage is activated by Delta signaling that initiates a triple positive feedback loop that locks down the pigment specification state. I propose that the use of compound positive feedback circuitry provides the endodermal cells enough time to turn off mesodermal genes and ensures correct mesoderm vs. endoderm fate decision. Thus, I argue that understanding the control properties of repeatedly used regulatory architectures illuminates their role in embryogenesis and provides possible explanations to their resistance to evolutionary change.
-
Modular design of synthetic gene circuits with biological parts and pools.
Marchisio, Mario Andrea
2015-01-01
Synthetic gene circuits can be designed in an electronic fashion by displaying their basic components-Standard Biological Parts and Pools of molecules-on the computer screen and connecting them with hypothetical wires. This procedure, achieved by our add-on for the software ProMoT, was successfully applied to bacterial circuits. Recently, we have extended this design-methodology to eukaryotic cells. Here, highly complex components such as promoters and Pools of mRNA contain hundreds of species and reactions whose calculation demands a rule-based modeling approach. We showed how to build such complex modules via the joint employment of the software BioNetGen (rule-based modeling) and ProMoT (modularization). In this chapter, we illustrate how to utilize our computational tool for synthetic biology with the in silico implementation of a simple eukaryotic gene circuit that performs the logic AND operation.
-
Imran, Muhammad; Asad, Shaheen; Barboza, Andre Luiz; Galeano, Esteban; Carrer, Helaine; Mukhtar, Zahid
2017-04-01
Glyphosate quashes the synthesis of 5-enolpyruvylshikimate-3- phosphate synthase (EPSPS) enzyme which intercedes the functioning of shikimate pathway for the production of aromatic amino acids. Herbicide resistant crops are developed using glyphosate insensitive EPSPS gene isolated from Agrobacterium sp. strain CP4, which give farmers a sustainable weed control option. Intentions behind this study were to design and characterize the synthetic herbicide resistant CP4 - EPSPS gene in a model plant system and check the effectiveness of transformed tobacco against application of glyphosate. Putative transgenic plants were obtained from independent transformation events, and stable plant transformation, transgene expression and integration were demonstrated respectively by PCR, qRT-PCR and Southern hybridization. Gene transcript level and gene copy number (1-4) varied among the tested transgenic tobacco lines. Herbicide assays showed that transgenic plants were resistant to glyphosate after 12 days of spraying with glyphosate, and EPSPS activity remained at sufficient level to withstand the spray at 1000 ppm of the chemical. T 1 plants analyzed through immunoblot strips and PCR showed that the gene was being translated into protein and transmitted to the next generation successfully. This codon optimized synthetic CP4 - EPSPS gene is functionally equivalent to the gene for glyphosate resistance available in the commercial crops and hence we recommend this gene for transformation into commercial crops.
-
An integer optimization algorithm for robust identification of non-linear gene regulatory networks
Directory of Open Access Journals (Sweden)
Chemmangattuvalappil Nishanth
2012-09-01
Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters
-
Popova, Blagovesta; Schubert, Steffen; Bulla, Ingo; Buchwald, Daniela; Kramer, Wilfried
2015-01-01
A major challenge in gene library generation is to guarantee a large functional size and diversity that significantly increases the chances of selecting different functional protein variants. The use of trinucleotides mixtures for controlled randomization results in superior library diversity and offers the ability to specify the type and distribution of the amino acids at each position. Here we describe the generation of a high diversity gene library using tHisF of the hyperthermophile Thermotoga maritima as a scaffold. Combining various rational criteria with contingency, we targeted 26 selected codons of the thisF gene sequence for randomization at a controlled level. We have developed a novel method of creating full-length gene libraries by combinatorial assembly of smaller sub-libraries. Full-length libraries of high diversity can easily be assembled on demand from smaller and much less diverse sub-libraries, which circumvent the notoriously troublesome long-term archivation and repeated proliferation of high diversity ensembles of phages or plasmids. We developed a generally applicable software tool for sequence analysis of mutated gene sequences that provides efficient assistance for analysis of library diversity. Finally, practical utility of the library was demonstrated in principle by assessment of the conformational stability of library members and isolating protein variants with HisF activity from it. Our approach integrates a number of features of nucleic acids synthetic chemistry, biochemistry and molecular genetics to a coherent, flexible and robust method of combinatorial gene synthesis. PMID:26355961
-
Rapid and accurate synthesis of TALE genes from synthetic oligonucleotides.
Wang, Fenghua; Zhang, Hefei; Gao, Jingxia; Chen, Fengjiao; Chen, Sijie; Zhang, Cuizhen; Peng, Gang
2016-01-01
Custom synthesis of transcription activator-like effector (TALE) genes has relied upon plasmid libraries of pre-fabricated TALE-repeat monomers or oligomers. Here we describe a novel synthesis method that directly incorporates annealed synthetic oligonucleotides into the TALE-repeat units. Our approach utilizes iterative sets of oligonucleotides and a translational frame check strategy to ensure the high efficiency and accuracy of TALE-gene synthesis. TALE arrays of more than 20 repeats can be constructed, and the majority of the synthesized constructs have perfect sequences. In addition, this novel oligonucleotide-based method can readily accommodate design changes to the TALE repeats. We demonstrated an increased gene targeting efficiency against a genomic site containing a potentially methylated cytosine by incorporating non-conventional repeat variable di-residue (RVD) sequences.
-
Dong, Shaowei; Adams, Keith L
2011-06-01
Polyploidy has occurred throughout plant evolution and can result in considerable changes to gene expression when it takes place and over evolutionary time. Little is known about the effects of abiotic stress conditions on duplicate gene expression patterns in polyploid plants. We examined the expression patterns of 60 duplicated genes in leaves, roots and cotyledons of allotetraploid Gossypium hirsutum in response to five abiotic stress treatments (heat, cold, drought, high salt and water submersion) using single-strand conformation polymorphism assays, and 20 genes in a synthetic allotetraploid. Over 70% of the genes showed stress-induced changes in the relative expression levels of the duplicates under one or more stress treatments with frequent variability among treatments. Twelve pairs showed opposite changes in expression levels in response to different abiotic stress treatments. Stress-induced expression changes occurred in the synthetic allopolyploid, but there was little correspondence in patterns between the natural and synthetic polyploids. Our results indicate that abiotic stress conditions can have considerable effects on duplicate gene expression in a polyploid, with the effects varying by gene, stress and organ type. Differential expression in response to environmental stresses may be a factor in the preservation of some duplicated genes in polyploids. © 2011 The Authors. New Phytologist © 2011 New Phytologist Trust.
-
Cloning of synthetic gene including antigens against Urinary Tract Infections in pET28a+ vector
Directory of Open Access Journals (Sweden)
Zohreh Haghri
2017-12-01
Full Text Available There are many different bacterial infections in the world that patients are suffering from and research teams are trying to find suitable ways to prevent and treat them. Urinary Tract Infections (UTIs are most important infections in the world , and they are more common among women because vaginal cavity is near to urethral opening. The aim of this study is cloning of synthetic gene include antigens against UTIs in pET28a+ vector. Antibiotic resistant has been increasing because of antibiotic overuse recently, so It shows the necessity of developing a vaccine against these infections. There for, it will be imperative to develop a vaccine instead of antibiotics. This infection causes by many organisms, most important of which are Uropathogenic Escherichia coli (UPEC, Proteus mirabilis and Klebsiella pneumoniae Uropathogenic Escherichia .coli is the most important microorganism that causes these infections more than other bacteria, so in developing a vaccine it is the most important one, that have to be considered. The synthetic Gene which was designed against these three bacteria including antigens which are important and common to cause these infections. This gene has involved 1293bp. It was ordered to Gene Ray Biotechnology. Primers were designed by Gene Runner. Gene and pET28a+ vector was checked by SnappGene. Synthetic gene was multiplied by PCR and cloned in pET28a+ vector. Construct was transformed into E. coli TOP10.The clone was confirmed by PCR, Digestion. This data indicates that this gene can be expressed and it might be a vaccine candidate to protect people from these infections in the future.
-
A simple and robust method for connecting small-molecule drugs using gene-expression signatures
Directory of Open Access Journals (Sweden)
Gant Timothy W
2008-06-01
Full Text Available Abstract Background Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties by gene expression profile. Lamb et al first proposed the Connectivity Map [Lamb et al (2006, Science 313, 1929–1935] to make successful connections among small molecules, genes, and diseases using genomic signatures. Results Here we have built on the principles of the Connectivity Map to present a simpler and more robust method for the construction of reference gene-expression profiles and for the connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with two randomly generated gene signatures and three experimentally derived gene signatures (for HDAC inhibitors, estrogens, and immunosuppressive drugs, respectively. Our testing with this method indicates that it achieves a higher level of specificity and sensitivity and so advances the original method. Conclusion The method presented here not only offers more principled statistical procedures for testing connections, but more importantly it provides effective safeguard against false connections at the same time achieving increased sensitivity. With its robust performance, the method has potential use in the drug development pipeline for the early recognition of pharmacological and toxicological properties in chemicals and new drug candidates, and also more broadly in other 'omics sciences.
-
Chen, Bor-Sen; Wu, Chia-Chou
2013-01-01
Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. PMID:24709875
-
Directory of Open Access Journals (Sweden)
Bor-Sen Chen
2013-10-01
Full Text Available Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.
-
From noise to synthetic nucleoli: can synthetic biology achieve new insights?
Ciechonska, Marta; Grob, Alice; Isalan, Mark
2016-04-18
Synthetic biology aims to re-organise and control biological components to make functional devices. Along the way, the iterative process of designing and testing gene circuits has the potential to yield many insights into the functioning of the underlying chassis of cells. Thus, synthetic biology is converging with disciplines such as systems biology and even classical cell biology, to give a new level of predictability to gene expression, cell metabolism and cellular signalling networks. This review gives an overview of the contributions that synthetic biology has made in understanding gene expression, in terms of cell heterogeneity (noise), the coupling of growth and energy usage to expression, and spatiotemporal considerations. We mainly compare progress in bacterial and mammalian systems, which have some of the most-developed engineering frameworks. Overall, one view of synthetic biology can be neatly summarised as "creating in order to understand."
-
Mammalian synthetic biology: emerging medical applications.
Kis, Zoltán; Pereira, Hugo Sant'Ana; Homma, Takayuki; Pedrigi, Ryan M; Krams, Rob
2015-05-06
In this review, we discuss new emerging medical applications of the rapidly evolving field of mammalian synthetic biology. We start with simple mammalian synthetic biological components and move towards more complex and therapy-oriented gene circuits. A comprehensive list of ON-OFF switches, categorized into transcriptional, post-transcriptional, translational and post-translational, is presented in the first sections. Subsequently, Boolean logic gates, synthetic mammalian oscillators and toggle switches will be described. Several synthetic gene networks are further reviewed in the medical applications section, including cancer therapy gene circuits, immuno-regulatory networks, among others. The final sections focus on the applicability of synthetic gene networks to drug discovery, drug delivery, receptor-activating gene circuits and mammalian biomanufacturing processes. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
-
Potential energy landscape and robustness of a gene regulatory network: toggle switch.
Directory of Open Access Journals (Sweden)
Keun-Young Kim
2007-03-01
Full Text Available Finding a multidimensional potential landscape is the key for addressing important global issues, such as the robustness of cellular networks. We have uncovered the underlying potential energy landscape of a simple gene regulatory network: a toggle switch. This was realized by explicitly constructing the steady state probability of the gene switch in the protein concentration space in the presence of the intrinsic statistical fluctuations due to the small number of proteins in the cell. We explored the global phase space for the system. We found that the protein synthesis rate and the unbinding rate of proteins to the gene were small relative to the protein degradation rate; the gene switch is monostable with only one stable basin of attraction. When both the protein synthesis rate and the unbinding rate of proteins to the gene are large compared with the protein degradation rate, two global basins of attraction emerge for a toggle switch. These basins correspond to the biologically stable functional states. The potential energy barrier between the two basins determines the time scale of conversion from one to the other. We found as the protein synthesis rate and protein unbinding rate to the gene relative to the protein degradation rate became larger, the potential energy barrier became larger. This also corresponded to systems with less noise or the fluctuations on the protein numbers. It leads to the robustness of the biological basins of the gene switches. The technique used here is general and can be applied to explore the potential energy landscape of the gene networks.
-
A Small-Molecule Inducible Synthetic Circuit for Control of the SOS Gene Network without DNA Damage.
Kubiak, Jeffrey M; Culyba, Matthew J; Liu, Monica Yun; Mo, Charlie Y; Goulian, Mark; Kohli, Rahul M
2017-11-17
The bacterial SOS stress-response pathway is a pro-mutagenic DNA repair system that mediates bacterial survival and adaptation to genotoxic stressors, including antibiotics and UV light. The SOS pathway is composed of a network of genes under the control of the transcriptional repressor, LexA. Activation of the pathway involves linked but distinct events: an initial DNA damage event leads to activation of RecA, which promotes autoproteolysis of LexA, abrogating its repressor function and leading to induction of the SOS gene network. These linked events can each independently contribute to DNA repair and mutagenesis, making it difficult to separate the contributions of the different events to observed phenotypes. We therefore devised a novel synthetic circuit to unlink these events and permit induction of the SOS gene network in the absence of DNA damage or RecA activation via orthogonal cleavage of LexA. Strains engineered with the synthetic SOS circuit demonstrate small-molecule inducible expression of SOS genes as well as the associated resistance to UV light. Exploiting our ability to activate SOS genes independently of upstream events, we further demonstrate that the majority of SOS-mediated mutagenesis on the chromosome does not readily occur with orthogonal pathway induction alone, but instead requires DNA damage. More generally, our approach provides an exemplar for using synthetic circuit design to separate an environmental stressor from its associated stress-response pathway.
-
Robust dynamical pattern formation from a multifunctional minimal genetic circuit
Directory of Open Access Journals (Sweden)
Carrera Javier
2010-04-01
Full Text Available Abstract Background A practical problem during the analysis of natural networks is their complexity, thus the use of synthetic circuits would allow to unveil the natural mechanisms of operation. Autocatalytic gene regulatory networks play an important role in shaping the development of multicellular organisms, whereas oscillatory circuits are used to control gene expression under variable environments such as the light-dark cycle. Results We propose a new mechanism to generate developmental patterns and oscillations using a minimal number of genes. For this, we design a synthetic gene circuit with an antagonistic self-regulation to study the spatio-temporal control of protein expression. Here, we show that our minimal system can behave as a biological clock or memory, and it exhibites an inherent robustness due to a quorum sensing mechanism. We analyze this property by accounting for molecular noise in an heterogeneous population. We also show how the period of the oscillations is tunable by environmental signals, and we study the bifurcations of the system by constructing different phase diagrams. Conclusions As this minimal circuit is based on a single transcriptional unit, it provides a new mechanism based on post-translational interactions to generate targeted spatio-temporal behavior.
-
Synthetic Nucleic Acid Analogues in Gene Therapy: An Update for Peptide–Oligonucleotide Conjugates
DEFF Research Database (Denmark)
Taskova, Maria; Mantsiou, Anna; Astakhova, Kira
2017-01-01
The main objective of this work is to provide an update on synthetic nucleic acid analogues and nanoassemblies as tools in gene therapy. In particular, the synthesis and properties of peptide–oligonucleotide conjugates (POCs), which have high potential in research and as therapeutics, are described...
-
Control theory meets synthetic biology.
Del Vecchio, Domitilla; Dy, Aaron J; Qian, Yili
2016-07-01
The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology. © 2016 The Author(s).
-
Directory of Open Access Journals (Sweden)
Emre Guney
Full Text Available Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO analysis highlighted the role of functional diversity for such diseases.
-
Synthetic RNAs for Gene Regulation: Design Principles and Computational Tools
International Nuclear Information System (INIS)
Laganà, Alessandro; Shasha, Dennis; Croce, Carlo Maria
2014-01-01
The use of synthetic non-coding RNAs for post-transcriptional regulation of gene expression has not only become a standard laboratory tool for gene functional studies but it has also opened up new perspectives in the design of new and potentially promising therapeutic strategies. Bioinformatics has provided researchers with a variety of tools for the design, the analysis, and the evaluation of RNAi agents such as small-interfering RNA (siRNA), short-hairpin RNA (shRNA), artificial microRNA (a-miR), and microRNA sponges. More recently, a new system for genome engineering based on the bacterial CRISPR-Cas9 system (Clustered Regularly Interspaced Short Palindromic Repeats), was shown to have the potential to also regulate gene expression at both transcriptional and post-transcriptional level in a more specific way. In this mini review, we present RNAi and CRISPRi design principles and discuss the advantages and limitations of the current design approaches.
-
Synthetic RNAs for Gene Regulation: Design Principles and Computational Tools
Energy Technology Data Exchange (ETDEWEB)
Laganà, Alessandro [Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH (United States); Shasha, Dennis [Courant Institute of Mathematical Sciences, New York University, New York, NY (United States); Croce, Carlo Maria [Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH (United States)
2014-12-11
The use of synthetic non-coding RNAs for post-transcriptional regulation of gene expression has not only become a standard laboratory tool for gene functional studies but it has also opened up new perspectives in the design of new and potentially promising therapeutic strategies. Bioinformatics has provided researchers with a variety of tools for the design, the analysis, and the evaluation of RNAi agents such as small-interfering RNA (siRNA), short-hairpin RNA (shRNA), artificial microRNA (a-miR), and microRNA sponges. More recently, a new system for genome engineering based on the bacterial CRISPR-Cas9 system (Clustered Regularly Interspaced Short Palindromic Repeats), was shown to have the potential to also regulate gene expression at both transcriptional and post-transcriptional level in a more specific way. In this mini review, we present RNAi and CRISPRi design principles and discuss the advantages and limitations of the current design approaches.
-
Human synthetic lethal inference as potential anti-cancer target gene detection
Directory of Open Access Journals (Sweden)
Solé Ricard V
2009-12-01
Full Text Available Abstract Background Two genes are called synthetic lethal (SL if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases as well as on existent approved drugs (DrugBank database supports our selection of cancer-therapy candidates. Conclusions Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.
-
Robust, synergistic regulation of human gene expression using TALE activators.
Maeder, Morgan L; Linder, Samantha J; Reyon, Deepak; Angstman, James F; Fu, Yanfang; Sander, Jeffry D; Joung, J Keith
2013-03-01
Artificial activators designed using transcription activator-like effector (TALE) technology have broad utility, but previous studies suggest that these monomeric proteins often exhibit low activities. Here we demonstrate that TALE activators can robustly function individually or in synergistic combinations to increase expression of endogenous human genes over wide dynamic ranges. These findings will encourage applications of TALE activators for research and therapy, and guide design of monomeric TALE-based fusion proteins.
-
Ghysels, Bart; Ochsner, Urs; Möllman, Ute; Heinisch, Lothar; Vasil, Michael; Cornelis, Pierre; Matthijs, Sandra
2005-05-15
Actively secreted iron chelating agents termed siderophores play an important role in the virulence and rhizosphere competence of fluorescent pseudomonads, including Pseudomonas aeruginosa which secretes a high affinity siderophore, pyoverdine, and the low affinity siderophore, pyochelin. Uptake of the iron-siderophore complexes is an active process that requires specific outer membrane located receptors, which are dependent of the inner membrane-associated protein TonB and two other inner membrane proteins, ExbB and ExbC. P. aeruginosa is also capable of using a remarkable variety of heterologous siderophores as sources of iron, apparently by expressing their cognate receptors. Illustrative of this feature are the 32 (of which 28 putative) siderophore receptor genes observed in the P. aeruginosa PAO1 genome. However, except for a few (pyoverdine, pyochelin, enterobactin), the vast majority of P. aeruginosa siderophore receptor genes still remain to be characterized. Ten synthetic iron chelators of catecholate type stimulated growth of a pyoverdine/pyochelin deficient P. aeruginosa PAO1 mutant under condition of severe iron limitation. Null mutants of the 32 putative TonB-dependent siderophore receptor encoding genes engineered in the same genetic background were screened for obvious deficiencies in uptake of the synthetic siderophores, but none showed decreased growth stimulation in the presence of the different siderophores. However, a double knock-out mutant of ferrienterobactin receptor encoding gene pfeA (PA 2688) and pirA (PA0931) failed to be stimulated by 4 of the tested synthetic catecholate siderophores whose chemical structures resemble enterobactin. Ferric-enterobactin also failed to stimulate growth of the double pfeA-pirA mutant although, like its synthetic analogues, it stimulated growth of the corresponding single mutants. Hence, we confirmed that pirA represents a second P. aeruginosa ferric-enterobactin receptor. The example of these two
-
Parallel logic gates in synthetic gene networks induced by non-Gaussian noise.
Xu, Yong; Jin, Xiaoqin; Zhang, Huiqing
2013-11-01
The recent idea of logical stochastic resonance is verified in synthetic gene networks induced by non-Gaussian noise. We realize the switching between two kinds of logic gates under optimal moderate noise intensity by varying two different tunable parameters in a single gene network. Furthermore, in order to obtain more logic operations, thus providing additional information processing capacity, we obtain in a two-dimensional toggle switch model two complementary logic gates and realize the transformation between two logic gates via the methods of changing different parameters. These simulated results contribute to improve the computational power and functionality of the networks.
-
Molecular Imaging in Synthetic Biology, and Synthetic Biology in Molecular Imaging.
Gilad, Assaf A; Shapiro, Mikhail G
2017-06-01
Biomedical synthetic biology is an emerging field in which cells are engineered at the genetic level to carry out novel functions with relevance to biomedical and industrial applications. This approach promises new treatments, imaging tools, and diagnostics for diseases ranging from gastrointestinal inflammatory syndromes to cancer, diabetes, and neurodegeneration. As these cellular technologies undergo pre-clinical and clinical development, it is becoming essential to monitor their location and function in vivo, necessitating appropriate molecular imaging strategies, and therefore, we have created an interest group within the World Molecular Imaging Society focusing on synthetic biology and reporter gene technologies. Here, we highlight recent advances in biomedical synthetic biology, including bacterial therapy, immunotherapy, and regenerative medicine. We then discuss emerging molecular imaging approaches to facilitate in vivo applications, focusing on reporter genes for noninvasive modalities such as magnetic resonance, ultrasound, photoacoustic imaging, bioluminescence, and radionuclear imaging. Because reporter genes can be incorporated directly into engineered genetic circuits, they are particularly well suited to imaging synthetic biological constructs, and developing them provides opportunities for creative molecular and genetic engineering.
-
Genome engineering using a synthetic gene circuit in Bacillus subtilis.
Jeong, Da-Eun; Park, Seung-Hwan; Pan, Jae-Gu; Kim, Eui-Joong; Choi, Soo-Keun
2015-03-31
Genome engineering without leaving foreign DNA behind requires an efficient counter-selectable marker system. Here, we developed a genome engineering method in Bacillus subtilis using a synthetic gene circuit as a counter-selectable marker system. The system contained two repressible promoters (B. subtilis xylA (Pxyl) and spac (Pspac)) and two repressor genes (lacI and xylR). Pxyl-lacI was integrated into the B. subtilis genome with a target gene containing a desired mutation. The xylR and Pspac-chloramphenicol resistant genes (cat) were located on a helper plasmid. In the presence of xylose, repression of XylR by xylose induced LacI expression, the LacIs repressed the Pspac promoter and the cells become chloramphenicol sensitive. Thus, to survive in the presence of chloramphenicol, the cell must delete Pxyl-lacI by recombination between the wild-type and mutated target genes. The recombination leads to mutation of the target gene. The remaining helper plasmid was removed easily under the chloramphenicol absent condition. In this study, we showed base insertion, deletion and point mutation of the B. subtilis genome without leaving any foreign DNA behind. Additionally, we successfully deleted a 2-kb gene (amyE) and a 38-kb operon (ppsABCDE). This method will be useful to construct designer Bacillus strains for various industrial applications. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
-
Directory of Open Access Journals (Sweden)
Ling-Yun Dai
2017-01-01
Full Text Available Differential expression plays an important role in cancer diagnosis and classification. In recent years, many methods have been used to identify differentially expressed genes. However, the recognition rate and reliability of gene selection still need to be improved. In this paper, a novel constrained method named robust nonnegative matrix factorization via joint graph Laplacian and discriminative information (GLD-RNMF is proposed for identifying differentially expressed genes, in which manifold learning and the discriminative label information are incorporated into the traditional nonnegative matrix factorization model to train the objective matrix. Specifically, L2,1-norm minimization is enforced on both the error function and the regularization term which is robust to outliers and noise in gene data. Furthermore, the multiplicative update rules and the details of convergence proof are shown for the new model. The experimental results on two publicly available cancer datasets demonstrate that GLD-RNMF is an effective method for identifying differentially expressed genes.
-
Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E
2016-03-11
Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.
-
Synthetic biology and occupational risk.
Howard, John; Murashov, Vladimir; Schulte, Paul
2017-03-01
Synthetic biology is an emerging interdisciplinary field of biotechnology that involves applying the principles of engineering and chemical design to biological systems. Biosafety professionals have done an excellent job in addressing research laboratory safety as synthetic biology and gene editing have emerged from the larger field of biotechnology. Despite these efforts, risks posed by synthetic biology are of increasing concern as research procedures scale up to industrial processes in the larger bioeconomy. A greater number and variety of workers will be exposed to commercial synthetic biology risks in the future, including risks to a variety of workers from the use of lentiviral vectors as gene transfer devices. There is a need to review and enhance current protection measures in the field of synthetic biology, whether in experimental laboratories where new advances are being researched, in health care settings where treatments using viral vectors as gene delivery systems are increasingly being used, or in the industrial bioeconomy. Enhanced worker protection measures should include increased injury and illness surveillance of the synthetic biology workforce; proactive risk assessment and management of synthetic biology products; research on the relative effectiveness of extrinsic and intrinsic biocontainment methods; specific safety guidance for synthetic biology industrial processes; determination of appropriate medical mitigation measures for lentiviral vector exposure incidents; and greater awareness and involvement in synthetic biology safety by the general occupational safety and health community as well as by government occupational safety and health research and regulatory agencies.
-
Directory of Open Access Journals (Sweden)
David A Garfield
2013-10-01
Full Text Available Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear, allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.
-
Kim, Juhyun; Salvador, Manuel; Saunders, Elizabeth; González, Jaime; Avignone-Rossa, Claudio
2016-01-01
The chassis is the cellular host used as a recipient of engineered biological systems in synthetic biology. They are required to propagate the genetic information and to express the genes encoded in it. Despite being an essential element for the appropriate function of genetic circuits, the chassis is rarely considered in their design phase. Consequently, the circuits are transferred to model organisms commonly used in the laboratory, such as Escherichia coli, that may be suboptimal for a required function. In this review, we discuss some of the properties desirable in a versatile chassis and summarize some examples of alternative hosts for synthetic biology amenable for engineering. These properties include a suitable life style, a robust cell wall, good knowledge of its regulatory network as well as of the interplay of the host components with the exogenous circuits, and the possibility of developing whole-cell models and tuneable metabolic fluxes that could allow a better distribution of cellular resources (metabolites, ATP, nucleotides, amino acids, transcriptional and translational machinery). We highlight Pseudomonas putida, widely used in many different biotechnological applications as a prominent organism for synthetic biology due to its metabolic diversity, robustness and ease of manipulation. PMID:27903818
-
How to turn a genetic circuit into a synthetic tunable oscillator, or a bistable switch.
Directory of Open Access Journals (Sweden)
Lucia Marucci
2009-12-01
Full Text Available Systems and Synthetic Biology use computational models of biological pathways in order to study in silico the behaviour of biological pathways. Mathematical models allow to verify biological hypotheses and to predict new possible dynamical behaviours. Here we use the tools of non-linear analysis to understand how to change the dynamics of the genes composing a novel synthetic network recently constructed in the yeast Saccharomyces cerevisiae for In-vivo Reverse-engineering and Modelling Assessment (IRMA. Guided by previous theoretical results that make the dynamics of a biological network depend on its topological properties, through the use of simulation and continuation techniques, we found that the network can be easily turned into a robust and tunable synthetic oscillator or a bistable switch. Our results provide guidelines to properly re-engineering in vivo the network in order to tune its dynamics.
-
Celedon, J M; Bohlmann, J
2016-01-01
Terpenoid fragrances are powerful mediators of ecological interactions in nature and have a long history of traditional and modern industrial applications. Plants produce a great diversity of fragrant terpenoid metabolites, which make them a superb source of biosynthetic genes and enzymes. Advances in fragrance gene discovery have enabled new approaches in synthetic biology of high-value speciality molecules toward applications in the fragrance and flavor, food and beverage, cosmetics, and other industries. Rapid developments in transcriptome and genome sequencing of nonmodel plant species have accelerated the discovery of fragrance biosynthetic pathways. In parallel, advances in metabolic engineering of microbial and plant systems have established platforms for synthetic biology applications of some of the thousands of plant genes that underlie fragrance diversity. While many fragrance molecules (eg, simple monoterpenes) are abundant in readily renewable plant materials, some highly valuable fragrant terpenoids (eg, santalols, ambroxides) are rare in nature and interesting targets for synthetic biology. As a representative example for genomics/transcriptomics enabled gene and enzyme discovery, we describe a strategy used successfully for elucidation of a complete fragrance biosynthetic pathway in sandalwood (Santalum album) and its reconstruction in yeast (Saccharomyces cerevisiae). We address questions related to the discovery of specific genes within large gene families and recovery of rare gene transcripts that are selectively expressed in recalcitrant tissues. To substantiate the validity of the approaches, we describe the combination of methods used in the gene and enzyme discovery of a cytochrome P450 in the fragrant heartwood of tropical sandalwood, responsible for the fragrance defining, final step in the biosynthesis of (Z)-santalols. © 2016 Elsevier Inc. All rights reserved.
-
[Research progress of mammalian synthetic biology in biomedical field].
Yang, Linfeng; Yin, Jianli; Wang, Meiyan; Ye, Haifeng
2017-03-25
Although still in its infant stage, synthetic biology has achieved remarkable development and progress during the past decade. Synthetic biology applies engineering principles to design and construct gene circuits uploaded into living cells or organisms to perform novel or improved functions, and it has been widely used in many fields. In this review, we describe the recent advances of mammalian synthetic biology for the treatment of diseases. We introduce common tools and design principles of synthetic gene circuits, and then we demonstrate open-loop gene circuits induced by different trigger molecules used in disease diagnosis and close-loop gene circuits used for biomedical applications. Finally, we discuss the perspectives and potential challenges of synthetic biology for clinical applications.
-
Lei, Qiong; Wang, Lin; Tan, Dun-Xian; Zhao, Yu; Zheng, Xiao-Dong; Chen, Hao; Li, Qing-Tian; Zuo, Bi-Xiao; Kong, Jin
2013-11-01
Melatonin is present in many edible fruits; however, the presence of melatonin in apple has not previously been reported. In this study, the genes for melatonin synthetic enzymes including tryptophan decarboxylase, tryptamine 5-hydroxylase (T5H), arylalkylamine N-acetyltransferase, and N-acetylserotonin methyltransferase were identified in 'Red Fuji' apple. Each gene has several homologous genes. Sequence analysis shows that these genes have little homology with those of animals and they only have limited homology with known genes of rice melatonin synthetic enzymes. Multiple origins of melatonin synthetic genes during the evolution are expected. The expression of these genes is fully coordinated with melatonin production in apple development. Melatonin levels in apple exhibit an inverse relationship with the content of malondialdehyde, a product of lipid peroxidation. Two major melatonin synthetic peaks appeared on July 17 and on October 8 in both unbagged and bagged apple samples. At the periods mentioned above, apples experienced rapid expansion and increased respiration. These episodes significantly elevate reactive oxygen species production in the apple. Current data further confirmed that melatonin produced in apple was used to neutralize the toxic oxidants and protect the developing apple against oxidative stress. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
-
BAY11 enhances OCT4 synthetic mRNA expression in adult human skin cells.
Awe, Jason P; Crespo, Agustin Vega; Li, You; Kiledjian, Megerditch; Byrne, James A
2013-02-06
The OCT4 transcription factor is involved in many cellular processes, including development, reprogramming, maintaining pluripotency and differentiation. Synthetic OCT4 mRNA was recently used (in conjunction with other reprogramming factors) to generate human induced pluripotent stem cells. Here, we discovered that BAY 11-7082 (BAY11), at least partially through an NF-κB-inhibition based mechanism, could significantly increase the expression of OCT4 following transfection of synthetic mRNA (synRNA) into adult human skin cells. We tested various chemical and molecular small molecules on their ability to suppress the innate immune response seen upon synthetic mRNA transfection. Three molecules - B18R, BX795, and BAY11 - were used in immunocytochemical and proliferation-based assays. We also utilized global transcriptional meta-analysis coupled with quantitative PCR to identify relative gene expression downstream of OCT4. We found that human skin cells cultured in the presence of BAY11 resulted in reproducible increased expression of OCT4 that did not inhibit normal cell proliferation. The increased levels of OCT4 resulted in significantly increased expression of genes downstream of OCT4, including the previously identified SPP1, DUSP4 and GADD45G, suggesting the expressed OCT4 was functional. We also discovered a novel OCT4 putative downstream target gene SLC16A9 which demonstrated significantly increased expression following elevation of OCT4 levels. For the first time we have shown that small molecule-based stabilization of synthetic mRNA expression can be achieved with use of BAY11. This small molecule-based inhibition of innate immune responses and subsequent robust expression of transfected synthetic mRNAs may have multiple applications for future cell-based research and therapeutics.
-
Strategy revealing phenotypic differences among synthetic oscillator designs.
Lomnitz, Jason G; Savageau, Michael A
2014-09-19
Considerable progress has been made in identifying and characterizing the component parts of genetic oscillators, which play central roles in all organisms. Nonlinear interaction among components is sufficiently complex that mathematical models are required to elucidate their elusive integrated behavior. Although natural and synthetic oscillators exhibit common architectures, there are numerous differences that are poorly understood. Utilizing synthetic biology to uncover basic principles of simpler circuits is a way to advance understanding of natural circadian clocks and rhythms. Following this strategy, we address the following questions: What are the implications of different architectures and molecular modes of transcriptional control for the phenotypic repertoire of genetic oscillators? Are there designs that are more realizable or robust? We compare synthetic oscillators involving one of three architectures and various combinations of the two modes of transcriptional control using a methodology that provides three innovations: a rigorous definition of phenotype, a procedure for deconstructing complex systems into qualitatively distinct phenotypes, and a graphical representation for illuminating the relationship between genotype, environment, and the qualitatively distinct phenotypes of a system. These methods provide a global perspective on the behavioral repertoire, facilitate comparisons of alternatives, and assist the rational design of synthetic gene circuitry. In particular, the results of their application here reveal distinctive phenotypes for several designs that have been studied experimentally as well as a best design among the alternatives that has yet to be constructed and tested.
-
Scognamiglio, Viviana; Antonacci, Amina; Lambreva, Maya D; Litescu, Simona C; Rea, Giuseppina
2015-12-15
Biosensors are powerful tunable systems able to switch between an ON/OFF status in response to an external stimulus. This extraordinary property could be engineered by adopting synthetic biology or biomimetic chemistry to obtain tailor-made biosensors having the desired requirements of robustness, sensitivity and detection range. Recent advances in both disciplines, in fact, allow to re-design the configuration of the sensing elements - either by modifying toggle switches and gene networks, or by producing synthetic entities mimicking key properties of natural molecules. The present review considered the role of synthetic biology in sustaining biosensor technology, reporting examples from the literature and reflecting on the features that make it a useful tool for designing and constructing engineered biological systems for sensing application. Besides, a section dedicated to bioinspired synthetic molecules as powerful tools to enhance biosensor potential is reported, and treated as an extension of the concept of biomimetic chemistry, where organic synthesis is used to generate artificial molecules that mimic natural molecules. Thus, the design of synthetic molecules, such as aptamers, biomimetics, molecular imprinting polymers, peptide nucleic acids, and ribozymes were encompassed as "products" of biomimetic chemistry. Copyright © 2015 Elsevier B.V. All rights reserved.
-
Kaznessis, Yiannis N
2007-11-06
Synthetic biological engineering is emerging from biology as a distinct discipline based on quantification. The technologies propelling synthetic biology are not new, nor is the concept of designing novel biological molecules. What is new is the emphasis on system behavior. The objective is the design and construction of new biological devices and systems to deliver useful applications. Numerous synthetic gene circuits have been created in the past decade, including bistable switches, oscillators, and logic gates, and possible applications abound, including biofuels, detectors for biochemical and chemical weapons, disease diagnosis, and gene therapies. More than fifty years after the discovery of the molecular structure of DNA, molecular biology is mature enough for real quantification that is useful for biological engineering applications, similar to the revolution in modeling in chemistry in the 1950s. With the excitement that synthetic biology is generating, the engineering and biological science communities appear remarkably willing to cross disciplinary boundaries toward a common goal.
-
Engineering Robustness of Microbial Cell Factories.
Gong, Zhiwei; Nielsen, Jens; Zhou, Yongjin J
2017-10-01
Metabolic engineering and synthetic biology offer great prospects in developing microbial cell factories capable of converting renewable feedstocks into fuels, chemicals, food ingredients, and pharmaceuticals. However, prohibitively low production rate and mass concentration remain the major hurdles in industrial processes even though the biosynthetic pathways are comprehensively optimized. These limitations are caused by a variety of factors unamenable for host cell survival, such as harsh industrial conditions, fermentation inhibitors from biomass hydrolysates, and toxic compounds including metabolic intermediates and valuable target products. Therefore, engineered microbes with robust phenotypes is essential for achieving higher yield and productivity. In this review, the recent advances in engineering robustness and tolerance of cell factories is described to cope with these issues and briefly introduce novel strategies with great potential to enhance the robustness of cell factories, including metabolic pathway balancing, transporter engineering, and adaptive laboratory evolution. This review also highlights the integration of advanced systems and synthetic biology principles toward engineering the harmony of overall cell function, more than the specific pathways or enzymes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
-
Zess, Erin K; Begemann, Matthew B; Pfleger, Brian F
2016-02-01
Predictive control of gene expression is an essential tool for developing synthetic biological systems. The current toolbox for controlling gene expression in cyanobacteria is a barrier to more in-depth genetic analysis and manipulation. Towards relieving this bottleneck, this work describes the use of synthetic biology to construct an anhydrotetracycline-based induction system and adapt a trans-acting small RNA (sRNA) system for use in the cyanobacterium Synechococcus sp. strain PCC 7002. An anhydrotetracycline-inducible promoter was developed to maximize intrinsic strength and dynamic range. The resulting construct, PEZtet , exhibited tight repression and a maximum 32-fold induction upon addition of anhydrotetracycline. Additionally, a sRNA system based on the Escherichia coli IS10 RNA-IN/OUT regulator was adapted for use in Synechococcus sp. strain PCC 7002. This system exhibited 70% attenuation of target gene expression, providing a demonstration of the use of sRNAs for differential gene expression in cyanobacteria. These systems were combined to produce an inducible sRNA system, which demonstrated 59% attenuation of target gene expression. Lastly, the role of Hfq, a critical component of sRNA systems in E. coli, was investigated. Genetic studies showed that the Hfq homolog in Synechococcus sp. strain PCC 7002 did not impact repression by the engineered sRNA system. In summary, this work describes new synthetic biology tools that can be applied to physiological studies, metabolic engineering, or sRNA platforms in Synechococcus sp. strain PCC 7002. © 2015 Wiley Periodicals, Inc.
-
Tunable promoters in synthetic and systems biology
DEFF Research Database (Denmark)
Dehli, Tore; Solem, Christian; Jensen, Peter Ruhdal
2012-01-01
in synthetic biology. A number of tools exist to manipulate the steps in between gene sequence and functional protein in living cells, but out of these the most straight-forward approach is to alter the gene expression level by manipulating the promoter sequence. Some of the promoter tuning tools available......Synthetic and systems biologists need standardized, modular and orthogonal tools yielding predictable functions in vivo. In systems biology such tools are needed to quantitatively analyze the behavior of biological systems while the efficient engineering of artificial gene networks is central...... for accomplishing such altered gene expression levels are discussed here along with examples of their use, and ideas for new tools are described. The road ahead looks very promising for synthetic and systems biologists as tools to achieve just about anything in terms of tuning and timing multiple gene expression...
-
Directory of Open Access Journals (Sweden)
Mohammad Manir Hossain Mollah
Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large
-
Schreiber, Tom; Tissier, Alain
2017-01-01
Transcription factors with programmable DNA-binding specificity constitute valuable tools for the design of orthogonal gene regulatory networks for synthetic biology. Transcription activator-like effectors (TALEs), as natural transcription regulators, were used to design, build, and test libraries of synthetic TALE-activated promoters (STAPs) that show a broad range of expression levels in plants. In this chapter, we present protocols for the construction of artificial TALEs and corresponding STAPs.
-
International Nuclear Information System (INIS)
Archer, Eric; Süel, Gürol M
2013-01-01
Despite their obvious relationship and overlap, the field of physics is blessed with many insightful laws, while such laws are sadly absent in biology. Here we aim to discuss how the rise of a more recent field known as synthetic biology may allow us to more directly test hypotheses regarding the possible design principles of natural biological networks and systems. In particular, this review focuses on synthetic gene regulatory networks engineered to perform specific functions or exhibit particular dynamic behaviors. Advances in synthetic biology may set the stage to uncover the relationship of potential biological principles to those developed in physics. (review article)
-
Steiner, Christopher F.
2012-01-01
The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934
-
Challenges for the European governance of synthetic biology for human health
Stemerding, D.; Douglas, C.
2014-01-01
Synthetic biology is a series of scientific and technological practices involved in the application of engineering principles to the design and production of predictable and robust biological systems. While policy discussions abound in this area, emerging technologies like synthetic biology present
-
Indirect two-sided relative ranking: a robust similarity measure for gene expression data
Directory of Open Access Journals (Sweden)
Licamele Louis
2010-03-01
Full Text Available Abstract Background There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights. Results In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries. Conclusions We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public. We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related cell types. Even in the absence of a known (i.e., labeled experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.
-
The cellular robustness by genetic redundancy in budding yeast.
Directory of Open Access Journals (Sweden)
Jingjing Li
2010-11-01
Full Text Available The frequent dispensability of duplicated genes in budding yeast is heralded as a hallmark of genetic robustness contributed by genetic redundancy. However, theoretical predictions suggest such backup by redundancy is evolutionarily unstable, and the extent of genetic robustness contributed from redundancy remains controversial. It is anticipated that, to achieve mutual buffering, the duplicated paralogs must at least share some functional overlap. However, counter-intuitively, several recent studies reported little functional redundancy between these buffering duplicates. The large yeast genetic interactions released recently allowed us to address these issues on a genome-wide scale. We herein characterized the synthetic genetic interactions for ∼500 pairs of yeast duplicated genes originated from either whole-genome duplication (WGD or small-scale duplication (SSD events. We established that functional redundancy between duplicates is a pre-requisite and thus is highly predictive of their backup capacity. This observation was particularly pronounced with the use of a newly introduced metric in scoring functional overlap between paralogs on the basis of gene ontology annotations. Even though mutual buffering was observed to be prevalent among duplicated genes, we showed that the observed backup capacity is largely an evolutionarily transient state. The loss of backup capacity generally follows a neutral mode, with the buffering strength decreasing in proportion to divergence time, and the vast majority of the paralogs have already lost their backup capacity. These observations validated previous theoretic predictions about instability of genetic redundancy. However, departing from the general neutral mode, intriguingly, our analysis revealed the presence of natural selection in stabilizing functional overlap between SSD pairs. These selected pairs, both WGD and SSD, tend to have decelerated functional evolution, have higher propensities of co
-
Lukes, George E.; Cain, Joel M.
1996-02-01
The Advanced Distributed Simulation (ADS) Synthetic Environments Program seeks to create robust virtual worlds from operational terrain and environmental data sources of sufficient fidelity and currency to interact with the real world. While some applications can be met by direct exploitation of standard digital terrain data, more demanding applications -- particularly those support operations 'close to the ground' -- are well-served by emerging capabilities for 'value-adding' by the user working with controlled imagery. For users to rigorously refine and exploit controlled imagery within functionally different workstations they must have a shared framework to allow interoperability within and between these environments in terms of passing image and object coordinates and other information using a variety of validated sensor models. The Synthetic Environments Program is now being expanded to address rapid construction of virtual worlds with research initiatives in digital mapping, softcopy workstations, and cartographic image understanding. The Synthetic Environments Program is also participating in a joint initiative for a sensor model applications programer's interface (API) to ensure that a common controlled imagery exploitation framework is available to all researchers, developers and users. This presentation provides an introduction to ADS and the associated requirements for synthetic environments to support synthetic theaters of war. It provides a technical rationale for exploring applications of image understanding technology to automated cartography in support of ADS and related programs benefitting from automated analysis of mapping, earth resources and reconnaissance imagery. And it provides an overview and status of the joint initiative for a sensor model API.
-
Directory of Open Access Journals (Sweden)
Dipak K. Sahoo
2014-01-01
Full Text Available To enhance the natural plant resistance and to evaluate the antimicrobial properties of phylloplanin against blue mold, we have expressed a synthetic chimeric native-phylloplanin-GFP protein fusion in transgenic Nicotiana tabacum cv. KY14, a cultivar that is highly susceptible to infection by Peronospora tabacina. The coding sequence of the tobacco phylloplanin gene along with its native signal peptide was fused with GFP at the carboxy terminus. The synthetic chimeric gene (native-phylloplanin-GFP was placed between the modified Mirabilis mosaic virus full-length transcript promoter with duplicated enhancer domains and the terminator sequence from the rbcSE9 gene. The chimeric gene, expressed in transgenic tobacco, was stably inherited in successive plant generations as shown by molecular characterization, GFP quantification, and confocal fluorescent microscopy. Transgenic plants were morphologically similar to wild-type plants and showed no deleterious effects due to transgene expression. Blue mold-sensitivity assays of tobacco lines were performed by applying P. tabacina sporangia to the upper leaf surface. Transgenic lines expressing the fused synthetic native-phyllopanin-GFP gene in the leaf apoplast showed resistance to infection. Our results demonstrate that in vivo expression of a synthetic fused native-phylloplanin-GFP gene in plants can potentially achieve natural protection against microbial plant pathogens, including P. tabacina in tobacco.
-
Super-delta: a new differential gene expression analysis procedure with robust data normalization.
Liu, Yuhang; Zhang, Jinfeng; Qiu, Xing
2017-12-21
Normalization is an important data preparation step in gene expression analyses, designed to remove various systematic noise. Sample variance is greatly reduced after normalization, hence the power of subsequent statistical analyses is likely to increase. On the other hand, variance reduction is made possible by borrowing information across all genes, including differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias. This bias typically inflates type I error; and can reduce statistical power in certain situations. In this study we propose a new differential expression analysis pipeline, dubbed as super-delta, that consists of a multivariate extension of the global normalization and a modified t-test. A robust procedure is designed to minimize the bias introduced by DEGs in the normalization step. The modified t-test is derived based on asymptotic theory for hypothesis testing that suitably pairs with the proposed robust normalization. We first compared super-delta with four commonly used normalization methods: global, median-IQR, quantile, and cyclic loess normalization in simulation studies. Super-delta was shown to have better statistical power with tighter control of type I error rate than its competitors. In many cases, the performance of super-delta is close to that of an oracle test in which datasets without technical noise were used. We then applied all methods to a collection of gene expression datasets on breast cancer patients who received neoadjuvant chemotherapy. While there is a substantial overlap of the DEGs identified by all of them, super-delta were able to identify comparatively more DEGs than its competitors. Downstream gene set enrichment analysis confirmed that all these methods selected largely consistent pathways. Detailed investigations on the relatively small differences showed that pathways identified by super-delta have better connections to breast cancer than other methods. As a new pipeline, super
-
Clayton, M A; Clayton, J M; Brown, D R; Middlebrook, J L
1995-01-01
A completely synthetic gene encoding fragment C, a approximately 50-kDa fragment, of botulinum neurotoxin serotype A was constructed from oligonucleotides. The gene was expressed in Escherichia coli, and full-sized product was produced as judged by Western blot (immunoblot) analysis. Crude extracts of E. coli expressing the gene were used to vaccinate mice and evaluate their survival against challenge with active toxin. Mice given three subcutaneous vaccinations were protected against an intr...
-
Fang, Xin; Sastry, Anand; Mih, Nathan; Kim, Donghyuk; Tan, Justin; Lloyd, Colton J.; Gao, Ye; Yang, Laurence; Palsson, Bernhard O.
2017-01-01
Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN—probably the best characterized TRN—several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predict gene expression using this TRN; and (iii) how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes. The 3,797 high-confidence regulatory interactions were collected from published, validated chromatin immunoprecipitation (ChIP) data and RegulonDB. For 21 different TF knockouts, up to 63% of the differentially expressed genes in the hiTRN were traced to the knocked-out TF through regulatory cascades. Second, we trained supervised machine learning algorithms to predict the expression of 1,364 TUs given TF activities using 441 samples. The algorithms accurately predicted condition-specific expression for 86% (1,174 of 1,364) of the TUs, while 193 TUs (14%) were predicted better than random TRNs. Third, we identified 10 regulatory modules whose definitions were robust against changes to the TRN or expression compendium. Using surrogate variable analysis, we also identified three unmodeled factors that systematically influenced gene expression. Our computational workflow comprehensively characterizes the predictive capabilities and systems-level functions of an organism’s TRN from disparate data types. PMID:28874552
-
Directory of Open Access Journals (Sweden)
Li He
2014-01-01
Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.
-
Yang, Hongxin; Su, Fulin
2018-01-01
We propose a moving target analysis algorithm using speeded-up robust features (SURF) and regular moment in inverse synthetic aperture radar (ISAR) image sequences. In our study, we first extract interest points from ISAR image sequences by SURF. Different from traditional feature point extraction methods, SURF-based feature points are invariant to scattering intensity, target rotation, and image size. Then, we employ a bilateral feature registering model to match these feature points. The feature registering scheme can not only search the isotropic feature points to link the image sequences but also reduce the error matching pairs. After that, the target centroid is detected by regular moment. Consequently, a cost function based on correlation coefficient is adopted to analyze the motion information. Experimental results based on simulated and real data validate the effectiveness and practicability of the proposed method.
-
Shrinkage covariance matrix approach based on robust trimmed mean in gene sets detection
Karjanto, Suryaefiza; Ramli, Norazan Mohamed; Ghani, Nor Azura Md; Aripin, Rasimah; Yusop, Noorezatty Mohd
2015-02-01
Microarray involves of placing an orderly arrangement of thousands of gene sequences in a grid on a suitable surface. The technology has made a novelty discovery since its development and obtained an increasing attention among researchers. The widespread of microarray technology is largely due to its ability to perform simultaneous analysis of thousands of genes in a massively parallel manner in one experiment. Hence, it provides valuable knowledge on gene interaction and function. The microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints. Therefore, the sample covariance matrix in Hotelling's T2 statistic is not positive definite and become singular, thus it cannot be inverted. In this research, the Hotelling's T2 statistic is combined with a shrinkage approach as an alternative estimation to estimate the covariance matrix to detect significant gene sets. The use of shrinkage covariance matrix overcomes the singularity problem by converting an unbiased to an improved biased estimator of covariance matrix. Robust trimmed mean is integrated into the shrinkage matrix to reduce the influence of outliers and consequently increases its efficiency. The performance of the proposed method is measured using several simulation designs. The results are expected to outperform existing techniques in many tested conditions.
-
Kageyama, Hakuto; Waditee-Sirisattha, Rungaroon; Sirisattha, Sophon; Tanaka, Yoshito; Mahakhant, Aparat; Takabe, Teruhiro
2015-07-01
Cyanobacteria possess the unique capacity to produce alkane. In this study, effects of nitrogen deficiency and salt stress on biosynthesis of alkanes were investigated in three kinds of cyanobacteria. Intracellular alkane accumulation was increased in nitrogen-fixing cyanobacterium Anabaena sp. PCC7120, but decreased in non-diazotrophic cyanobacterium Synechococcus elongatus PCC7942 and constant in a halotolerant cyanobacterium Aphanothece halophytica under nitrogen-deficient condition. We also found that salt stress increased alkane accumulation in Anabaena sp. PCC7120 and A. halophytica. The expression levels of two alkane synthetic genes were not upregulated significantly under nitrogen deficiency or salt stress in Anabaena sp. PCC7120. The transformant Anabaena sp. PCC7120 cells with additional alkane synthetic gene set from A. halophytica increased intracellular alkane accumulation level compared to control cells. These results provide a prospect to improve bioproduction of alkanes in nitrogen-fixing halotolerant cyanobacteria via abiotic stresses and genetic engineering.
-
Yeast synthetic biology toolbox and applications for biofuel production.
Tsai, Ching-Sung; Kwak, Suryang; Turner, Timothy L; Jin, Yong-Su
2015-02-01
Yeasts are efficient biofuel producers with numerous advantages outcompeting bacterial counterparts. While most synthetic biology tools have been developed and customized for bacteria especially for Escherichia coli, yeast synthetic biological tools have been exploited for improving yeast to produce fuels and chemicals from renewable biomass. Here we review the current status of synthetic biological tools and their applications for biofuel production, focusing on the model strain Saccharomyces cerevisiae We describe assembly techniques that have been developed for constructing genes, pathways, and genomes in yeast. Moreover, we discuss synthetic parts for allowing precise control of gene expression at both transcriptional and translational levels. Applications of these synthetic biological approaches have led to identification of effective gene targets that are responsible for desirable traits, such as cellulosic sugar utilization, advanced biofuel production, and enhanced tolerance against toxic products for biofuel production from renewable biomass. Although an array of synthetic biology tools and devices are available, we observed some gaps existing in tool development to achieve industrial utilization. Looking forward, future tool development should focus on industrial cultivation conditions utilizing industrial strains. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.
-
Synthetic analog computation in living cells.
Daniel, Ramiz; Rubens, Jacob R; Sarpeshkar, Rahul; Lu, Timothy K
2013-05-30
A central goal of synthetic biology is to achieve multi-signal integration and processing in living cells for diagnostic, therapeutic and biotechnology applications. Digital logic has been used to build small-scale circuits, but other frameworks may be needed for efficient computation in the resource-limited environments of cells. Here we demonstrate that synthetic analog gene circuits can be engineered to execute sophisticated computational functions in living cells using just three transcription factors. Such synthetic analog gene circuits exploit feedback to implement logarithmically linear sensing, addition, ratiometric and power-law computations. The circuits exhibit Weber's law behaviour as in natural biological systems, operate over a wide dynamic range of up to four orders of magnitude and can be designed to have tunable transfer functions. Our circuits can be composed to implement higher-order functions that are well described by both intricate biochemical models and simple mathematical functions. By exploiting analog building-block functions that are already naturally present in cells, this approach efficiently implements arithmetic operations and complex functions in the logarithmic domain. Such circuits may lead to new applications for synthetic biology and biotechnology that require complex computations with limited parts, need wide-dynamic-range biosensing or would benefit from the fine control of gene expression.
-
Agapakis, Christina M
2014-03-21
Synthetic biology is frequently defined as the application of engineering design principles to biology. Such principles are intended to streamline the practice of biological engineering, to shorten the time required to design, build, and test synthetic gene networks. This streamlining of iterative design cycles can facilitate the future construction of biological systems for a range of applications in the production of fuels, foods, materials, and medicines. The promise of these potential applications as well as the emphasis on design has prompted critical reflection on synthetic biology from design theorists and practicing designers from many fields, who can bring valuable perspectives to the discipline. While interdisciplinary connections between biologists and engineers have built synthetic biology via the science and the technology of biology, interdisciplinary collaboration with artists, designers, and social theorists can provide insight on the connections between technology and society. Such collaborations can open up new avenues and new principles for research and design, as well as shed new light on the challenging context-dependence-both biological and social-that face living technologies at many scales. This review is inspired by the session titled "Design and Synthetic Biology: Connecting People and Technology" at Synthetic Biology 6.0 and covers a range of literature on design practice in synthetic biology and beyond. Critical engagement with how design is used to shape the discipline opens up new possibilities for how we might design the future of synthetic biology.
-
International Nuclear Information System (INIS)
Korkola, James E; Waldman, Frederic M; Blaveri, Ekaterina; DeVries, Sandy; Moore, Dan H II; Hwang, E Shelley; Chen, Yunn-Yi; Estep, Anne LH; Chew, Karen L; Jensen, Ronald H
2007-01-01
Breast cancer is a heterogeneous disease, presenting with a wide range of histologic, clinical, and genetic features. Microarray technology has shown promise in predicting outcome in these patients. We profiled 162 breast tumors using expression microarrays to stratify tumors based on gene expression. A subset of 55 tumors with extensive follow-up was used to identify gene sets that predicted outcome. The predictive gene set was further tested in previously published data sets. We used different statistical methods to identify three gene sets associated with disease free survival. A fourth gene set, consisting of 21 genes in common to all three sets, also had the ability to predict patient outcome. To validate the predictive utility of this derived gene set, it was tested in two published data sets from other groups. This gene set resulted in significant separation of patients on the basis of survival in these data sets, correctly predicting outcome in 62–65% of patients. By comparing outcome prediction within subgroups based on ER status, grade, and nodal status, we found that our gene set was most effective in predicting outcome in ER positive and node negative tumors. This robust gene selection with extensive validation has identified a predictive gene set that may have clinical utility for outcome prediction in breast cancer patients
-
DAF-12 Regulates a Connected Network of Genes to Ensure Robust Developmental Decisions
Stuckenholz, Carsten; Labhart, Paul; Alexiadis, Vassili; Martin, René; Knölker, Hans-Joachim; Fisher, Alfred L.
2011-01-01
The nuclear receptor DAF-12 has roles in normal development, the decision to pursue dauer development in unfavorable conditions, and the modulation of adult aging. Despite the biologic importance of DAF-12, target genes for this receptor are largely unknown. To identify DAF-12 targets, we performed chromatin immunoprecipitation followed by hybridization to whole-genome tiling arrays. We identified 1,175 genomic regions to be bound in vivo by DAF-12, and these regions are enriched in known DAF-12 binding motifs and act as DAF-12 response elements in transfected cells and in transgenic worms. The DAF-12 target genes near these binding sites include an extensive network of interconnected heterochronic and microRNA genes. We also identify the genes encoding components of the miRISC, which is required for the control of target genes by microRNA, as a target of DAF-12 regulation. During reproductive development, many of these target genes are misregulated in daf-12(0) mutants, but this only infrequently results in developmental phenotypes. In contrast, we and others have found that null daf-12 mutations enhance the phenotypes of many miRISC and heterochronic target genes. We also find that environmental fluctuations significantly strengthen the weak heterochronic phenotypes of null daf-12 alleles. During diapause, DAF-12 represses the expression of many heterochronic and miRISC target genes, and prior work has demonstrated that dauer formation can suppress the heterochronic phenotypes of many of these target genes in post-dauer development. Together these data are consistent with daf-12 acting to ensure developmental robustness by committing the animal to adult or dauer developmental programs despite variable internal or external conditions. PMID:21814518
-
Ethical perception of synthetic biology | Amin | African Journal of ...
African Journals Online (AJOL)
Modern biotechnology has moved forward by the introduction of the synthetic biology technique. By using synthetic biology, it is possible to construct mice genes in the laboratory and replace the need for the genes to be split out from the original animal. The purpose of this paper is to examine how the public in the Klang ...
-
Synthetic biology: Novel approaches for microbiology.
Padilla-Vaca, Felipe; Anaya-Velázquez, Fernando; Franco, Bernardo
2015-06-01
In the past twenty years, molecular genetics has created powerful tools for genetic manipulation of living organisms. Whole genome sequencing has provided necessary information to assess knowledge on gene function and protein networks. In addition, new tools permit to modify organisms to perform desired tasks. Gene function analysis is speed up by novel approaches that couple both high throughput data generation and mining. Synthetic biology is an emerging field that uses tools for generating novel gene networks, whole genome synthesis and engineering. New applications in biotechnological, pharmaceutical and biomedical research are envisioned for synthetic biology. In recent years these new strategies have opened up the possibilities to study gene and genome editing, creation of novel tools for functional studies in virus, parasites and pathogenic bacteria. There is also the possibility to re-design organisms to generate vaccine subunits or produce new pharmaceuticals to combat multi-drug resistant pathogens. In this review we provide our opinion on the applicability of synthetic biology strategies for functional studies of pathogenic organisms and some applications such as genome editing and gene network studies to further comprehend virulence factors and determinants in pathogenic organisms. We also discuss what we consider important ethical issues for this field of molecular biology, especially for potential misuse of the new technologies. Copyright© by the Spanish Society for Microbiology and Institute for Catalan Studies.
-
Synthetic biology era: Improving antibiotic's world.
Guzmán-Trampe, Silvia; Ceapa, Corina D; Manzo-Ruiz, Monserrat; Sánchez, Sergio
2017-06-15
The emergence of antibiotic-resistant pathogen microorganisms is problematic in the context of the current spectrum of available medication. The poor specificity and the high toxicity of some available molecules have made imperative the search for new strategies to improve the specificity and to pursue the discovery of novel compounds with increased bioactivity. Using living cells as platforms, synthetic biology has counteracted this problem by offering novel pathways to create synthetic systems with improved and desired functions. Among many other biotechnological approaches, the advances in synthetic biology have made it possible to design and construct novel biological systems in order to look for new drugs with increased bioactivity. Advancements have also been made in the redesigning of RNA and DNA molecules in order to engineer antibiotic clusters for antibiotic overexpression. As for the production of these antibacterial compounds, yeasts and filamentous fungi as well as gene therapy are utilized to enhance protein solubility. Specific delivery is achieved by creating chimeras using plant genes into bacterial hosts. Some of these synthetic systems are currently in clinical trials, proving the proficiency of synthetic biology in terms of both pharmacological activities as well as an increase in the biosafety of treatments. It is possible that we may just be seeing the tip of the iceberg, and synthetic biology applications will overpass expectations beyond our present knowledge. Copyright © 2017. Published by Elsevier Inc.
-
Effects of sample size on robustness and prediction accuracy of a prognostic gene signature
Directory of Open Access Journals (Sweden)
Kim Seon-Young
2009-05-01
Full Text Available Abstract Background Few overlap between independently developed gene signatures and poor inter-study applicability of gene signatures are two of major concerns raised in the development of microarray-based prognostic gene signatures. One recent study suggested that thousands of samples are needed to generate a robust prognostic gene signature. Results A data set of 1,372 samples was generated by combining eight breast cancer gene expression data sets produced using the same microarray platform and, using the data set, effects of varying samples sizes on a few performances of a prognostic gene signature were investigated. The overlap between independently developed gene signatures was increased linearly with more samples, attaining an average overlap of 16.56% with 600 samples. The concordance between predicted outcomes by different gene signatures also was increased with more samples up to 94.61% with 300 samples. The accuracy of outcome prediction also increased with more samples. Finally, analysis using only Estrogen Receptor-positive (ER+ patients attained higher prediction accuracy than using both patients, suggesting that sub-type specific analysis can lead to the development of better prognostic gene signatures Conclusion Increasing sample sizes generated a gene signature with better stability, better concordance in outcome prediction, and better prediction accuracy. However, the degree of performance improvement by the increased sample size was different between the degree of overlap and the degree of concordance in outcome prediction, suggesting that the sample size required for a study should be determined according to the specific aims of the study.
-
Design principles for robust oscillatory behavior.
Castillo-Hair, Sebastian M; Villota, Elizabeth R; Coronado, Alberto M
2015-09-01
Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.
-
Lu, Tao
2016-01-01
The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.
-
Interdependence of cell growth and gene expression: origins and consequences.
Scott, Matthew; Gunderson, Carl W; Mateescu, Eduard M; Zhang, Zhongge; Hwa, Terence
2010-11-19
In bacteria, the rate of cell proliferation and the level of gene expression are intimately intertwined. Elucidating these relations is important both for understanding the physiological functions of endogenous genetic circuits and for designing robust synthetic systems. We describe a phenomenological study that reveals intrinsic constraints governing the allocation of resources toward protein synthesis and other aspects of cell growth. A theory incorporating these constraints can accurately predict how cell proliferation and gene expression affect one another, quantitatively accounting for the effect of translation-inhibiting antibiotics on gene expression and the effect of gratuitous protein expression on cell growth. The use of such empirical relations, analogous to phenomenological laws, may facilitate our understanding and manipulation of complex biological systems before underlying regulatory circuits are elucidated.
-
Super-Resolution for Synthetic Zooming
Directory of Open Access Journals (Sweden)
Li Xin
2006-01-01
Full Text Available Optical zooming is an important feature of imaging systems. In this paper, we investigate a low-cost signal processing alternative to optical zooming—synthetic zooming by super-resolution (SR techniques. Synthetic zooming is achieved by registering a sequence of low-resolution (LR images acquired at varying focal lengths and reconstructing the SR image at a larger focal length or increased spatial resolution. Under the assumptions of constant scene depth and zooming speed, we argue that the motion trajectories of all physical points are related to each other by a unique vanishing point and present a robust technique for estimating its D coordinate. Such a line-geometry-based registration is the foundation of SR for synthetic zooming. We address the issue of data inconsistency arising from the varying focal length of optical lens during the zooming process. To overcome the difficulty of data inconsistency, we propose a two-stage Delaunay-triangulation-based interpolation for fusing the LR image data. We also present a PDE-based nonlinear deblurring to accommodate the blindness and variation of sensor point spread functions. Simulation results with real-world images have verified the effectiveness of the proposed SR techniques for synthetic zooming.
-
Directory of Open Access Journals (Sweden)
Mir A Hossain
2016-01-01
Full Text Available Reactivation of γ-globin expression has been shown to ameliorate disease phenotypes associated with mutations in the adult β-globin gene, including sickle cell disease. Specific mutations in the promoter of the γ-globin genes are known to prevent repression of the genes in the adult and thus lead to hereditary persistence of fetal hemoglobin. One such hereditary persistence of fetal hemoglobin is associated with a sequence located 567 bp upstream of the Gγ-globin gene which assembles a GATA-containing repressor complex. We generated two synthetic zinc-finger DNA-binding domains (ZF-DBDs targeting this sequence. The -567Gγ ZF-DBDs associated with high affinity and specificity with the target site in the γ-globin gene promoter. We delivered the -567Gγ ZF-DBDs directly to primary erythroid cells. Exposure of these cells to the recombinant -567Gγ ZF-DBDs led to increased expression of the γ-globin gene. Direct protein delivery of ZF-DBDs that compete with transcription regulatory proteins will have broad implications for modulating gene expression in analytical or therapeutic settings.
-
International Nuclear Information System (INIS)
Munir, I.; Hussan, W.; Kazi, M.; Mian, A.
2016-01-01
Brassica juncea is an important oil seed crop throughout the world. The demand and cultivation of oil seed crops has gained importance due to rapid increase in world population and industrialization. Fungal diseases pose a great threat to Brassica productivity worldwide. Absence of resistance genes against fungal infection within crossable germplasms of this crop necessitates deployment of genetic engineering approaches to produce transgenic plants with resistance against fungal infections. In the current study, hypocotyls and cotyledons of Brassica juncea, used as explants, were transformed with Agrobacterium tumefacien strain EHA101 harboring binary vector pEKB/NIC containing synthetic chitinase gene (NIC), an antifungal gene under the control of cauliflower mosaic virus promoter (CaMV35S). Bar genes and nptII gene were used as selectable markers. Presence of chitinase gene in trangenic lines was confirmed by PCR and southern blotting analysis. Effect of the extracted proteins from non-transgenic and transgenic lines was observed on the growth of Alternaria brassicicola, a common disease causing pathogen in brassica crop. In comparison to non-transgenic control lines, the leaf tissue extracts of the transgenic lines showed considerable resistance and antifungal activity against A. brassicicola. The antifungal activity in transgenic lines was observed as corresponding to the transgene copy number. (author)
-
New Frontiers in Synthetic Biology for Spaceflight
Galazka, Jonathan M.
2017-01-01
Exploration of the solar system is constrained by the cost of moving mass off Earth. Producing materials in situ will reduce the mass that must be delivered from earth. CO2 is abundant on Mars and manned spacecraft. On the ISS, NASA reacts excess CO2 with H2 to generate CH4 and H2O using the Sabatier System. The resulting water is recovered into the ISS, but the methane is vented to space. Thus, there is a capability need for systems that convert methane into valuable materials. Methanotrophic bacteria consume methane but these are poor synthetic biology platforms. Thus, there is a knowledge gap in utilizing methane in a robust and flexible synthetic biology platform. The yeast Pichia pastoris is a refined microbial factory that is used widely by industry because it efficiently secretes products. Pichia could produce a variety of useful products in space. Pichia does not consume methane but robustly consumes methanol, which is one enzymatic step removed from methane. Our goal is to engineer Pichia to consume methane thereby creating a powerful methane-consuming microbial factory.
-
Directory of Open Access Journals (Sweden)
Kristen K. Merritt
2014-10-01
Full Text Available Background: Many synthetic biologists seek to increase the degree of autonomy in the assembly of long DNA (L-DNA constructs from short synthetic DNA fragments, which are today quite inexpensive because of automated solid-phase synthesis. However, the low information density of DNA built from just four nucleotide “letters”, the presence of strong (G:C and weak (A:T nucleobase pairs, the non-canonical folded structures that compete with Watson–Crick pairing, and other features intrinsic to natural DNA, generally prevent the autonomous assembly of short single-stranded oligonucleotides greater than a dozen or so.Results: We describe a new strategy to autonomously assemble L-DNA constructs from fragments of synthetic single-stranded DNA. This strategy uses an artificially expanded genetic information system (AEGIS that adds nucleotides to the four (G, A, C, and T found in standard DNA by shuffling hydrogen-bonding units on the nucleobases, all while retaining the overall Watson–Crick base-pairing geometry. The added information density allows larger numbers of synthetic fragments to self-assemble without off-target hybridization, hairpin formation, and non-canonical folding interactions. The AEGIS pairs are then converted into standard pairs to produce a fully natural L-DNA product. Here, we report the autonomous assembly of a gene encoding kanamycin resistance using this strategy. Synthetic fragments were built from a six-letter alphabet having two AEGIS components, 5-methyl-2’-deoxyisocytidine and 2’-deoxyisoguanosine (respectively S and B, at their overlapping ends. Gaps in the overlapped assembly were then filled in using DNA polymerases, and the nicks were sealed by ligase. The S:B pairs in the ligated construct were then converted to T:A pairs during PCR amplification. When cloned into a plasmid, the product was shown to make Escherichia coli resistant to kanamycin. A parallel study that attempted to assemble similarly sized genes
-
Kang, Zhen; Zhang, Junli; Jin, Peng; Yang, Sen
2015-01-01
Owing to our limited understanding of the relationship between sequence and function and the interaction between intracellular pathways and regulatory systems, the rational design of enzyme-coding genes and de novo assembly of a brand-new artificial genome for a desired functionality or phenotype are difficult to achieve. As an alternative approach, directed evolution has been widely used to engineer genomes and enzyme-coding genes. In particular, significant developments toward DNA synthesis, DNA assembly (in vitro or in vivo), recombination-mediated genetic engineering, and high-throughput screening techniques in the field of synthetic biology have been matured and widely adopted, enabling rapid semi-rational genome engineering to generate variants with desired properties. In this commentary, these novel tools and their corresponding applications in the directed evolution of genomes and enzymes are discussed. Moreover, the strategies for genome engineering and rapid in vitro enzyme evolution are also proposed.
-
Perspective: Evolution and detection of genetic robustness
Visser, de J.A.G.M.; Hermisson, J.; Wagner, G.P.; Ancel Meyers, L.; Bagheri-Chaichian, H.; Blanchard, J.L.; Chao, L.; Cheverud, J.M.; Elena, S.F.; Fontana, W.; Gibson, G.; Hansen, T.F.; Krakauer, D.; Lewontin, R.C.; Ofria, C.; Rice, S.H.; Dassow, von G.; Wagner, A.; Whitlock, M.C.
2003-01-01
Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms
-
TinkerCell: modular CAD tool for synthetic biology
Chandran, Deepak; Bergmann, Frank T; Sauro, Herbert M
2009-01-01
Background Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD) is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks. Results An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API). TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at . Conclusion An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled and analyzed computationally. TinkerCell can readily
-
TinkerCell: modular CAD tool for synthetic biology
Directory of Open Access Journals (Sweden)
Bergmann Frank T
2009-10-01
Full Text Available Abstract Background Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks. Results An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API. TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at http://www.tinkercell.com. Conclusion An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled
-
Directory of Open Access Journals (Sweden)
Han Kyungsook
2010-06-01
Full Text Available Abstract Background Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited for annotating gene functions and dissecting specific pathway structures. However, our understanding is rather limited to the relationship between double concurrent perturbation and various higher level phenotypic changes, e.g. those in cells, tissues or organs. Modifier screens, such as synthetic genetic arrays (SGA can help us to understand the phenotype caused by combined gene mutations. Unfortunately, exhaustive tests on all possible combined mutations in any genome are vulnerable to combinatorial explosion and are infeasible either technically or financially. Therefore, an accurate computational approach to predict genetic interaction is highly desirable, and such methods have the potential of alleviating the bottleneck on experiment design. Results In this work, we introduce a computational systems biology approach for the accurate prediction of pairwise synthetic genetic interactions (SGI. First, a high-coverage and high-precision functional gene network (FGN is constructed by integrating protein-protein interaction (PPI, protein complex and gene expression data; then, a graph-based semi-supervised learning (SSL classifier is utilized to identify SGI, where the topological properties of protein pairs in weighted FGN is used as input features of the classifier. We compare the proposed SSL method with the state-of-the-art supervised classifier, the support vector machines (SVM, on a benchmark dataset in S. cerevisiae to validate our method's ability to distinguish synthetic genetic interactions from non-interaction gene pairs. Experimental results show that the proposed method can accurately predict genetic interactions in S. cerevisiae (with a sensitivity of 92% and specificity of 91%. Noticeably, the SSL method is more efficient than SVM, especially for
-
Mammalian Synthetic Biology: Time for Big MACs.
Martella, Andrea; Pollard, Steven M; Dai, Junbiao; Cai, Yizhi
2016-10-21
The enabling technologies of synthetic biology are opening up new opportunities for engineering and enhancement of mammalian cells. This will stimulate diverse applications in many life science sectors such as regenerative medicine, development of biosensing cell lines, therapeutic protein production, and generation of new synthetic genetic regulatory circuits. Harnessing the full potential of these new engineering-based approaches requires the design and assembly of large DNA constructs-potentially up to chromosome scale-and the effective delivery of these large DNA payloads to the host cell. Random integration of large transgenes, encoding therapeutic proteins or genetic circuits into host chromosomes, has several drawbacks such as risks of insertional mutagenesis, lack of control over transgene copy-number and position-specific effects; these can compromise the intended functioning of genetic circuits. The development of a system orthogonal to the endogenous genome is therefore beneficial. Mammalian artificial chromosomes (MACs) are functional, add-on chromosomal elements, which behave as normal chromosomes-being replicating and portioned to daughter cells at each cell division. They are deployed as useful gene expression vectors as they remain independent from the host genome. MACs are maintained as a single-copy and can accommodate multiple gene expression cassettes of, in theory, unlimited DNA size (MACs up to 10 megabases have been constructed). MACs therefore enabled control over ectopic gene expression and represent an excellent platform to rapidly prototype and characterize novel synthetic gene circuits without recourse to engineering the host genome. This review describes the obstacles synthetic biologists face when working with mammalian systems and how the development of improved MACs can overcome these-particularly given the spectacular advances in DNA synthesis and assembly that are fuelling this research area.
-
Gene flow analysis method, the D-statistic, is robust in a wide parameter space.
Zheng, Yichen; Janke, Axel
2018-01-08
We evaluated the sensitivity of the D-statistic, a parsimony-like method widely used to detect gene flow between closely related species. This method has been applied to a variety of taxa with a wide range of divergence times. However, its parameter space and thus its applicability to a wide taxonomic range has not been systematically studied. Divergence time, population size, time of gene flow, distance of outgroup and number of loci were examined in a sensitivity analysis. The sensitivity study shows that the primary determinant of the D-statistic is the relative population size, i.e. the population size scaled by the number of generations since divergence. This is consistent with the fact that the main confounding factor in gene flow detection is incomplete lineage sorting by diluting the signal. The sensitivity of the D-statistic is also affected by the direction of gene flow, size and number of loci. In addition, we examined the ability of the f-statistics, [Formula: see text] and [Formula: see text], to estimate the fraction of a genome affected by gene flow; while these statistics are difficult to implement to practical questions in biology due to lack of knowledge of when the gene flow happened, they can be used to compare datasets with identical or similar demographic background. The D-statistic, as a method to detect gene flow, is robust against a wide range of genetic distances (divergence times) but it is sensitive to population size. The D-statistic should only be applied with critical reservation to taxa where population sizes are large relative to branch lengths in generations.
-
Directory of Open Access Journals (Sweden)
Leclerc Xavier
2009-04-01
Full Text Available Abstract Background Current strategies for gene therapy of inherited diseases consist in adding functional copies of the gene that is defective. An attractive alternative to these approaches would be to correct the endogenous mutated gene in the affected individual. This study presents a quantitative comparison of the repair efficiency using different forms of donor nucleic acids, including synthetic DNA oligonucleotides, double stranded DNA fragments with sizes ranging from 200 to 2200 bp and sequences carried by a recombinant adeno-associated virus (rAAV-1. Evaluation of each gene repair strategy was carried out using two different reporter systems, a mutated eGFP gene or a dual construct with a functional eGFP and an inactive luciferase gene, in several different cell systems. Gene targeting events were scored either following transient co-transfection of reporter plasmids and donor DNAs, or in a system where a reporter construct was stably integrated into the chromosome. Results In both episomal and chromosomal assays, DNA fragments were more efficient at gene repair than oligonucleotides or rAAV-1. Furthermore, the gene targeting frequency could be significantly increased by using DNA repair stimulating drugs such as doxorubicin and phleomycin. Conclusion Our results show that it is possible to obtain repair frequencies of 1% of the transfected cell population under optimized transfection protocols when cells were pretreated with phleomycin using rAAV-1 and dsDNA fragments.
-
Synthetic Biology: Applications in the Food Sector.
Tyagi, Ashish; Kumar, Ashwani; Aparna, S V; Mallappa, Rashmi H; Grover, Sunita; Batish, Virender Kumar
2016-08-17
Synthetic biology also termed as "genomic alchemy" represents a powerful area of science that is based on the convergence of biological sciences with systems engineering. It has been fittingly described as "moving from reading the genetic code to writing it" as it focuses on building, modeling, designing and fabricating novel biological systems using customized gene components that result in artificially created genetic circuitry. The scientifically compelling idea of the technological manipulation of life has been advocated since long time. Realization of this idea has gained momentum with development of high speed automation and the falling cost of gene sequencing and synthesis following the completion of the human genome project. Synthetic biology will certainly be instrumental in shaping the development of varying areas ranging from biomedicine, biopharmaceuticals, chemical production, food and dairy quality monitoring, packaging, and storage of food and dairy products, bioremediation and bioenergy production, etc. However, potential dangers of using synthetic life forms have to be acknowledged and adoption of policies by the scientific community to ensure safe practice while making important advancements in the ever expanding field of synthetic biology is to be fully supported and implemented.
-
[Applications of synthetic biology in materials science].
Zhao, Tianxin; Zhong, Chao
2017-03-25
Materials are the basis for human being survival and social development. To keep abreast with the increasing needs from all aspects of human society, there are huge needs in the development of advanced materials as well as high-efficiency but low-cost manufacturing strategies that are both sustainable and tunable. Synthetic biology, a new engineering principle taking gene regulation and engineering design as the core, greatly promotes the development of life sciences. This discipline has also contributed to the development of material sciences and will continuously bring new ideas to future new material design. In this paper, we review recent advances in applications of synthetic biology in material sciences, with the focus on how synthetic biology could enable synthesis of new polymeric biomaterials and inorganic materials, phage display and directed evolution of proteins relevant to materials development, living functional materials, engineered bacteria-regulated artificial photosynthesis system as well as applications of gene circuits for material sciences.
-
A robust data-driven approach for gene ontology annotation.
Li, Yanpeng; Yu, Hong
2014-01-01
Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For the evidence sentence extraction subtask, we built a binary classifier to identify evidence sentences using reference distance estimator (RDE), a recently proposed semi-supervised learning method that learns new features from around 10 million unlabeled sentences, achieving an F1 of 19.3% in exact match and 32.5% in relaxed match. In the post-submission experiment, we obtained 22.1% and 35.7% F1 performance by incorporating bigram features in RDE learning. In both development and test sets, RDE-based method achieved over 20% relative improvement on F1 and AUC performance against classical supervised learning methods, e.g. support vector machine and logistic regression. For the GO term prediction subtask, we developed an information retrieval-based method to retrieve the GO term most relevant to each evidence sentence using a ranking function that combined cosine similarity and the frequency of GO terms in documents, and a filtering method based on high-level GO classes. The best performance of our submitted runs was 7.8% F1 and 22.2% hierarchy F1. We found that the incorporation of frequency information and hierarchy filtering substantially improved the performance. In the post-submission evaluation, we obtained a 10.6% F1 using a simpler setting. Overall, the experimental analysis showed our approaches were robust in both the two tasks. © The Author(s) 2014. Published by Oxford University Press.
-
Synthetic generation of influenza vaccine viruses for rapid response to pandemics.
Dormitzer, Philip R; Suphaphiphat, Pirada; Gibson, Daniel G; Wentworth, David E; Stockwell, Timothy B; Algire, Mikkel A; Alperovich, Nina; Barro, Mario; Brown, David M; Craig, Stewart; Dattilo, Brian M; Denisova, Evgeniya A; De Souza, Ivna; Eickmann, Markus; Dugan, Vivien G; Ferrari, Annette; Gomila, Raul C; Han, Liqun; Judge, Casey; Mane, Sarthak; Matrosovich, Mikhail; Merryman, Chuck; Palladino, Giuseppe; Palmer, Gene A; Spencer, Terika; Strecker, Thomas; Trusheim, Heidi; Uhlendorff, Jennifer; Wen, Yingxia; Yee, Anthony C; Zaveri, Jayshree; Zhou, Bin; Becker, Stephan; Donabedian, Armen; Mason, Peter W; Glass, John I; Rappuoli, Rino; Venter, J Craig
2013-05-15
During the 2009 H1N1 influenza pandemic, vaccines for the virus became available in large quantities only after human infections peaked. To accelerate vaccine availability for future pandemics, we developed a synthetic approach that very rapidly generated vaccine viruses from sequence data. Beginning with hemagglutinin (HA) and neuraminidase (NA) gene sequences, we combined an enzymatic, cell-free gene assembly technique with enzymatic error correction to allow rapid, accurate gene synthesis. We then used these synthetic HA and NA genes to transfect Madin-Darby canine kidney (MDCK) cells that were qualified for vaccine manufacture with viral RNA expression constructs encoding HA and NA and plasmid DNAs encoding viral backbone genes. Viruses for use in vaccines were rescued from these MDCK cells. We performed this rescue with improved vaccine virus backbones, increasing the yield of the essential vaccine antigen, HA. Generation of synthetic vaccine seeds, together with more efficient vaccine release assays, would accelerate responses to influenza pandemics through a system of instantaneous electronic data exchange followed by real-time, geographically dispersed vaccine production.
-
Synthetic biology in mammalian cells: Next generation research tools and therapeutics
Lienert, Florian; Lohmueller, Jason J; Garg, Abhishek; Silver, Pamela A
2014-01-01
Recent progress in DNA manipulation and gene circuit engineering has greatly improved our ability to programme and probe mammalian cell behaviour. These advances have led to a new generation of synthetic biology research tools and potential therapeutic applications. Programmable DNA-binding domains and RNA regulators are leading to unprecedented control of gene expression and elucidation of gene function. Rebuilding complex biological circuits such as T cell receptor signalling in isolation from their natural context has deepened our understanding of network motifs and signalling pathways. Synthetic biology is also leading to innovative therapeutic interventions based on cell-based therapies, protein drugs, vaccines and gene therapies. PMID:24434884
-
Microfluidic Technologies for Synthetic Biology
Directory of Open Access Journals (Sweden)
Sung Kuk Lee
2011-06-01
Full Text Available Microfluidic technologies have shown powerful abilities for reducing cost, time, and labor, and at the same time, for increasing accuracy, throughput, and performance in the analysis of biological and biochemical samples compared with the conventional, macroscale instruments. Synthetic biology is an emerging field of biology and has drawn much attraction due to its potential to create novel, functional biological parts and systems for special purposes. Since it is believed that the development of synthetic biology can be accelerated through the use of microfluidic technology, in this review work we focus our discussion on the latest microfluidic technologies that can provide unprecedented means in synthetic biology for dynamic profiling of gene expression/regulation with high resolution, highly sensitive on-chip and off-chip detection of metabolites, and whole-cell analysis.
-
Application of improved PSO-RBF neural network in the synthetic ammonia decarbonization
Directory of Open Access Journals (Sweden)
Yongwei LI
2017-12-01
Full Text Available The synthetic ammonia decarbonization is a typical complex industrial process, which has the characteristics of time variation, nonlinearity and uncertainty, and the on-line control model is difficult to be established. An improved PSO-RBF neural network control algorithm is proposed to solve the problems of low precision and poor robustness in the complex process of the synthetic ammonia decarbonization. The particle swarm optimization algorithm and RBF neural network are combined. The improved particle swarm algorithm is used to optimize the RBF neural network's hidden layer primary function center, width and the output layer's connection value to construct the RBF neural network model optimized by the improved PSO algorithm. The improved PSO-RBF neural network control model is applied to the key carbonization process and compared with the traditional fuzzy neural network. The simulation results show that the improved PSO-RBF neural network control method used in the synthetic ammonia decarbonization process has higher control accuracy and system robustness, which provides an effective way to solve the modeling and optimization control of a complex industrial process.
-
Chromatin regulators, phenotypic robustness and autism risk
Directory of Open Access Journals (Sweden)
Reut eSuliman
2014-04-01
Full Text Available Though extensively characterized clinically, the causes of autism spectrum disorder (ASD remain a mystery. ASD is known to have a strong genetic basis, but it is genetically very heterogeneous. Recent studies have estimated that de novo disruptive mutations in hundreds of genes may contribute to ASD. However, it is unclear how it is possible for mutations in so many different genes to contribute to ASD. Recent findings suggest that many of the mutations disrupt genes involved in transcription regulation that are expressed prenatally in the developing brain. De novo disruptive mutations are also more frequent in girls with ASD, despite the fact that ASD is more prevalent in boys. In this paper, we hypothesize that loss of robustness may contribute to ASD. Loss of phenotypic robustness may be caused by mutations that disrupt capacitors that operate in the developing brain. This may lead to the release of cryptic genetic variation that contributes to ASD. Reduced robustness is consistent with the observed variability in expressivity and incomplete penetrance. It is also consistent with the hypothesis that the development of the female brain is more robust, and it may explain the higher rate and severity of disruptive de novo mutations in girls with ASD.
-
Developments in the Tools and Methodologies of Synthetic Biology
Kelwick, Richard; MacDonald, James T.; Webb, Alexander J.; Freemont, Paul
2014-01-01
Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a “body of knowledge” from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community. PMID:25505788
-
Developments in the tools and methodologies of synthetic biology
Directory of Open Access Journals (Sweden)
Richard eKelwick
2014-11-01
Full Text Available Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices or systems. However, biological systems are generally complex and unpredictable and are therefore intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a ‘body of knowledge’ from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled and its functionality tested. At each stage of the design cycle an expanding repertoire of tools is being developed. In this review we highlight several of these tools in terms of their applications and benefits to the synthetic biology community.
-
Building robust functionality in synthetic circuits using engineered feedback regulation.
Chen, Susan; Harrigan, Patrick; Heineike, Benjamin; Stewart-Ornstein, Jacob; El-Samad, Hana
2013-08-01
The ability to engineer novel functionality within cells, to quantitatively control cellular circuits, and to manipulate the behaviors of populations, has many important applications in biotechnology and biomedicine. These applications are only beginning to be explored. In this review, we advocate the use of feedback control as an essential strategy for the engineering of robust homeostatic control of biological circuits and cellular populations. We also describe recent works where feedback control, implemented in silico or with biological components, was successfully employed for this purpose. Copyright © 2013 Elsevier Ltd. All rights reserved.
-
Kanofsky, Konstantin; Lehmeyer, Mona; Schulze, Jutta; Hehl, Reinhard
2016-01-01
Plants recognize pathogens by microbe-associated molecular patterns (MAMPs) and subsequently induce an immune response. The regulation of gene expression during the immune response depends largely on cis-sequences conserved in promoters of MAMP-responsive genes. These cis-sequences can be analyzed by constructing synthetic promoters linked to a reporter gene and by testing these constructs in transient expression systems. Here, the use of the parsley (Petroselinum crispum) protoplast system for analyzing MAMP-responsive synthetic promoters is described. The synthetic promoter consists of four copies of a potential MAMP-responsive cis-sequence cloned upstream of a minimal promoter and the uidA reporter gene. The reporter plasmid contains a second reporter gene, which is constitutively expressed and hence eliminates the requirement of a second plasmid used as a transformation control. The reporter plasmid is transformed into parsley protoplasts that are elicited by the MAMP Pep25. The MAMP responsiveness is validated by comparing the reporter gene activity from MAMP-treated and untreated cells and by normalizing reporter gene activity using the constitutively expressed reporter gene.
-
Understanding Biological Regulation Through Synthetic Biology.
Bashor, Caleb J; Collins, James J
2018-03-16
Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry-biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function. Expected final online publication date for the Annual Review of Biophysics Volume 47 is May 20, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
-
Chen, Bor-Sen; Lin, Ying-Po
2011-01-01
In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563
-
Synthetic promoter libraries- tuning of gene expression
DEFF Research Database (Denmark)
Hammer, Karin; Mijakovic, Ivan; Jensen, Peter Ruhdal
2006-01-01
knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wildtype expression level of the studied gene; this requirement can......The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene...
-
Characterization of high speed synthetic jet actuators
Pikcilingis, Lucia
Over the last 20 years, synthetic jets have been studied as a means for aerodynamic active flow control. Specifically, synthetic jets provide momentum transfer with zero-net mass flux, which has been proven to be effective for controlling flow fields. A synthetic jet is created by the periodic formation of vortex rings at its orifice due to the periodic motion of a piezoelectric disk(s). The present study seeks to optimize the performance of a synthetic jet actuator by utilizing different geometrical parameters such as disk thickness, orifice width and length, cavity height and cavity diameter, and different input parameters such as driving voltage and frequency. Two apparatuses were used with a cavity diameter of either 80 mm or 160 mm. Piezoelectric-based disks were provided by the Mide Corporation. Experiments were conducted using several synthetic jet apparatuses designed for various geometrical parameters utilizing a dual disk configuration. Velocity and temperature measurements were acquired at the center of the synthetic jet orifice using a temperature compensated hotwire and thermocouple probe. The disk(s) displacement was measured at the center of the disk with a laser displacement sensor. It was shown that the synthetic jets, having the 80 mm cavity diameter, are capable of exceeding peak velocities of 200 m/s with a relatively large orifice of dimensions AR = 12, hc* = 3, and hn* = 4. In addition, the conditions at which the disks were manufactured had minimal effect on the performance of the jet, except for the pair with overnight resting time as opposed to less than an hour resting time for the control units. Altering the tab style of the disks, where the tab allows the electrical circuit to be exposed for external power connection, showed that a thin fragile tab versus a tab of the same thickness as the disk has minimal effect on the performance but affects the durability of the disk due to the fragility or robustness of the tab. The synthetic jets
-
Robust adaptive multichannel SAR processing based on covariance matrix reconstruction
Tan, Zhen-ya; He, Feng
2018-04-01
With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.
-
Katayama, Shintaro; Skoog, Tiina; Jouhilahti, Eeva-Mari; Siitonen, H Annika; Nuutila, Kristo; Tervaniemi, Mari H; Vuola, Jyrki; Johnsson, Anna; Lönnerberg, Peter; Linnarsson, Sten; Elomaa, Outi; Kankuri, Esko; Kere, Juha
2015-06-25
Keratinocytes (KCs) are the most frequent cells in the epidermis, and they are often isolated and cultured in vitro to study the molecular biology of the skin. Cultured primary cells and various immortalized cells have been frequently used as skin models but their comparability to intact skin has been questioned. Moreover, when analyzing KC transcriptomes, fluctuation of polyA+ RNA content during the KCs' lifecycle has been omitted. We performed STRT RNA sequencing on 10 ng samples of total RNA from three different sample types: i) epidermal tissue (split-thickness skin grafts), ii) cultured primary KCs, and iii) HaCaT cell line. We observed significant variation in cellular polyA+ RNA content between tissue and cell culture samples of KCs. The use of synthetic RNAs and SAMstrt in normalization enabled comparison of gene expression levels in the highly heterogenous samples and facilitated discovery of differences between the tissue samples and cultured cells. The transcriptome analysis sensitively revealed genes involved in KC differentiation in skin grafts and cell cycle regulation related genes in cultured KCs and emphasized the fluctuation of transcription factors and non-coding RNAs associated to sample types. The epidermal keratinocytes derived from tissue and cell culture samples showed highly different polyA+ RNA contents. The use of SAMstrt and synthetic RNA based normalization allowed the comparison between tissue and cell culture samples and thus proved to be valuable tools for RNA-seq analysis with translational approach. Transciptomics revealed clear difference both between tissue and cell culture samples and between primary KCs and immortalized HaCaT cells.
-
Angelici, Bartolomeo; Mailand, Erik; Haefliger, Benjamin; Benenson, Yaakov
2016-08-30
One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.
-
Ede, Christopher; Chen, Ximin; Lin, Meng-Yin; Chen, Yvonne Y.
2016-01-01
Inducible transcription systems play a crucial role in a wide array of synthetic biology circuits. However, the majority of inducible promoters are constructed from a limited set of tried-and-true promoter parts, which are susceptible to common shortcomings such as high basal expression levels (i.e., leakiness). To expand the toolbox for regulated mammalian gene expression and facilitate the construction of mammalian genetic circuits with precise functionality, we quantitatively characterized a panel of eight core promoters, including sequences with mammalian, viral, and synthetic origins. We demonstrate that this selection of core promoters can provide a wide range of basal gene expression levels and achieve a gradient of fold-inductions spanning two orders of magnitude. Furthermore, commonly used parts such as minimal CMV and minimal SV40 promoters were shown to achieve robust gene expression upon induction, but also suffer from high levels of leakiness. In contrast, a synthetic promoter, YB_TATA, was shown to combine low basal expression with high transcription rate in the induced state to achieve significantly higher fold-induction ratios compared to all other promoters tested. These behaviors remain consistent when the promoters are coupled to different genetic outputs and different response elements, as well as across different host-cell types and DNA copy numbers. We apply this quantitative understanding of core promoter properties to the successful engineering of human T cells that respond to antigen stimulation via chimeric antigen receptor signaling specifically under hypoxic environments. Results presented in this study can facilitate the design and calibration of future mammalian synthetic biology systems capable of precisely programmed functionality. PMID:26883397
-
Efficient engineering of marker-free synthetic allotetraploids of Saccharomyces.
Alexander, William G; Peris, David; Pfannenstiel, Brandon T; Opulente, Dana A; Kuang, Meihua; Hittinger, Chris Todd
2016-04-01
Saccharomyces interspecies hybrids are critical biocatalysts in the fermented beverage industry, including in the production of lager beers, Belgian ales, ciders, and cold-fermented wines. Current methods for making synthetic interspecies hybrids are cumbersome and/or require genome modifications. We have developed a simple, robust, and efficient method for generating allotetraploid strains of prototrophic Saccharomyces without sporulation or nuclear genome manipulation. S. cerevisiae×S. eubayanus, S. cerevisiae×S. kudriavzevii, and S. cerevisiae×S. uvarum designer hybrid strains were created as synthetic lager, Belgian, and cider strains, respectively. The ploidy and hybrid nature of the strains were confirmed using flow cytometry and PCR-RFLP analysis, respectively. This method provides an efficient means for producing novel synthetic hybrids for beverage and biofuel production, as well as for constructing tetraploids to be used for basic research in evolutionary genetics and genome stability. Copyright © 2015 Elsevier Inc. All rights reserved.
-
Synthetic Electric Microbial Biosensors
2017-06-10
domains and DNA-binding domains into a single protein for deregulation of down stream genes of have been favored [10]. Initially experiments with... Germany DISTRIBUTION A. Approved for public release: distribution unlimited. Talk title: “Synthetic biology based microbial biosensors for the...toolbox” in Heidelberg, Germany Poster title: “Anaerobic whole cell microbial biosensors” Link: http://phdsymposium.embl.org/#home September, 2014
-
Poinsettia protoplasts - a simple, robust and efficient system for transient gene expression studies
Directory of Open Access Journals (Sweden)
Pitzschke Andrea
2012-05-01
Full Text Available Abstract Background Transient gene expression systems are indispensable tools in molecular biology. Yet, their routine application is limited to few plant species often requiring substantial equipment and facilities. High chloroplast and chlorophyll content may further impede downstream applications of transformed cells from green plant tissue. Results Here, we describe a fast and simple technique for the high-yield isolation and efficient transformation (>70% of mesophyll-derived protoplasts from red leaves of the perennial plant Poinsettia (Euphorbia pulccherrima. In this method no particular growth facilities or expensive equipments are needed. Poinsettia protoplasts display an astonishing robustness and can be employed in a variety of commonly-used downstream applications, such as subcellular localisation (multi-colour fluorescence or promoter activity studies. Due to low abundance of chloroplasts or chromoplasts, problems encountered in other mesophyll-derived protoplast systems (particularly autofluorescence are alleviated. Furthermore, the transgene expression is detectable within 90 minutes of transformation and lasts for several days. Conclusions The simplicity of the isolation and transformation procedure renders Poinsettia protoplasts an attractive system for transient gene expression experiments, including multi-colour fluorescence, subcellular localisation and promoter activity studies. In addition, they offer hitherto unknown possibilities for anthocyan research and industrial applications.
-
UNIX-based operating systems robustness evaluation
Chang, Yu-Ming
1996-01-01
Robust operating systems are required for reliable computing. Techniques for robustness evaluation of operating systems not only enhance the understanding of the reliability of computer systems, but also provide valuable feed- back to system designers. This thesis presents results from robustness evaluation experiments on five UNIX-based operating systems, which include Digital Equipment's OSF/l, Hewlett Packard's HP-UX, Sun Microsystems' Solaris and SunOS, and Silicon Graphics' IRIX. Three sets of experiments were performed. The methodology for evaluation tested (1) the exception handling mechanism, (2) system resource management, and (3) system capacity under high workload stress. An exception generator was used to evaluate the exception handling mechanism of the operating systems. Results included exit status of the exception generator and the system state. Resource management techniques used by individual operating systems were tested using programs designed to usurp system resources such as physical memory and process slots. Finally, the workload stress testing evaluated the effect of the workload on system performance by running a synthetic workload and recording the response time of local and remote user requests. Moderate to severe performance degradations were observed on the systems under stress.
-
Ishimatsu, Kana; Hata, Takashi; Mochizuki, Atsushi; Sekine, Ryoji; Yamamura, Masayuki; Kiga, Daisuke
2014-09-19
Control of the cell-type ratio in multistable systems requires wide-range control of the initial states of cells. Here, using a synthetic circuit in E. coli, we describe the use of a simple gene-overexpression system combined with a bistable toggle switch, for the purposes of enabling the wide-range control of cellular states and thus generating arbitrary cell-type ratios. Theoretically, overexpression induction temporarily alters the bistable system to a monostable system, in which the location of the single steady state of cells can be manipulated over a wide range by regulating the overexpression levels. This induced cellular state becomes the initial state of the basal bistable system upon overexpression cessation, which restores the original bistable system. We experimentally demonstrated that the overexpression induced a monomodal cell distribution, and subsequent overexpression withdrawal generated a bimodal distribution. Furthermore, as designed theoretically, regulating the overexpression levels by adjusting the concentrations of small molecules generated arbitrary cell-type ratios.
-
Hyperspectral Unmixing with Robust Collaborative Sparse Regression
Directory of Open Access Journals (Sweden)
Chang Li
2016-07-01
Full Text Available Recently, sparse unmixing (SU of hyperspectral data has received particular attention for analyzing remote sensing images. However, most SU methods are based on the commonly admitted linear mixing model (LMM, which ignores the possible nonlinear effects (i.e., nonlinearity. In this paper, we propose a new method named robust collaborative sparse regression (RCSR based on the robust LMM (rLMM for hyperspectral unmixing. The rLMM takes the nonlinearity into consideration, and the nonlinearity is merely treated as outlier, which has the underlying sparse property. The RCSR simultaneously takes the collaborative sparse property of the abundance and sparsely distributed additive property of the outlier into consideration, which can be formed as a robust joint sparse regression problem. The inexact augmented Lagrangian method (IALM is used to optimize the proposed RCSR. The qualitative and quantitative experiments on synthetic datasets and real hyperspectral images demonstrate that the proposed RCSR is efficient for solving the hyperspectral SU problem compared with the other four state-of-the-art algorithms.
-
DEFF Research Database (Denmark)
Dossani, Zain Y.; Apel, Amanda Reider; Szmidt-Middleton, Heather
2018-01-01
regions, we have built a library of hybrid promoters that are regulated by a synthetic transcription factor. The hybrid promoters consist of native S. cerevisiae promoters, in which the operator regions have been replaced with sequences that are recognized by the bacterial LexA DNA binding protein....... Correspondingly, the synthetic transcription factor (TF) consists of the DNA binding domain of the LexA protein, fused with the human estrogen binding domain and the viral activator domain, VP16. The resulting system with a bacterial DNA binding domain avoids the transcription of native S. cerevisiae genes...... levels, using the same synthetic TF and a given estradiol. This set of promoters, in combination with our synthetic TF, has the potential to regulate numerous genes or pathways simultaneously, to multiple desired levels, in a single strain....
-
Visual gene developer: a fully programmable bioinformatics software for synthetic gene optimization
Directory of Open Access Journals (Sweden)
McDonald Karen
2011-08-01
Full Text Available Abstract Background Direct gene synthesis is becoming more popular owing to decreases in gene synthesis pricing. Compared with using natural genes, gene synthesis provides a good opportunity to optimize gene sequence for specific applications. In order to facilitate gene optimization, we have developed a stand-alone software called Visual Gene Developer. Results The software not only provides general functions for gene analysis and optimization along with an interactive user-friendly interface, but also includes unique features such as programming capability, dedicated mRNA secondary structure prediction, artificial neural network modeling, network & multi-threaded computing, and user-accessible programming modules. The software allows a user to analyze and optimize a sequence using main menu functions or specialized module windows. Alternatively, gene optimization can be initiated by designing a gene construct and configuring an optimization strategy. A user can choose several predefined or user-defined algorithms to design a complicated strategy. The software provides expandable functionality as platform software supporting module development using popular script languages such as VBScript and JScript in the software programming environment. Conclusion Visual Gene Developer is useful for both researchers who want to quickly analyze and optimize genes, and those who are interested in developing and testing new algorithms in bioinformatics. The software is available for free download at http://www.visualgenedeveloper.net.
-
Directory of Open Access Journals (Sweden)
Matthew C Hiemenz
Full Text Available Next-generation sequencing (NGS is a powerful platform for identifying cancer mutations. Routine clinical adoption of NGS requires optimized quality control metrics to ensure accurate results. To assess the robustness of our clinical NGS pipeline, we analyzed the results of 304 solid tumor and hematologic malignancy specimens tested simultaneously by NGS and one or more targeted single-gene tests (EGFR, KRAS, BRAF, NPM1, FLT3, and JAK2. For samples that passed our validated tumor percentage and DNA quality and quantity thresholds, there was perfect concordance between NGS and targeted single-gene tests with the exception of two FLT3 internal tandem duplications that fell below the stringent pre-established reporting threshold but were readily detected by manual inspection. In addition, NGS identified clinically significant mutations not covered by single-gene tests. These findings confirm NGS as a reliable platform for routine clinical use when appropriate quality control metrics, such as tumor percentage and DNA quality cutoffs, are in place. Based on our findings, we suggest a simple workflow that should facilitate adoption of clinical oncologic NGS services at other institutions.
-
Dar, Saira; Shuja, Rukhsana N; Shakoori, Abdul Rauf
2013-02-01
Metallothioneins (MTs) are metal binding proteins that are rich in cysteine residues constituting 10-30 % of the total protein, and in which the thiol groups bind to the metal ions. The increasing amount of metal ions in the medium have shown increased production of MTs by different organisms such as bacteria, protozoa and mammals like humans. PMCd1 is the first gene ever discovered in Paramecium, a ciliated protozoan, that could produce this MT in response to cadmium. In this study the PMCd1syn gene has been cloned in pET41a expression vector and expressed in an Escherichia coli BL21-codonplus strain for the first time. Since the gene PMCd1 amplified from Paramecium contained 10 codons, which could act as stop codons during expression in E. coli, this gene of 612 bps was synthesized to substitute these (stop) codons for the Paramecium sp. specific amino acids. For stability of the expressed protein, glutathione-S-transferase gene was fused with PMCd1syn gene and coexpressed. The cells expressing PMCd1syn demonstrated increased accumulation of cadmium. This is the first report of cadmium MT protein expressed from Paramecium species, particularly from synthetic MT gene (PMCd1syn). This fusion protein, the molecular weight of which has been confirmed to be 53.03 kDa with MALDI analysis, is rich in cysteine residues, and has been shown for the first time in this ciliate to bind to and sequester Cd(2+)-ions.
-
Carpenetti, Tiffany L. G.; Aryan, Azadeh; Myles, Kevin M.; Adelman, Zach N.
2011-01-01
Aedes aegypti is an important vector of the viruses that cause dengue fever, dengue hemorrhagic fever, and yellow fever. Reverse genetic approaches to the study of gene function in this mosquito have been limited by the lack of a robust inducible promoter to allow precise temporal control over a protein-encoding or hairpin RNA transgene. Likewise, investigations into the molecular and biochemical basis of vector competence would benefit from the ability to activate an anti-pathogen molecule at specific times during infection. We have characterized the ability of genomic sequences derived from two Ae. aegypti hsp70 genes to drive heat-inducible expression of a reporter in both transient and germline transformation contexts. AaHsp70-luciferase transcripts accumulated specifically after heat shock, and displayed a pattern of rapid induction and decay similar to endogenous AaHsp70 genes. Luciferase expression in transgenic Ae. aegypti increased by ∼25-50 fold in whole adults by four hours after heat-shock, with significant activity (∼20 fold) remaining at 24 hr. Heat-induced expression was even more dramatic in midgut tissues, with one strain showing a ∼2500-fold increase in luciferase activity. The AaHsp70 promoters described could be valuable for gene function studies as well as for the precise timing of the expression of anti-pathogen molecules. PMID:22142225
-
Robust photometric stereo using structural light sources
Han, Tian-Qi; Cheng, Yue; Shen, Hui-Liang; Du, Xin
2014-05-01
We propose a robust photometric stereo method by using structural arrangement of light sources. In the arrangement, light sources are positioned on a planar grid and form a set of collinear combinations. The shadow pixels are detected by adaptive thresholding. The specular highlight and diffuse pixels are distinguished according to their intensity deviations of the collinear combinations, thanks to the special arrangement of light sources. The highlight detection problem is cast as a pattern classification problem and is solved using support vector machine classifiers. Considering the possible misclassification of highlight pixels, the ℓ1 regularization is further employed in normal map estimation. Experimental results on both synthetic and real-world scenes verify that the proposed method can robustly recover the surface normal maps in the case of heavy specular reflection and outperforms the state-of-the-art techniques.
-
RegnANN: Reverse Engineering Gene Networks using Artificial Neural Networks.
Directory of Open Access Journals (Sweden)
Marco Grimaldi
Full Text Available RegnANN is a novel method for reverse engineering gene networks based on an ensemble of multilayer perceptrons. The algorithm builds a regressor for each gene in the network, estimating its neighborhood independently. The overall network is obtained by joining all the neighborhoods. RegnANN makes no assumptions about the nature of the relationships between the variables, potentially capturing high-order and non linear dependencies between expression patterns. The evaluation focuses on synthetic data mimicking plausible submodules of larger networks and on biological data consisting of submodules of Escherichia coli. We consider Barabasi and Erdös-Rényi topologies together with two methods for data generation. We verify the effect of factors such as network size and amount of data to the accuracy of the inference algorithm. The accuracy scores obtained with RegnANN is methodically compared with the performance of three reference algorithms: ARACNE, CLR and KELLER. Our evaluation indicates that RegnANN compares favorably with the inference methods tested. The robustness of RegnANN, its ability to discover second order correlations and the agreement between results obtained with this new methods on both synthetic and biological data are promising and they stimulate its application to a wider range of problems.
-
Robust Learning of High-dimensional Biological Networks with Bayesian Networks
Nägele, Andreas; Dejori, Mathäus; Stetter, Martin
Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.
-
Comparison of evolutionary algorithms in gene regulatory network model inference.
LENUS (Irish Health Repository)
2010-01-01
ABSTRACT: BACKGROUND: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very difficult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insufficient. RESULTS: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and offer a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. CONCLUSIONS: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identified and a platform for development of appropriate model formalisms is established.
-
A Powerful Toolkit for Synthetic Biology: Over 3.8 Billion Years of Evolution
Rothschild, Lynn J.
2010-01-01
The combination of evolutionary with engineering principles will enhance synthetic biology. Conversely, synthetic biology has the potential to enrich evolutionary biology by explaining why some adaptive space is empty, on Earth or elsewhere. Synthetic biology, the design and construction of artificial biological systems, substitutes bio-engineering for evolution, which is seen as an obstacle. But because evolution has produced the complexity and diversity of life, it provides a proven toolkit of genetic materials and principles available to synthetic biology. Evolution operates on the population level, with the populations composed of unique individuals that are historical entities. The source of genetic novelty includes mutation, gene regulation, sex, symbiosis, and interspecies gene transfer. At a phenotypic level, variation derives from regulatory control, replication and diversification of components, compartmentalization, sexual selection and speciation, among others. Variation is limited by physical constraints such as diffusion, and chemical constraints such as reaction rates and membrane fluidity. While some of these tools of evolution are currently in use in synthetic biology, all ought to be examined for utility. A hybrid approach of synthetic biology coupled with fine-tuning through evolution is suggested
-
Genome Engineering and Modification Toward Synthetic Biology for the Production of Antibiotics.
Zou, Xuan; Wang, Lianrong; Li, Zhiqiang; Luo, Jie; Wang, Yunfu; Deng, Zixin; Du, Shiming; Chen, Shi
2018-01-01
Antibiotic production is often governed by large gene clusters composed of genes related to antibiotic scaffold synthesis, tailoring, regulation, and resistance. With the expansion of genome sequencing, a considerable number of antibiotic gene clusters has been isolated and characterized. The emerging genome engineering techniques make it possible towards more efficient engineering of antibiotics. In addition to genomic editing, multiple synthetic biology approaches have been developed for the exploration and improvement of antibiotic natural products. Here, we review the progress in the development of these genome editing techniques used to engineer new antibiotics, focusing on three aspects of genome engineering: direct cloning of large genomic fragments, genome engineering of gene clusters, and regulation of gene cluster expression. This review will not only summarize the current uses of genomic engineering techniques for cloning and assembly of antibiotic gene clusters or for altering antibiotic synthetic pathways but will also provide perspectives on the future directions of rebuilding biological systems for the design of novel antibiotics. © 2017 Wiley Periodicals, Inc.
-
International Nuclear Information System (INIS)
Wang, Y.J.; Wang, C.Y.; Zhang, H.
2015-01-01
Synthetic hexaploid wheat is an important germplasm resource for transfer of beneficial genes from alien species to common wheat (Triticum aestivum L.). Synthetic hexaploid wheat SE5756 confers a high level of resistance against a wide range of races of Puccinia striiformis West. f. sp. tritici Eriks. et Henn.(Pst). The objectives of this study were to determine the inheritance pattern, adjacent molecular markers, and chromosomal location of the stripe rust resistance gene in SE5756 and to develop new germplasm. We constructed a segregating population of 116 F2 plants and corresponding F2:3 families from a cross between SE5756 and Xinong979 with Pst races CYR32. Genetic analysis revealed that a single dominant gene, tentatively designated as YrSE5756, was responsible for seedling stage stripe rust resistance in SE5756. A genetic map, encompassing Xwmc626, Xwmc269, Xgwm11, Xbarx137, Xwmc419, Xwmc85, Xgpw5237, Xwmc134, WE173, Xwmc631, and YrSE5756, spanned 70.1 cM on chromosome 1BS. Xwmc419 and Xwmc85 were flanking markers tightly linked to YrSE5756 at genetic distances of 2.3 and 1.8 cM. Typical adult plant responses of the SE5756, varieties of the carrier Yr10 and Yr15, Chuanmai 42 (Yr24/Yr26), Yuanfeng 175 (Yr24/Yr26) and Huixianhong resistant to mixture Pst races (CYR32, CYR33 and V26) were experimented. The results showed that YrSE5756 was likely a new resistance stripe rust gene different from Yr24/Yr26, Yr10 and Yr15. From cross and backcross populations of SE5756/Xinong 979, we developed four new wheat lines with large seeds, stripe rust resistance, and improved agronomic traits: N07178-1, N07178-2, N08256-1, and N08256-2. These new germplasm lines could serve as sources of resistance to stripe rust in wheat breeding. SE5756 has the very vital significance in the development of breeding and expand our resistance germplasm resource gene pool. (author)
-
MIDAS: A Modular DNA Assembly System for Synthetic Biology.
van Dolleweerd, Craig J; Kessans, Sarah A; Van de Bittner, Kyle C; Bustamante, Leyla Y; Bundela, Rudranuj; Scott, Barry; Nicholson, Matthew J; Parker, Emily J
2018-04-20
A modular and hierarchical DNA assembly platform for synthetic biology based on Golden Gate (Type IIS restriction enzyme) cloning is described. This enabling technology, termed MIDAS (for Modular Idempotent DNA Assembly System), can be used to precisely assemble multiple DNA fragments in a single reaction using a standardized assembly design. It can be used to build genes from libraries of sequence-verified, reusable parts and to assemble multiple genes in a single vector, with full user control over gene order and orientation, as well as control of the direction of growth (polarity) of the multigene assembly, a feature that allows genes to be nested between other genes or genetic elements. We describe the detailed design and use of MIDAS, exemplified by the reconstruction, in the filamentous fungus Penicillium paxilli, of the metabolic pathway for production of paspaline and paxilline, key intermediates in the biosynthesis of a range of indole diterpenes-a class of secondary metabolites produced by several species of filamentous fungi. MIDAS was used to efficiently assemble a 25.2 kb plasmid from 21 different modules (seven genes, each composed of three basic parts). By using a parts library-based system for construction of complex assemblies, and a unique set of vectors, MIDAS can provide a flexible route to assembling tailored combinations of genes and other genetic elements, thereby supporting synthetic biology applications in a wide range of expression hosts.
-
Industrial scale gene synthesis.
Notka, Frank; Liss, Michael; Wagner, Ralf
2011-01-01
The most recent developments in the area of deep DNA sequencing and downstream quantitative and functional analysis are rapidly adding a new dimension to understanding biochemical pathways and metabolic interdependencies. These increasing insights pave the way to designing new strategies that address public needs, including environmental applications and therapeutic inventions, or novel cell factories for sustainable and reconcilable energy or chemicals sources. Adding yet another level is building upon nonnaturally occurring networks and pathways. Recent developments in synthetic biology have created economic and reliable options for designing and synthesizing genes, operons, and eventually complete genomes. Meanwhile, high-throughput design and synthesis of extremely comprehensive DNA sequences have evolved into an enabling technology already indispensable in various life science sectors today. Here, we describe the industrial perspective of modern gene synthesis and its relationship with synthetic biology. Gene synthesis contributed significantly to the emergence of synthetic biology by not only providing the genetic material in high quality and quantity but also enabling its assembly, according to engineering design principles, in a standardized format. Synthetic biology on the other hand, added the need for assembling complex circuits and large complexes, thus fostering the development of appropriate methods and expanding the scope of applications. Synthetic biology has also stimulated interdisciplinary collaboration as well as integration of the broader public by addressing socioeconomic, philosophical, ethical, political, and legal opportunities and concerns. The demand-driven technological achievements of gene synthesis and the implemented processes are exemplified by an industrial setting of large-scale gene synthesis, describing production from order to delivery. Copyright © 2011 Elsevier Inc. All rights reserved.
-
Manikandan, R; Balakrishnan, N; Sudhakar, D; Udayasuriyan, V
2016-06-01
Bacillus thuringiensis is a major source of insecticidal genes imparting insect resistance in transgenic plants. Level of expression of transgenes in transgenic plants is important to achieve desirable level of resistance against target insects. In order to achieve desirable level of expression, rice chloroplast transit peptide sequence was fused with synthetic cry2AX1 gene to target its protein in chloroplasts. Sixteen PCR positive lines of rice were generated by Agrobacterium mediated transformation using immature embryos. Southern blot hybridization analysis of T 0 transgenic plants confirmed the integration of cry2AX1 gene in two to five locations of rice genome and ELISA demonstrated its expression. Concentration of Cry2AX1 in transgenic rice events ranged 5.0-120 ng/g of fresh leaf tissue. Insect bioassay of T 0 transgenic rice plants against neonate larvae of rice leaffolder showed larval mortality ranging between 20 and 80 % in comparison to control plant. Stable inheritance and expression of cry2AX1 gene was demonstrated in T 1 progenies through Southern and ELISA. In T 1 progenies, the highest concentration of Cry2AX1 and mortality of rice leaffolder larvae were recorded as 150 ng/g of fresh leaf tissue and 80 %, respectively. The Cry2AX1 expression even at a very low concentration (120-150 ng/g) in transgenic rice plants was found effective against rice leaffolder larvae.
-
Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies
Chen, Yi-Hau; Chatterjee, Nilanjan; Carroll, Raymond J.
2009-01-01
Case-control association studies often aim to investigate the role of genes and gene-environment interactions in terms of the underlying haplotypes (i.e., the combinations of alleles at multiple genetic loci along chromosomal regions). The goal of this article is to develop robust but efficient approaches to the estimation of disease odds-ratio parameters associated with haplotypes and haplotype-environment interactions. We consider "shrinkage" estimation techniques that can adaptively relax the model assumptions of Hardy-Weinberg-Equilibrium and gene-environment independence required by recently proposed efficient "retrospective" methods. Our proposal involves first development of a novel retrospective approach to the analysis of case-control data, one that is robust to the nature of the gene-environment distribution in the underlying population. Next, it involves shrinkage of the robust retrospective estimator toward a more precise, but model-dependent, retrospective estimator using novel empirical Bayes and penalized regression techniques. Methods for variance estimation are proposed based on asymptotic theories. Simulations and two data examples illustrate both the robustness and efficiency of the proposed methods.
-
Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies
Chen, Yi-Hau
2009-03-01
Case-control association studies often aim to investigate the role of genes and gene-environment interactions in terms of the underlying haplotypes (i.e., the combinations of alleles at multiple genetic loci along chromosomal regions). The goal of this article is to develop robust but efficient approaches to the estimation of disease odds-ratio parameters associated with haplotypes and haplotype-environment interactions. We consider "shrinkage" estimation techniques that can adaptively relax the model assumptions of Hardy-Weinberg-Equilibrium and gene-environment independence required by recently proposed efficient "retrospective" methods. Our proposal involves first development of a novel retrospective approach to the analysis of case-control data, one that is robust to the nature of the gene-environment distribution in the underlying population. Next, it involves shrinkage of the robust retrospective estimator toward a more precise, but model-dependent, retrospective estimator using novel empirical Bayes and penalized regression techniques. Methods for variance estimation are proposed based on asymptotic theories. Simulations and two data examples illustrate both the robustness and efficiency of the proposed methods.
-
Energy Technology Data Exchange (ETDEWEB)
Paquette, Stéphane G. [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario (Canada); Banner, David [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); Chi, Le Thi Bao [Department of Microbiology, Hue University of Medicine and Pharmacy, Thua Thien Hue (Viet Nam); Carlo Urbani Centre, Hue University of Medicine and Pharmacy, Thua Thien Hue (Viet Nam); Leon, Alberto J. [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); International Institute of Infection and Immunity, Shantou University Medical College, Shantou, Guangdong (China); Xu, Luoling; Ran, Longsi [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); Huang, Stephen S.H. [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); Department of Immunology, Faculty of Medicine, University of Toronto, Toronto, Ontario (Canada); Farooqui, Amber [Division of Experimental Therapeutics, Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario (Canada); International Institute of Infection and Immunity, Shantou University Medical College, Shantou, Guangdong (China); and others
2014-01-05
Pandemic H1N1 influenza A (H1N1pdm) elicits stronger pulmonary inflammation than previously circulating seasonal H1N1 influenza A (sH1N1), yet mechanisms of inflammatory activation in respiratory epithelial cells during H1N1pdm infection are unclear. We investigated host responses to H1N1pdm/sH1N1 infection and virus entry mechanisms in primary human bronchial epithelial cells in vitro. H1N1pdm infection rapidly initiated a robust inflammatory gene signature (3 h post-infection) not elicited by sH1N1 infection. Protein secretion inhibition had no effect on gene induction. Infection with membrane fusion deficient H1N1pdm failed to induce robust inflammatory gene expression which was rescued with restoration of fusion ability, suggesting H1N1pdm directly triggered the inflammatory signature downstream of membrane fusion. Investigation of intra-virion components revealed H1N1pdm viral RNA (vRNA) triggered a stronger inflammatory phenotype than sH1N1 vRNA. Thus, our study is first to report H1N1pdm induces greater inflammatory gene expression than sH1N1 in vitro due to direct virus–epithelial cell interaction. - Highlights: • We investigated H1N1pdm/sH1N1 infection in primary epithelial cells. • H1N1pdm directly initiated a robust inflammatory gene signature, sH1N1 did not. • H1N1pdm viral RNA triggered a stronger response than sH1N1. • H1N1pdm induces greater response due to direct virus–cell interaction. • These results have potential to impact vaccine and therapeutic development.
-
International Nuclear Information System (INIS)
Paquette, Stéphane G.; Banner, David; Chi, Le Thi Bao; Leon, Alberto J.; Xu, Luoling; Ran, Longsi; Huang, Stephen S.H.; Farooqui, Amber
2014-01-01
Pandemic H1N1 influenza A (H1N1pdm) elicits stronger pulmonary inflammation than previously circulating seasonal H1N1 influenza A (sH1N1), yet mechanisms of inflammatory activation in respiratory epithelial cells during H1N1pdm infection are unclear. We investigated host responses to H1N1pdm/sH1N1 infection and virus entry mechanisms in primary human bronchial epithelial cells in vitro. H1N1pdm infection rapidly initiated a robust inflammatory gene signature (3 h post-infection) not elicited by sH1N1 infection. Protein secretion inhibition had no effect on gene induction. Infection with membrane fusion deficient H1N1pdm failed to induce robust inflammatory gene expression which was rescued with restoration of fusion ability, suggesting H1N1pdm directly triggered the inflammatory signature downstream of membrane fusion. Investigation of intra-virion components revealed H1N1pdm viral RNA (vRNA) triggered a stronger inflammatory phenotype than sH1N1 vRNA. Thus, our study is first to report H1N1pdm induces greater inflammatory gene expression than sH1N1 in vitro due to direct virus–epithelial cell interaction. - Highlights: • We investigated H1N1pdm/sH1N1 infection in primary epithelial cells. • H1N1pdm directly initiated a robust inflammatory gene signature, sH1N1 did not. • H1N1pdm viral RNA triggered a stronger response than sH1N1. • H1N1pdm induces greater response due to direct virus–cell interaction. • These results have potential to impact vaccine and therapeutic development
-
Application of synthetic biology for production of chemicals in yeast Saccharomyces cerevisiae
DEFF Research Database (Denmark)
Borodina, Irina; Li, Mingji
2015-01-01
Synthetic biology and metabolic engineering enable generation of novel cell factories that efficiently convert renewable feedstocks into biofuels, bulk, and fine chemicals, thus creating the basis for biosustainable economy independent on fossil resources. While over a hundred proof...... biology has the potential to bring down this cost by improving our ability to predictably engineer biological systems. This review highlights synthetic biology applications for design, assembly, and optimization of non-native biochemical pathways in baker's yeast Saccharomyces cerevisiae. We describe......-of-concept chemicals have been made in yeast, only a very small fraction of those has reached commercial-scale production so far. The limiting factor is the high research cost associated with the development of a robust cell factory that can produce the desired chemical at high titer, rate, and yield. Synthetic...
-
Directory of Open Access Journals (Sweden)
Mohammad S. Khan
2017-07-01
Full Text Available Transgenic Brassica napus harboring the synthetic chitinase (NiC gene exhibits broad-spectrum antifungal resistance. As the rhizosphere microorganisms play an important role in element cycling and nutrient transformation, therefore, biosafety assessment of NiC containing transgenic plants on soil ecosystem is a regulatory requirement. The current study is designed to evaluate the impact of NiC gene on the rhizosphere enzyme activities and microbial community structure. The transgenic lines with the synthetic chitinase gene (NiC showed resistance to Alternaria brassicicola, a common disease causing fungal pathogen. The rhizosphere enzyme analysis showed no significant difference in the activities of fivesoil enzymes: alkalyine phosphomonoestarase, arylsulphatase, β-glucosidase, urease and sucrase between the transgenic and non-transgenic lines of B. napus varieties, Durr-e-NIFA (DN and Abasyne-95 (AB-95. However, varietal differences were observed based on the analysis of molecular variance. Some individual enzymes were significantly different in the transgenic lines from those of non-transgenic but the results were not reproducible in the second trail and thus were considered as environmental effect. Genotypic diversity of soil microbes through 16S–23S rRNA intergenic spacer region amplification was conducted to evaluate the potential impact of the transgene. No significant diversity (4% for bacteria and 12% for fungal between soil microbes of NiC B. napus and the non-transgenic lines was found. However, significant varietal differences were observed between DN and AB-95 with 79% for bacterial and 54% for fungal diversity. We conclude that the NiC B. napus lines may not affect the microbial enzyme activities and community structure of the rhizosphere soil. Varietal differences might be responsible for minor changes in the tested parameters.
-
Synthetic genome engineering forging new frontiers for wine yeast.
Pretorius, Isak S
2017-02-01
Over the past 15 years, the seismic shifts caused by the convergence of biomolecular, chemical, physical, mathematical, and computational sciences alongside cutting-edge developments in information technology and engineering have erupted into a new field of scientific endeavor dubbed Synthetic Biology. Recent rapid advances in high-throughput DNA sequencing and DNA synthesis techniques are enabling the design and construction of new biological parts (genes), devices (gene networks) and modules (biosynthetic pathways), and the redesign of biological systems (cells and organisms) for useful purposes. In 2014, the budding yeast Saccharomyces cerevisiae became the first eukaryotic cell to be equipped with a fully functional synthetic chromosome. This was achieved following the synthesis of the first viral (poliovirus in 2002 and bacteriophage Phi-X174 in 2003) and bacterial (Mycoplasma genitalium in 2008 and Mycoplasma mycoides in 2010) genomes, and less than two decades after revealing the full genome sequence of a laboratory (S288c in 1996) and wine (AWRI1631 in 2008) yeast strain. A large international project - the Synthetic Yeast Genome (Sc2.0) Project - is now underway to synthesize all 16 chromosomes (∼12 Mb carrying ∼6000 genes) of the sequenced S288c laboratory strain by 2018. If successful, S. cerevisiae will become the first eukaryote to cross the horizon of in silico design of complex cells through de novo synthesis, reshuffling, and editing of genomes. In the meantime, yeasts are being used as cell factories for the semi-synthetic production of high-value compounds, such as the potent antimalarial artemisinin, and food ingredients, such as resveratrol, vanillin, stevia, nootkatone, and saffron. As a continuum of previously genetically engineered industrially important yeast strains, precision genome engineering is bound to also impact the study and development of wine yeast strains supercharged with synthetic DNA. The first taste of what the future
-
Ensemble Modeling for Robustness Analysis in engineering non-native metabolic pathways.
Lee, Yun; Lafontaine Rivera, Jimmy G; Liao, James C
2014-09-01
Metabolic pathways in cells must be sufficiently robust to tolerate fluctuations in expression levels and changes in environmental conditions. Perturbations in expression levels may lead to system failure due to the disappearance of a stable steady state. Increasing evidence has suggested that biological networks have evolved such that they are intrinsically robust in their network structure. In this article, we presented Ensemble Modeling for Robustness Analysis (EMRA), which combines a continuation method with the Ensemble Modeling approach, for investigating the robustness issue of non-native pathways. EMRA investigates a large ensemble of reference models with different parameters, and determines the effects of parameter drifting until a bifurcation point, beyond which a stable steady state disappears and system failure occurs. A pathway is considered to have high bifurcational robustness if the probability of system failure is low in the ensemble. To demonstrate the utility of EMRA, we investigate the bifurcational robustness of two synthetic central metabolic pathways that achieve carbon conservation: non-oxidative glycolysis and reverse glyoxylate cycle. With EMRA, we determined the probability of system failure of each design and demonstrated that alternative designs of these pathways indeed display varying degrees of bifurcational robustness. Furthermore, we demonstrated that target selection for flux improvement should consider the trade-offs between robustness and performance. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
-
Peripherally applied synthetic peptide isoAsp7-Aβ(1-42) triggers cerebral β-amyloidosis.
Kozin, S A; Cheglakov, I B; Ovsepyan, A A; Telegin, G B; Tsvetkov, P O; Lisitsa, A V; Makarov, A A
2013-10-01
Intracerebral and intraperitoneal inoculation with β-amyloid-rich brain extracts originating from patients with Alzheimer's disease as well as intracerebral injection of aggregates composed of synthetic Aβ can induce cerebral β-amyloidosis, and associated cognitive dysfunctions in susceptible animal hosts. We have found that repetitive intravenous administration of 100 μg of synthetic peptide corresponding to isoAsp7-containing Aβ(1-42), an abundant age-dependent Aβ isoform present both in the pathological brain and in synthetic Aβ preparations, robustly accelerates formation of classic dense-core congophilic amyloid plaques in the brain of β-amyloid precursor protein transgenic mice. Our findings indicate this peptide as an inductive agent of cerebral β-amyloidosis in vivo.
-
Agent-based modelling in synthetic biology.
Gorochowski, Thomas E
2016-11-30
Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).
-
Foureau, E; Carqueijeiro, I; Dugé de Bernonville, T; Melin, C; Lafontaine, F; Besseau, S; Lanoue, A; Papon, N; Oudin, A; Glévarec, G; Clastre, M; St-Pierre, B; Giglioli-Guivarc'h, N; Courdavault, V
2016-01-01
Natural compounds extracted from microorganisms or plants constitute an inexhaustible source of valuable molecules whose supply can be potentially challenged by limitations in biological sourcing. The recent progress in synthetic biology combined to the increasing access to extensive transcriptomics and genomics data now provide new alternatives to produce these molecules by transferring their whole biosynthetic pathway in heterologous production platforms such as yeasts or bacteria. While the generation of high titer producing strains remains per se an arduous field of investigation, elucidation of the biosynthetic pathways as well as characterization of their complex subcellular organization are essential prequels to the efficient development of such bioengineering approaches. Using examples from plants and yeasts as a framework, we describe potent methods to rationalize the study of partially characterized pathways, including the basics of computational applications to identify candidate genes in transcriptomics data and the validation of their function by an improved procedure of virus-induced gene silencing mediated by direct DNA transfer to get around possible resistance to Agrobacterium-delivery of viral vectors. To identify potential alterations of biosynthetic fluxes resulting from enzyme mislocalizations in reconstituted pathways, we also detail protocols aiming at characterizing subcellular localizations of protein in plant cells by expression of fluorescent protein fusions through biolistic-mediated transient transformation, and localization of transferred enzymes in yeast using similar fluorescence procedures. Albeit initially developed for the Madagascar periwinkle, these methods may be applied to other plant species or organisms in order to establish synthetic biology platform. © 2016 Elsevier Inc. All rights reserved.
-
Synthetic biology, inspired by synthetic chemistry.
Malinova, V; Nallani, M; Meier, W P; Sinner, E K
2012-07-16
The topic synthetic biology appears still as an 'empty basket to be filled'. However, there is already plenty of claims and visions, as well as convincing research strategies about the theme of synthetic biology. First of all, synthetic biology seems to be about the engineering of biology - about bottom-up and top-down approaches, compromising complexity versus stability of artificial architectures, relevant in biology. Synthetic biology accounts for heterogeneous approaches towards minimal and even artificial life, the engineering of biochemical pathways on the organismic level, the modelling of molecular processes and finally, the combination of synthetic with nature-derived materials and architectural concepts, such as a cellular membrane. Still, synthetic biology is a discipline, which embraces interdisciplinary attempts in order to have a profound, scientific base to enable the re-design of nature and to compose architectures and processes with man-made matter. We like to give an overview about the developments in the field of synthetic biology, regarding polymer-based analogs of cellular membranes and what questions can be answered by applying synthetic polymer science towards the smallest unit in life, namely a cell. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
-
Yeast synthetic biology for high-value metabolites.
Dai, Zhubo; Liu, Yi; Guo, Juan; Huang, Luqi; Zhang, Xueli
2015-02-01
Traditionally, high-value metabolites have been produced through direct extraction from natural biological sources which are inefficient, given the low abundance of these compounds. On the other hand, these high-value metabolites are usually difficult to be synthesized chemically, due to their complex structures. In the last few years, the discovery of genes involved in the synthetic pathways of these metabolites, combined with advances in synthetic biology tools, has allowed the construction of increasing numbers of yeast cell factories for production of these metabolites from renewable biomass. This review summarizes recent advances in synthetic biology in terms of the use of yeasts as microbial hosts for the identification of the pathways involved in the synthesis, as well as for the production of high-value metabolites. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.
-
Synthetic biology for microbial heavy metal biosensors.
Kim, Hyun Ju; Jeong, Haeyoung; Lee, Sang Jun
2018-02-01
Using recombinant DNA technology, various whole-cell biosensors have been developed for detection of environmental pollutants, including heavy metal ions. Whole-cell biosensors have several advantages: easy and inexpensive cultivation, multiple assays, and no requirement of any special techniques for analysis. In the era of synthetic biology, cutting-edge DNA sequencing and gene synthesis technologies have accelerated the development of cell-based biosensors. Here, we summarize current technological advances in whole-cell heavy metal biosensors, including the synthetic biological components (bioparts), sensing and reporter modules, genetic circuits, and chassis cells. We discuss several opportunities for improvement of synthetic cell-based biosensors. First, new functional modules must be discovered in genome databases, and this knowledge must be used to upgrade specific bioparts through molecular engineering. Second, modules must be assembled into functional biosystems in chassis cells. Third, heterogeneity of individual cells in the microbial population must be eliminated. In the perspectives, the development of whole-cell biosensors is also discussed in the aspects of cultivation methods and synthetic cells.
-
Richardson, Joshua B.; Uppendahl, Locke D.; Traficante, Maria K.; Levy, Sasha F.; Siegal, Mark L.
2013-01-01
Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact) to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA) lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1) to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be caused by loss of
-
Directory of Open Access Journals (Sweden)
Joshua B Richardson
Full Text Available Biological systems produce phenotypes that appear to be robust to perturbation by mutations and environmental variation. Prior studies identified genes that, when impaired, reveal previously cryptic genetic variation. This result is typically interpreted as evidence that the disrupted gene normally increases robustness to mutations, as such robustness would allow cryptic variants to accumulate. However, revelation of cryptic genetic variation is not necessarily evidence that a mutationally robust state has been made less robust. Demonstrating a difference in robustness requires comparing the ability of each state (with the gene perturbed or intact to suppress the effects of new mutations. Previous studies used strains in which the existing genetic variation had been filtered by selection. Here, we use mutation accumulation (MA lines that have experienced minimal selection, to test the ability of histone H2A.Z (HTZ1 to increase robustness to mutations in the yeast Saccharomyces cerevisiae. HTZ1, a regulator of chromatin structure and gene expression, represents a class of genes implicated in mutational robustness. It had previously been shown to increase robustness of yeast cell morphology to fluctuations in the external or internal microenvironment. We measured morphological variation within and among 79 MA lines with and without HTZ1. Analysis of within-line variation confirms that HTZ1 increases microenvironmental robustness. Analysis of between-line variation shows the morphological effects of eliminating HTZ1 to be highly dependent on the line, which implies that HTZ1 interacts with mutations that have accumulated in the lines. However, lines without HTZ1 are, as a group, not more phenotypically diverse than lines with HTZ1 present. The presence of HTZ1, therefore, does not confer greater robustness to mutations than its absence. Our results provide experimental evidence that revelation of cryptic genetic variation cannot be assumed to be
-
Synthetic biology devices and circuits for RNA-based 'smart vaccines': a propositional review.
Andries, Oliwia; Kitada, Tasuku; Bodner, Katie; Sanders, Niek N; Weiss, Ron
2015-02-01
Nucleic acid vaccines have been gaining attention as an alternative to the standard attenuated pathogen or protein based vaccine. However, an unrealized advantage of using such DNA or RNA based vaccination modalities is the ability to program within these nucleic acids regulatory devices that would provide an immunologist with the power to control the production of antigens and adjuvants in a desirable manner by administering small molecule drugs as chemical triggers. Advances in synthetic biology have resulted in the creation of highly predictable and modular genetic parts and devices that can be composed into synthetic gene circuits with complex behaviors. With the recent advent of modified RNA gene delivery methods and developments in the RNA replicon platform, we foresee a future in which mammalian synthetic biologists will create genetic circuits encoded exclusively on RNA. Here, we review the current repertoire of devices used in RNA synthetic biology and propose how programmable 'smart vaccines' will revolutionize the field of RNA vaccination.
-
Cell-free synthetic biology for in vitro prototype engineering.
Moore, Simon J; MacDonald, James T; Freemont, Paul S
2017-06-15
Cell-free transcription-translation is an expanding field in synthetic biology as a rapid prototyping platform for blueprinting the design of synthetic biological devices. Exemplar efforts include translation of prototype designs into medical test kits for on-site identification of viruses (Zika and Ebola), while gene circuit cascades can be tested, debugged and re-designed within rapid turnover times. Coupled with mathematical modelling, this discipline lends itself towards the precision engineering of new synthetic life. The next stages of cell-free look set to unlock new microbial hosts that remain slow to engineer and unsuited to rapid iterative design cycles. It is hoped that the development of such systems will provide new tools to aid the transition from cell-free prototype designs to functioning synthetic genetic circuits and engineered natural product pathways in living cells. © 2017 The Author(s).
-
Biosynthesis of therapeutic natural products using synthetic biology.
Awan, Ali R; Shaw, William M; Ellis, Tom
2016-10-01
Natural products are a group of bioactive structurally diverse chemicals produced by microorganisms and plants. These molecules and their derivatives have contributed to over a third of the therapeutic drugs produced in the last century. However, over the last few decades traditional drug discovery pipelines from natural products have become far less productive and far more expensive. One recent development with promise to combat this trend is the application of synthetic biology to therapeutic natural product biosynthesis. Synthetic biology is a young discipline with roots in systems biology, genetic engineering, and metabolic engineering. In this review, we discuss the use of synthetic biology to engineer improved yields of existing therapeutic natural products. We further describe the use of synthetic biology to combine and express natural product biosynthetic genes in unprecedented ways, and how this holds promise for opening up completely new avenues for drug discovery and production. Copyright © 2016 Elsevier B.V. All rights reserved.
-
The validation of synthetic spectra used in the performance evaluation of radionuclide identifiers
International Nuclear Information System (INIS)
Flynn, A.; Boardman, D.; Reinhard, M.I.
2013-01-01
This work has evaluated synthetic gamma-ray spectra created by the RASE sampler using experimental data. The RASE sampler resamples experimental data to create large data libraries which are subsequently available for use in evaluation of radionuclide identification algorithms. A statistical evaluation of the synthetic energy bins has shown the variation to follow a Poisson distribution identical to experimental data. The minimum amount of statistics required in each base spectrum to ensure the subsequent use of the base spectrum in the generation of statistically robust synthetic data was determined. A requirement that the simulated acquisition time of the synthetic spectra was not more than 4% of the acquisition time of the base spectrum was also determined. Further validation of RASE was undertaken using two different radionuclide identification algorithms. - Highlights: • A validation of synthetic data created in order to evaluate radionuclide identification systems has been carried out. • Statistical analysis has shown that the data accurately represents experimental data. • A limit to the amount of data which could be created using this method was evaluated. • Analysis of the synthetic gamma spectra show identical results to analysis carried out with experimental data
-
Distributed detection of communities in complex networks using synthetic coordinates
International Nuclear Information System (INIS)
Papadakis, H; Fragopoulou, P; Panagiotakis, C
2014-01-01
Various applications like finding Web communities, detecting the structure of social networks, and even analyzing a graph’s structure to uncover Internet attacks are just some of the applications for which community detection is important. In this paper, we propose an algorithm that finds the entire community structure of a network, on the basis of local interactions between neighboring nodes and an unsupervised distributed hierarchical clustering algorithm. The novelty of the proposed approach, named SCCD (standing for synthetic coordinate community detection), lies in the fact that the algorithm is based on the use of Vivaldi synthetic network coordinates computed by a distributed algorithm. The current paper not only presents an efficient distributed community finding algorithm, but also demonstrates that synthetic network coordinates could be used to derive efficient solutions to a variety of problems. Experimental results and comparisons with other methods from the literature are presented for a variety of benchmark graphs with known community structure, derived from varying a number of graph parameters and real data set graphs. The experimental results and comparisons to existing methods with similar computation cost on real and synthetic data sets demonstrate the high performance and robustness of the proposed scheme. (paper)
-
Truong, Cong-Doan; Kwon, Yung-Keun
2017-12-21
Biological networks consisting of molecular components and interactions are represented by a graph model. There have been some studies based on that model to analyze a relationship between structural characteristics and dynamical behaviors in signaling network. However, little attention has been paid to changes of modularity and robustness in mutant networks. In this paper, we investigated the changes of modularity and robustness by edge-removal mutations in three signaling networks. We first observed that both the modularity and robustness increased on average in the mutant network by the edge-removal mutations. However, the modularity change was negatively correlated with the robustness change. This implies that it is unlikely that both the modularity and the robustness values simultaneously increase by the edge-removal mutations. Another interesting finding is that the modularity change was positively correlated with the degree, the number of feedback loops, and the edge betweenness of the removed edges whereas the robustness change was negatively correlated with them. We note that these results were consistently observed in randomly structure networks. Additionally, we identified two groups of genes which are incident to the highly-modularity-increasing and the highly-robustness-decreasing edges with respect to the edge-removal mutations, respectively, and observed that they are likely to be central by forming a connected component of a considerably large size. The gene-ontology enrichment of each of these gene groups was significantly different from the rest of genes. Finally, we showed that the highly-robustness-decreasing edges can be promising edgetic drug-targets, which validates the usefulness of our analysis. Taken together, the analysis of changes of robustness and modularity against edge-removal mutations can be useful to unravel novel dynamical characteristics underlying in signaling networks.
-
The population genetics of X-autosome synthetic lethals and steriles.
Lachance, Joseph; Johnson, Norman A; True, John R
2011-11-01
Epistatic interactions are widespread, and many of these interactions involve combinations of alleles at different loci that are deleterious when present in the same individual. The average genetic environment of sex-linked genes differs from that of autosomal genes, suggesting that the population genetics of interacting X-linked and autosomal alleles may be complex. Using both analytical theory and computer simulations, we analyzed the evolutionary trajectories and mutation-selection balance conditions for X-autosome synthetic lethals and steriles. Allele frequencies follow a set of fundamental trajectories, and incompatible alleles are able to segregate at much higher frequencies than single-locus expectations. Equilibria exist, and they can involve fixation of either autosomal or X-linked alleles. The exact equilibrium depends on whether synthetic alleles are dominant or recessive and whether fitness effects are seen in males, females, or both sexes. When single-locus fitness effects and synthetic incompatibilities are both present, population dynamics depend on the dominance of alleles and historical contingency (i.e., whether X-linked or autosomal mutations occur first). Recessive synthetic lethality can result in high-frequency X-linked alleles, and dominant synthetic lethality can result in high-frequency autosomal alleles. Many X-autosome incompatibilities in natural populations may be cryptic, appearing to be single-locus effects because one locus is fixed. We also discuss the implications of these findings with respect to standing genetic variation and the origins of Haldane's rule.
-
Hopkins, Suzanna R; McGregor, Grant A; Murray, Johanne M; Downs, Jessica A; Savic, Velibor
2016-10-01
In recent years, research into synthetic lethality and how it can be exploited in cancer treatments has emerged as major focus in cancer research. However, the lack of a simple to use, sensitive and standardised assay to test for synthetic interactions has been slowing the efforts. Here we present a novel approach to synthetic lethality screening based on co-culturing two syngeneic cell lines containing individual fluorescent tags. By associating shRNAs for a target gene or control to individual fluorescence labels, we can easily follow individual cell fates upon siRNA treatment and high content imaging. We have demonstrated that the system can recapitulate the functional defects of the target gene depletion and is capable of discovering novel synthetic interactors and phenotypes. In a trial screen, we show that TIP60 exhibits synthetic lethality interaction with BAF180, and that in the absence of TIP60, there is an increase micronuclei dependent on the level of BAF180 loss, significantly above levels seen with BAF180 present. Moreover, the severity of the interactions correlates with proxy measurements of BAF180 knockdown efficacy, which may expand its usefulness to addressing synthetic interactions through titratable hypomorphic gene expression. Copyright © 2016. Published by Elsevier B.V.
-
van de Water, Steven; Albertini, Francesca; Weber, Damien C.; Heijmen, Ben J. M.; Hoogeman, Mischa S.; Lomax, Antony J.
2018-01-01
The aim of this study is to develop an anatomical robust optimization method for intensity-modulated proton therapy (IMPT) that accounts for interfraction variations in nasal cavity filling, and to compare it with conventional single-field uniform dose (SFUD) optimization and online plan adaptation. We included CT data of five patients with tumors in the sinonasal region. Using the planning CT, we generated for each patient 25 ‘synthetic’ CTs with varying nasal cavity filling. The robust optimization method available in our treatment planning system ‘Erasmus-iCycle’ was extended to also account for anatomical uncertainties by including (synthetic) CTs with varying patient anatomy as error scenarios in the inverse optimization. For each patient, we generated treatment plans using anatomical robust optimization and, for benchmarking, using SFUD optimization and online plan adaptation. Clinical target volume (CTV) and organ-at-risk (OAR) doses were assessed by recalculating the treatment plans on the synthetic CTs, evaluating dose distributions individually and accumulated over an entire fractionated 50 GyRBE treatment, assuming each synthetic CT to correspond to a 2 GyRBE fraction. Treatment plans were also evaluated using actual repeat CTs. Anatomical robust optimization resulted in adequate CTV doses (V95% ⩾ 98% and V107% ⩽ 2%) if at least three synthetic CTs were included in addition to the planning CT. These CTV requirements were also fulfilled for online plan adaptation, but not for the SFUD approach, even when applying a margin of 5 mm. Compared with anatomical robust optimization, OAR dose parameters for the accumulated dose distributions were on average 5.9 GyRBE (20%) higher when using SFUD optimization and on average 3.6 GyRBE (18%) lower for online plan adaptation. In conclusion, anatomical robust optimization effectively accounted for changes in nasal cavity filling during IMPT, providing substantially improved CTV and
-
Inactivation of CDK2 is synthetically lethal to MYCN over-expressing cancer cells
Molenaar, Jan J.; Ebus, Marli E.; Geerts, Dirk; Koster, Jan; Lamers, Fieke; Valentijn, Linda J.; Westerhout, Ellen M.; Versteeg, Rogier; Caron, Huib N.
2009-01-01
Two genes have a synthetically lethal relationship when the silencing or inhibiting of 1 gene is only lethal in the context of a mutation or activation of the second gene. This situation offers an attractive therapeutic strategy, as inhibition of such a gene will only trigger cell death in tumor cells with an activated second oncogene but spare normal cells without activation of the second oncogene. Here we present evidence that CDK2 is synthetically lethal to neuroblastoma cells with MYCN amplification and over-expression. Neuroblastomas are childhood tumors with an often lethal outcome. Twenty percent of the tumors have MYCN amplification, and these tumors are ultimately refractory to any therapy. Targeted silencing of CDK2 by 3 RNA interference techniques induced apoptosis in MYCN-amplified neuroblastoma cell lines, but not in MYCN single copy cells. Silencing of MYCN abrogated this apoptotic response in MYCN-amplified cells. Inversely, silencing of CDK2 in MYCN single copy cells did not trigger apoptosis, unless a MYCN transgene was activated. The MYCN induced apoptosis after CDK2 silencing was accompanied by nuclear stabilization of P53, and mRNA profiling showed up-regulation of P53 target genes. Silencing of P53 rescued the cells from MYCN-driven apoptosis. The synthetic lethality of CDK2 silencing in MYCN activated neuroblastoma cells can also be triggered by inhibition of CDK2 with a small molecule drug. Treatment of neuroblastoma cells with roscovitine, a CDK inhibitor, at clinically achievable concentrations induced MYCN-dependent apoptosis. The synthetically lethal relationship between CDK2 and MYCN indicates CDK2 inhibitors as potential MYCN-selective cancer therapeutics. PMID:19525400
-
Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh
2017-12-19
Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.
-
ACRE: Absolute concentration robustness exploration in module-based combinatorial networks
Kuwahara, Hiroyuki; Umarov, Ramzan; Almasri, Islam; Gao, Xin
2017-01-01
To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.
-
ACRE: Absolute concentration robustness exploration in module-based combinatorial networks
Kuwahara, Hiroyuki
2017-03-01
To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.
-
Ferreira, Joshua P; Peacock, Ryan W S; Lawhorn, Ingrid E B; Wang, Clifford L
2011-12-01
The human cytomegalovirus and elongation factor 1α promoters are constitutive promoters commonly employed by mammalian expression vectors. These promoters generally produce high levels of expression in many types of cells and tissues. To generate a library of synthetic promoters capable of generating a range of low, intermediate, and high expression levels, the TATA and CAAT box elements of these promoters were mutated. Other promoter variants were also generated by random mutagenesis. Evaluation using plasmid vectors integrated at a single site in the genome revealed that these various synthetic promoters were capable of expression levels spanning a 40-fold range. Retroviral vectors were equipped with the synthetic promoters and evaluated for their ability to reproduce the graded expression demonstrated by plasmid integration. A vector with a self-inactivating long terminal repeat could neither reproduce the full range of expression levels nor produce stable expression. Using a second vector design, the different synthetic promoters enabled stable expression over a broad range of expression levels in different cell lines. The online version of this article (doi:10.1007/s11693-011-9089-0) contains supplementary material, which is available to authorized users.
-
Gschmeidler, Brigitte; Seiringer, Alexandra
2012-02-01
Although still a side issue in the German-language media, attention towards synthetic biology has risen clearly during the last years, in line with the first applications being presented. This paper presents findings from a content analysis of synthetic biology coverage in German-language media over the years 2004-2009. In the media, synthetic biology is not clearly separated from gene technology. News value is attributed to established categories such as persons and events. Many metaphors and analogies used in describing gene technology can also be found in the coverage of synthetic biology; however, engineering metaphors are more prominent. In addition, playfulness constitutes an aspect rarely found in genetic engineering coverage. Overall, the picture emerging is ambivalent, which leaves prospects for the further development of public debate ambiguous.
-
CNS-restricted Transduction and CRISPR/Cas9-mediated Gene Deletion with an Engineered AAV Vector
Directory of Open Access Journals (Sweden)
Giridhar Murlidharan
2016-01-01
Full Text Available Gene therapy using recombinant adeno-associated viral (AAV vectors is emerging as a promising approach to treat central nervous system disorders such as Spinal muscular atrophy, Batten, Parkinson and Alzheimer disease amongst others. A critical remaining challenge for central nervous system-targeted gene therapy, silencing or gene editing is to limit potential vector dose-related toxicity in off-target cells and organs. Here, we characterize a lab-derived AAV chimeric (AAV2g9, which displays favorable central nervous system attributes derived from both parental counterparts, AAV2 and AAV9. This synthetic AAV strain displays preferential, robust, and widespread neuronal transduction within the brain and decreased glial tropism. Importantly, we observed minimal systemic leakage, decreased sequestration and gene transfer in off-target organs with AAV2g9, when administered into the cerebrospinal fluid. A single intracranial injection of AAV2g9 vectors encoding guide RNAs targeting the schizophrenia risk gene MIR137 (encoding MIR137 in CRISPR/Cas9 knockin mice resulted in brain-specific gene deletion with no detectable events in the liver. This engineered AAV vector is a promising platform for treating neurological disorders through gene therapy, silencing or editing modalities.
-
Gradient descent for robust kernel-based regression
Guo, Zheng-Chu; Hu, Ting; Shi, Lei
2018-06-01
In this paper, we study the gradient descent algorithm generated by a robust loss function over a reproducing kernel Hilbert space (RKHS). The loss function is defined by a windowing function G and a scale parameter σ, which can include a wide range of commonly used robust losses for regression. There is still a gap between theoretical analysis and optimization process of empirical risk minimization based on loss: the estimator needs to be global optimal in the theoretical analysis while the optimization method can not ensure the global optimality of its solutions. In this paper, we aim to fill this gap by developing a novel theoretical analysis on the performance of estimators generated by the gradient descent algorithm. We demonstrate that with an appropriately chosen scale parameter σ, the gradient update with early stopping rules can approximate the regression function. Our elegant error analysis can lead to convergence in the standard L 2 norm and the strong RKHS norm, both of which are optimal in the mini-max sense. We show that the scale parameter σ plays an important role in providing robustness as well as fast convergence. The numerical experiments implemented on synthetic examples and real data set also support our theoretical results.
-
Jiménez, Juan J; Borrero, Juan; Gútiez, Loreto; Arbulu, Sara; Herranz, Carmen; Cintas, Luis M; Hernández, Pablo E
2014-06-01
The use of synthetic genes may constitute a successful approach for the heterologous production and functional expression of bacterial antimicrobial peptides (bacteriocins) by recombinant yeasts. In this work, synthetic genes with adapted codon usage designed from the mature amino acid sequence of the bacteriocin enterocin A (EntA), produced by Enterococcus faecium T136, and the mature bacteriocin E 50-52 (BacE50-52), produced by E. faecium NRRL B-32746, were synthesized. The synthetic entA and bacE50-52 were cloned into the protein expression vectors pPICZαA and pKLAC2 for transformation of derived vectors into Pichia pastoris X-33 and Kluyveromyces lactis GG799, respectively. The recombinant vectors were linearized and transformed into competent cells selecting for P. pastoris X-33EAS (entA), P. pastoris X-33BE50-52S (bacE50-52), K. lactis GG799EAS (entA), and K. lactis GG799BE50-52S (bacE50-52). P. pastoris X-33EAS and K. lactis GG799EAS, but not P. pastoris X-33BE50-52S and K. lactis GG799BE50-52S, showed antimicrobial activity in their supernatants. However, purification of the supernatants of the producer yeasts permitted recovery of the bacteriocins EntA and BacE50-52. Both purified bacteriocins were active against Gram-positive bacteria such as Listeria monocytogenes but not against Gram-negative bacteria, including Campylobacter jejuni.
-
Transcriptional robustness and protein interactions are associated in yeast
Directory of Open Access Journals (Sweden)
Conant Gavin C
2011-05-01
Full Text Available Abstract Background Robustness to insults, both external and internal, is a characteristic feature of life. One level of biological organization for which noise and robustness have been extensively studied is gene expression. Cells have a variety of mechanisms for buffering noise in gene expression, but it is not completely clear what rules govern whether or not a given gene uses such tools to maintain appropriate expression. Results Here, we show a general association between the degree to which yeast cells have evolved mechanisms to buffer changes in gene expression and whether they possess protein-protein interactions. We argue that this effect bears an affinity to epistasis, because yeast appears to have evolved regulatory mechanisms such that distant changes in gene copy number for a protein-protein interaction partner gene can alter a gene's expression. This association is not unexpected given recent work linking epistasis and the deleterious effects of changes in gene dosage (i.e., the dosage balance hypothesis. Using gene expression data from artificial aneuploid strains of bakers' yeast, we found that genes coding for proteins that physically interact with other proteins show less expression variation in response to aneuploidy than do other genes. This effect is even more pronounced for genes whose products interact with proteins encoded on aneuploid chromosomes. We further found that genes targeted by transcription factors encoded on aneuploid chromosomes were more likely to change in expression after aneuploidy. Conclusions We suggest that these observations can be best understood as resulting from the higher fitness cost of misexpression in epistatic genes and a commensurate greater regulatory control of them.
-
DEFF Research Database (Denmark)
Lachowiec, Jennifer; Queitsch, Christine; Kliebenstein, Daniel James
2016-01-01
-genome duplications, tandem gene duplication and hybridization are emerging as major regulators of robustness in development. Despite their obvious implications for plant evolution and plant breeding, the mechanistic underpinnings by which plants modulate precise levels of robustness, plasticity and evolvability...
-
Mockett, Robin J; Nobles, Amber C
2013-10-01
The hypothesis tested in this study was that single-gene mutations found previously to extend the life span of Drosophila melanogaster could do so consistently in both long-lived y w and standard w (1118) genetic backgrounds. GAL4 drivers were used to express upstream activation sequence (UAS)-responder transgenes globally or in the nervous system. Transgenes associated with oxidative damage prevention (UAS-hSOD1 and UAS-GCLc) or removal (EP-UAS-Atg8a and UAS-dTOR (FRB) ) failed to increase mean life spans in any expression pattern in either genetic background. Flies containing a UAS-EGFP-bMSRA (C) transgene associated with protein repair were found not to exhibit life extension or detectable enhanced green fluorescent protein (EGFP) activity. The presence of UAS-responder transgenes was confirmed by PCR amplification and sequencing at the 5' and 3' end of each insertion. These results cast doubt on the robustness of life extension in flies carrying single-gene mutations and suggest that the effects of all such mutations should be tested independently in multiple genetic backgrounds and laboratory environments.
-
Industrial systems biology and its impact on synthetic biology of yeast cell factories
DEFF Research Database (Denmark)
Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens
2016-01-01
Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools......, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex...... regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal...
-
Synthetic Genetic Targeting of Genome Instability in Cancer
International Nuclear Information System (INIS)
Sajesh, Babu V.; Guppy, Brent J.; McManus, Kirk J.
2013-01-01
Cancer is a leading cause of death throughout the World. A limitation of many current chemotherapeutic approaches is that their cytotoxic effects are not restricted to cancer cells, and adverse side effects can occur within normal tissues. Consequently, novel strategies are urgently needed to better target cancer cells. As we approach the era of personalized medicine, targeting the specific molecular defect(s) within a given patient’s tumor will become a more effective treatment strategy than traditional approaches that often target a given cancer type or sub-type. Synthetic genetic interactions are now being examined for their therapeutic potential and are designed to target the specific genetic and epigenetic phenomena associated with tumor formation, and thus are predicted to be highly selective. In general, two complementary approaches have been employed, including synthetic lethality and synthetic dosage lethality, to target aberrant expression and/or function associated with tumor suppressor genes and oncogenes, respectively. Here we discuss the concepts of synthetic lethality and synthetic dosage lethality, and explain three general experimental approaches designed to identify novel genetic interactors. We present examples and discuss the merits and caveats of each approach. Finally, we provide insight into the subsequent pre-clinical work required to validate novel candidate drug targets
-
Pele, Laetitia C; Haas, Carolin T; Hewitt, Rachel E; Robertson, Jack; Skepper, Jeremy; Brown, Andy; Hernandez-Garrido, Juan Carlos; Midgley, Paul A; Faria, Nuno; Chappell, Helen; Powell, Jonathan J
2017-02-01
Amorphous magnesium-substituted calcium phosphate (AMCP) nanoparticles (75-150nm) form constitutively in large numbers in the mammalian gut. Collective evidence indicates that they trap and deliver luminal macromolecules to mucosal antigen presenting cells (APCs) and facilitate gut immune homeostasis. Here, we report on a synthetic mimetic of the endogenous AMCP and show that it has marked capacity to trap macromolecules during formation. Macromolecular capture into AMCP involved incorporation as shown by STEM tomography of the synthetic AMCP particle with 5nm ultra-fine iron (III) oxohydroxide. In vitro, organic cargo-loaded synthetic AMCP was taken up by APCs and tracked to lysosomal compartments. The AMCP itself did not regulate any gene, or modify any gene regulation by its cargo, based upon whole genome transcriptomic analyses. We conclude that synthetic AMCP can efficiently trap macromolecules and deliver them to APCs in a silent fashion, and may thus represent a new platform for antigen delivery. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.
-
Robust MST-Based Clustering Algorithm.
Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing
2018-06-01
Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.
-
Gandhi, Adarsh S.; Zhu, Mingshe; Pang, Shaokun; Wohlfarth, Ariane; Scheidweiler, Karl B.; Liu, Hua-fen; Huestis, Marilyn A.
2013-01-01
Since the federal authorities scheduled the first synthetic cannabinoids, JWH-018 and JWH-073, new synthetic cannabinoids were robustly marketed. N-(1-Adamantyl)-1-pentylindazole-3-carboxamide (AKB-48), also known as APINACA, was recently observed in Japanese herbal smoking blends. The National Forensic Laboratory Information System registered 443 reports of AKB-48 cases in the USA from March 2010 to January 2013. In May 2013, the Drug Enforcement Administration listed AKB-48 as a Schedule I ...
-
Pareto Optimal Design for Synthetic Biology.
Patanè, Andrea; Santoro, Andrea; Costanza, Jole; Carapezza, Giovanni; Nicosia, Giuseppe
2015-08-01
Recent advances in synthetic biology call for robust, flexible and efficient in silico optimization methodologies. We present a Pareto design approach for the bi-level optimization problem associated to the overproduction of specific metabolites in Escherichia coli. Our method efficiently explores the high dimensional genetic manipulation space, finding a number of trade-offs between synthetic and biological objectives, hence furnishing a deeper biological insight to the addressed problem and important results for industrial purposes. We demonstrate the computational capabilities of our Pareto-oriented approach comparing it with state-of-the-art heuristics in the overproduction problems of i) 1,4-butanediol, ii) myristoyl-CoA, i ii) malonyl-CoA , iv) acetate and v) succinate. We show that our algorithms are able to gracefully adapt and scale to more complex models and more biologically-relevant simulations of the genetic manipulations allowed. The Results obtained for 1,4-butanediol overproduction significantly outperform results previously obtained, in terms of 1,4-butanediol to biomass formation ratio and knock-out costs. In particular overproduction percentage is of +662.7%, from 1.425 mmolh⁻¹gDW⁻¹ (wild type) to 10.869 mmolh⁻¹gDW⁻¹, with a knockout cost of 6. Whereas, Pareto-optimal designs we have found in fatty acid optimizations strictly dominate the ones obtained by the other methodologies, e.g., biomass and myristoyl-CoA exportation improvement of +21.43% (0.17 h⁻¹) and +5.19% (1.62 mmolh⁻¹gDW⁻¹), respectively. Furthermore CPU time required by our heuristic approach is more than halved. Finally we implement pathway oriented sensitivity analysis, epsilon-dominance analysis and robustness analysis to enhance our biological understanding of the problem and to improve the optimization algorithm capabilities.
-
Targeted genome regulation via synthetic programmable transcriptional regulators
Piatek, Agnieszka Anna
2016-04-19
Regulation of gene transcription controls cellular functions and coordinates responses to developmental, physiological and environmental cues. Precise and efficient molecular tools are needed to characterize the functions of single and multiple genes in linear and interacting pathways in a native context. Modular DNA-binding domains from zinc fingers (ZFs) and transcriptional activator-like proteins (TALE) are amenable to bioengineering to bind DNA target sequences of interest. As a result, ZF and TALE proteins were used to develop synthetic programmable transcription factors. However, these systems are limited by the requirement to re-engineer proteins for each new target sequence. The clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR associated 9 (Cas9) genome editing tool was recently repurposed for targeted transcriptional regulation by inactivation of the nuclease activity of Cas9. Due to the facile engineering, simplicity, precision and amenability to library construction, the CRISPR/Cas9 system is poised to revolutionize the functional genomics field across diverse eukaryotic species. In this review, we discuss the development of synthetic customizable transcriptional regulators and provide insights into their current and potential applications, with special emphasis on plant systems, in characterization of gene functions, elucidation of molecular mechanisms and their biotechnological applications. © 2016 Informa UK Limited, trading as Taylor & Francis Group
-
Natural - synthetic - artificial!
DEFF Research Database (Denmark)
Nielsen, Peter E
2010-01-01
The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....
-
Lorimer, Don; Raymond, Amy; Walchli, John; Mixon, Mark; Barrow, Adrienne; Wallace, Ellen; Grice, Rena; Burgin, Alex; Stewart, Lance
2009-04-21
To improve efficiency in high throughput protein structure determination, we have developed a database software package, Gene Composer, which facilitates the information-rich design of protein constructs and their codon engineered synthetic gene sequences. With its modular workflow design and numerous graphical user interfaces, Gene Composer enables researchers to perform all common bio-informatics steps used in modern structure guided protein engineering and synthetic gene engineering. An interactive Alignment Viewer allows the researcher to simultaneously visualize sequence conservation in the context of known protein secondary structure, ligand contacts, water contacts, crystal contacts, B-factors, solvent accessible area, residue property type and several other useful property views. The Construct Design Module enables the facile design of novel protein constructs with altered N- and C-termini, internal insertions or deletions, point mutations, and desired affinity tags. The modifications can be combined and permuted into multiple protein constructs, and then virtually cloned in silico into defined expression vectors. The Gene Design Module uses a protein-to-gene algorithm that automates the back-translation of a protein amino acid sequence into a codon engineered nucleic acid gene sequence according to a selected codon usage table with minimal codon usage threshold, defined G:C% content, and desired sequence features achieved through synonymous codon selection that is optimized for the intended expression system. The gene-to-oligo algorithm of the Gene Design Module plans out all of the required overlapping oligonucleotides and mutagenic primers needed to synthesize the desired gene constructs by PCR, and for physically cloning them into selected vectors by the most popular subcloning strategies. We present a complete description of Gene Composer functionality, and an efficient PCR-based synthetic gene assembly procedure with mis-match specific endonuclease
-
Gene Composer: database software for protein construct design, codon engineering, and gene synthesis
Directory of Open Access Journals (Sweden)
Mixon Mark
2009-04-01
Full Text Available Abstract Background To improve efficiency in high throughput protein structure determination, we have developed a database software package, Gene Composer, which facilitates the information-rich design of protein constructs and their codon engineered synthetic gene sequences. With its modular workflow design and numerous graphical user interfaces, Gene Composer enables researchers to perform all common bio-informatics steps used in modern structure guided protein engineering and synthetic gene engineering. Results An interactive Alignment Viewer allows the researcher to simultaneously visualize sequence conservation in the context of known protein secondary structure, ligand contacts, water contacts, crystal contacts, B-factors, solvent accessible area, residue property type and several other useful property views. The Construct Design Module enables the facile design of novel protein constructs with altered N- and C-termini, internal insertions or deletions, point mutations, and desired affinity tags. The modifications can be combined and permuted into multiple protein constructs, and then virtually cloned in silico into defined expression vectors. The Gene Design Module uses a protein-to-gene algorithm that automates the back-translation of a protein amino acid sequence into a codon engineered nucleic acid gene sequence according to a selected codon usage table with minimal codon usage threshold, defined G:C% content, and desired sequence features achieved through synonymous codon selection that is optimized for the intended expression system. The gene-to-oligo algorithm of the Gene Design Module plans out all of the required overlapping oligonucleotides and mutagenic primers needed to synthesize the desired gene constructs by PCR, and for physically cloning them into selected vectors by the most popular subcloning strategies. Conclusion We present a complete description of Gene Composer functionality, and an efficient PCR-based synthetic gene
-
Robust Multimodal Dictionary Learning
Cao, Tian; Jojic, Vladimir; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc
2014-01-01
We propose a robust multimodal dictionary learning method for multimodal images. Joint dictionary learning for both modalities may be impaired by lack of correspondence between image modalities in training data, for example due to areas of low quality in one of the modalities. Dictionaries learned with such non-corresponding data will induce uncertainty about image representation. In this paper, we propose a probabilistic model that accounts for image areas that are poorly corresponding between the image modalities. We cast the problem of learning a dictionary in presence of problematic image patches as a likelihood maximization problem and solve it with a variant of the EM algorithm. Our algorithm iterates identification of poorly corresponding patches and re-finements of the dictionary. We tested our method on synthetic and real data. We show improvements in image prediction quality and alignment accuracy when using the method for multimodal image registration. PMID:24505674
-
Antiangiogenic effects of synthetic analogs of curcumin in vivo ...
African Journals Online (AJOL)
The active compound curcumin is isolated from the spice turmeric. Curcumin, curcuminoids and their synthetic analogs have been shown to inhibit the progression of cancer in animal models. In colon and skin carcinogenesis the genetic changes engross different genes, but curcumin is effective in preventing ...
-
Synthetic Biology: Putting Synthesis into Biology
Liang, Jing; Luo, Yunzi; Zhao, Huimin
2010-01-01
The ability to manipulate living organisms is at the heart of a range of emerging technologies that serve to address important and current problems in environment, energy, and health. However, with all its complexity and interconnectivity, biology has for many years been recalcitrant to engineering manipulations. The recent advances in synthesis, analysis, and modeling methods have finally provided the tools necessary to manipulate living systems in meaningful ways, and have led to the coining of a field named synthetic biology. The scope of synthetic biology is as complicated as life itself – encompassing many branches of science, and across many scales of application. New DNA synthesis and assembly techniques have made routine the customization of very large DNA molecules. This in turn has allowed the incorporation of multiple genes and pathways. By coupling these with techniques that allow for the modeling and design of protein functions, scientists have now gained the tools to create completely novel biological machineries. Even the ultimate biological machinery – a self-replicating organism – is being pursued at this moment. It is the purpose of this review to dissect and organize these various components of synthetic biology into a coherent picture. PMID:21064036
-
Miró-Bueno, Jesús M.; Rodríguez-Patón, Alfonso
2011-01-01
Negative and positive transcriptional feedback loops are present in natural and synthetic genetic oscillators. A single gene with negative transcriptional feedback needs a time delay and sufficiently strong nonlinearity in the transmission of the feedback signal in order to produce biochemical rhythms. A single gene with only positive transcriptional feedback does not produce oscillations. Here, we demonstrate that this single-gene network in conjunction with a simple negative interaction can also easily produce rhythms. We examine a model comprised of two well-differentiated parts. The first is a positive feedback created by a protein that binds to the promoter of its own gene and activates the transcription. The second is a negative interaction in which a repressor molecule prevents this protein from binding to its promoter. A stochastic study shows that the system is robust to noise. A deterministic study identifies that the dynamics of the oscillator are mainly driven by two types of biomolecules: the protein, and the complex formed by the repressor and this protein. The main conclusion of this paper is that a simple and usual negative interaction, such as degradation, sequestration or inhibition, acting on the positive transcriptional feedback of a single gene is a sufficient condition to produce reliable oscillations. One gene is enough and the positive transcriptional feedback signal does not need to activate a second repressor gene. This means that at the genetic level an explicit negative feedback loop is not necessary. The model needs neither cooperative binding reactions nor the formation of protein multimers. Therefore, our findings could help to clarify the design principles of cellular clocks and constitute a new efficient tool for engineering synthetic genetic oscillators. PMID:22205920
-
DNA recognition by synthetic constructs.
Pazos, Elena; Mosquera, Jesús; Vázquez, M Eugenio; Mascareñas, José L
2011-09-05
The interaction of transcription factors with specific DNA sites is key for the regulation of gene expression. Despite the availability of a large body of structural data on protein-DNA complexes, we are still far from fully understanding the molecular and biophysical bases underlying such interactions. Therefore, the development of non-natural agents that can reproduce the DNA-recognition properties of natural transcription factors remains a major and challenging goal in chemical biology. In this review we summarize the basics of double-stranded DNA recognition by transcription factors, and describe recent developments in the design and preparation of synthetic DNA binders. We mainly focus on synthetic peptides that have been designed by following the DNA interaction of natural proteins, and we discuss how the tools of organic synthesis can be used to make artificial constructs equipped with functionalities that introduce additional properties to the recognition process, such as sensing and controllability. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
-
Topology and robustness in the Drosophila segment polarity network.
Directory of Open Access Journals (Sweden)
Nicholas T Ingolia
2004-06-01
Full Text Available A complex hierarchy of genetic interactions converts a single-celled Drosophila melanogaster egg into a multicellular embryo with 14 segments. Previously, von Dassow et al. reported that a mathematical model of the genetic interactions that defined the polarity of segments (the segment polarity network was robust (von Dassow et al. 2000. As quantitative information about the system was unavailable, parameters were sampled randomly. A surprisingly large fraction of these parameter sets allowed the model to maintain and elaborate on the segment polarity pattern. This robustness is due to the positive feedback of gene products on their own expression, which induces individual cells in a model segment to adopt different stable expression states (bistability corresponding to different cell types in the segment polarity pattern. A positive feedback loop will only yield multiple stable states when the parameters that describe it satisfy a particular inequality. By testing which random parameter sets satisfy these inequalities, I show that bistability is necessary to form the segment polarity pattern and serves as a strong predictor of which parameter sets will succeed in forming the pattern. Although the original model was robust to parameter variation, it could not reproduce the observed effects of cell division on the pattern of gene expression. I present a modified version that incorporates recent experimental evidence and does successfully mimic the consequences of cell division. The behavior of this modified model can also be understood in terms of bistability in positive feedback of gene expression. I discuss how this topological property of networks provides robust pattern formation and how large changes in parameters can change the specific pattern produced by a network.
-
He, Fei; Murabito, Ettore; Westerhoff, Hans V
2016-04-01
Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways. © 2016 The Author(s).
-
Regulation of endogenous human gene expression by ligand-inducible TALE transcription factors.
Mercer, Andrew C; Gaj, Thomas; Sirk, Shannon J; Lamb, Brian M; Barbas, Carlos F
2014-10-17
The construction of increasingly sophisticated synthetic biological circuits is dependent on the development of extensible tools capable of providing specific control of gene expression in eukaryotic cells. Here, we describe a new class of synthetic transcription factors that activate gene expression in response to extracellular chemical stimuli. These inducible activators consist of customizable transcription activator-like effector (TALE) proteins combined with steroid hormone receptor ligand-binding domains. We demonstrate that these ligand-responsive TALE transcription factors allow for tunable and conditional control of gene activation and can be used to regulate the expression of endogenous genes in human cells. Since TALEs can be designed to recognize any contiguous DNA sequence, the conditional gene regulatory system described herein will enable the design of advanced synthetic gene networks.
-
Synthetic biology devices for in vitro and in vivo diagnostics.
Slomovic, Shimyn; Pardee, Keith; Collins, James J
2015-11-24
There is a growing need to enhance our capabilities in medical and environmental diagnostics. Synthetic biologists have begun to focus their biomolecular engineering approaches toward this goal, offering promising results that could lead to the development of new classes of inexpensive, rapidly deployable diagnostics. Many conventional diagnostics rely on antibody-based platforms that, although exquisitely sensitive, are slow and costly to generate and cannot readily confront rapidly emerging pathogens or be applied to orphan diseases. Synthetic biology, with its rational and short design-to-production cycles, has the potential to overcome many of these limitations. Synthetic biology devices, such as engineered gene circuits, bring new capabilities to molecular diagnostics, expanding the molecular detection palette, creating dynamic sensors, and untethering reactions from laboratory equipment. The field is also beginning to move toward in vivo diagnostics, which could provide near real-time surveillance of multiple pathological conditions. Here, we describe current efforts in synthetic biology, focusing on the translation of promising technologies into pragmatic diagnostic tools and platforms.
-
Synthetic biology approaches: Towards sustainable exploitation of marine bioactive molecules.
Seghal Kiran, G; Ramasamy, Pasiyappazham; Sekar, Sivasankari; Ramu, Meenatchi; Hassan, Saqib; Ninawe, A S; Selvin, Joseph
2018-06-01
The discovery of genes responsible for the production of bioactive metabolites via metabolic pathways combined with the advances in synthetic biology tools, has allowed the establishment of numerous microbial cell factories, for instance the yeast cell factories, for the manufacture of highly useful metabolites from renewable biomass. Genome mining and metagenomics are two platforms provide base-line data for reconstruction of genomes and metabolomes which is based in the development of synthetic/semi-synthetic genomes for marine natural products discovery. Engineered biofilms are being innovated on synthetic biology platform using genetic circuits and cell signalling systems as represillators controlling biofilm formation. Recombineering is a process of homologous recombination mediated genetic engineering, includes insertion, deletion or modification of any sequence specifically. Although this discipline considered new to the scientific domain, this field has now developed as promising endeavor on the accomplishment of sustainable exploitation of marine natural products. Copyright © 2018 Elsevier B.V. All rights reserved.
-
A robust neural network-based approach for microseismic event detection
Akram, Jubran
2017-08-17
We present an artificial neural network based approach for robust event detection from low S/N waveforms. We use a feed-forward network with a single hidden layer that is tuned on a training dataset and later applied on the entire example dataset for event detection. The input features used include the average of absolute amplitudes, variance, energy-ratio and polarization rectilinearity. These features are calculated in a moving-window of same length for the entire waveform. The output is set as a user-specified relative probability curve, which provides a robust way of distinguishing between weak and strong events. An optimal network is selected by studying the weight-based saliency and effect of number of neurons on the predicted results. Using synthetic data examples, we demonstrate that this approach is effective in detecting weaker events and reduces the number of false positives.
-
Classification of mislabelled microarrays using robust sparse logistic regression.
Bootkrajang, Jakramate; Kabán, Ata
2013-04-01
Previous studies reported that labelling errors are not uncommon in microarray datasets. In such cases, the training set may become misleading, and the ability of classifiers to make reliable inferences from the data is compromised. Yet, few methods are currently available in the bioinformatics literature to deal with this problem. The few existing methods focus on data cleansing alone, without reference to classification, and their performance crucially depends on some tuning parameters. In this article, we develop a new method to detect mislabelled arrays simultaneously with learning a sparse logistic regression classifier. Our method may be seen as a label-noise robust extension of the well-known and successful Bayesian logistic regression classifier. To account for possible mislabelling, we formulate a label-flipping process as part of the classifier. The regularization parameter is automatically set using Bayesian regularization, which not only saves the computation time that cross-validation would take, but also eliminates any unwanted effects of label noise when setting the regularization parameter. Extensive experiments with both synthetic data and real microarray datasets demonstrate that our approach is able to counter the bad effects of labelling errors in terms of predictive performance, it is effective at identifying marker genes and simultaneously it detects mislabelled arrays to high accuracy. The code is available from http://cs.bham.ac.uk/∼jxb008. Supplementary data are available at Bioinformatics online.
-
It's in the Name: A Synthetic Inquiry of the Knowledge Is Power Program [KIPP
Ellison, Scott
2012-01-01
The task of this article is to interrogate the Knowledge Is Power Program (KIPP) model to develop a more robust understanding of a prominent trend in the charter school movement and education policy more generally. To accomplish this task, this article details the findings of a synthetic analysis that examines the KIPP model as a Hegelian whole…
-
Effects of methodology and analysis strategy on robustness of pestivirus phylogeny.
Liu, Lihong; Xia, Hongyan; Baule, Claudia; Belák, Sándor; Wahlberg, Niklas
2010-01-01
Phylogenetic analysis of pestiviruses is a useful tool for classifying novel pestiviruses and for revealing their phylogenetic relationships. In this study, robustness of pestivirus phylogenies has been compared by analyses of the 5'UTR, and complete N(pro) and E2 gene regions separately and combined, performed by four methods: neighbour-joining (NJ), maximum parsimony (MP), maximum likelihood (ML), and Bayesian inference (BI). The strategy of analysing the combined sequence dataset by BI, ML, and MP methods resulted in a single, well-supported tree topology, indicating a reliable and robust pestivirus phylogeny. By contrast, the single-gene analysis strategy resulted in 12 trees of different topologies, revealing different relationships among pestiviruses. These results indicate that the strategies and methodologies are two vital aspects affecting the robustness of the pestivirus phylogeny. The strategy and methodologies outlined in this paper may have a broader application in inferring phylogeny of other RNA viruses.
-
Synthetic addiction extends the productive life time of engineered Escherichia coli populations
DEFF Research Database (Denmark)
Rugbjerg, Peter; Sarup-Lytzen, Kira; Nagy, Mariann
2018-01-01
range of genetic variants that disrupt the biosynthetic capacity of the engineered organism. Synthetic product addiction that couples high-yield production of a desired metabolite to expression of nonconditionally essential genes could offer a solution to this problem by selectively favoring cells...... with biosynthetic capacity in the population without constraining the medium. We constructed such synthetic product addiction by controlling the expression of two nonconditionally essential genes with a mevalonic acid biosensor. The product-addicted production organism retained high-yield mevalonic acid production...... through 95 generations of cultivation, corresponding to the number of cell generations required for >200-m3 industrial-scale production, at which time the nonaddicted strain completely abolished production. Using deep DNA sequencing, we find that the product-addicted populations do not accumulate genetic...
-
Synthetic Biology: A Unifying View and Review Using Analog Circuits.
Teo, Jonathan J Y; Woo, Sung Sik; Sarpeshkar, Rahul
2015-08-01
We review the field of synthetic biology from an analog circuits and analog computation perspective, focusing on circuits that have been built in living cells. This perspective is well suited to pictorially, symbolically, and quantitatively representing the nonlinear, dynamic, and stochastic (noisy) ordinary and partial differential equations that rigorously describe the molecular circuits of synthetic biology. This perspective enables us to construct a canonical analog circuit schematic that helps unify and review the operation of many fundamental circuits that have been built in synthetic biology at the DNA, RNA, protein, and small-molecule levels over nearly two decades. We review 17 circuits in the literature as particular examples of feedforward and feedback analog circuits that arise from special topological cases of the canonical analog circuit schematic. Digital circuit operation of these circuits represents a special case of saturated analog circuit behavior and is automatically incorporated as well. Many issues that have prevented synthetic biology from scaling are naturally represented in analog circuit schematics. Furthermore, the deep similarity between the Boltzmann thermodynamic equations that describe noisy electronic current flow in subthreshold transistors and noisy molecular flux in biochemical reactions has helped map analog circuit motifs in electronics to analog circuit motifs in cells and vice versa via a `cytomorphic' approach. Thus, a body of knowledge in analog electronic circuit design, analysis, simulation, and implementation may also be useful in the robust and efficient design of molecular circuits in synthetic biology, helping it to scale to more complex circuits in the future.
-
Sarpeshkar, R
2014-03-28
We analyse the pros and cons of analog versus digital computation in living cells. Our analysis is based on fundamental laws of noise in gene and protein expression, which set limits on the energy, time, space, molecular count and part-count resources needed to compute at a given level of precision. We conclude that analog computation is significantly more efficient in its use of resources than deterministic digital computation even at relatively high levels of precision in the cell. Based on this analysis, we conclude that synthetic biology must use analog, collective analog, probabilistic and hybrid analog-digital computational approaches; otherwise, even relatively simple synthetic computations in cells such as addition will exceed energy and molecular-count budgets. We present schematics for efficiently representing analog DNA-protein computation in cells. Analog electronic flow in subthreshold transistors and analog molecular flux in chemical reactions obey Boltzmann exponential laws of thermodynamics and are described by astoundingly similar logarithmic electrochemical potentials. Therefore, cytomorphic circuits can help to map circuit designs between electronic and biochemical domains. We review recent work that uses positive-feedback linearization circuits to architect wide-dynamic-range logarithmic analog computation in Escherichia coli using three transcription factors, nearly two orders of magnitude more efficient in parts than prior digital implementations.
-
Liu, Wusheng; Stewart, C Neal
2015-05-01
Plant synthetic biology is an emerging field that combines engineering principles with plant biology toward the design and production of new devices. This emerging field should play an important role in future agriculture for traditional crop improvement, but also in enabling novel bioproduction in plants. In this review we discuss the design cycles of synthetic biology as well as key engineering principles, genetic parts, and computational tools that can be utilized in plant synthetic biology. Some pioneering examples are offered as a demonstration of how synthetic biology can be used to modify plants for specific purposes. These include synthetic sensors, synthetic metabolic pathways, and synthetic genomes. We also speculate about the future of synthetic biology of plants. Copyright © 2015 Elsevier Ltd. All rights reserved.
-
The PLOS ONE Synthetic Biology Collection: Six Years and Counting
Peccoud, Jean; Isalan, Mark
2012-01-01
Since it was launched in 2006, PLOS ONE has published over fifty articles illustrating the many facets of the emerging field of synthetic biology. This article reviews these publications by organizing them into broad categories focused on DNA synthesis and assembly techniques, the development of libraries of biological parts, the use of synthetic biology in protein engineering applications, and the engineering of gene regulatory networks and metabolic pathways. Finally, we review articles that describe enabling technologies such as software and modeling, along with new instrumentation. In order to increase the visibility of this body of work, the papers have been assembled into the PLOS ONE Synthetic Biology Collection (www.ploscollections.org/synbio). Many of the innovative features of the PLOS ONE web site will help make this collection a resource that will support a lively dialogue between readers and authors of PLOS ONE synthetic biology papers. The content of the collection will be updated periodically by including relevant articles as they are published by the journal. Thus, we hope that this collection will continue to meet the publishing needs of the synthetic biology community. PMID:22916228
-
Yusufaly, Tahir; Boedicker, James
Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating density-dependent gene expression. However, the biology of QS remains incompletely understood in heterogeneous communities, where crosstalk between distinct QS systems leads to novel effects. Such knowledge is necessary both for understanding signaling in real microbial communities, and for the rational design of synthetic communities with designer properties. As a step towards this goal, we investigate the effects of crosstalk between Gram-negative bacteria communicating via LuxI/LuxR-type QS systems, with acyl-homoserine lactone (AHL) AI molecules. After mapping QS in a heterogeneous community onto an artificial neural network model, we systematically analyze how heterogeneity regulates the community's capability for stable yet flexible decision making. We find that there are preferred distributions of interactions which provide optimal tradeoffs between capacity, or the number of different decisions a population can make, and robustness, or the tolerance of the community to disturbances. We compare our results to inferences made from experimental data, and critically discuss implications for the biological significance of crosstalk.
-
PGASO: A synthetic biology tool for engineering a cellulolytic yeast
Directory of Open Access Journals (Sweden)
Chang Jui-Jen
2012-07-01
Full Text Available Abstract Background To achieve an economical cellulosic ethanol production, a host that can do both cellulosic saccharification and ethanol fermentation is desirable. However, to engineer a non-cellulolytic yeast to be such a host requires synthetic biology techniques to transform multiple enzyme genes into its genome. Results A technique, named Promoter-based Gene Assembly and Simultaneous Overexpression (PGASO, that employs overlapping oligonucleotides for recombinatorial assembly of gene cassettes with individual promoters, was developed. PGASO was applied to engineer Kluyveromycesmarxianus KY3, which is a thermo- and toxin-tolerant yeast. We obtained a recombinant strain, called KR5, that is capable of simultaneously expressing exoglucanase and endoglucanase (both of Trichodermareesei, a beta-glucosidase (from a cow rumen fungus, a neomycin phosphotransferase, and a green fluorescent protein. High transformation efficiency and accuracy were achieved as ~63% of the transformants was confirmed to be correct. KR5 can utilize beta-glycan, cellobiose or CMC as the sole carbon source for growth and can directly convert cellobiose and beta-glycan to ethanol. Conclusions This study provides the first example of multi-gene assembly in a single step in a yeast species other than Saccharomyces cerevisiae. We successfully engineered a yeast host with a five-gene cassette assembly and the new host is capable of co-expressing three types of cellulase genes. Our study shows that PGASO is an efficient tool for simultaneous expression of multiple enzymes in the kefir yeast KY3 and that KY3 can serve as a host for developing synthetic biology tools.
-
Breeding value of primary synthetic wheat genotypes for grain yield
To introduce new genetic diversity into the bread wheat gene pool from its progenitor, Aegilops tauschii (Coss.) Schmalh, 33 primary synthetic hexaploid wheat genotypes (SYN) were crossed to 20 spring bread wheat (BW) cultivars at the International Wheat and Maize Improvement Center. Modified single...
-
Chang, Huijuan; Gao, Qiuying; Ding, Wei; Qing, Xueqin
2018-01-01
Acute myeloid leukemia (AML) is a heterogeneous disease, and survival signatures are urgently needed to better monitor treatment. MiRNAs displayed vital regulatory roles on target genes, which was necessary involved in the complex disease. We therefore examined the expression levels of miRNAs and genes to identify robust signatures for survival benefit analyses. First, we reconstructed subpathway graphs by embedding miRNA components that were derived from low-throughput miRNA-gene interactions. Then, we randomly divided the data sets from The Cancer Genome Atlas (TCGA) into training and testing sets, and further formed 100 subsets based on the training set. Using each subset, we identified survival-related miRNAs and genes, and identified survival subpathways based on the reconstructed subpathway graphs. After statistical analyses of these survival subpathways, the most robust subpathways with the top three ranks were identified, and risk scores were calculated based on these robust subpathways for AML patient prognoses. Among these robust subpathways, three representative subpathways, path: 05200_10 from Pathways in cancer, path: 04110_20 from Cell cycle, and path: 04510_8 from Focal adhesion, were significantly associated with patient survival in the TCGA training and testing sets based on subpathway risk scores. In conclusion, we performed integrated analyses of miRNAs and genes to identify robust prognostic subpathways, and calculated subpathway risk scores to characterize AML patient survival.
-
Industrial systems biology and its impact on synthetic biology of yeast cell factories.
Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens
2016-06-01
Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
-
EcoFlex: A Multifunctional MoClo Kit for E. coli Synthetic Biology.
Moore, Simon J; Lai, Hung-En; Kelwick, Richard J R; Chee, Soo Mei; Bell, David J; Polizzi, Karen Marie; Freemont, Paul S
2016-10-21
Golden Gate cloning is a prominent DNA assembly tool in synthetic biology for the assembly of plasmid constructs often used in combinatorial pathway optimization, with a number of assembly kits developed specifically for yeast and plant-based expression. However, its use for synthetic biology in commonly used bacterial systems such as Escherichia coli has surprisingly been overlooked. Here, we introduce EcoFlex a simplified modular package of DNA parts for a variety of applications in E. coli, cell-free protein synthesis, protein purification and hierarchical assembly of transcription units based on the MoClo assembly standard. The kit features a library of constitutive promoters, T7 expression, RBS strength variants, synthetic terminators, protein purification tags and fluorescence proteins. We validate EcoFlex by assembling a 68-part containing (20 genes) plasmid (31 kb), characterize in vivo and in vitro library parts, and perform combinatorial pathway assembly, using pooled libraries of either fluorescent proteins or the biosynthetic genes for the antimicrobial pigment violacein as a proof-of-concept. To minimize pathway screening, we also introduce a secondary module design site to simplify MoClo pathway optimization. In summary, EcoFlex provides a standardized and multifunctional kit for a variety of applications in E. coli synthetic biology.
-
Directory of Open Access Journals (Sweden)
Duan S
2012-07-01
Full Text Available Shi-Yue Duan, Xue-Mei Ge, Nan Lu, Fei Wu, Weien Yuan, Tuo JinSchool of Pharmacy, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of ChinaAbstract: A chemically dynamic spermine-based polymer: polyspermine imidazole-4, 5-amide (PSIA, Mw > 7 kDa was designed, synthesized, and evaluated in terms of its ability to deliver nucleic acids. This polymer was made from an endogenous monomer professionally condensing genes in sperms, spermine, and a known safety drug metabolite, imidazole-4, 5-dicarboxylic acid, through a bis-amide bond conjugated with the imidazole ring. This polymer can condense pDNA at a W/W ratio above 10 to form polyplexes (100–200 nm in diameter, which is consistent with the observation by transmission electron microscopy (TEM, and the zeta potential was in the range of 10–20 mV. The pDNA packaged polymer was stable in phosphate buffer solution (PBS at pH 7.4 (simulated body fluid while the polyplexes were releasing pDNA into the solution at pH 5.8 (simulated endo-lysosomes due to the degradation of the bis-amide linkages in response to changes in pH values. PSIA-polyplexes were able to achieve efficient cellular uptake and luciferase gene silencing by co-transfection of pDNA and siRNA in COS-7 cells and HepG2 cells with negligible cytotoxicity. Biodistribution of Rhodamine B-labeled PSIA-polyplexes after being systemically injected in BALB/c nude-mice showed that the polyplexes circulated throughout the body, accumulated mainly in the kidney at 4 hours of sample administration, and moved to the liver and spleen after 24 hours. All the results suggested that PSIA offered a promising example to balance the transfection efficiency and toxicity of a synthetic carrier system for the delivery of therapeutic nucleic acids.Keywords: gene delivery, polyspermine, cytotoxicity, transfection efficiency, biodistribution
-
Directory of Open Access Journals (Sweden)
Aslihan Okan Ibiloglu
2017-09-01
Full Text Available Synthetic cannabinoids which is a subgroup of cannabinoids are commonly used for recreational drug use throughout the whole world. Although both marijuana and synthetic cannabinoids stimulate the same receptors, cannabinoid receptor 1 (CB1 and cannabinoid receptor 2 (CB2, studies have shown that synthetic cannabinoids are much more potent than marijuana. The longer use of synthetic cannabinoids can cause severe physical and psychological symptoms that might even result in death, similar to many known illicit drugs. Main treatment options mostly involve symptom management and supportive care. The aim of this article is to discuss clinical and pharmacological properties of the increasingly used synthetic cannabinoids. [Psikiyatride Guncel Yaklasimlar - Current Approaches in Psychiatry 2017; 9(3.000: 317-328
-
Cry3A δ-endotoxin gene mutagenized for enhanced toxicity
African Journals Online (AJOL)
Bacillus thuringiensis Cry3A gene was redesigned for high expression in Norwegian spruce and the sequence was slightly modified to allow for simple N- and C- terminal deletions and domain II loop 1 exchange for synthetic oligos. Modified Cry3A toxins from 13 variants of the synthetic gene were expressed in Escherichia ...
-
Simultaneous identification of synthetic and natural dyes in different food samples by UPLC-MS
Mandal, Badal Kumar; Mathiyalagan, Siva; Dalavai, Ramesh; Ling, Yong-Chien
2017-11-01
Fast foods and variety food items are populating among the food lovers. To improve the appearance of the food product in surviving gigantic competitive environment synthetic or natural food dyes are added to food items and beverages. Although regulatory bodies permit addition of natural colorants due to its safe and nontoxic nature in food, synthetic dyes are stringently controlled in all food products due to their toxicity by regulatory bodies. Artificial colors are need certification from the regulatory bodies for human consumption. To analyze food dyes in different food samples many analytical techniques are available like high pressure liquid chromatography (HPLC), thin layer chromatography (TLC), spectroscopic and gas chromatographic methods. However all these reported methods analyzed only synthetic dyes or natural dyes. Not a single method has analyzed both synthetic and natural dyes in a single run. In this study a robust ultra-performance liquid chromatographic method for simultaneous identification of 6 synthetic dyes (Tartrazine, Indigo carmine, Briliant blue, Fast green, malachite green, sunset yellow) and one natural dye (Na-Cu-Chlorophyllin) was developed using acquitic UPLC system equipped with Mass detector and acquity UPLC HSS T3 column (1.8 μm, 2.1 × 50 mm, 100Å). All the dyes were separated and their masses were determined through fragments’ masses analyses.
-
Application of synthetic biology for production of chemicals in yeast Saccharomyces cerevisiae.
Li, Mingji; Borodina, Irina
2015-02-01
Synthetic biology and metabolic engineering enable generation of novel cell factories that efficiently convert renewable feedstocks into biofuels, bulk, and fine chemicals, thus creating the basis for biosustainable economy independent on fossil resources. While over a hundred proof-of-concept chemicals have been made in yeast, only a very small fraction of those has reached commercial-scale production so far. The limiting factor is the high research cost associated with the development of a robust cell factory that can produce the desired chemical at high titer, rate, and yield. Synthetic biology has the potential to bring down this cost by improving our ability to predictably engineer biological systems. This review highlights synthetic biology applications for design, assembly, and optimization of non-native biochemical pathways in baker's yeast Saccharomyces cerevisiae We describe computational tools for the prediction of biochemical pathways, molecular biology methods for assembly of DNA parts into pathways, and for introducing the pathways into the host, and finally approaches for optimizing performance of the introduced pathways. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.
-
Robust experiment design for estimating myocardial β adrenergic receptor concentration using PET
International Nuclear Information System (INIS)
Salinas, Cristian; Muzic, Raymond F. Jr.; Ernsberger, Paul; Saidel, Gerald M.
2007-01-01
Myocardial β adrenergic receptor (β-AR) concentration can substantially decrease in congestive heart failure and significantly increase in chronic volume overload, such as in severe aortic valve regurgitation. Positron emission tomography (PET) with an appropriate ligand-receptor model can be used for noninvasive estimation of myocardial β-AR concentration in vivo. An optimal design of the experiment protocol, however, is needed for sufficiently precise estimates of β-AR concentration in a heterogeneous population. Standard methods of optimal design do not account for a heterogeneous population with a wide range of β-AR concentrations and other physiological parameters and consequently are inadequate. To address this, we have developed a methodology to design a robust two-injection protocol that provides reliable estimates of myocardial β-AR concentration in normal and pathologic states. A two-injection protocol of the high affinity β-AR antagonist [ 18 F]-(S)-fluorocarazolol was designed based on a computer-generated (or synthetic) population incorporating a wide range of β-AR concentrations. Timing and dosage of the ligand injections were optimally designed with minimax criterion to provide the least bad β-AR estimates for the worst case in the synthetic population. This robust experiment design for PET was applied to experiments with pigs before and after β-AR upregulation by chemical sympathectomy. Estimates of β-AR concentration were found by minimizing the difference between the model-predicted and experimental PET data. With this robust protocol, estimates of β-AR concentration showed high precision in both normal and pathologic states. The increase in β-AR concentration after sympathectomy predicted noninvasively with PET is consistent with the increase shown by in vitro assays in pig myocardium. A robust experiment protocol was designed for PET that yields reliable estimates of β-AR concentration in a population with normal and pathologic
-
Designing synthetic networks in silico: a generalised evolutionary algorithm approach.
Smith, Robert W; van Sluijs, Bob; Fleck, Christian
2017-12-02
Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.
-
[From synthetic biology to synthetic humankind].
Nouvel, Pascal
2015-01-01
In this paper, we propose an historical survey of the expression "synthetic biology" in order to identify its main philosophical components. The result of the analysis is then used to investigate the meaning of the notion of "synthetic man". It is shown that both notions share a common philosophical background that can be summed up by the short but meaningful assertion: "biology is technology". The analysis allows us to distinguish two notions that are often confused in transhumanist literature: the notion of synthetic man and the notion of renewed man. The consequences of this crucial distinction are discussed. Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.
-
Dymond, Jessica S.; Scheifele, Lisa Z.; Richardson, Sarah; Lee, Pablo; Chandrasegaran, Srinivasan; Bader, Joel S.; Boeke, Jef D.
2009-01-01
A major challenge in undergraduate life science curricula is the continual evaluation and development of courses that reflect the constantly shifting face of contemporary biological research. Synthetic biology offers an excellent framework within which students may participate in cutting-edge interdisciplinary research and is therefore an attractive addition to the undergraduate biology curriculum. This new discipline offers the promise of a deeper understanding of gene function, gene order, and chromosome structure through the de novo synthesis of genetic information, much as synthetic approaches informed organic chemistry. While considerable progress has been achieved in the synthesis of entire viral and prokaryotic genomes, fabrication of eukaryotic genomes requires synthesis on a scale that is orders of magnitude higher. These high-throughput but labor-intensive projects serve as an ideal way to introduce undergraduates to hands-on synthetic biology research. We are pursuing synthesis of Saccharomyces cerevisiae chromosomes in an undergraduate laboratory setting, the Build-a-Genome course, thereby exposing students to the engineering of biology on a genomewide scale while focusing on a limited region of the genome. A synthetic chromosome III sequence was designed, ordered from commercial suppliers in the form of oligonucleotides, and subsequently assembled by students into ∼750-bp fragments. Once trained in assembly of such DNA “building blocks” by PCR, the students accomplish high-yield gene synthesis, becoming not only technically proficient but also constructively critical and capable of adapting their protocols as independent researchers. Regular “lab meeting” sessions help prepare them for future roles in laboratory science. PMID:19015540
-
Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance.
Kalluri, Udaya C; Yin, Hengfu; Yang, Xiaohan; Davison, Brian H
2014-12-01
Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host that carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.
-
Robustness Metrics: Consolidating the multiple approaches to quantify Robustness
DEFF Research Database (Denmark)
Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.
2016-01-01
robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...
-
RNA and RNP as Building Blocks for Nanotechnology and Synthetic Biology.
Ohno, Hirohisa; Saito, Hirohide
2016-01-01
Recent technologies that aimed to elucidate cellular function have revealed essential roles for RNA molecules in living systems. Our knowledge concerning functional and structural information of naturally occurring RNA and RNA-protein (RNP) complexes is increasing rapidly. RNA and RNP interaction motifs are structural units that function as building blocks to constitute variety of complex structures. RNA-central synthetic biology and nanotechnology are constructive approaches that employ the accumulated information and build synthetic RNA (RNP)-based circuits and nanostructures. Here, we describe how to design and construct synthetic RNA (RNP)-based devices and structures at the nanometer-scale for biological and future therapeutic applications. RNA/RNP nanostructures can also be utilized as the molecular scaffold to control the localization or interactions of target molecule(s). Moreover, RNA motifs recognized by RNA-binding proteins can be applied to make protein-responsive translational "switches" that can turn gene expression "on" or "off" depending on the intracellular environment. This "synthetic RNA and RNP world" will expand tools for nanotechnology and synthetic biology. In addition, these reconstructive approaches would lead to a greater understanding of building principle in naturally occurring RNA/RNP molecules and systems. Copyright © 2016 Elsevier Inc. All rights reserved.
-
Artificial magnetic-field quenches in synthetic dimensions
Yılmaz, F.; Oktel, M. Ö.
2018-02-01
Recent cold atom experiments have realized models where each hyperfine state at an optical lattice site can be regarded as a separate site in a synthetic dimension. In such synthetic ribbon configurations, manipulation of the transitions between the hyperfine levels provide direct control of the hopping in the synthetic dimension. This effect was used to simulate a magnetic field through the ribbon. Precise control over the hopping matrix elements in the synthetic dimension makes it possible to change this artificial magnetic field much faster than the time scales associated with atomic motion in the lattice. In this paper, we consider such a magnetic-flux quench scenario in synthetic dimensions. Sudden changes have not been considered for real magnetic fields as such changes in a conducting system would result in large induced currents. Hence we first study the difference between a time varying real magnetic field and an artificial magnetic field using a minimal six-site model. This minimal model clearly shows the connection between gauge dependence and the lack of on-site induced scalar potential terms. We then investigate the dynamics of a wave packet in an infinite two- or three-leg ladder following a flux quench and find that the gauge choice has a dramatic effect on the packet dynamics. Specifically, a wave packet splits into a number of smaller packets moving with different velocities. Both the weights and the number of packets depend on the implemented gauge. If an initial packet, prepared under zero flux in an n -leg ladder, is quenched to Hamiltonian with a vector potential parallel to the ladder, it splits into at most n smaller wave packets. The same initial wave packet splits into up to n2 packets if the vector potential is implemented to be along the rungs. Even a trivial difference in the gauge choice such as the addition of a constant to the vector potential produces observable effects. We also calculate the packet weights for arbitrary initial and
-
Technical Improvement and Application of Hydrodynamic Gene Delivery in Study of Liver Diseases
Directory of Open Access Journals (Sweden)
Mei Huang
2017-08-01
Full Text Available Development of an safe and efficient in vivo gene delivery method is indispensable for molecular biology research and the progress in the following gene therapy. Over the past few years, hydrodynamic gene delivery (HGD with naked DNA has drawn increasing interest in both research and potential clinic applications due to its high efficiency and low risk in triggering immune responses and carcinogenesis in comparison to viral vectors. This method, involving intravenous injection (i.v. of massive DNA in a short duration, gives a transient but high in vivo gene expression especially in the liver of small animals. In addition to DNA, it has also been shown to deliver other substance such as RNA, proteins, synthetic small compounds and even viruses in vivo. Given its ability to robustly mimic in vivo hepatitis B virus (HBV production in liver, HGD has become a fundamental and important technology on HBV studies in our group and many other groups. Recently, there have been interesting reports about the applications and further improvement of this technology in other liver research. Here, we review the principle, safety, current application and development of hydrodynamic delivery in liver disease studies, and discuss its future prospects, clinical potential and challenges.
-
Genetic control of mammalian T-cell proliferation with synthetic RNA regulatory systems
Chen, Yvonne Y.; Jensen, Michael C.; Smolke, Christina D.
2010-01-01
RNA molecules perform diverse regulatory functions in natural biological systems, and numerous synthetic RNA-based control devices that integrate sensing and gene-regulatory functions have been demonstrated, predominantly in bacteria and yeast. Despite potential advantages of RNA-based genetic control strategies in clinical applications, there has been limited success in extending engineered RNA devices to mammalian gene-expression control and no example of their application to functional res...
-
Measure of robustness for complex networks
Youssef, Mina Nabil
to the spread of susceptible/infected/recovered (SIR) epidemics. To compute VCSIR, we propose a novel individual-based approach to model the spread of SIR epidemics in networks, which captures the infection size for a given effective infection rate. Thus, VCSIR quantitatively integrates the infection strength with the corresponding infection size. To optimize the VCSIR metric, a new mitigation strategy is proposed, based on a temporary reduction of contacts in social networks. The social contact network is modeled as a weighted graph that describes the frequency of contacts among the individuals. Thus, we consider the spread of an epidemic as a dynamical system, and the total number of infection cases as the state of the system, while the weight reduction in the social network is the controller variable leading to slow/reduce the spread of epidemics. Using optimal control theory, the obtained solution represents an optimal adaptive weighted network defined over a finite time interval. Moreover, given the high complexity of the optimization problem, we propose two heuristics to find the near optimal solutions by reducing the contacts among the individuals in a decentralized way. Finally, the cascading failures that can take place in power grids and have recently caused several blackouts are studied. We propose a new metric to assess the robustness of the power grid with respect to the cascading failures. The power grid topology is modeled as a network, which consists of nodes and links representing power substations and transmission lines, respectively. We also propose an optimal islanding strategy to protect the power grid when a cascading failure event takes place in the grid. The robustness metrics are numerically evaluated using real and synthetic networks to quantify their robustness with respect to disturbing dynamics. We show that the proposed metrics outperform the classical metrics in quantifying the robustness of networks and the efficiency of the mitigation
-
A synthetic system for expression of components of a bacterial microcompartment.
Sargent, Frank; Davidson, Fordyce A; Kelly, Ciarán L; Binny, Rachelle; Christodoulides, Natasha; Gibson, David; Johansson, Emelie; Kozyrska, Katarzyna; Lado, Lucia Licandro; Maccallum, Jane; Montague, Rachel; Ortmann, Brian; Owen, Richard; Coulthurst, Sarah J; Dupuy, Lionel; Prescott, Alan R; Palmer, Tracy
2013-11-01
In general, prokaryotes are considered to be single-celled organisms that lack internal membrane-bound organelles. However, many bacteria produce proteinaceous microcompartments that serve a similar purpose, i.e. to concentrate specific enzymic reactions together or to shield the wider cytoplasm from toxic metabolic intermediates. In this paper, a synthetic operon encoding the key structural components of a microcompartment was designed based on the genes for the Salmonella propanediol utilization (Pdu) microcompartment. The genes chosen included pduA, -B, -J, -K, -N, -T and -U, and each was shown to produce protein in an Escherichia coli chassis. In parallel, a set of compatible vectors designed to express non-native cargo proteins was also designed and tested. Engineered hexa-His tags allowed isolation of the components of the microcompartments together with co-expressed, untagged, cargo proteins. Finally, an in vivo protease accessibility assay suggested that a PduD-GFP fusion could be protected from proteolysis when co-expressed with the synthetic microcompartment operon. This work gives encouragement that it may be possible to harness the genes encoding a non-native microcompartment for future biotechnological applications.
-
Hacking DNA copy number for circuit engineering.
Wu, Feilun; You, Lingchong
2017-07-27
DNA copy number represents an essential parameter in the dynamics of synthetic gene circuits but typically is not explicitly considered. A new study demonstrates how dynamic control of DNA copy number can serve as an effective strategy to program robust oscillations in gene expression circuits.
-
Robustness from flexibility in the fungal circadian clock
Directory of Open Access Journals (Sweden)
Akman Ozgur E
2010-06-01
Full Text Available Abstract Background Robustness is a central property of living systems, enabling function to be maintained against environmental perturbations. A key challenge is to identify the structures in biological circuits that confer system-level properties such as robustness. Circadian clocks allow organisms to adapt to the predictable changes of the 24-hour day/night cycle by generating endogenous rhythms that can be entrained to the external cycle. In all organisms, the clock circuits typically comprise multiple interlocked feedback loops controlling the rhythmic expression of key genes. Previously, we showed that such architectures increase the flexibility of the clock's rhythmic behaviour. We now test the relationship between flexibility and robustness, using a mathematical model of the circuit controlling conidiation in the fungus Neurospora crassa. Results The circuit modelled in this work consists of a central negative feedback loop, in which the frequency (frq gene inhibits its transcriptional activator white collar-1 (wc-1, interlocked with a positive feedback loop in which FRQ protein upregulates WC-1 production. Importantly, our model reproduces the observed entrainment of this circuit under light/dark cycles with varying photoperiod and cycle duration. Our simulations show that whilst the level of frq mRNA is driven directly by the light input, the falling phase of FRQ protein, a molecular correlate of conidiation, maintains a constant phase that is uncoupled from the times of dawn and dusk. The model predicts the behaviour of mutants that uncouple WC-1 production from FRQ's positive feedback, and shows that the positive loop enhances the buffering of conidiation phase against seasonal photoperiod changes. This property is quantified using Kitano's measure for the overall robustness of a regulated system output. Further analysis demonstrates that this functional robustness is a consequence of the greater evolutionary flexibility conferred on
-
Egbert, Matthew D.; Pérez-Mercader, Juan
2016-01-01
Genetic mutations, infection by parasites or symbionts, and other events can transform the way that an organism’s internal state changes in response to a given environment. We use a minimalistic computational model to support an argument that by behaving “interoceptively,” i.e. responding to internal state rather than to the environment, organisms can be robust to these organisational-transformations. We suggest that the robustness of interoceptive behaviour is due, in part, to the asymmetrical relationship between an organism and its environment, where the latter more substantially influences the former than vice versa. This relationship means that interoceptive behaviour can respond to the environment, the internal state and the interaction between the two, while exteroceptive behaviour can only respond to the environment. We discuss the possibilities that (i) interoceptive behaviour may play an important role of facilitating adaptive evolution (especially in the early evolution of primitive life) and (ii) interoceptive mechanisms could prove useful in efforts to create more robust synthetic life-forms. PMID:26743579
-
Designing synthetic RNA for delivery by nanoparticles
International Nuclear Information System (INIS)
Jedrzejczyk, Dominika; Pawlowska, Roza; Chworos, Arkadiusz; Gendaszewska-Darmach, Edyta
2017-01-01
The rapid development of synthetic biology and nanobiotechnology has led to the construction of various synthetic RNA nanoparticles of different functionalities and potential applications. As they occur naturally, nucleic acids are an attractive construction material for biocompatible nanoscaffold and nanomachine design. In this review, we provide an overview of the types of RNA and nucleic acid’s nanoparticle design, with the focus on relevant nanostructures utilized for gene-expression regulation in cellular models. Structural analysis and modeling is addressed along with the tools available for RNA structural prediction. The functionalization of RNA-based nanoparticles leading to prospective applications of such constructs in potential therapies is shown. The route from the nanoparticle design and modeling through synthesis and functionalization to cellular application is also described. For a better understanding of the fate of targeted RNA after delivery, an overview of RNA processing inside the cell is also provided. (topical review)
-
Cascade-robustness optimization of coupling preference in interconnected networks
International Nuclear Information System (INIS)
Zhang, Xue-Jun; Xu, Guo-Qiang; Zhu, Yan-Bo; Xia, Yong-Xiang
2016-01-01
Highlights: • A specific memetic algorithm was proposed to optimize coupling links. • A small toy model was investigated to examine the underlying mechanism. • The MA optimized strategy exhibits a moderate assortative pattern. • A novel coupling coefficient index was proposed to quantify coupling preference. - Abstract: Recently, the robustness of interconnected networks has attracted extensive attentions, one of which is to investigate the influence of coupling preference. In this paper, the memetic algorithm (MA) is employed to optimize the coupling links of interconnected networks. Afterwards, a comparison is made between MA optimized coupling strategy and traditional assortative, disassortative and random coupling preferences. It is found that the MA optimized coupling strategy with a moderate assortative value shows an outstanding performance against cascading failures on both synthetic scale-free interconnected networks and real-world networks. We then provide an explanation for this phenomenon from a micro-scope point of view and propose a coupling coefficient index to quantify the coupling preference. Our work is helpful for the design of robust interconnected networks.
-
Open set recognition of aircraft in aerial imagery using synthetic template models
Bapst, Aleksander B.; Tran, Jonathan; Koch, Mark W.; Moya, Mary M.; Swahn, Robert
2017-05-01
Fast, accurate and robust automatic target recognition (ATR) in optical aerial imagery can provide game-changing advantages to military commanders and personnel. ATR algorithms must reject non-targets with a high degree of confidence in a world with an infinite number of possible input images. Furthermore, they must learn to recognize new targets without requiring massive data collections. Whereas most machine learning algorithms classify data in a closed set manner by mapping inputs to a fixed set of training classes, open set recognizers incorporate constraints that allow for inputs to be labelled as unknown. We have adapted two template-based open set recognizers to use computer generated synthetic images of military aircraft as training data, to provide a baseline for military-grade ATR: (1) a frequentist approach based on probabilistic fusion of extracted image features, and (2) an open set extension to the one-class support vector machine (SVM). These algorithms both use histograms of oriented gradients (HOG) as features as well as artificial augmentation of both real and synthetic image chips to take advantage of minimal training data. Our results show that open set recognizers trained with synthetic data and tested with real data can successfully discriminate real target inputs from non-targets. However, there is still a requirement for some knowledge of the real target in order to calibrate the relationship between synthetic template and target score distributions. We conclude by proposing algorithm modifications that may improve the ability of synthetic data to represent real data.
-
Beyond Cost-Benefit Analysis in the Governance of Synthetic Biology.
Wallach, Wendell; Saner, Marc; Marchant, Gary
2018-01-01
For many innovations, oversight fits nicely within existing governance mechanisms; nevertheless, others pose unique public health, environmental, and ethical challenges. Synthetic artemisinin, for example, has many precursors in laboratory-developed drugs that emulate natural forms of the same drug. The policy challenges posed by synthetic artemisinin do not differ significantly in kind from other laboratory-formulated drugs. Synthetic biofuels and gene drives, however, fit less clearly into existing governance structures. How many of the new categories of products require new forms of regulatory oversight, or at least extensive forms of testing, remains unclear. Any effort to improve the governance of synthetic biology should start with a rich understanding of the different possible science-policy interfaces that could help to inform governance. CBA falls into a subset of the overall range of possibilities, and which interface is appropriate may turn out to depend on context, on the demands of the decision at hand. In what follows, we lay out a typology of interfaces. After that, we turn to the question of how to draw upon the range of possible interfaces and effectively address the factual and moral complexities of emerging technologies. We propose a governance model built around structures that we call "governance coordinating committees." GCCs are intended to be mechanisms for accommodating the complexities of innovations that have far-ranging societal impacts. The production of biofuels, for example, could contaminate water supplies and have a destructive environmental impact if not managed correctly. The introduction of a gene drive could have economic and environmental impacts that are not restricted to one nation. Forging appropriate means for determining and evaluating those societal impacts, to the best of a corporation's, industry's, or government's ability, is central to responsible research and innovation. Public policy must be shaped in a manner that
-
Chakravarti, Deboki; Cho, Jang Hwan; Weinberg, Benjamin H; Wong, Nicole M; Wong, Wilson W
2016-04-18
Investigations into cells and their contents have provided evolving insight into the emergence of complex biological behaviors. Capitalizing on this knowledge, synthetic biology seeks to manipulate the cellular machinery towards novel purposes, extending discoveries from basic science to new applications. While these developments have demonstrated the potential of building with biological parts, the complexity of cells can pose numerous challenges. In this review, we will highlight the broad and vital role that the synthetic biology approach has played in applying fundamental biological discoveries in receptors, genetic circuits, and genome-editing systems towards translation in the fields of immunotherapy, biosensors, disease models and gene therapy. These examples are evidence of the strength of synthetic approaches, while also illustrating considerations that must be addressed when developing systems around living cells.
-
Phage Therapy in the Era of Synthetic Biology.
Barbu, E Magda; Cady, Kyle C; Hubby, Bolyn
2016-10-03
For more than a century, bacteriophage (or phage) research has enabled some of the most important discoveries in biological sciences and has equipped scientists with many of the molecular biology tools that have advanced our understanding of replication, maintenance, and expression of genetic material. Phages have also been recognized and exploited as natural antimicrobial agents and nanovectors for gene therapy, but their potential as therapeutics has not been fully exploited in Western medicine because of challenges such as narrow host range, bacterial resistance, and unique pharmacokinetics. However, increasing concern related to the emergence of bacteria resistant to multiple antibiotics has heightened interest in phage therapy and the development of strategies to overcome hurdles associated with bacteriophage therapeutics. Recent progress in sequencing technologies, DNA manipulation, and synthetic biology allowed scientists to refactor the entire bacterial genome of Mycoplasma mycoides, thereby creating the first synthetic cell. These new strategies for engineering genomes may have the potential to accelerate the construction of designer phage genomes with superior therapeutic potential. Here, we discuss the use of phage as therapeutics, as well as how synthetic biology can create bacteriophage with desirable attributes. Copyright © 2016 Cold Spring Harbor Laboratory Press; all rights reserved.
-
Robust Linear Models for Cis-eQTL Analysis.
Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C
2015-01-01
Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.
-
Biotechnology and synthetic biology approaches for metabolic engineering of bioenergy crops.
Shih, Patrick M; Liang, Yan; Loqué, Dominique
2016-07-01
The Green Revolution has fuelled an exponential growth in human population since the mid-20th century. Due to population growth, food and energy demands will soon surpass supply capabilities. To overcome these impending problems, significant improvements in genetic engineering will be needed to complement breeding efforts in order to accelerate the improvement of agronomical traits. The new field of plant synthetic biology has emerged in recent years and is expected to support rapid, precise, and robust engineering of plants. In this review, we present recent advances made in the field of plant synthetic biology, specifically in genome editing, transgene expression regulation, and bioenergy crop engineering, with a focus on traits related to lignocellulose, oil, and soluble sugars. Ultimately, progress and innovation in these fields may facilitate the development of beneficial traits in crop plants to meet society's bioenergy needs. © 2016 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.
-
Robust estimation of hydrological model parameters
Directory of Open Access Journals (Sweden)
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
-
Synthetic biology as it relates to CAM photosynthesis: challenges and opportunities.
DePaoli, Henrique C; Borland, Anne M; Tuskan, Gerald A; Cushman, John C; Yang, Xiaohan
2014-07-01
To meet future food and energy security needs, which are amplified by increasing population growth and reduced natural resource availability, metabolic engineering efforts have moved from manipulating single genes/proteins to introducing multiple genes and novel pathways to improve photosynthetic efficiency in a more comprehensive manner. Biochemical carbon-concentrating mechanisms such as crassulacean acid metabolism (CAM), which improves photosynthetic, water-use, and possibly nutrient-use efficiency, represent a strategic target for synthetic biology to engineer more productive C3 crops for a warmer and drier world. One key challenge for introducing multigene traits like CAM onto a background of C3 photosynthesis is to gain a better understanding of the dynamic spatial and temporal regulatory events that underpin photosynthetic metabolism. With the aid of systems and computational biology, vast amounts of experimental data encompassing transcriptomics, proteomics, and metabolomics can be related in a network to create dynamic models. Such models can undergo simulations to discover key regulatory elements in metabolism and suggest strategic substitution or augmentation by synthetic components to improve photosynthetic performance and water-use efficiency in C3 crops. Another key challenge in the application of synthetic biology to photosynthesis research is to develop efficient systems for multigene assembly and stacking. Here, we review recent progress in computational modelling as applied to plant photosynthesis, with attention to the requirements for CAM, and recent advances in synthetic biology tool development. Lastly, we discuss possible options for multigene pathway construction in plants with an emphasis on CAM-into-C3 engineering. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
-
Directory of Open Access Journals (Sweden)
Soltis Pamela S
2010-09-01
Full Text Available Abstract Background Tragopogon mirus and T. miscellus are allotetraploids (2n = 24 that formed repeatedly during the past 80 years in eastern Washington and adjacent Idaho (USA following the introduction of the diploids T. dubius, T. porrifolius, and T. pratensis (2n = 12 from Europe. In most natural populations of T. mirus and T. miscellus, there are far fewer 35S rRNA genes (rDNA of T. dubius than there are of the other diploid parent (T. porrifolius or T. pratensis. We studied the inheritance of parental rDNA loci in allotetraploids resynthesized from diploid accessions. We investigate the dynamics and directionality of these rDNA losses, as well as the contribution of gene copy number variation in the parental diploids to rDNA variation in the derived tetraploids. Results Using Southern blot hybridization and fluorescent in situ hybridization (FISH, we analyzed copy numbers and distribution of these highly reiterated genes in seven lines of synthetic T. mirus (110 individuals and four lines of synthetic T. miscellus (71 individuals. Variation among diploid parents accounted for most of the observed gene imbalances detected in F1 hybrids but cannot explain frequent deviations from repeat additivity seen in the allotetraploid lines. Polyploid lineages involving the same diploid parents differed in rDNA genotype, indicating that conditions immediately following genome doubling are crucial for rDNA changes. About 19% of the resynthesized allotetraploid individuals had equal rDNA contributions from the diploid parents, 74% were skewed towards either T. porrifolius or T. pratensis-type units, and only 7% had more rDNA copies of T. dubius-origin compared to the other two parents. Similar genotype frequencies were observed among natural populations. Despite directional reduction of units, the additivity of 35S rDNA locus number is maintained in 82% of the synthetic lines and in all natural allotetraploids. Conclusions Uniparental reductions of
-
Neutrality and robustness in evo-devo: emergence of lateral inhibition.
Directory of Open Access Journals (Sweden)
Andreea Munteanu
2008-11-01
Full Text Available Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype into a spatial gene expression pattern (phenotype providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype-phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo. We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles.
-
Otoupal, Peter B; Erickson, Keesha E; Escalas-Bordoy, Antoni; Chatterjee, Anushree
2017-01-20
The evolution of antibiotic resistance has engendered an impending global health crisis that necessitates a greater understanding of how resistance emerges. The impact of nongenetic factors and how they influence the evolution of resistance is a largely unexplored area of research. Here we present a novel application of CRISPR-Cas9 technology for investigating how gene expression governs the adaptive pathways available to bacteria during the evolution of resistance. We examine the impact of gene expression changes on bacterial adaptation by constructing a library of deactivated CRISPR-Cas9 synthetic devices to tune the expression of a set of stress-response genes in Escherichia coli. We show that artificially inducing perturbations in gene expression imparts significant synthetic control over fitness and growth during stress exposure. We present evidence that these impacts are reversible; strains with synthetically perturbed gene expression regained wild-type growth phenotypes upon stress removal, while maintaining divergent growth characteristics under stress. Furthermore, we demonstrate a prevailing trend toward negative epistatic interactions when multiple gene perturbations are combined simultaneously, thereby posing an intrinsic constraint on gene expression underlying adaptive trajectories. Together, these results emphasize how CRISPR-Cas9 can be employed to engineer gene expression changes that shape bacterial adaptation, and present a novel approach to synthetically control the evolution of antimicrobial resistance.
-
Development of synthetic selfish elements based on modular nucleases in Drosophila melanogaster
Simoni, A; Siniscalchi, C; Chan, Y-S; Huen, DS; Russell, S; Windbichler, N; Crisanti, A
2014-01-01
Selfish genes are DNA elements that increase their rate of genetic transmission at the expense of other genes in the genome and can therefore quickly spread within a population. It has been suggested that selfish elements could be exploited to modify the genome of entire populations for medical and ecological applications. Here we report that transcription activator-like effector nuclease (TALEN) and zinc finger nuclease (ZFN) can be engineered into site-specific synthetic selfish elements (S...
-
Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.
Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver
2018-02-15
Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R
-
Robust segmentation of focal lesions on multi-sequence MRI in multiple sclerosis
International Nuclear Information System (INIS)
Garcia-Lorenzo, Daniel
2010-01-01
Multiple sclerosis (MS) affects around 80.000 people in France. Magnetic resonance imaging (MRI) is an essential tool for diagnosis of MS and MRI-derived surrogate markers such as MS lesion volumes are often used as measures in MS clinical trials for the development of new treatments. The manual segmentation of these MS lesions is a time-consuming task that shows high inter- and intra-rater variability. We developed an automatic work flow for the segmentation of focal MS lesions on MRI. The segmentation method is based on the robust estimation of a parametric model of the intensities of the brain; lesions are detected as outliers to the model. We proposed two methods to include spatial information in the segmentation using mean shift and graph cut. We performed a quantitative evaluation of our work flow using synthetic and clinical images of two different centers to verify its accuracy and robustness. (author)
-
The Role of Synthetic Reconstruction Tests in Seismic Tomography
Rawlinson, N.; Spakman, W.
2015-12-01
Synthetic reconstruction tests are widely used in seismic tomography as a means for assessing the robustness of solutions produced by linear or iterative non-linear inversion schemes. The most common test is the so-called checkerboard resolution test, which uses an alternating pattern of high and low wavespeeds (or some other seismic property such as attenuation). However, checkerboard tests have a number of limitations, including that they (1) only provide indirect evidence of quantitative measures of reliability such as resolution and uncertainty; (2) give a potentially misleading impression of the range of scale-lengths that can be resolved; (3) don't give a true picture of the structural distortion or smearing caused by the data coverage; and (4) result in an inverse problem that is biased towards an accurate reconstruction. The widespread use of synthetic reconstruction tests in seismic tomography is likely to continue for some time yet, so it is important to implement best practice where possible. The goal here is to provide a general set of guidelines, derived from the underlying theory and illustrated by a series of numerical experiments, on their implementation in seismic tomography. In particular, we recommend (1) using a sparse distribution of spikes, rather than the more conventional tightly-spaced checkerboard; (2) using the identical data coverage (e.g. geometric rays) for the synthetic model that was computed for the observation-based model; (3) carrying out multiple tests using anomalies of different scale length; (4) exercising caution when analysing synthetic recovery tests that use anomaly patterns that closely mimic the observation-based model; (5) investigating the trade-off between data noise levels and the minimum wavelength of recovered structure; (6) where possible, test the extent to which preconditioning (e.g. identical parameterization for input and output models) influences the recovery of anomalies.
-
pTRA - A reporter system for monitoring the intracellular dynamics of gene expression.
Wagner, Sabine G; Ziegler, Martin; Löwe, Hannes; Kremling, Andreas; Pflüger-Grau, Katharina
2018-01-01
The presence of standardised tools and methods to measure and represent accurately biological parts and functions is a prerequisite for successful metabolic engineering and crucial to understand and predict the behaviour of synthetic genetic circuits. Many synthetic gene networks are based on transcriptional circuits, thus information on transcriptional and translational activity is important for understanding and fine-tuning the synthetic function. To this end, we have developed a toolkit to analyse systematically the transcriptional and translational activity of a specific synthetic part in vivo. It is based on the plasmid pTRA and allows the assignment of specific transcriptional and translational outputs to the gene(s) of interest (GOI) and to compare different genetic setups. By this, the optimal combination of transcriptional strength and translational activity can be identified. The design is tested in a case study using the gene encoding the fluorescent mCherry protein as GOI. We show the intracellular dynamics of mRNA and protein formation and discuss the potential and shortcomings of the pTRA plasmid.
-
Bukhari, Hassan J.
2017-12-01
In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.
-
Azmi, Fazren; Skwarczynski, Mariusz; Toth, Istvan
2016-01-01
Virtually every living organism produces gene-encoded antimicrobial peptides (AMPs) that provide an immediate defence against pathogen invasion. Many AMPs have been isolated and used as antibiotics that are effective against multidrug-resistant bacteria. Although encouraging, AMPs have such poor drug-like properties that their application for clinical use is restricted. In turn, this has diverted research to the development of synthetic molecules that retain the therapeutic efficacy of AMPs but are endowed with greater biological stability and safety profiles. Most of the synthetic molecules, either based on a peptidic or non-peptidic scaffold, have been designed to mimic the amphiphilic properties of native AMPs, which are widely believed to be the key determinant of their antibacterial activity. In this review, the structural, chemical and biophysical features that govern the biological activities of various synthetic designs are discussed extensively. Recent innovative approaches from the literature that exhibit novel concepts towards the development of new synthetic antibacterial agents, including the engineered delivery platform incorporated with AMP mimetics, are also emphasised.
-
Fiorini, Rodolfo A.; Dacquino, Gianfranco
2005-03-01
GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous
-
Directory of Open Access Journals (Sweden)
Gian Andri Thun
Full Text Available Several infrequent genetic polymorphisms in the SERPINA1 gene are known to substantially reduce concentration of alpha1-antitrypsin (AAT in the blood. Since low AAT serum levels fail to protect pulmonary tissue from enzymatic degradation, these polymorphisms also increase the risk for early onset chronic obstructive pulmonary disease (COPD. The role of more common SERPINA1 single nucleotide polymorphisms (SNPs in respiratory health remains poorly understood. We present here an agnostic investigation of genetic determinants of circulating AAT levels in a general population sample by performing a genome-wide association study (GWAS in 1392 individuals of the SAPALDIA cohort. Five common SNPs, defined by showing minor allele frequencies (MAFs >5%, reached genome-wide significance, all located in the SERPINA gene cluster at 14q32.13. The top-ranking genotyped SNP rs4905179 was associated with an estimated effect of β = -0.068 g/L per minor allele (P = 1.20*10(-12. But denser SERPINA1 locus genotyping in 5569 participants with subsequent stepwise conditional analysis, as well as exon-sequencing in a subsample (N = 410, suggested that AAT serum level is causally determined at this locus by rare (MAF<1% and low-frequent (MAF 1-5% variants only, in particular by the well-documented protein inhibitor S and Z (PI S, PI Z variants. Replication of the association of rs4905179 with AAT serum levels in the Copenhagen City Heart Study (N = 8273 was successful (P<0.0001, as was the replication of its synthetic nature (the effect disappeared after adjusting for PI S and Z, P = 0.57. Extending the analysis to lung function revealed a more complex situation. Only in individuals with severely compromised pulmonary health (N = 397, associations of common SNPs at this locus with lung function were driven by rarer PI S or Z variants. Overall, our meta-analysis of lung function in ever-smokers does not support a functional role of common SNPs in the SERPINA gene
-
Singha, Harisankar; Goyal, Sachin K; Malik, Praveen; Khurana, Sandip K; Singh, Raj K
2013-12-01
Equine infectious anemia (EIA)-a retroviral disease caused by equine infectious anemia virus (EIAV)-is a chronic, debilitating disease of horses, mules, and donkeys. EIAV infection has been reported worldwide and is recognized as pathogen of significant economic importance to the horse industry. This disease falls under regulatory control program in many countries including India. Control of EIA is based on identification of inapparent carriers by detection of antibodies to EIAV in serologic tests and "Stamping Out" policy. The current internationally accepted test for diagnosis of EIA is the agar gel immune-diffusion test (AGID), which detects antibodies to the major gag gene (p26) product. The objective of this study was to develop recombinant p26 based in-house immunoassays [enzyme linked immunosorbent assays (ELISA), and AGID] for EIA diagnosis. The synthetic p26 gene of EIAV was expressed in Escherichia coli and diagnostic potential of recombinant p26 protein were evaluated in ELISA and AGID on 7,150 and 1,200 equine serum samples, respectively, and compared with commercial standard AGID kit. The relative sensitivity and specificity of the newly developed ELISA were 100 and 98.6 %, respectively. Whereas, relative sensitivity and specificity of the newly developed AGID were in complete agreement in respect to commercial AGID kit. Here, we have reported the validation of an ELISA and AGID on large number of equine serum samples using recombinant p26 protein produced from synthetic gene which does not require handling of pathogenic EIAV. Since the indigenously developed reagents would be economical than commercial diagnostic kit, the rp26 based-immunoassays could be adopted for the sero-diagnosis and control of EIA in India.
-
Production of Fatty Acid-Derived Valuable Chemicals in Synthetic Microbes
International Nuclear Information System (INIS)
Yu, Ai-Qun; Pratomo Juwono, Nina Kurniasih; Leong, Susanna Su Jan; Chang, Matthew Wook
2014-01-01
Fatty acid derivatives, such as hydroxy fatty acids, fatty alcohols, fatty acid methyl/ethyl esters, and fatty alka(e)nes, have a wide range of industrial applications including plastics, lubricants, and fuels. Currently, these chemicals are obtained mainly through chemical synthesis, which is complex and costly, and their availability from natural biological sources is extremely limited. Metabolic engineering of microorganisms has provided a platform for effective production of these valuable biochemicals. Notably, synthetic biology-based metabolic engineering strategies have been extensively applied to refactor microorganisms for improved biochemical production. Here, we reviewed: (i) the current status of metabolic engineering of microbes that produce fatty acid-derived valuable chemicals, and (ii) the recent progress of synthetic biology approaches that assist metabolic engineering, such as mRNA secondary structure engineering, sensor-regulator system, regulatable expression system, ultrasensitive input/output control system, and computer science-based design of complex gene circuits. Furthermore, key challenges and strategies were discussed. Finally, we concluded that synthetic biology provides useful metabolic engineering strategies for economically viable production of fatty acid-derived valuable chemicals in engineered microbes.
-
Production of Fatty Acid-Derived Valuable Chemicals in Synthetic Microbes
Energy Technology Data Exchange (ETDEWEB)
Yu, Ai-Qun; Pratomo Juwono, Nina Kurniasih [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore); Leong, Susanna Su Jan [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore); Singapore Institute of Technology, Singapore (Singapore); Chang, Matthew Wook, E-mail: bchcmw@nus.edu.sg [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore)
2014-12-23
Fatty acid derivatives, such as hydroxy fatty acids, fatty alcohols, fatty acid methyl/ethyl esters, and fatty alka(e)nes, have a wide range of industrial applications including plastics, lubricants, and fuels. Currently, these chemicals are obtained mainly through chemical synthesis, which is complex and costly, and their availability from natural biological sources is extremely limited. Metabolic engineering of microorganisms has provided a platform for effective production of these valuable biochemicals. Notably, synthetic biology-based metabolic engineering strategies have been extensively applied to refactor microorganisms for improved biochemical production. Here, we reviewed: (i) the current status of metabolic engineering of microbes that produce fatty acid-derived valuable chemicals, and (ii) the recent progress of synthetic biology approaches that assist metabolic engineering, such as mRNA secondary structure engineering, sensor-regulator system, regulatable expression system, ultrasensitive input/output control system, and computer science-based design of complex gene circuits. Furthermore, key challenges and strategies were discussed. Finally, we concluded that synthetic biology provides useful metabolic engineering strategies for economically viable production of fatty acid-derived valuable chemicals in engineered microbes.
-
Freedom and Responsibility in Synthetic Genomics: The Synthetic Yeast Project
Sliva, Anna; Yang, Huanming; Boeke, Jef D.; Mathews, Debra J. H.
2015-01-01
First introduced in 2011, the Synthetic Yeast Genome (Sc2.0) Project is a large international synthetic genomics project that will culminate in the first eukaryotic cell (Saccharomyces cerevisiae) with a fully synthetic genome. With collaborators from across the globe and from a range of institutions spanning from do-it-yourself biology (DIYbio) to commercial enterprises, it is important that all scientists working on this project are cognizant of the ethical and policy issues associated with...
-
Directory of Open Access Journals (Sweden)
Laura R. Jarboe
2010-01-01
Full Text Available Production of fuels and chemicals through microbial fermentation of plant material is a desirable alternative to petrochemical-based production. Fermentative production of biorenewable fuels and chemicals requires the engineering of biocatalysts that can quickly and efficiently convert sugars to target products at a cost that is competitive with existing petrochemical-based processes. It is also important that biocatalysts be robust to extreme fermentation conditions, biomass-derived inhibitors, and their target products. Traditional metabolic engineering has made great advances in this area, but synthetic biology has contributed and will continue to contribute to this field, particularly with next-generation biofuels. This work reviews the use of metabolic engineering and synthetic biology in biocatalyst engineering for biorenewable fuels and chemicals production, such as ethanol, butanol, acetate, lactate, succinate, alanine, and xylitol. We also examine the existing challenges in this area and discuss strategies for improving biocatalyst tolerance to chemical inhibitors.
-
Robust mesoscopic superposition of strongly correlated ultracold atoms
International Nuclear Information System (INIS)
Hallwood, David W.; Ernst, Thomas; Brand, Joachim
2010-01-01
We propose a scheme to create coherent superpositions of annular flow of strongly interacting bosonic atoms in a one-dimensional ring trap. The nonrotating ground state is coupled to a vortex state with mesoscopic angular momentum by means of a narrow potential barrier and an applied phase that originates from either rotation or a synthetic magnetic field. We show that superposition states in the Tonks-Girardeau regime are robust against single-particle loss due to the effects of strong correlations. The coupling between the mesoscopically distinct states scales much more favorably with particle number than in schemes relying on weak interactions, thus making particle numbers of hundreds or thousands feasible. Coherent oscillations induced by time variation of parameters may serve as a 'smoking gun' signature for detecting superposition states.
-
Characterization of Thermal Stability of Synthetic and Semi-Synthetic Engine Oils
Directory of Open Access Journals (Sweden)
Anand Kumar Tripathi
2015-03-01
Full Text Available Engine oils undergo oxidative degradation and wears out during service. Hence it is important to characterize ageing of engine oils at different simulated conditions to evaluate the performance of existing oils and also design new formulations. This work focuses on characterizing the thermo-oxidative degradation of synthetic and semi-synthetic engine oils aged at 120, 149 and 200 °C. Apparent activation energy of decomposition of aged oils evaluated using the isoconversional Kissinger-Akahira-Sunose technique was used as a thermal stability marker. The temporal variation of stability at different ageing temperatures was corroborated with kinematic viscosity, oxidation, sulfation and nitration indices, total base number, antiwear additive content and molecular structure of the organic species present in the oils. At the lowest temperature employed, synthetic oil underwent higher rate of oxidation, while semi-synthetic oil was stable for longer time periods. At higher temperatures, the initial rate of change of average apparent activation energy of synthetic oil correlated well with a similar variation in oxidation number. A mixture of long chain linear, branched, and cyclic hydrocarbons were observed when semi-synthetic oil was degraded at higher temperatures.
-
Synthetic biology stretching the realms of possibility in wine yeast research.
Jagtap, Umesh B; Jadhav, Jyoti P; Bapat, Vishwas A; Pretorius, Isak S
2017-07-03
It took several millennia to fully understand the scientific intricacies of the process through which grape juice is turned into wine. This yeast-driven fermentation process is still being perfected and advanced today. Motivated by ever-changing consumer preferences and the belief that the 'best' wine is yet to be made, numerous approaches are being pursued to improve the process of yeast fermentation and the quality of wine. Central to recent enhancements in winemaking processes and wine quality is the development of Saccharomyces cerevisiae yeast strains with improved robustness, fermentation efficiencies and sensory properties. The emerging science of Synthetic Biology - including genome engineering and DNA editing technologies - is taking yeast strain development into a totally new realm of possibility. The first example of how future wine strain development might be impacted by these new 'history-making' Synthetic Biology technologies, is the de novo production of the raspberry ketone aroma compound, 4-[4-hydroxyphenyl]butan-2-one, in a wine yeast containing a synthetic DNA cassette. This article explores how this breakthrough and the imminent outcome of the international Yeast 2.0 (or Sc2.0) project, aimed at the synthesis of the entire genome of a laboratory strain of S. cerevisiae, might accelerate the design of improved wine yeasts. Copyright © 2017 Elsevier B.V. All rights reserved.
-
Quillien, Aurelie; Abdalla, Mary; Yu, Jun; Ou, Jianhong; Zhu, Lihua Julie; Lawson, Nathan D
2017-07-18
Identification of tissue-specific and developmentally active enhancers provides insights into mechanisms that control gene expression during embryogenesis. However, robust detection of these regulatory elements remains challenging, especially in vertebrate genomes. Here, we apply fluorescent-activated nuclei sorting (FANS) followed by Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) to identify developmentally active endothelial enhancers in the zebrafish genome. ATAC-seq of nuclei from Tg(fli1a:egfp) y1 transgenic embryos revealed expected patterns of nucleosomal positioning at transcriptional start sites throughout the genome and association with active histone modifications. Comparison of ATAC-seq from GFP-positive and -negative nuclei identified more than 5,000 open elements specific to endothelial cells. These elements flanked genes functionally important for vascular development and that displayed endothelial-specific gene expression. Importantly, a majority of tested elements drove endothelial gene expression in zebrafish embryos. Thus, FANS-assisted ATAC-seq using transgenic zebrafish embryos provides a robust approach for genome-wide identification of active tissue-specific enhancer elements. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
-
Mammalian Synthetic Biology: Engineering Biological Systems.
Black, Joshua B; Perez-Pinera, Pablo; Gersbach, Charles A
2017-06-21
The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.
-
DEFF Research Database (Denmark)
Pedersen, Søren Nygaard
The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... been presented. Therefore, this study set out to contribute to the understanding and application of perceptual robust design. To achieve this, a state-of-the-art and current practice review was performed. From the review two main research problems were identified. Firstly, a lack of tools...... for perceptual robustness was found to overlap with the optimum for functional robustness and at most approximately 2.2% out of the 14.74% could be ascribed solely to the perceptual robustness optimisation. In conclusion, the thesis have offered a new perspective on robust design by merging robust design...
-
DEFF Research Database (Denmark)
Liu, Gang; Lee, Seunggeun; Lee, Alice W
2018-01-01
test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides power gain compared to the standard logistic regression analysis and better control of Type I error when compared to the analysis......There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances the power for testing multiplicative interaction in case......-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated Type I error in the corresponding tests can occur. This paper extends the empirical Bayes (EB) approach previously developed for multiplicative interaction that trades off between bias and efficiency...
-
Freedom and Responsibility in Synthetic Genomics: The Synthetic Yeast Project.
Sliva, Anna; Yang, Huanming; Boeke, Jef D; Mathews, Debra J H
2015-08-01
First introduced in 2011, the Synthetic Yeast Genome (Sc2.0) PROJECT is a large international synthetic genomics project that will culminate in the first eukaryotic cell (Saccharomyces cerevisiae) with a fully synthetic genome. With collaborators from across the globe and from a range of institutions spanning from do-it-yourself biology (DIYbio) to commercial enterprises, it is important that all scientists working on this project are cognizant of the ethical and policy issues associated with this field of research and operate under a common set of principles. In this commentary, we survey the current ethics and regulatory landscape of synthetic biology and present the Sc2.0 Statement of Ethics and Governance to which all members of the project adhere. This statement focuses on four aspects of the Sc2.0 PROJECT: societal benefit, intellectual property, safety, and self-governance. We propose that such project-level agreements are an important, valuable, and flexible model of self-regulation for similar global, large-scale synthetic biology projects in order to maximize the benefits and minimize potential harms. Copyright © 2015 by the Genetics Society of America.
-
A robust state-space kinetics-guided framework for dynamic PET image reconstruction
International Nuclear Information System (INIS)
Tong, S; Alessio, A M; Kinahan, P E; Liu, H; Shi, P
2011-01-01
Dynamic PET image reconstruction is a challenging issue due to the low SNR and the large quantity of spatio-temporal data. We propose a robust state-space image reconstruction (SSIR) framework for activity reconstruction in dynamic PET. Unlike statistically-based frame-by-frame methods, tracer kinetic modeling is incorporated to provide physiological guidance for the reconstruction, harnessing the temporal information of the dynamic data. Dynamic reconstruction is formulated in a state-space representation, where a compartmental model describes the kinetic processes in a continuous-time system equation, and the imaging data are expressed in a discrete measurement equation. Tracer activity concentrations are treated as the state variables, and are estimated from the dynamic data. Sampled-data H ∞ filtering is adopted for robust estimation. H ∞ filtering makes no assumptions on the system and measurement statistics, and guarantees bounded estimation error for finite-energy disturbances, leading to robust performance for dynamic data with low SNR and/or errors. This alternative reconstruction approach could help us to deal with unpredictable situations in imaging (e.g. data corruption from failed detector blocks) or inaccurate noise models. Experiments on synthetic phantom and patient PET data are performed to demonstrate feasibility of the SSIR framework, and to explore its potential advantages over frame-by-frame statistical reconstruction approaches.
-
A comparative analysis of biclustering algorithms for gene expression data
Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V.
2013-01-01
The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters. PMID:22772837
-
Reward-based hypertension control by a synthetic brain-dopamine interface.
Rössger, Katrin; Charpin-El Hamri, Ghislaine; Fussenegger, Martin
2013-11-05
Synthetic biology has significantly advanced the design of synthetic trigger-controlled devices that can reprogram mammalian cells to interface with complex metabolic activities. In the brain, the neurotransmitter dopamine coordinates communication with target neurons via a set of dopamine receptors that control behavior associated with reward-driven learning. This dopamine transmission has recently been suggested to increase central sympathetic outflow, resulting in plasma dopamine levels that correlate with corresponding brain activities. By functionally rewiring the human dopamine receptor D1 (DRD1) via the second messenger cyclic adenosine monophosphate (cAMP) to synthetic promoters containing cAMP response element-binding protein 1(CREB1)-specific cAMP-responsive operator modules, we have designed a synthetic dopamine-sensitive transcription controller that reversibly fine-tunes specific target gene expression at physiologically relevant brain-derived plasma dopamine levels. Following implantation of circuit-transgenic human cell lines insulated by semipermeable immunoprotective microcontainers into mice, the designer device interfaced with dopamine-specific brain activities and produced a systemic expression response when the animal's reward system was stimulated by food, sexual arousal, or addictive drugs. Reward-triggered brain activities were able to remotely program peripheral therapeutic implants to produce sufficient amounts of the atrial natriuretic peptide, which reduced the blood pressure of hypertensive mice to the normal physiologic range. Seamless control of therapeutic transgenes by subconscious behavior may provide opportunities for treatment strategies of the future.
-
Library of synthetic transcriptional AND gates built with split T7 RNA polymerase mutants.
Shis, David L; Bennett, Matthew R
2013-03-26
The construction of synthetic gene circuits relies on our ability to engineer regulatory architectures that are orthogonal to the host's native regulatory pathways. However, as synthetic gene circuits become larger and more complicated, we are limited by the small number of parts, especially transcription factors, that work well in the context of the circuit. The current repertoire of transcription factors consists of a limited selection of activators and repressors, making the implementation of transcriptional logic a complicated and component-intensive process. To address this, we modified bacteriophage T7 RNA polymerase (T7 RNAP) to create a library of transcriptional AND gates for use in Escherichia coli by first splitting the protein and then mutating the DNA recognition domain of the C-terminal fragment to alter its promoter specificity. We first demonstrate that split T7 RNAP is active in vivo and compare it with full-length enzyme. We then create a library of mutant split T7 RNAPs that have a range of activities when used in combination with a complimentary set of altered T7-specific promoters. Finally, we assay the two-input function of both wild-type and mutant split T7 RNAPs and find that regulated expression of the N- and C-terminal fragments of the split T7 RNAPs creates AND logic in each case. This work demonstrates that mutant split T7 RNAP can be used as a transcriptional AND gate and introduces a unique library of components for use in synthetic gene circuits.
-
Synthetic Biology: Life, Jim, but Not As We Know It
Hallinan, Jennifer
Frankenstein, Mary Shelley's classic tale of horror, warns of the perils of hubris: of the terrible fate that awaits when Man plays God and attempts to create life. Molecular biologists are clearly not listening. Not content with merely inserting the occasional gene into the genome of an existing organism. they are developing a whole new field, Synthetic Biology, which aims to engineer from first principles organisms with desirable, controllable qualities.
-
Mai, Hans-Jörg; Pateyron, Stéphanie; Bauer, Petra
2016-10-03
FIT (FER-LIKE IRON DEFICIENCY-INDUCED TRANSCRIPTION FACTOR) is the central regulator of iron uptake in Arabidopsis thaliana roots. We performed transcriptome analyses of six day-old seedlings and roots of six week-old plants using wild type, a fit knock-out mutant and a FIT over-expression line grown under iron-sufficient or iron-deficient conditions. We compared genes regulated in a FIT-dependent manner depending on the developmental stage of the plants. We assembled a high likelihood dataset which we used to perform co-expression and functional analysis of the most stably iron deficiency-induced genes. 448 genes were found FIT-regulated. Out of these, 34 genes were robustly FIT-regulated in root and seedling samples and included 13 novel FIT-dependent genes. Three hundred thirty-one genes showed differential regulation in response to the presence and absence of FIT only in the root samples, while this was the case for 83 genes in the seedling samples. We assembled a virtual dataset of iron-regulated genes based on a total of 14 transcriptomic analyses of iron-deficient and iron-sufficient wild-type plants to pinpoint the best marker genes for iron deficiency and analyzed this dataset in depth. Co-expression analysis of this dataset revealed 13 distinct regulons part of which predominantly contained functionally related genes. We could enlarge the list of FIT-dependent genes and discriminate between genes that are robustly FIT-regulated in roots and seedlings or only in one of those. FIT-regulated genes were mostly induced, few of them were repressed by FIT. With the analysis of a virtual dataset we could filter out and pinpoint new candidates among the most reliable marker genes for iron deficiency. Moreover, co-expression and functional analysis of this virtual dataset revealed iron deficiency-induced and functionally distinct regulons.
-
Computer-aided biochemical programming of synthetic microreactors as diagnostic devices.
Courbet, Alexis; Amar, Patrick; Fages, François; Renard, Eric; Molina, Franck
2018-04-26
Biological systems have evolved efficient sensing and decision-making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non-living biomolecular devices could offer promising avenues toward various real-world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell-like microreactors embedding biochemical logic circuits, or protosensors , to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof-of-concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.
-
Synthetic Biology and Microbial Fuel Cells: Towards Self-Sustaining Life Support Systems
Hogan, John Andrew
2014-01-01
NASA ARC and the J. Craig Venter Institute (JCVI) collaborated to investigate the development of advanced microbial fuels cells (MFCs) for biological wastewater treatment and electricity production (electrogenesis). Synthetic biology techniques and integrated hardware advances were investigated to increase system efficiency and robustness, with the intent of increasing power self-sufficiency and potential product formation from carbon dioxide. MFCs possess numerous advantages for space missions, including rapid processing, reduced biomass and effective removal of organics, nitrogen and phosphorus. Project efforts include developing space-based MFC concepts, integration analyses, increasing energy efficiency, and investigating novel bioelectrochemical system applications
-
Chen, Yu; Wang, Yingying; Chen, Jinjin; Zhang, Tianzhen; Zhou, Baoliang
2015-01-01
Gossypium herbaceum, a cultivated diploid cotton species (2n = 2x = 26, A1A1), has favorable traits such as excellent drought tolerance and resistance to sucking insects and leaf curl virus. G. australe, a wild diploid cotton species (2n = 2x = 26, G2G2), possesses numerous economically valuable characteristics such as delayed pigment gland morphogenesis (which is conducive to the production of seeds with very low levels of gossypol as a potential food source for humans and animals) and resistance to insects, wilt diseases and abiotic stress. Creating synthetic allotetraploid cotton from these two species would lay the foundation for simultaneously transferring favorable genes into cultivated tetraploid cotton. Here, we crossed G. herbaceum (as the maternal parent) with G. australe to produce an F1 interspecific hybrid and doubled its chromosome complement with colchicine, successfully generating a synthetic tetraploid. The obtained tetraploid was confirmed by morphology, cytology and molecular markers and then self-pollinated. The S1 seedlings derived from this tetraploid gradually became flavescent after emergence of the fifth true leaf, but they were rescued by grafting and produced S2 seeds. The rescued S1 plants were partially fertile due to the existence of univalents at Metaphase I of meiosis, leading to the formation of unbalanced, nonviable gametes lacking complete sets of chromosomes. The S2 plants grew well and no flavescence was observed, implying that interspecific incompatibility, to some extent, had been alleviated in the S2 generation. The synthetic allotetraploid will be quite useful for polyploidy evolutionary studies and as a bridge for transferring favorable genes from these two diploid species into Upland cotton through hybridization. PMID:25879660
-
Robust Bayesian Experimental Design for Conceptual Model Discrimination
Pham, H. V.; Tsai, F. T. C.
2015-12-01
A robust Bayesian optimal experimental design under uncertainty is presented to provide firm information for model discrimination, given the least number of pumping wells and observation wells. Firm information is the maximum information of a system can be guaranteed from an experimental design. The design is based on the Box-Hill expected entropy decrease (EED) before and after the experiment design and the Bayesian model averaging (BMA) framework. A max-min programming is introduced to choose the robust design that maximizes the minimal Box-Hill EED subject to that the highest expected posterior model probability satisfies a desired probability threshold. The EED is calculated by the Gauss-Hermite quadrature. The BMA method is used to predict future observations and to quantify future observation uncertainty arising from conceptual and parametric uncertainties in calculating EED. Monte Carlo approach is adopted to quantify the uncertainty in the posterior model probabilities. The optimal experimental design is tested by a synthetic 5-layer anisotropic confined aquifer. Nine conceptual groundwater models are constructed due to uncertain geological architecture and boundary condition. High-performance computing is used to enumerate all possible design solutions in order to identify the most plausible groundwater model. Results highlight the impacts of scedasticity in future observation data as well as uncertainty sources on potential pumping and observation locations.
-
2D Vector Field Simplification Based on Robustness
Skraba, Primoz
2014-03-01
Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. These geometric metrics do not consider the flow magnitude, an important physical property of the flow. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness, which provides a complementary view on flow structure compared to the traditional topological-skeleton-based approaches. Robustness enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory, has fewer boundary restrictions, and so can handle more general cases. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. © 2014 IEEE.
-
A Synthetic-Biology-Inspired Therapeutic Strategy for Targeting and Treating Hepatogenous Diabetes.
Xue, Shuai; Yin, Jianli; Shao, Jiawei; Yu, Yuanhuan; Yang, Linfeng; Wang, Yidan; Xie, Mingqi; Fussenegger, Martin; Ye, Haifeng
2017-02-01
Hepatogenous diabetes is a complex disease that is typified by the simultaneous presence of type 2 diabetes and many forms of liver disease. The chief pathogenic determinant in this pathophysiological network is insulin resistance (IR), an asymptomatic disease state in which impaired insulin signaling in target tissues initiates a variety of organ dysfunctions. However, pharmacotherapies targeting IR remain limited and are generally inapplicable for liver disease patients. Oleanolic acid (OA) is a plant-derived triterpenoid that is frequently used in Chinese medicine as a safe but slow-acting treatment in many liver disorders. Here, we utilized the congruent pharmacological activities of OA and glucagon-like-peptide 1 (GLP-1) in relieving IR and improving liver and pancreas functions and used a synthetic-biology-inspired design principle to engineer a therapeutic gene circuit that enables a concerted action of both drugs. In particular, OA-triggered short human GLP-1 (shGLP-1) expression in hepatogenous diabetic mice rapidly and simultaneously attenuated many disease-specific metabolic failures, whereas OA or shGLP-1 monotherapy failed to achieve corresponding therapeutic effects. Collectively, this work shows that rationally engineered synthetic gene circuits are capable of treating multifactorial diseases in a synergistic manner by multiplexing the targeting efficacies of single therapeutics. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.
-
J Olive, David
2017-01-01
This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...
-
A multi-frame particle tracking algorithm robust against input noise
International Nuclear Information System (INIS)
Li, Dongning; Zhang, Yuanhui; Sun, Yigang; Yan, Wei
2008-01-01
The performance of a particle tracking algorithm which detects particle trajectories from discretely recorded particle positions could be substantially hindered by the input noise. In this paper, a particle tracking algorithm is developed which is robust against input noise. This algorithm employs the regression method instead of the extrapolation method usually employed by existing algorithms to predict future particle positions. If a trajectory cannot be linked to a particle at a frame, the algorithm can still proceed by trying to find a candidate at the next frame. The connectivity of tracked trajectories is inspected to remove the false ones. The algorithm is validated with synthetic data. The result shows that the algorithm is superior to traditional algorithms in the aspect of tracking long trajectories
-
Opportunities in plant synthetic biology.
Cook, Charis; Martin, Lisa; Bastow, Ruth
2014-05-01
Synthetic biology is an emerging field uniting scientists from all disciplines with the aim of designing or re-designing biological processes. Initially, synthetic biology breakthroughs came from microbiology, chemistry, physics, computer science, materials science, mathematics, and engineering disciplines. A transition to multicellular systems is the next logical step for synthetic biologists and plants will provide an ideal platform for this new phase of research. This meeting report highlights some of the exciting plant synthetic biology projects, and tools and resources, presented and discussed at the 2013 GARNet workshop on plant synthetic biology.
-
DEFF Research Database (Denmark)
Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard
2011-01-01
In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...... the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...
-
'Molecular switch' vectors for hypoxia- and radiation-mediated gene therapy of cancer
International Nuclear Information System (INIS)
Greco, O.; Marples, B.; Joiner, M.C.; Scott, S.D.
2003-01-01
Intratumoral areas of low oxygen concentration are known to be refractive to radiotherapy treatment. However, this physiological condition can be exploited for selective cancer gene therapy. We have developed a series of synthetic promoters selectively responsive to both hypoxia and ionizing radiation (IR). These promoters contain hypoxia regulatory elements (HREs) from the erythropoietin (Epo), the phosphoglycerate kinase1(PGK1) and vascular endothelial growth factor (VEGF) genes, and/or IR-responsive CArG elements from the Early Growth Response 1 (Egr1) gene. The HRE and CArG promoters were able to regulate expression of reporter and suicide genes in human tumor cells, following corresponding stimulation with hypoxia (0.1% O2) or X-irradiation (5Gy) [Greco et al, 2002, Gene Therapy 9:1403]. Furthermore, the chimeric HRE + CArG promoters could be activated by these stimuli independently or even more significantly when given in combination, with the Epo HRE/CArG promoter proving to be the most responsive and robust. In order to amplify and maintain transgene expression even following withdrawal of the triggering stimuli, we have developed a 'molecular switch' system [Scott et al, 2000, Gene Therapy 7:1121]. This 'switch' system has now been engineered as a single vector molecule, containing HRE and CArG promoters. This new series of HRE/CArG switch vectors have been tested in a herpes simplex thymidine kinase (HSVtk)/ganciclovir (GCV) suicide gene assay. Results indicate that a) higher and more selective tumor cell kill is achieved with the switch when compared with the HRE and CArG promoters directly driving HSVtk expression and b) the Epo HRE/CArG switch vectors appear to function as efficiently as the strong constitutive cytomegalovirus (CMV) promoter construct
-
Directory of Open Access Journals (Sweden)
Anne Dallas
2013-01-01
Full Text Available We previously identified short synthetic shRNAs (sshRNAs that target a conserved hepatitis C virus (HCV sequence within the internal ribosome entry site (IRES of HCV and potently inhibit HCV IRES-linked gene expression. To assess in vivo liver delivery and activity, the HCV-directed sshRNA, SG220 was formulated into lipid nanoparticles (LNP and injected i.v. into mice whose livers supported stable HCV IRES-luciferase expression from a liver-specific promoter. After a single injection, RNase protection assays for the sshRNA and 3H labeling of a lipid component of the nanoparticles showed efficient liver uptake of both components and long-lasting survival of a significant fraction of the sshRNA in the liver. In vivo imaging showed a dose-dependent inhibition of luciferase expression (>90% 1 day after injection of 2.5 mg/kg sshRNA with t1/2 for recovery of about 3 weeks. These results demonstrate the ability of moderate levels of i.v.-injected, LNP-formulated sshRNAs to be taken up by liver hepatocytes at a level sufficient to substantially suppress gene expression. Suppression is rapid and durable, suggesting that sshRNAs may have promise as therapeutic agents for liver indications.
-
Robust Matching Pursuit Extreme Learning Machines
Directory of Open Access Journals (Sweden)
Zejian Yuan
2018-01-01
Full Text Available Extreme learning machine (ELM is a popular learning algorithm for single hidden layer feedforward networks (SLFNs. It was originally proposed with the inspiration from biological learning and has attracted massive attentions due to its adaptability to various tasks with a fast learning ability and efficient computation cost. As an effective sparse representation method, orthogonal matching pursuit (OMP method can be embedded into ELM to overcome the singularity problem and improve the stability. Usually OMP recovers a sparse vector by minimizing a least squares (LS loss, which is efficient for Gaussian distributed data, but may suffer performance deterioration in presence of non-Gaussian data. To address this problem, a robust matching pursuit method based on a novel kernel risk-sensitive loss (in short KRSLMP is first proposed in this paper. The KRSLMP is then applied to ELM to solve the sparse output weight vector, and the new method named the KRSLMP-ELM is developed for SLFN learning. Experimental results on synthetic and real-world data sets confirm the effectiveness and superiority of the proposed method.
-
Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.
Otero-Muras, Irene; Banga, Julio R
2017-07-21
In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.
-
Directory of Open Access Journals (Sweden)
Rosalind A. Le Feuvre
2018-06-01
Full Text Available Society is on the cusp of harnessing recent advances in synthetic biology to discover new bio-based products and routes to their affordable and sustainable manufacture. This is no more evident than in the discovery and manufacture of Synthetic Biological Materials, where synthetic biology has the capacity to usher in a new Materials from Biology era that will revolutionise the discovery and manufacture of innovative synthetic biological materials. These will encompass novel, smart, functionalised and hybrid materials for diverse applications whose discovery and routes to bio-production will be stimulated by the fusion of new technologies positioned across physical, digital and biological spheres. This article, which developed from an international workshop held in Manchester, United Kingdom, in 2017 [1], sets out to identify opportunities in the new materials from biology era. It considers requirements, early understanding and foresight of the challenges faced in delivering a Discovery to Manufacturing Pipeline for synthetic biological materials using synthetic biology approaches. This challenge spans the complete production cycle from intelligent and predictive design, fabrication, evaluation and production of synthetic biological materials to new ways of bringing these products to market. Pathway opportunities are identified that will help foster expertise sharing and infrastructure development to accelerate the delivery of a new generation of synthetic biological materials and the leveraging of existing investments in synthetic biology and advanced materials research to achieve this goal. Keywords: Synthetic biology, Materials, Biological materials, Biomaterials, Advanced materials
-
Synthetic biology and metabolic engineering.
Stephanopoulos, Gregory
2012-11-16
Metabolic engineering emerged 20 years ago as the discipline occupied with the directed modification of metabolic pathways for the microbial synthesis of various products. As such, it deals with the engineering (design, construction, and optimization) of native as well as non-natural routes of product synthesis, aided in this task by the availability of synthetic DNA, the core enabling technology of synthetic biology. The two fields, however, only partially overlap in their interest in pathway engineering. While fabrication of biobricks, synthetic cells, genetic circuits, and nonlinear cell dynamics, along with pathway engineering, have occupied researchers in the field of synthetic biology, the sum total of these areas does not constitute a coherent definition of synthetic biology with a distinct intellectual foundation and well-defined areas of application. This paper reviews the origins of the two fields and advances two distinct paradigms for each of them: that of unit operations for metabolic engineering and electronic circuits for synthetic biology. In this context, metabolic engineering is about engineering cell factories for the biological manufacturing of chemical and pharmaceutical products, whereas the main focus of synthetic biology is fundamental biological research facilitated by the use of synthetic DNA and genetic circuits.
-
Chen, Po-Wei; Chen, Bor-Sen
2011-08-01
Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. Copyright © 2011 Elsevier Inc. All rights reserved.
-
Mutual repression enhances the steepness and precision of gene expression boundaries.
Directory of Open Access Journals (Sweden)
Thomas R Sokolowski
Full Text Available Embryonic development is driven by spatial patterns of gene expression that determine the fate of each cell in the embryo. While gene expression is often highly erratic, embryonic development is usually exceedingly precise. In particular, gene expression boundaries are robust not only against intra-embryonic fluctuations such as noise in gene expression and protein diffusion, but also against embryo-to-embryo variations in the morphogen gradients, which provide positional information to the differentiating cells. How development is robust against intra- and inter-embryonic variations is not understood. A common motif in the gene regulation networks that control embryonic development is mutual repression between pairs of genes. To assess the role of mutual repression in the robust formation of gene expression patterns, we have performed large-scale stochastic simulations of a minimal model of two mutually repressing gap genes in Drosophila, hunchback (hb and knirps (kni. Our model includes not only mutual repression between hb and kni, but also the stochastic and cooperative activation of hb by the anterior morphogen Bicoid (Bcd and of kni by the posterior morphogen Caudal (Cad, as well as the diffusion of Hb and Kni between neighboring nuclei. Our analysis reveals that mutual repression can markedly increase the steepness and precision of the gap gene expression boundaries. In contrast to other mechanisms such as spatial averaging and cooperative gene activation, mutual repression thus allows for gene-expression boundaries that are both steep and precise. Moreover, mutual repression dramatically enhances their robustness against embryo-to-embryo variations in the morphogen levels. Finally, our simulations reveal that diffusion of the gap proteins plays a critical role not only in reducing the width of the gap gene expression boundaries via the mechanism of spatial averaging, but also in repairing patterning errors that could arise because of the
-
Allard, Sarah M; Walsh, Christopher S; Wallis, Anna E; Ottesen, Andrea R; Brown, Eric W; Micallef, Shirley A
2016-12-15
Due to the intimate association between plants and their microbial symbionts, an examination of the influence of agricultural practices on phytobiome structure and diversity could foster a more comprehensive understanding of plant health and produce safety. Indeed, the impact of upstream crop producti006Fn practices cannot be overstated in their role in assuring an abundant and safe food supply. To assess whether fertilizer type impacted rhizosphere and phyllosphere bacterial communities associating with tomato plants, the bacterial microbiome of tomato cv. 'BHN602' grown in soils amended with fresh poultry litter, commercially available sterilized poultry litter pellets, vermicompost or synthetic fertilizer was described. Culture independent DNA was extracted from bulk and rhizosphere soils, and washes of tomato blossoms and ripe fruit. PCR amplicons of hypervariable regions of the 16S rRNA gene were sequenced and profiled using the QIIME pipeline. Bulk and rhizosphere soil, and blossom and fruit surfaces all supported distinct bacterial communities according to principal coordinate analysis and ANOSIM (R=0.87, p=0.001 in year 1; R=0.93, p=0.001 in year 2). Use of microbiologically diverse organic fertilizers generally did not influence bacterial diversity, community structure or relative abundance of specific taxa on any plant organ surface. However, statistically significant differences in sand and silt contents of soil (pfertilized plants. Plant anatomy, and other factors related to field location, possibly associated with edaphic and air characteristics, were more influential drivers of different tomato organ microbiomes than were diverse soil amendment applications. Copyright © 2016 Elsevier B.V. All rights reserved.
-
Synthetic strategies for plant signalling studies: molecular toolbox and orthogonal platforms
Braguy, Justine
2016-05-26
Plants deploy a wide array of signalling networks integrating environmental cues with growth, defence and developmental responses. The high level of complexity, redundancy and connection between several pathways hampers a comprehensive understanding of involved functional and regulatory mechanisms. The implementation of synthetic biology approaches is revolutionizing experimental biology in prokaryotes, yeasts and animal systems and can likewise contribute to a new era in plant biology. This review gives an overview on synthetic biology approaches for the development and implementation of synthetic molecular tools and techniques to interrogate, understand and control signalling events in plants, ranging from strategies for the targeted manipulation of plant genomes up to the spatiotemporally resolved control of gene expression using optogenetic approaches. We also describe strategies based on the partial reconstruction of signalling pathways in orthogonal platforms, like yeast, animal and in vitro systems. This allows a targeted analysis of individual signalling hubs devoid of inter-connectivity with endogenous interacting components. Implementation of the interdisciplinary synthetic biology tools and strategies is not exempt of challenges and hardships but simultaneously most rewarding in terms of the advances in basic and applied research. As witnessed in other areas, these original theoretical-experimental avenues will lead to a breakthrough in the ability to study and comprehend plant signalling networks. This article is protected by copyright. All rights reserved.
-
DEFF Research Database (Denmark)
Manijak, Mieszko P.; Nielsen, Henrik Bjørn
2011-01-01
circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....
-
Li, Jing
2017-12-22
A robust imaging technology is reviewed that provide subsurface information in challenging environments: wave-equation dispersion inversion (WD) of surface waves for the shear velocity model. We demonstrate the benefits and liabilities of the method with synthetic seismograms and field data. The benefits of WD are that 1) there is no layered medium assumption, as there is in conventional inversion of dispersion curves, so that the 2D or 3D S-velocity model can be reliably obtained with seismic surveys over rugged topography, and 2) WD mostly avoids getting stuck in local minima. The synthetic and field data examples demonstrate that WD can accurately reconstruct the S-wave velocity distributions in laterally heterogeneous media if the dispersion curves can be identified and picked. The WD method is easily extended to anisotropic media and the inversion of dispersion curves associated with Love wave. The liability is that is almost as expensive as FWI and only recovers the Vs distribution to a depth no deeper than about 1/2~1/3 wavelength.
-
Le Feuvre, Rosalind A; Scrutton, Nigel S
2018-06-01
Society is on the cusp of harnessing recent advances in synthetic biology to discover new bio-based products and routes to their affordable and sustainable manufacture. This is no more evident than in the discovery and manufacture of Synthetic Biological Materials , where synthetic biology has the capacity to usher in a new Materials from Biology era that will revolutionise the discovery and manufacture of innovative synthetic biological materials. These will encompass novel, smart, functionalised and hybrid materials for diverse applications whose discovery and routes to bio-production will be stimulated by the fusion of new technologies positioned across physical, digital and biological spheres. This article, which developed from an international workshop held in Manchester, United Kingdom, in 2017 [1], sets out to identify opportunities in the new materials from biology era. It considers requirements, early understanding and foresight of the challenges faced in delivering a Discovery to Manufacturing Pipeline for synthetic biological materials using synthetic biology approaches. This challenge spans the complete production cycle from intelligent and predictive design, fabrication, evaluation and production of synthetic biological materials to new ways of bringing these products to market. Pathway opportunities are identified that will help foster expertise sharing and infrastructure development to accelerate the delivery of a new generation of synthetic biological materials and the leveraging of existing investments in synthetic biology and advanced materials research to achieve this goal.
-
Shape, size, and robustness: feasible regions in the parameter space of biochemical networks.
Directory of Open Access Journals (Sweden)
Adel Dayarian
2009-01-01
Full Text Available The concept of robustness of regulatory networks has received much attention in the last decade. One measure of robustness has been associated with the volume of the feasible region, namely, the region in the parameter space in which the system is functional. In this paper, we show that, in addition to volume, the geometry of this region has important consequences for the robustness and the fragility of a network. We develop an approximation within which we could algebraically specify the feasible region. We analyze the segment polarity gene network to illustrate our approach. The study of random walks in the parameter space and how they exit the feasible region provide us with a rich perspective on the different modes of failure of this network model. In particular, we found that, between two alternative ways of activating Wingless, one is more robust than the other. Our method provides a more complete measure of robustness to parameter variation. As a general modeling strategy, our approach is an interesting alternative to Boolean representation of biochemical networks.
-
From Never Born Proteins to Minimal Living Cells: two projects in synthetic biology.
Luisi, Pier Luigi; Chiarabelli, Cristiano; Stano, Pasquale
2006-12-01
The Never Born Proteins (NBPs) and the Minimal Cell projects are two currently developed research lines belonging to the field of synthetic biology. The first deals with the investigation of structural and functional properties of de novo proteins with random sequences, selected and isolated using phage display methods. The minimal cell is the simplest cellular construct which displays living properties, such as self-maintenance, self-reproduction and evolvability. The semi-synthetic approach to minimal cells involves the use of extant genes and proteins in order to build a supramolecular construct based on lipid vesicles. Results and outlooks on these two research lines are shortly discussed, mainly focusing on their relevance to the origin of life studies.
-
Building ProteomeTools based on a complete synthetic human proteome
Zolg, Daniel P.; Wilhelm, Mathias; Schnatbaum, Karsten; Zerweck, Johannes; Knaute, Tobias; Delanghe, Bernard; Bailey, Derek J.; Gessulat, Siegfried; Ehrlich, Hans-Christian; Weininger, Maximilian; Yu, Peng; Schlegl, Judith; Kramer, Karl; Schmidt, Tobias; Kusebauch, Ulrike; Deutsch, Eric W.; Aebersold, Ruedi; Moritz, Robert L.; Wenschuh, Holger; Moehring, Thomas; Aiche, Stephan; Huhmer, Andreas; Reimer, Ulf; Kuster, Bernhard
2018-01-01
The ProteomeTools project builds molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we report the generation and multimodal LC-MS/MS analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products and exemplify the utility of this data. The resource will be extended to >1 million peptides and all data will be shared with the community via ProteomicsDB and proteomeXchange. PMID:28135259
-
Water conservation efforts have focused on greywater (GW) usage, especially for applications that do not require potable water quality. However, there is a need to better understand environmental pathogens and their free-living amoebae (FLA) hosts within GW. Using synthetic gre...
-
International Nuclear Information System (INIS)
Keitel, David; Prix, Reinhard
2015-01-01
The multi-detector F-statistic is close to optimal for detecting continuous gravitational waves (CWs) in Gaussian noise. However, it is susceptible to false alarms from instrumental artefacts, for example quasi-monochromatic disturbances (‘lines’), which resemble a CW signal more than Gaussian noise. In a recent paper (Keitel et al 2014 Phys. Rev. D 89 064023), a Bayesian model selection approach was used to derive line-robust detection statistics for CW signals, generalizing both the F-statistic and the F-statistic consistency veto technique and yielding improved performance in line-affected data. Here we investigate a generalization of the assumptions made in that paper: if a CW analysis uses data from two or more detectors with very different sensitivities, the line-robust statistics could be less effective. We investigate the boundaries within which they are still safe to use, in comparison with the F-statistic. Tests using synthetic draws show that the optimally-tuned version of the original line-robust statistic remains safe in most cases of practical interest. We also explore a simple idea on further improving the detection power and safety of these statistics, which we, however, find to be of limited practical use. (paper)
-
Synthetic Biology and Personalized Medicine
Jain, K.K.
2013-01-01
Synthetic biology, application of synthetic chemistry to biology, is a broad term that covers the engineering of biological systems with structures and functions not found in nature to process information, manipulate chemicals, produce energy, maintain cell environment and enhance human health. Synthetic biology devices contribute not only to improve our understanding of disease mechanisms, but also provide novel diagnostic tools. Methods based on synthetic biology enable the design of novel strategies for the treatment of cancer, immune diseases metabolic disorders and infectious diseases as well as the production of cheap drugs. The potential of synthetic genome, using an expanded genetic code that is designed for specific drug synthesis as well as delivery and activation of the drug in vivo by a pathological signal, was already pointed out during a lecture delivered at Kuwait University in 2005. Of two approaches to synthetic biology, top-down and bottom-up, the latter is more relevant to the development of personalized medicines as it provides more flexibility in constructing a partially synthetic cell from basic building blocks for a desired task. PMID:22907209
-
Unthan, Simon; Baumgart, Meike; Radek, Andreas; Herbst, Marius; Siebert, Daniel; Brühl, Natalie; Bartsch, Anna; Bott, Michael; Wiechert, Wolfgang; Marin, Kay; Hans, Stephan; Krämer, Reinhard; Seibold, Gerd; Frunzke, Julia; Kalinowski, Jörn; Rückert, Christian; Wendisch, Volker F; Noack, Stephan
2015-02-01
For synthetic biology applications, a robust structural basis is required, which can be constructed either from scratch or in a top-down approach starting from any existing organism. In this study, we initiated the top-down construction of a chassis organism from Corynebacterium glutamicum ATCC 13032, aiming for the relevant gene set to maintain its fast growth on defined medium. We evaluated each native gene for its essentiality considering expression levels, phylogenetic conservation, and knockout data. Based on this classification, we determined 41 gene clusters ranging from 3.7 to 49.7 kbp as target sites for deletion. 36 deletions were successful and 10 genome-reduced strains showed impaired growth rates, indicating that genes were hit, which are relevant to maintain biological fitness at wild-type level. In contrast, 26 deleted clusters were found to include exclusively irrelevant genes for growth on defined medium. A combinatory deletion of all irrelevant gene clusters would, in a prophage-free strain, decrease the size of the native genome by about 722 kbp (22%) to 2561 kbp. Finally, five combinatory deletions of irrelevant gene clusters were investigated. The study introduces the novel concept of relevant genes and demonstrates general strategies to construct a chassis suitable for biotechnological application. © 2014 The Authors. Biotechnology Journal published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution-Non-Commercial-NoDerivs Licence, which permits use and distribution in any medium, provided the original work is properly cited, the use is non- commercial and no modifications or adaptations are made.
-
Tracking the emergence of synthetic biology.
Shapira, Philip; Kwon, Seokbeom; Youtie, Jan
2017-01-01
Synthetic biology is an emerging domain that combines biological and engineering concepts and which has seen rapid growth in research, innovation, and policy interest in recent years. This paper contributes to efforts to delineate this emerging domain by presenting a newly constructed bibliometric definition of synthetic biology. Our approach is dimensioned from a core set of papers in synthetic biology, using procedures to obtain benchmark synthetic biology publication records, extract keywords from these benchmark records, and refine the keywords, supplemented with articles published in dedicated synthetic biology journals. We compare our search strategy with other recent bibliometric approaches to define synthetic biology, using a common source of publication data for the period from 2000 to 2015. The paper details the rapid growth and international spread of research in synthetic biology in recent years, demonstrates that diverse research disciplines are contributing to the multidisciplinary development of synthetic biology research, and visualizes this by profiling synthetic biology research on the map of science. We further show the roles of a relatively concentrated set of research sponsors in funding the growth and trajectories of synthetic biology. In addition to discussing these analyses, the paper notes limitations and suggests lines for further work.
-
Printability of Synthetic Papers by Electrophotography
Directory of Open Access Journals (Sweden)
Rozália Szentgyörgyvölgyi
2010-04-01
Full Text Available This paper deals with the printability of synthetic papers by the electrophotography technique. Prints of cmyk colour fields from 20% to 100% raster tone values were printed on three types of synthetic papers (one film synthetic paper and two fiber synthetic papers. The investigation of the appearance included densitometric measurement of the cmyk prints. The results have shown differences in the optical density and optical tone value between cmyk prints made on various synthetic papers. The highest optical density and the increase of the optical tone value were observed on the film synthetic paper, where cmyk prints were more saturated. The highest abrasion resistance of cmyk prints was obtained from the fibre synthetic paper.
-
Li, Aitao; Acevedo-Rocha, Carlos G; Sun, Zhoutong; Cox, Tony; Xu, Jia Lucy; Reetz, Manfred T
2018-02-02
Saturation mutagenesis (SM) constitutes a widely used technique in the directed evolution of selective enzymes as catalysts in organic chemistry and in the manipulation of metabolic paths and genomes, but the quality of the libraries is far from optimal due to the inherent amino acid bias. Herein, it is shown how this fundamental problem can be solved by applying high-fidelity solid-phase chemical gene synthesis on silicon chips followed by efficient gene assembly. Limonene epoxide hydrolase was chosen as the catalyst in the model desymmetrization of cyclohexene oxide with the stereoselective formation of (R,R)- and (S,S)-cyclohexane-1,2-diol. A traditional combinatorial PCR-based SM library, produced by simultaneous randomization at several residues by using a reduced amino acid alphabet, and the respective synthetic library were constructed and compared. Statistical analysis at the DNA level with massive sequencing demonstrates that, in the synthetic approach, 97 % of the theoretically possible DNA mutants are formed, whereas the traditional SM library contained only about 50 %. Screening at the protein level also showed the superiority of the synthetic library; many highly (R,R)- and (S,S)-selective variants being discovered are not found in the traditional SM library. With the prices of synthetic genes decreasing, this approach may point the way to future directed evolution. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
-
Defining robustness protocols: a method to include and evaluate robustness in clinical plans
International Nuclear Information System (INIS)
McGowan, S E; Albertini, F; Lomax, A J; Thomas, S J
2015-01-01
We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties. (paper)
-
Defining robustness protocols: a method to include and evaluate robustness in clinical plans
McGowan, S. E.; Albertini, F.; Thomas, S. J.; Lomax, A. J.
2015-04-01
We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties.
-
Robust and transferable quantification of NMR spectral quality using IROC analysis
Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.
2017-12-01
Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.
-
Ferreira, Joshua P.; Peacock, Ryan W. S.; Lawhorn, Ingrid E. B.; Wang, Clifford L.
2011-01-01
The human cytomegalovirus and elongation factor 1α promoters are constitutive promoters commonly employed by mammalian expression vectors. These promoters generally produce high levels of expression in many types of cells and tissues. To generate a library of synthetic promoters capable of generating a range of low, intermediate, and high expression levels, the TATA and CAAT box elements of these promoters were mutated. Other promoter variants were also generated by random mutagenesis. Evalua...
-
Tension and robustness in multitasking cellular networks.
Directory of Open Access Journals (Sweden)
Jeffrey V Wong
Full Text Available Cellular networks multitask by exhibiting distinct, context-dependent dynamics. However, network states (parameters that generate a particular dynamic are often sub-optimal for others, defining a source of "tension" between them. Though multitasking is pervasive, it is not clear where tension arises, what consequences it has, and how it is resolved. We developed a generic computational framework to examine the source and consequences of tension between pairs of dynamics exhibited by the well-studied RB-E2F switch regulating cell cycle entry. We found that tension arose from task-dependent shifts in parameters associated with network modules. Although parameter sets common to distinct dynamics did exist, tension reduced both their accessibility and resilience to perturbation, indicating a trade-off between "one-size-fits-all" solutions and robustness. With high tension, robustness can be preserved by dynamic shifting of modules, enabling the network to toggle between tasks, and by increasing network complexity, in this case by gene duplication. We propose that tension is a general constraint on the architecture and operation of multitasking biological networks. To this end, our work provides a framework to quantify the extent of tension between any network dynamics and how it affects network robustness. Such analysis would suggest new ways to interfere with network elements to elucidate the design principles of cellular networks.
-
Synthetic alienation of microbial organisms by using genetic code engineering: Why and how?
Kubyshkin, Vladimir; Budisa, Nediljko
2017-08-01
The main goal of synthetic biology (SB) is the creation of biodiversity applicable for biotechnological needs, while xenobiology (XB) aims to expand the framework of natural chemistries with the non-natural building blocks in living cells to accomplish artificial biodiversity. Protein and proteome engineering, which overcome limitation of the canonical amino acid repertoire of 20 (+2) prescribed by the genetic code by using non-canonic amino acids (ncAAs), is one of the main focuses of XB research. Ideally, estranging the genetic code from its current form via systematic introduction of ncAAs should enable the development of bio-containment mechanisms in synthetic cells potentially endowing them with a "genetic firewall" i.e. orthogonality which prevents genetic information transfer to natural systems. Despite rapid progress over the past two decades, it is not yet possible to completely alienate an organism that would use and maintain different genetic code associations permanently. In order to engineer robust bio-contained life forms, the chemical logic behind the amino acid repertoire establishment should be considered. Starting from recent proposal of Hartman and Smith about the genetic code establishment in the RNA world, here the authors mapped possible biotechnological invasion points for engineering of bio-contained synthetic cells equipped with non-canonical functionalities. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
-
Conovaloff, Aaron W.; Beier, Brooke L.; Irazoqui, Pedro P.; Panitch, Alyssa
2011-01-01
Previous work has revealed robust dorsal root ganglia neurite growth in hydrogels of chondroitin sulfate. In the current work, it was determined whether addition of a synthetic bioactive peptide could augment neurite growth in these matrices via enhanced binding and sequestering of growth factors. Fluorescence recovery after photobleaching studies revealed that addition of peptide slowed nerve growth factor diffusivity in chondroitin sulfate gels, but not in control gels of hyaluronic acid. F...
-
Computational approaches in the design of synthetic receptors - A review.
Cowen, Todd; Karim, Kal; Piletsky, Sergey
2016-09-14
The rational design of molecularly imprinted polymers (MIPs) has been a major contributor to their reputation as "plastic antibodies" - high affinity robust synthetic receptors which can be optimally designed, and produced for a much reduced cost than their biological equivalents. Computational design has become a routine procedure in the production of MIPs, and has led to major advances in functional monomer screening, selection of cross-linker and solvent, optimisation of monomer(s)-template ratio and selectivity analysis. In this review the various computational methods will be discussed with reference to all the published relevant literature since the end of 2013, with each article described by the target molecule, the computational approach applied (whether molecular mechanics/molecular dynamics, semi-empirical quantum mechanics, ab initio quantum mechanics (Hartree-Fock, Møller-Plesset, etc.) or DFT) and the purpose for which they were used. Detailed analysis is given to novel techniques including analysis of polymer binding sites, the use of novel screening programs and simulations of MIP polymerisation reaction. The further advances in molecular modelling and computational design of synthetic receptors in particular will have serious impact on the future of nanotechnology and biotechnology, permitting the further translation of MIPs into the realms of analytics and medical technology. Copyright © 2016 Elsevier B.V. All rights reserved.
-
Evolvable synthetic neural system
Curtis, Steven A. (Inventor)
2009-01-01
An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.
-
Synthetic Biology of Polyhydroxyalkanoates (PHA).
Meng, De-Chuan; Chen, Guo-Qiang
Microbial polyhydroxyalkanoates (PHA) are a family of biodegradable and biocompatible polyesters which have been extensively studied using synthetic biology and metabolic engineering methods for improving production and for widening its diversity. Synthetic biology has allowed PHA to become composition controllable random copolymers, homopolymers, and block copolymers. Recent developments showed that it is possible to establish a microbial platform for producing not only random copolymers with controllable monomers and their ratios but also structurally defined homopolymers and block copolymers. This was achieved by engineering the genome of Pseudomonas putida or Pseudomonas entomophiles to weaken the β-oxidation and in situ fatty acid synthesis pathways, so that a fatty acid fed to the bacteria maintains its original chain length and structures when incorporated into the PHA chains. The engineered bacterium allows functional groups in a fatty acid to be introduced into PHA, forming functional PHA, which, upon grafting, generates endless PHA variety. Recombinant Escherichia coli also succeeded in producing efficiently poly(3-hydroxypropionate) or P3HP, the strongest member of PHA. Synthesis pathways of P3HP and its copolymer P3HB3HP of 3-hydroxybutyrate and 3-hydroxypropionate were assembled respectively to allow their synthesis from glucose. CRISPRi was also successfully used to manipulate simultaneously multiple genes and control metabolic flux in E. coli to obtain a series of copolymer P3HB4HB of 3-hydroxybutyrate (3HB) and 4-hydroxybutyrate (4HB). The bacterial shapes were successfully engineered for enhanced PHA accumulation.
-
Science with Synthetic Stellar Surveys
Sanderson, Robyn Ellyn
2018-04-01
A new generation of observational projects is poised to revolutionize our understanding of the resolved stellar populations of Milky-Way-like galaxies at an unprecedented level of detail, ushering in an era of precision studies of galaxy formation. In the Milky Way itself, astrometric, spectroscopic and photometric surveys will measure three-dimensional positions and velocities and numerous chemical abundances for stars from the disk to the halo, as well as for many satellite dwarf galaxies. In the Local Group and beyond, HST, JWST and eventually WFIRST will deliver pristine views of resolved stars. The groundbreaking scale and dimensionality of this new view of resolved stellar populations in galaxies challenge us to develop new theoretical tools to robustly compare these surveys to simulated galaxies, in order to take full advantage of our new ability to make detailed predictions for stellar populations within a cosmological context. I will describe a framework for generating realistic synthetic star catalogs and mock surveys from state-of-the-art cosmological-hydrodynamical simulations, and present several early scientific results from, and predictions for, resolved stellar surveys of our Galaxy and its neighbors.
-
Synthetic marijuana "K2" induced ITP.
Öztürk, Erman; Oral, Alihan; Özdemir, Melek; Bambul, Nail
2015-01-01
Immune thrombocytopenia (ITP) is a heterogeneous disease which can be primary or secondary due to other conditions such as drugs. CB2 receptors (CB2R) also have a role in the ITP pathogenesis as CB2 receptor gene (CNR2) polymorphisms are associated with chronic immune thrombocytopenia and autoimmune diseases. K2 is synthetic marijuana which acts on cannabinoid receptors that are found on immune cells and thrombocytes. Here, we present a case who presented with ITP secondary to K2 usage and was successfully treated with 1 mg/kg prednisolone. This is the first ITP case in the literature due to K2. It is important in the era of the new drugs development of the CB2R mimetics.
-
An algebra-based method for inferring gene regulatory networks.
Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard
2014-03-26
The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the
-
Methods for robustness programming
Olieman, N.J.
2008-01-01
Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition
-
Genome-wide analysis of E. coli cell-gene interactions.
Cardinale, S; Cambray, G
2017-11-23
The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. We found that most perturbations modulate expression indirectly through an effect on cell size, putting forward the existence of a generic Size-Expression interaction in the model prokaryote Escherichia coli. The Size-Expression interaction was quantified by inserting a dual fluorescent reporter gene construct into each of the 3822 single-gene deletion strains comprised in the KEIO collection. Cellular size was measured for single cells via flow cytometry. Regression analyses were used to discriminate between expression-specific and gene-specific effects. Functions of the deleted genes broadly mapped onto three systems with distinct primary influence on the Size-Expression map. Perturbations in the Division and Biosynthesis (DB) system led to a large-cell and high-expression phenotype. In contrast, disruptions of the Membrane and Motility (MM) system caused small-cell and low-expression phenotypes. The Energy, Protein synthesis and Ribosome (EPR) system was predominantly associated with smaller cells and positive feedback on ribosome function. Feedback between cell growth and gene expression is widespread across cell systems. Even though most gene disruptions proximally affect one component of the Size-Expression interaction, the effect therefore ultimately propagates to both. More specifically, we describe the dual impact of growth on cell size and gene expression through cell division and ribosomal content
-
Reisman, Scott A; Lee, Chun-Yue I; Meyer, Colin J; Proksch, Joel W; Ward, Keith W
2014-07-01
RTA 408 is a member of the synthetic oleanane triterpenoid class of compounds known to potently activate the cytoprotective transcription factor Nrf2. Because skin is constantly exposed to external oxidative stress, such as that from ultraviolet radiation, from chemical exposure, during improper wound healing, and throughout the course of cancer radiation therapy, it may benefit from activation of Nrf2. This study was conducted to evaluate the transdermal penetration properties and Nrf2 activation potential of RTA 408 in normal rat skin. RTA 408 (0.1, 1.0, or 3.0%) was applied topically to the shaved skin of male Sprague-Dawley rats twice daily for 4 days and once on Day 5. Topical application of RTA 408 resulted in transdermal penetration, with low but dose-dependent plasma exposure with AUC(0-24 h) values of 3.6, 26.0, and 41.1 h ng/mL for the 0.1, 1.0, and 3.0% doses, respectively. Further, topical application of RTA 408 resulted in increased translocation of Nrf2 to the nucleus, dose-dependent mRNA induction of Nrf2 target genes (e.g. Nqo1, Srxn1, Gclc, and Gclm), and induction of the protein expression of the prototypical Nrf2 target gene Nqo1 and increased total glutathione (GSH) in normal rat skin. Immunohistochemistry demonstrated that increased staining for Nqo1 and total GSH of structures in both the epidermis and dermis was consistent with the full transdermal penetration of RTA 408. Finally, topically administered RTA 408 was well tolerated with no adverse in-life observations and normal skin histology. Thus, the data support the further development of RTA 408 for the potential treatment of skin diseases.
-
Integrative analysis of survival-associated gene sets in breast cancer.
Varn, Frederick S; Ung, Matthew H; Lou, Shao Ke; Cheng, Chao
2015-03-12
Patient gene expression information has recently become a clinical feature used to evaluate breast cancer prognosis. The emergence of prognostic gene sets that take advantage of these data has led to a rich library of information that can be used to characterize the molecular nature of a patient's cancer. Identifying robust gene sets that are consistently predictive of a patient's clinical outcome has become one of the main challenges in the field. We inputted our previously established BASE algorithm with patient gene expression data and gene sets from MSigDB to develop the gene set activity score (GSAS), a metric that quantitatively assesses a gene set's activity level in a given patient. We utilized this metric, along with patient time-to-event data, to perform survival analyses to identify the gene sets that were significantly correlated with patient survival. We then performed cross-dataset analyses to identify robust prognostic gene sets and to classify patients by metastasis status. Additionally, we created a gene set network based on component gene overlap to explore the relationship between gene sets derived from MSigDB. We developed a novel gene set based on this network's topology and applied the GSAS metric to characterize its role in patient survival. Using the GSAS metric, we identified 120 gene sets that were significantly associated with patient survival in all datasets tested. The gene overlap network analysis yielded a novel gene set enriched in genes shared by the robustly predictive gene sets. This gene set was highly correlated to patient survival when used alone. Most interestingly, removal of the genes in this gene set from the gene pool on MSigDB resulted in a large reduction in the number of predictive gene sets, suggesting a prominent role for these genes in breast cancer progression. The GSAS metric provided a useful medium by which we systematically investigated how gene sets from MSigDB relate to breast cancer patient survival. We used
-
International Nuclear Information System (INIS)
Johnson, P.H.; Castor, C.W.; Walz, D.A.
1986-01-01
CTAP-III, an α-granule protein secreted by human platelets, is known to stimulate mitogenesis, extracellular matrix synthesis, and plasminogen activator synthesis in human fibroblast cultures. From its primary sequence, a synthetic gene was constructed to code for a methionine-free derivative (Leu substituted for Met-21), then cloned and expressed in E. coli using a new expression vector containing regulatory elements of the colicin E1 operon. Partially purified recombinant CTAP-III showed a line of identity with CTAP-III by immunodiffusion against rabbit antibody to platelet-derived CTAP-III. Immunodetection of the reduced protein after SDS-PAGE electrophoresis showed a molecular weight (mobility) in agreement with the natural form. Biologic activity of rCTAP-III eluted from an antiCTAP-III immunoaffinity column was measured in human synovial cell bioassay systems. rCTAP-III stimulated synovial cell synthesis of 14 C-hyaluronic acid approximately 13-fold; significant (P < 0.001) mitogenesis was also observed. These studies indicate that a sufficient quantity of bioactive peptide can be obtained for a more comprehensive study of its biologic properties
-
Directory of Open Access Journals (Sweden)
Woan-Fang Tzeng
2009-07-01
Full Text Available A new synthetic compound, 6-hydroxy-2-tosylisoquinolin-1(2H-one (2-OH, was selected for immunopharmacological activity tests. The effects of 2-OH on human peripheral blood mononuclear cell (PBMC proliferation were determined by tritiated thymidine uptake. Compared to phytohemagglutinin (PHA; 5 μg/mL stimulation, 2-OH significantly enhanced PBMC proliferation in a dose-dependent manner. The 50% enhancement activity (EC50 for 2-OH was 4.4±0.1 μM. In addition, effects of 2-OH on interleukin-2 (IL-2 and interferon-γ (IFN-γ production in PBMC were determined by enzyme immunoassay. Results demonstrated that 2-OH stimulated IL-2 and IFN-γ production in PBMC. Data from reverse transcription-polymerase chain reaction (RT-PCR and real-time PCR indicated that IL-2 and IFN-γ mRNA expression in PBMC could be induced by 2-OH. Therefore, 2-OH enhanced IL-2 and IFN-γ production in PBMC by modulation their gene expression. We suggest that 2-OH may be an immunomodulatory agent.
-
Blount, Benjamin A.; Weenink, Tim; Vasylechko, Serge; Ellis, Tom
2012-01-01
Yeast is an ideal organism for the development and application of synthetic biology, yet there remain relatively few well-characterised biological parts suitable for precise engineering of this chassis. In order to address this current need, we present here a strategy that takes a single biological part, a promoter, and re-engineers it to produce a fine-graded output range promoter library and new regulated promoters desirable for orthogonal synthetic biology applications. A highly constitutive Saccharomyces cerevisiae promoter, PFY1p, was identified by bioinformatic approaches, characterised in vivo and diversified at its core sequence to create a 36-member promoter library. TetR regulation was introduced into PFY1p to create a synthetic inducible promoter (iPFY1p) that functions in an inverter device. Orthogonal and scalable regulation of synthetic promoters was then demonstrated for the first time using customisable Transcription Activator-Like Effectors (TALEs) modified and designed to act as orthogonal repressors for specific PFY1-based promoters. The ability to diversify a promoter at its core sequences and then independently target Transcription Activator-Like Orthogonal Repressors (TALORs) to virtually any of these sequences shows great promise toward the design and construction of future synthetic gene networks that encode complex “multi-wire” logic functions. PMID:22442681
-
Blount, Benjamin A; Weenink, Tim; Vasylechko, Serge; Ellis, Tom
2012-01-01
Yeast is an ideal organism for the development and application of synthetic biology, yet there remain relatively few well-characterised biological parts suitable for precise engineering of this chassis. In order to address this current need, we present here a strategy that takes a single biological part, a promoter, and re-engineers it to produce a fine-graded output range promoter library and new regulated promoters desirable for orthogonal synthetic biology applications. A highly constitutive Saccharomyces cerevisiae promoter, PFY1p, was identified by bioinformatic approaches, characterised in vivo and diversified at its core sequence to create a 36-member promoter library. TetR regulation was introduced into PFY1p to create a synthetic inducible promoter (iPFY1p) that functions in an inverter device. Orthogonal and scalable regulation of synthetic promoters was then demonstrated for the first time using customisable Transcription Activator-Like Effectors (TALEs) modified and designed to act as orthogonal repressors for specific PFY1-based promoters. The ability to diversify a promoter at its core sequences and then independently target Transcription Activator-Like Orthogonal Repressors (TALORs) to virtually any of these sequences shows great promise toward the design and construction of future synthetic gene networks that encode complex "multi-wire" logic functions.
-
Synthetic Cathinones ("Bath Salts")
... Alcohol Club Drugs Cocaine Fentanyl Hallucinogens Inhalants Heroin Marijuana MDMA (Ecstasy/Molly) Methamphetamine Opioids Over-the-Counter Medicines Prescription Medicines Steroids (Anabolic) Synthetic Cannabinoids (K2/Spice) Synthetic Cathinones (Bath Salts) Tobacco/ ...
-
Robustness of Structural Systems
DEFF Research Database (Denmark)
Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.
2007-01-01
The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have...... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...
-
A positive feedback-based gene circuit to increase the production of a membrane protein
Directory of Open Access Journals (Sweden)
Gennis Robert B
2010-05-01
Full Text Available Abstract Background Membrane proteins are an important class of proteins, playing a key role in many biological processes, and are a promising target in pharmaceutical development. However, membrane proteins are often difficult to produce in large quantities for the purpose of crystallographic or biochemical analyses. Results In this paper, we demonstrate that synthetic gene circuits designed specifically to overexpress certain genes can be applied to manipulate the expression kinetics of a model membrane protein, cytochrome bd quinol oxidase in E. coli, resulting in increased expression rates. The synthetic circuit involved is an engineered, autoinducer-independent variant of the lux operon activator LuxR from V. fischeri in an autoregulatory, positive feedback configuration. Conclusions Our proof-of-concept experiments indicate a statistically significant increase in the rate of production of the bd oxidase membrane protein. Synthetic gene networks provide a feasible solution for the problem of membrane protein production.
-
Biocontainment of genetically modified organisms by synthetic protein design
Mandell, Daniel J.; Lajoie, Marc J.; Mee, Michael T.; Takeuchi, Ryo; Kuznetsov, Gleb; Norville, Julie E.; Gregg, Christopher J.; Stoddard, Barry L.; Church, George M.
2015-02-01
Genetically modified organisms (GMOs) are increasingly deployed at large scales and in open environments. Genetic biocontainment strategies are needed to prevent unintended proliferation of GMOs in natural ecosystems. Existing biocontainment methods are insufficient because they impose evolutionary pressure on the organism to eject the safeguard by spontaneous mutagenesis or horizontal gene transfer, or because they can be circumvented by environmentally available compounds. Here we computationally redesign essential enzymes in the first organism possessing an altered genetic code (Escherichia coli strain C321.ΔA) to confer metabolic dependence on non-standard amino acids for survival. The resulting GMOs cannot metabolically bypass their biocontainment mechanisms using known environmental compounds, and they exhibit unprecedented resistance to evolutionary escape through mutagenesis and horizontal gene transfer. This work provides a foundation for safer GMOs that are isolated from natural ecosystems by a reliance on synthetic metabolites.
-
Star, L.
2008-01-01
The aim of the project ‘The genetics of robustness in laying hens’ was to investigate nature and regulation of robustness in laying hens under sub-optimal conditions and the possibility to increase robustness by using animal breeding without loss of production. At the start of the project, a robust
-
New designer drugs (synthetic cannabinoids and synthetic cathinones): review of literature.
Cottencin, Olivier; Rolland, Benjamin; Karila, Laurent
2014-01-01
New designer drugs (synthetic cannabinoids and synthetic cathinones) are new "legal highs" that are sold online for recreational public or private use. Synthetic cannabinoids are psychoactive herbal and chemical products that mimic the effects of cannabis when used. These drugs are available on the Internet or in head shops as incense or air fresheners to circumvent the law. Cathinone is a naturally occurring beta-ketone amphetamine analog found in the leaves of the Catha edulis plant. Synthetic cathinones are phenylalkylamine derivatives that may possess amphetamine-like properties. These drugs are sold online as bath salts. Designer drugs are often labeled as "not for human consumption" to circumvent drug abuse legislation. The absence of legal risks, the ease of obtaining these drugs, the moderate cost, and the availability via the Internet are the main features that attract users, but the number of intoxicated people presenting with emergencies is increasing. There is evidence that negative health and social consequences may affect recreational and chronic users. The addictive potential of designer drugs is not negligible.
-
Synthetic biology to access and expand nature’s chemical diversity
Smanski, Michael J.; Zhou, Hui; Claesen, Jan; Shen, Ben; Fischbach, Michael; Voigt, Christopher A.
2016-01-01
Bacterial genomes encode the biosynthetic potential to produce hundreds of thousands of complex molecules with diverse applications, from medicine to agriculture and materials. Economically accessing the potential encoded within sequenced genomes promises to reinvigorate waning drug discovery pipelines and provide novel routes to intricate chemicals. This is a tremendous undertaking, as the pathways often comprise dozens of genes spanning as much as 100+ kiliobases of DNA, are controlled by complex regulatory networks, and the most interesting molecules are made by non-model organisms. Advances in synthetic biology address these issues, including DNA construction technologies, genetic parts for precision expression control, synthetic regulatory circuits, computer aided design, and multiplexed genome engineering. Collectively, these technologies are moving towards an era when chemicals can be accessed en mass based on sequence information alone. This will enable the harnessing of metagenomic data and massive strain banks for high-throughput molecular discovery and, ultimately, the ability to forward design pathways to complex chemicals not found in nature. PMID:26876034
-
Plant synthetic biology for molecular engineering of signalling and development.
Nemhauser, Jennifer L; Torii, Keiko U
2016-03-02
Molecular genetic studies of model plants in the past few decades have identified many key genes and pathways controlling development, metabolism and environmental responses. Recent technological and informatics advances have led to unprecedented volumes of data that may uncover underlying principles of plants as biological systems. The newly emerged discipline of synthetic biology and related molecular engineering approaches is built on this strong foundation. Today, plant regulatory pathways can be reconstituted in heterologous organisms to identify and manipulate parameters influencing signalling outputs. Moreover, regulatory circuits that include receptors, ligands, signal transduction components, epigenetic machinery and molecular motors can be engineered and introduced into plants to create novel traits in a predictive manner. Here, we provide a brief history of plant synthetic biology and significant recent examples of this approach, focusing on how knowledge generated by the reference plant Arabidopsis thaliana has contributed to the rapid rise of this new discipline, and discuss potential future directions.
-
Current status of synthetic epikeratoplasty.
Thompson, K P; Hanna, K; Waring, G O; Gipson, I; Liu, Y; Gailitis, R P; Johnson-Wint, B; Green, K
1991-01-01
Many of the deficiencies with human tissue epikeratoplasty might be improved by the use of a suitable synthetic lenticule. Potential biomaterials for epikeratoplasty include collagen (types I, III, or IV), collagen-hydrogel copolymers, bioactive synthetics, and coated hydrogels. The biomaterial must be engineered to achieve strict specifications of optical clarity, support of epithelial migration and adhesion, permeability to solutes, and stability to corneal proteases. Attaching synthetic lenticules to the cornea without cutting Bowman's layer by adhesives, laser welding, or direct adhesion may also improve the efficacy of synthetic epikeratoplasty.
-
Tissue Harmonic Synthetic Aperture Imaging
DEFF Research Database (Denmark)
Rasmussen, Joachim
The main purpose of this PhD project is to develop an ultrasonic method for tissue harmonic synthetic aperture imaging. The motivation is to advance the field of synthetic aperture imaging in ultrasound, which has shown great potentials in the clinic. Suggestions for synthetic aperture tissue...... system complexity compared to conventional synthetic aperture techniques. In this project, SASB is sought combined with a pulse inversion technique for 2nd harmonic tissue harmonic imaging. The advantages in tissue harmonic imaging (THI) are expected to further improve the image quality of SASB...
-
DEFF Research Database (Denmark)
Rasmussen, Steen
2010-01-01
Nature asked eight synthetic-biology experts about the implications for science and society of the “synthetic cell” made by the J. Craig Venter Institute (JCVI). The institute's team assembled, modified and implanted a synthesized genome into a DNA-free bacterial shell to make a self-replicating ......Nature asked eight synthetic-biology experts about the implications for science and society of the “synthetic cell” made by the J. Craig Venter Institute (JCVI). The institute's team assembled, modified and implanted a synthesized genome into a DNA-free bacterial shell to make a self...
-
Living GenoChemetics by hyphenating synthetic biology and synthetic chemistry in vivo.
Sharma, Sunil V; Tong, Xiaoxue; Pubill-Ulldemolins, Cristina; Cartmell, Christopher; Bogosyan, Emma J A; Rackham, Emma J; Marelli, Enrico; Hamed, Refaat B; Goss, Rebecca J M
2017-08-09
Marrying synthetic biology with synthetic chemistry provides a powerful approach toward natural product diversification, combining the best of both worlds: expediency and synthetic capability of biogenic pathways and chemical diversity enabled by organic synthesis. Biosynthetic pathway engineering can be employed to insert a chemically orthogonal tag into a complex natural scaffold affording the possibility of site-selective modification without employing protecting group strategies. Here we show that, by installing a sufficiently reactive handle (e.g., a C-Br bond) and developing compatible mild aqueous chemistries, synchronous biosynthesis of the tagged metabolite and its subsequent chemical modification in living culture can be achieved. This approach can potentially enable many new applications: for example, assay of directed evolution of enzymes catalyzing halo-metabolite biosynthesis in living cells or generating and following the fate of tagged metabolites and biomolecules in living systems. We report synthetic biological access to new-to-nature bromo-metabolites and the concomitant biorthogonal cross-coupling of halo-metabolites in living cultures.Coupling synthetic biology and chemical reactions in cells is a challenging task. The authors engineer bacteria capable of generating bromo-metabolites, develop a mild Suzuki-Miyaura cross-coupling reaction compatible with cell growth and carry out the cross-coupling chemistry in live cell cultures.
-
Genotoxic effects of synthetic amorphous silica nanoparticles in the mouse lymphoma assay
Directory of Open Access Journals (Sweden)
Eşref Demir
Full Text Available Synthetic amorphous silica nanoparticles (SAS NPs have been used in various industries, such as plastics, glass, paints, electronics, synthetic rubber, in pharmaceutical drug tablets, and a as food additive in many processed foods. There are few studies in the literature on NPs using gene mutation approaches in mammalian cells, which represents an important gap for genotoxic risk estimations. To fill this gap, the mouse lymphoma L5178Y/Tk+/− assay (MLA was used to evaluate the mutagenic effect for five different concentrations (from 0.01 to 150 μg/mL of two different sizes of SAS NPs (7.172 and 7.652 nm and a fine collodial form of silicon dioxide (SiO2. This assay detects a broad spectrum of mutational events, from point mutations to chromosome alterations. The results obtained indicate that the two selected SAS NPs are mutagenic in the MLA assay, showing a concentration-dependent effect. The relative mutagenic potencies according to the induced mutant frequency (IMF are as follows: SAS NPs (7.172 nm (IMF = 705.5 × 10−6, SAS NPs (7.652 nm (IMF = 575.5 × 10−6, and SiO2 (IMF = 57.5 × 10−6. These in vitro results, obtained from mouse lymphoma cells, support the genotoxic potential of NPs as well as focus the discussion of the benefits/risks associated with their use in different areas. Keywords: Synthetic amorphous silica nanoparticles, Mouse lymphoma assay, Mutagenic agents, Thymidine kinase (Tk gene, In vitro mutagenicity
-
Biodegradable nanoparticles for gene therapy technology
International Nuclear Information System (INIS)
Hosseinkhani, Hossein; He, Wen-Jie; Chiang, Chiao-Hsi; Hong, Po-Da; Yu, Dah-Shyong; Domb, Abraham J.; Ou, Keng-Liang
2013-01-01
Rapid propagations in materials technology together with biology have initiated great hopes in the possibility of treating many diseases by gene therapy technology. Viral and non-viral gene carriers are currently applied for gene delivery. Non-viral technology is safe and effective for the delivery of genetic materials to cells and tissues. Non-viral systems are based on plasmid expression containing a gene encoding a therapeutic protein and synthetic biodegradable nanoparticles as a safe carrier of gene. Biodegradable nanoparticles have shown great interest in drug and gene delivery systems as they are easy to be synthesized and have no side effect in cells and tissues. This review provides a critical view of applications of biodegradable nanoparticles on gene therapy technology to enhance the localization of in vitro and in vivo and improve the function of administered genes
-
Fractal gene regulatory networks for robust locomotion control of modular robots
DEFF Research Database (Denmark)
Zahadat, Payam; Christensen, David Johan; Schultz, Ulrik Pagh
2010-01-01
Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed and the ......Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed...
-
Minty, Jeremy J; Singer, Marc E; Scholz, Scott A; Bae, Chang-Hoon; Ahn, Jung-Ho; Foster, Clifton E; Liao, James C; Lin, Xiaoxia Nina
2013-09-03
Synergistic microbial communities are ubiquitous in nature and exhibit appealing features, such as sophisticated metabolic capabilities and robustness. This has inspired fast-growing interest in engineering synthetic microbial consortia for biotechnology development. However, there are relatively few reports of their use in real-world applications, and achieving population stability and regulation has proven to be challenging. In this work, we bridge ecology theory with engineering principles to develop robust synthetic fungal-bacterial consortia for efficient biosynthesis of valuable products from lignocellulosic feedstocks. The required biological functions are divided between two specialists: the fungus Trichoderma reesei, which secretes cellulase enzymes to hydrolyze lignocellulosic biomass into soluble saccharides, and the bacterium Escherichia coli, which metabolizes soluble saccharides into desired products. We developed and experimentally validated a comprehensive mathematical model for T. reesei/E. coli consortia, providing insights on key determinants of the system's performance. To illustrate the bioprocessing potential of this consortium, we demonstrate direct conversion of microcrystalline cellulose and pretreated corn stover to isobutanol. Without costly nutrient supplementation, we achieved titers up to 1.88 g/L and yields up to 62% of theoretical maximum. In addition, we show that cooperator-cheater dynamics within T. reesei/E. coli consortia lead to stable population equilibria and provide a mechanism for tuning composition. Although we offer isobutanol production as a proof-of-concept application, our modular system could be readily adapted for production of many other valuable biochemicals.
-
Information processing in the transcriptional regulatory network of yeast: Functional robustness
Directory of Open Access Journals (Sweden)
Dehmer Matthias
2009-03-01
Full Text Available Abstract Background Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism. Results In this paper we study the functional robustness of the transcriptional regulatory network of S. cerevisiae. We model the information processing in the network as a first order Markov chain and study the influence of single gene perturbations on the global, asymptotic communication among genes. Modification in the communication is measured by an information theoretic measure allowing to predict genes that are 'fragile' with respect to single gene knockouts. Our results demonstrate that the predicted set of fragile genes contains a statistically significant enrichment of so called essential genes that are experimentally found to be necessary to ensure vital yeast. Further, a structural analysis of the transcriptional regulatory network reveals that there are significant differences between fragile genes, hub genes and genes with a high betweenness centrality value. Conclusion Our study does not only demonstrate that a combination of graph theoretical, information theoretical and statistical methods leads to meaningful biological results but also that such methods allow to study information processing in gene networks instead of just their structural properties.
-
Creating biological nanomaterials using synthetic biology
International Nuclear Information System (INIS)
Rice, MaryJoe K; Ruder, Warren C
2014-01-01
Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems. (review)
-
Creating biological nanomaterials using synthetic biology.
Rice, MaryJoe K; Ruder, Warren C
2014-02-01
Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems.
-
Exometabolomics Assisted Design and Validation of Synthetic Obligate Mutualism.
Kosina, Suzanne M; Danielewicz, Megan A; Mohammed, Mujahid; Ray, Jayashree; Suh, Yumi; Yilmaz, Suzan; Singh, Anup K; Arkin, Adam P; Deutschbauer, Adam M; Northen, Trent R
2016-07-15
Synthetic microbial ecology has the potential to enhance the productivity and resiliency of biotechnology processes compared to approaches using single isolates. Engineering microbial consortia is challenging; however, one approach that has attracted significant attention is the creation of synthetic obligate mutualism using auxotrophic mutants that depend on each other for exchange or cross-feeding of metabolites. Here, we describe the integration of mutant library fitness profiling with mass spectrometry based exometabolomics as a method for constructing synthetic mutualism based on cross-feeding. Two industrially important species lacking known ecological interactions, Zymomonas mobilis and Escherichia coli, were selected as the test species. Amino acid exometabolites identified in the spent medium of Z. mobilis were used to select three corresponding E. coli auxotrophs (proA, pheA and IlvA), as potential E. coli counterparts for the coculture. A pooled mutant fitness assay with a Z. mobilis transposon mutant library was used to identify mutants with improved growth in the presence of E. coli. An auxotroph mutant in a gene (ZMO0748) with sequence similarity to cysteine synthase A (cysK), was selected as the Z. mobilis counterpart for the coculture. Exometabolomic analysis of spent E. coli medium identified glutathione related metabolites as potentially available for rescue of the Z. mobilis cysteine synthase mutant. Three sets of cocultures between the Z. mobilis auxotroph and each of the three E. coli auxotrophs were monitored by optical density for growth and analyzed by flow cytometry to confirm high cell counts for each species. Taken together, our methods provide a technological framework for creating synthetic mutualisms combining existing screening based methods and exometabolomics for both the selection of obligate mutualism partners and elucidation of metabolites involved in auxotroph rescue.
-
Synthetic Defects for Vibrothermography
Renshaw, Jeremy; Holland, Stephen D.; Thompson, R. Bruce; Eisenmann, David J.
2010-02-01
Synthetic defects are an important tool used for characterizing the performance of nondestructive evaluation techniques. Viscous material-filled synthetic defects were developed for use in vibrothermography (also known as sonic IR) as a tool to improve inspection accuracy and reliability. This paper describes how the heat-generation response of these VMF synthetic defects is similar to the response of real defects. It also shows how VMF defects can be applied to improve inspection accuracy for complex industrial parts and presents a study of their application in an aircraft engine stator vane.
-
Synthetic biology: Emerging bioengineering in Indonesia
Suhandono, Sony
2017-05-01
The development of synthetic biology will shape the new era of science and technology. It is an emerging bioengineering technique involving genetic engineering which can alter the phenotype and behavior of the cell or the new product. Synthetic biology may produce biomaterials, drugs, vaccines, biosensors, and even a recombinant secondary metabolite used in herbal and complementary medicine, such as artemisinin, a malaria drug which is usually extracted from the plant Artemisia annua. The power of synthetic biology has encouraged scientists in Indonesia, and is still in early development. This paper also covers some research from an Indonesian research institute in synthetic biology such as observing the production of bio surfactants and the enhanced production of artemisinin using a transient expression system. Synthetic biology development in Indonesia may also be related to the iGEM competition, a large synthetic biology research competition which was attended by several universities in Indonesia. The application of synthetic biology for drug discovery will be discussed.
-
Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory
Directory of Open Access Journals (Sweden)
Haimin Yang
2017-01-01
Full Text Available Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam, for long short-term memory (LSTM to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.
-
Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.
Yang, Haimin; Pan, Zhisong; Tao, Qing
2017-01-01
Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.
-
Natural and synthetic saponin adjuvant QS-21 for vaccines against cancer
Ragupathi, Govind; Gardner, Jeffrey R; Livingston, Philip O; Gin, David Y
2013-01-01
One of the most widely used and potent immunological adjuvants is a mixture of soluble triterpene glycosides purified from the soap bark tree (Quillaja saponaria). Despite challenges in production, quality control, stability and toxicity, the QS-21 fraction from this extract has exhibited exceptional adjuvant properties for a range of antigens. It possesses an ability to augment clinically significant antibody and T-cell responses to vaccine antigens against a variety of infectious diseases, degenerative disorders and cancers. The recent synthesis of active molecules of QS-21 has provided a robust method to produce this leading vaccine adjuvant in high purity as well as to produce novel synthetic QS-21 congeners designed to induce increased immune responsiveness and decreased toxicity. PMID:21506644
-
Directory of Open Access Journals (Sweden)
Bangyan Zhu
2016-07-01
Full Text Available Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS.
-
A synthetic phylogeny of freshwater crayfish: insights for conservation
Owen, Christopher L.; Bracken-Grissom, Heather; Stern, David; Crandall, Keith A.
2015-01-01
Phylogenetic systematics is heading for a renaissance where we shift from considering our phylogenetic estimates as a static image in a published paper and taxonomies as a hardcopy checklist to treating both the phylogenetic estimate and dynamic taxonomies as metadata for further analyses. The Open Tree of Life project (opentreeoflife.org) is developing synthesis tools for harnessing the power of phylogenetic inference and robust taxonomy to develop a synthetic tree of life. We capitalize on this approach to estimate a synthesis tree for the freshwater crayfish. The crayfish make an exceptional group to demonstrate the utility of the synthesis approach, as there recently have been a number of phylogenetic studies on the crayfishes along with a robust underlying taxonomic framework. Importantly, the crayfish have also been extensively assessed by an IUCN Red List team and therefore have accurate and up-to-date area and conservation status data available for analysis within a phylogenetic context. Here, we develop a synthesis phylogeny for the world's freshwater crayfish and examine the phylogenetic distribution of threat. We also estimate a molecular phylogeny based on all available GenBank crayfish sequences and use this tree to estimate divergence times and test for divergence rate variation. Finally, we conduct EDGE and HEDGE analyses and identify a number of species of freshwater crayfish of highest priority in conservation efforts. PMID:25561670
-
Galdzicki, Michal; Clancy, Kevin P; Oberortner, Ernst; Pocock, Matthew; Quinn, Jacqueline Y; Rodriguez, Cesar A; Roehner, Nicholas; Wilson, Mandy L; Adam, Laura; Anderson, J Christopher; Bartley, Bryan A; Beal, Jacob; Chandran, Deepak; Chen, Joanna; Densmore, Douglas; Endy, Drew; Grünberg, Raik; Hallinan, Jennifer; Hillson, Nathan J; Johnson, Jeffrey D; Kuchinsky, Allan; Lux, Matthew; Misirli, Goksel; Peccoud, Jean; Plahar, Hector A; Sirin, Evren; Stan, Guy-Bart; Villalobos, Alan; Wipat, Anil; Gennari, John H; Myers, Chris J; Sauro, Herbert M
2014-06-01
The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. Here we describe the Synthetic Biology Open Language (SBOL), a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-driven, formalized format for exchange between software tools, research groups and commercial service providers. The SBOL Developers Group has implemented SBOL as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. We describe early successes, including a demonstration of the utility of SBOL for information exchange between several different software tools and repositories from both academic and industrial partners. As a community-driven standard, SBOL will be updated as synthetic biology evolves to provide specific capabilities for different aspects of the synthetic biology workflow.
-
Directory of Open Access Journals (Sweden)
Fabian Machens
2017-10-01
Full Text Available Orthogonal systems for heterologous protein expression as well as for the engineering of synthetic gene regulatory circuits in hosts like Saccharomyces cerevisiae depend on synthetic transcription factors (synTFs and corresponding cis-regulatory binding sites. We have constructed and characterized a set of synTFs based on either transcription activator-like effectors or CRISPR/Cas9, and corresponding small synthetic promoters (synPs with minimal sequence identity to the host’s endogenous promoters. The resulting collection of functional synTF/synP pairs confers very low background expression under uninduced conditions, while expression output upon induction of the various synTFs covers a wide range and reaches induction factors of up to 400. The broad spectrum of expression strengths that is achieved will be useful for various experimental setups, e.g., the transcriptional balancing of expression levels within heterologous pathways or the construction of artificial regulatory networks. Furthermore, our analyses reveal simple rules that enable the tuning of synTF expression output, thereby allowing easy modification of a given synTF/synP pair. This will make it easier for researchers to construct tailored transcriptional control systems.
-
International Nuclear Information System (INIS)
Saito, Nen; Kikuchi, Macoto
2013-01-01
Dynamics in biological networks are, in general, robust against several perturbations. We investigate a coupled map network as a model motivated by gene regulatory networks and design systems that are robust against phenotypic perturbations (perturbations in dynamics), as well as systems that are robust against mutation (perturbations in network structure). To achieve such a design, we apply a multicanonical Monte Carlo method. Analysis based on the maximum Lyapunov exponent and parameter sensitivity shows that systems with marginal stability, which are regarded as systems at the edge of chaos, emerge when robustness against network perturbations is required. This emergence of the edge of chaos is a self-organization phenomenon and does not need a fine tuning of parameters. (paper)
-
A Canadian refiner's perspective of synthetic crudes
International Nuclear Information System (INIS)
Halford, T.L.; McIntosh, A.P.; Rasmussen
1997-01-01
Some of the factors affecting a refiner's choice of crude oil include refinery hardware, particularly gas oil crackers, products slate and product specifications, crude availability, relative crude price and crude quality. An overview of synthetic crude, the use of synthetic crude combined with other crudes and a comparison of synthetic crude with conventional crude oil was given. The two main users of synthetic crude are basically two groups of refiners, those large groups who use synthetic crude combined with other crudes, and a smaller group who run synthetic crude on specially designed units as a sole feed. The effects of changes in fuel legislation were reviewed. It was predicted that the changes will have a mixed impact on the value of synthetic crude, but low sulphur diesel regulations and gasoline sulphur regulations will make current synthetic crudes attractive. The big future change with a negative impact will be diesel cetane increases to reduce engine emissions. This will reduce synthetic crude attractiveness due to distillate yields and quality and high gas oil yields. Similarly, any legislation limiting aromatics in diesel fuel will also make synthetic crudes less attractive. Problems experienced by refiners with hardware dedicated to synthetic crude (salt, naphthenic acid, fouling, quality variations) were also reviewed. 3 tabs
-
Wiles, Amy M.; Ravi, Dashnamoorthy; Bhavani, Selvaraj; Bishop, Alexander J.R.
2010-01-01
Genome-wide RNAi screening is a powerful, yet relatively immature technology that allows investigation into the role of individual genes in a process of choice. Most RNAi screens identify a large number of genes with a continuous gradient in the assessed phenotype. Screeners must then decide whether to examine just those genes with the most robust phenotype or to examine the full gradient of genes that cause an effect and how to identify the candidate genes to be validated. We have used RNAi in Drosophila cells to examine viability in a 384-well plate format and compare two screens, untreated control and treatment. We compare multiple normalization methods, which take advantage of different features within the data, including quantile normalization, background subtraction, scaling, cellHTS2 1, and interquartile range measurement. Considering the false-positive potential that arises from RNAi technology, a robust validation method was designed for the purpose of gene selection for future investigations. In a retrospective analysis, we describe the use of validation data to evaluate each normalization method. While no normalization method worked ideally, we found that a combination of two methods, background subtraction followed by quantile normalization and cellHTS2, at different thresholds, captures the most dependable and diverse candidate genes. Thresholds are suggested depending on whether a few candidate genes are desired or a more extensive systems level analysis is sought. In summary, our normalization approaches and experimental design to perform validation experiments are likely to apply to those high-throughput screening systems attempting to identify genes for systems level analysis. PMID:18753689
-
Doppelhofer, Gernot; Weeks, Melvyn
2011-01-01
This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...
-
Efficient and specific gene knockdown by small interfering RNAs produced in bacteria
Huang, Linfeng; Jin, Jingmin; Deighan, Padraig; Kiner, Evgeny; McReynolds, Larry; Lieberman, Judy
2013-01-01
Synthetic small interfering RNAs (siRNAs) are an indispensable tool to investigate gene function in eukaryotic cells1,2 and may be used for therapeutic purposes to knockdown genes implicated in disease3. Thus far, most synthetic siRNAs have been produced by chemical synthesis. Here we present a method to produce highly potent siRNAs in E. coli. This method relies on ectopic expression of p19, a siRNA-binding protein found in a plant RNA virus4, 5. When expressed in E. coli, p19 stabilizes ~21 nt siRNA-like species produced by bacterial RNase III. Transfection of mammalian cells with siRNAs, generated in bacteria expressing p19 and a hairpin RNA encoding 200 or more nucleotides of a target gene, at low nanomolar concentrations reproducibly knocks down gene expression by ~90% without immunogenicity or off-target effects. Because bacterially produced siRNAs contain multiple sequences against a target gene, they may be especially useful for suppressing polymorphic cellular or viral genes. PMID:23475073
-
Finding Hope in Synthetic Biology.
Takala, Tuija
2017-04-01
For some, synthetic biology represents great hope in offering possible solutions to many of the world's biggest problems, from hunger to sustainable development. Others remain fearful of the harmful uses, such as bioweapons, that synthetic biology can lend itself to, and most hold that issues of biosafety are of utmost importance. In this article, I will evaluate these points of view and conclude that although the biggest promises of synthetic biology are unlikely to become reality, and the probability of accidents is fairly substantial, synthetic biology could still be seen to benefit humanity by enhancing our ethical understanding and by offering a boost to world economy.
-
Geo synthetic-reinforced Pavement systems
International Nuclear Information System (INIS)
Zornberg, J. G.
2014-01-01
Geo synthetics have been used as reinforcement inclusions to improve pavement performance. while there are clear field evidence of the benefit of using geo synthetic reinforcements, the specific conditions or mechanisms that govern the reinforcement of pavements are, at best, unclear and have remained largely unmeasured. Significant research has been recently conducted with the objectives of: (i) determining the relevant properties of geo synthetics that contribute to the enhanced performance of pavement systems, (ii) developing appropriate analytical, laboratory and field methods capable of quantifying the pavement performance, and (iii) enabling the prediction of pavement performance as a function of the properties of the various types of geo synthetics. (Author)
-
Transport synthetic acceleration scheme for multi-dimensional neutron transport problems
Energy Technology Data Exchange (ETDEWEB)
Modak, R S; Kumar, Vinod; Menon, S V.G. [Theoretical Physics Div., Bhabha Atomic Research Centre, Mumbai (India); Gupta, Anurag [Reactor Physics Design Div., Bhabha Atomic Research Centre, Mumbai (India)
2005-09-15
The numerical solution of linear multi-energy-group neutron transport equation is required in several analyses in nuclear reactor physics and allied areas. Computer codes based on the discrete ordinates (Sn) method are commonly used for this purpose. These codes solve external source problem and K-eigenvalue problem. The overall solution technique involves solution of source problem in each energy group as intermediate procedures. Such a single-group source problem is solved by the so-called Source Iteration (SI) method. As is well-known, the SI-method converges very slowly for optically thick and highly scattering regions, leading to large CPU times. Over last three decades, many schemes have been tried to accelerate the SI; the most prominent being the Diffusion Synthetic Acceleration (DSA) scheme. The DSA scheme, however, often fails and is also rather difficult to implement. In view of this, in 1997, Ramone and others have developed a new acceleration scheme called Transport Synthetic Acceleration (TSA) which is much more robust and easy to implement. This scheme has been recently incorporated in 2-D and 3-D in-house codes at BARC. This report presents studies on the utility of TSA scheme for fairly general test problems involving many energy groups and anisotropic scattering. The scheme is found to be useful for problems in Cartesian as well as Cylindrical geometry. (author)
-
Transport synthetic acceleration scheme for multi-dimensional neutron transport problems
International Nuclear Information System (INIS)
Modak, R.S.; Vinod Kumar; Menon, S.V.G.; Gupta, Anurag
2005-09-01
The numerical solution of linear multi-energy-group neutron transport equation is required in several analyses in nuclear reactor physics and allied areas. Computer codes based on the discrete ordinates (Sn) method are commonly used for this purpose. These codes solve external source problem and K-eigenvalue problem. The overall solution technique involves solution of source problem in each energy group as intermediate procedures. Such a single-group source problem is solved by the so-called Source Iteration (SI) method. As is well-known, the SI-method converges very slowly for optically thick and highly scattering regions, leading to large CPU times. Over last three decades, many schemes have been tried to accelerate the SI; the most prominent being the Diffusion Synthetic Acceleration (DSA) scheme. The DSA scheme, however, often fails and is also rather difficult to implement. In view of this, in 1997, Ramone and others have developed a new acceleration scheme called Transport Synthetic Acceleration (TSA) which is much more robust and easy to implement. This scheme has been recently incorporated in 2-D and 3-D in-house codes at BARC. This report presents studies on the utility of TSA scheme for fairly general test problems involving many energy groups and anisotropic scattering. The scheme is found to be useful for problems in Cartesian as well as Cylindrical geometry. (author)
-
Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker.
Directory of Open Access Journals (Sweden)
Heewon Park
Full Text Available The personal genomics era has attracted a large amount of attention for anti-cancer therapy by patient-specific analysis. Patient-specific analysis enables discovery of individual genomic characteristics for each patient, and thus we can effectively predict individual genetic risk of disease and perform personalized anti-cancer therapy. Although the existing methods for patient-specific analysis have successfully uncovered crucial biomarkers, their performance takes a sudden turn for the worst in the presence of outliers, since the methods are based on non-robust manners. In practice, clinical and genomic alterations datasets usually contain outliers from various sources (e.g., experiment error, coding error, etc. and the outliers may significantly affect the result of patient-specific analysis. We propose a robust methodology for patient-specific analysis in line with the NetwrokProfiler. In the proposed method, outliers in high dimensional gene expression levels and drug response datasets are simultaneously controlled by robust Mahalanobis distance in robust principal component space. Thus, we can effectively perform for predicting anti-cancer drug sensitivity and identifying sensitivity-specific biomarkers for individual patients. We observe through Monte Carlo simulations that the proposed robust method produces outstanding performances for predicting response variable in the presence of outliers. We also apply the proposed methodology to the Sanger dataset in order to uncover cancer biomarkers and predict anti-cancer drug sensitivity, and show the effectiveness of our method.
-
Azmy, Y Y
2002-01-01
We construct a particle transport problem for which there exists no preconditioner with a cell-centered diffusion coupling stencil that is unconditionally stable and robust. In particular we consider an asymptotic limit of the periodic horizontal interface (PHI) configuration wherein the cell height in both layers approaches zero like sigma sup 2 while the total cross section vanishes like sigma in one layer and diverges like sigma sup - sup 1 as sigma->0 in the other layer. In such cases we show that the conditions for stability and robustness of the flat eigenmodes of the iteration residual imply instability of the modes flat in the y-dimension and rapidly varying in the x-dimension. Two assumptions are made in the proof. (i) Only cell-centered adjacent-cell preconditioners (AP) are considered; nevertheless numerical experiments with face-centered preconditioners of the diffusion synthetic acceleration (DSA) type on problem configurations with sharp material discontinuities suffer similar deterioration in s...
-
Beggel, Sebastian; Connon, Richard; Werner, Inge; Geist, Juergen
2011-09-01
The combination of molecular and whole-organism endpoints in ecotoxicology provides valuable information about the ecological relevance of sublethal stressor effects in aquatic ecosystems such as those caused by the use of insecticides and translocation of their residues into surface waters. This study contributes knowledge about the sublethal effects of a common use insecticide, the synthetic pyrethroid bifenthrin, on larval fathead minnow (Pimephales promelas). Transcriptomic responses, assessed by quantitative real-time PCR, combined with individual effects on swimming performance were used to estimate the ecological relevance of insecticide impacts. Significant transcriptomic responses were observed at 0.07 μg L(-1) bifenthrin (lowest observed effect concentration, LOEC) but mostly followed a biphasic rather than a linear dose-response with increasing concentration. Transcript patterns for genes involved in detoxification, neuromuscular function and energy metabolism were linked to an impairment of swimming performance at ≥0.14 μg L(-1) bifenthrin. With increasing treatment concentration, a significant down-regulation was observed for genes coding for cyp3a, aspartoacylase, and creatine kinase, whereas metallothionein was up-regulated. Additionally, bifenthrin induced endocrine responses as evident from a significant up-regulation of vitellogenin and down-regulation of insuline-like growth factor transcripts. Recovery occurred after 6 days and was dependent on the magnitude of the initial stress. During the recovery period, down-regulation of vitellogenin was observed at lowest exposure concentrations. The data presented here emphasize that links can be made between gene transcription changes and behavioral responses which is of great value for the evaluation and interpretation of biomarker responses. Copyright © 2011 Elsevier B.V. All rights reserved.
-
Computational optimization of synthetic water channels.
Energy Technology Data Exchange (ETDEWEB)
Rogers, David Michael; Rempe, Susan L. B.
2012-12-01
Membranes for liquid and gas separations and ion transport are critical to water purification, osmotic energy generation, fuel cells, batteries, supercapacitors, and catalysis. Often these membranes lack pore uniformity and robustness under operating conditions, which can lead to a decrease in performance. The lack of uniformity means that many pores are non-functional. Traditional membranes overcome these limitations by using thick membrane materials that impede transport and selectivity, which results in decreased performance and increased operating costs. For example, limitations in membrane performance demand high applied pressures to deionize water using reverse osmosis. In contrast, cellular membranes combine high flux and selective transport using membrane-bound protein channels operating at small pressure differences. Pore size and chemistry in the cellular channels is defined uniformly and with sub-nanometer precision through protein folding. The thickness of these cellular membranes is limited to that of the cellular membrane bilayer, about 4 nm thick, which enhances transport. Pores in the cellular membranes are robust under operating conditions in the body. Recent efforts to mimic cellular water channels for efficient water deionization produced a significant advance in membrane function. The novel biomimetic design achieved a 10-fold increase in membrane permeability to water flow compared to commercial membranes and still maintained high salt rejection. Despite this success, there is a lack of understanding about why this membrane performs so well. To address this lack of knowledge, we used highperformance computing to interrogate the structural and chemical environments experienced by water and electrolytes in the newly created biomimetic membranes. We also compared the solvation environments between the biomimetic membrane and cellular water channels. These results will help inform future efforts to optimize and tune the performance of synthetic
-
Effective Nanoparticle-based Gene Delivery by a Protease Triggered Charge Switch
DEFF Research Database (Denmark)
Gjetting, Torben; Jølck, Rasmus Irming; Andresen, Thomas Lars
2014-01-01
Gene carriers made from synthetic materials are of interest in relation to gene therapy but suffer from lack of transfection efficiency upon systemic delivery. To address this problem, a novel lipo-peptide-PEG conjugate constituted by a lipid-anchor, a peptide sensitive to proteases and a poly (e...
-
Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias
2013-04-24
Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.
-
DEFF Research Database (Denmark)
Vrouwenvelder, T.; Sørensen, John Dalsgaard
2009-01-01
After the collapse of the World Trade Centre towers in 2001 and a number of collapses of structural systems in the beginning of the century, robustness of structural systems has gained renewed interest. Despite many significant theoretical, methodical and technological advances, structural...... of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its uantification. A European COST action TU 601 on ‘Robustness of structures' has started in 2007...... by a group of members of the CSS. This paper describes the ongoing work in this action, with emphasis on the development of a theoretical and risk based quantification and optimization procedure on the one side and a practical pre-normative guideline on the other....
-
International Nuclear Information System (INIS)
Gandhy, Shruti U; Kim, KyoungHyun; Larsen, Lesley; Rosengren, Rhonda J; Safe, Stephen
2012-01-01
Curcumin inhibits growth of several cancer cell lines, and studies in this laboratory in bladder and pancreatic cancer cells show that curcumin downregulates specificity protein (Sp) transcription factors Sp1, Sp3 and Sp4 and pro-oncogenic Sp-regulated genes. In this study, we investigated the anticancer activity of curcumin and several synthetic cyclohexanone and piperidine analogs in colon cancer cells. The effects of curcumin and synthetic analogs on colon cancer cell proliferation and apoptosis were determined using standardized assays. The changes in Sp proteins and Sp-regulated gene products were analysed by western blots, and real time PCR was used to determine microRNA-27a (miR-27a), miR-20a, miR-17-5p and ZBTB10 and ZBTB4 mRNA expression. The IC 50 (half-maximal) values for growth inhibition (24 hr) of colon cancer cells by curcumin and synthetic cyclohexanone and piperidine analogs of curcumin varied from 10 μM for curcumin to 0.7 μM for the most active synthetic piperidine analog RL197, which was used along with curcumin as model agents in this study. Curcumin and RL197 inhibited RKO and SW480 colon cancer cell growth and induced apoptosis, and this was accompanied by downregulation of specificity protein (Sp) transcription factors Sp1, Sp3 and Sp4 and Sp-regulated genes including the epidermal growth factor receptor (EGFR), hepatocyte growth factor receptor (c-MET), survivin, bcl-2, cyclin D1 and NFκB (p65 and p50). Curcumin and RL197 also induced reactive oxygen species (ROS), and cotreatment with the antioxidant glutathione significantly attenuated curcumin- and RL197-induced growth inhibition and downregulation of Sp1, Sp3, Sp4 and Sp-regulated genes. The mechanism of curcumin-/RL197-induced repression of Sp transcription factors was ROS-dependent and due to induction of the Sp repressors ZBTB10 and ZBTB4 and downregulation of microRNAs (miR)-27a, miR-20a and miR-17-5p that regulate these repressors. These results identify a new and highly potent
-
Directory of Open Access Journals (Sweden)
Gandhy Shruti U
2012-11-01
Full Text Available Abstract Background Curcumin inhibits growth of several cancer cell lines, and studies in this laboratory in bladder and pancreatic cancer cells show that curcumin downregulates specificity protein (Sp transcription factors Sp1, Sp3 and Sp4 and pro-oncogenic Sp-regulated genes. In this study, we investigated the anticancer activity of curcumin and several synthetic cyclohexanone and piperidine analogs in colon cancer cells. Methods The effects of curcumin and synthetic analogs on colon cancer cell proliferation and apoptosis were determined using standardized assays. The changes in Sp proteins and Sp-regulated gene products were analysed by western blots, and real time PCR was used to determine microRNA-27a (miR-27a, miR-20a, miR-17-5p and ZBTB10 and ZBTB4 mRNA expression. Results The IC50 (half-maximal values for growth inhibition (24 hr of colon cancer cells by curcumin and synthetic cyclohexanone and piperidine analogs of curcumin varied from 10 μM for curcumin to 0.7 μM for the most active synthetic piperidine analog RL197, which was used along with curcumin as model agents in this study. Curcumin and RL197 inhibited RKO and SW480 colon cancer cell growth and induced apoptosis, and this was accompanied by downregulation of specificity protein (Sp transcription factors Sp1, Sp3 and Sp4 and Sp-regulated genes including the epidermal growth factor receptor (EGFR, hepatocyte growth factor receptor (c-MET, survivin, bcl-2, cyclin D1 and NFκB (p65 and p50. Curcumin and RL197 also induced reactive oxygen species (ROS, and cotreatment with the antioxidant glutathione significantly attenuated curcumin- and RL197-induced growth inhibition and downregulation of Sp1, Sp3, Sp4 and Sp-regulated genes. The mechanism of curcumin-/RL197-induced repression of Sp transcription factors was ROS-dependent and due to induction of the Sp repressors ZBTB10 and ZBTB4 and downregulation of microRNAs (miR-27a, miR-20a and miR-17-5p that regulate these repressors
-
A Robust Statistics Approach to Minimum Variance Portfolio Optimization
Yang, Liusha; Couillet, Romain; McKay, Matthew R.
2015-12-01
We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns. For large portfolios, the number of available market returns is often of similar order to the number of assets, so that the sample covariance matrix performs poorly as a covariance estimator. Additionally, financial market data often contain outliers which, if not correctly handled, may further corrupt the covariance estimation. We address these shortcomings by studying the performance of a hybrid covariance matrix estimator based on Tyler's robust M-estimator and on Ledoit-Wolf's shrinkage estimator while assuming samples with heavy-tailed distribution. Employing recent results from random matrix theory, we develop a consistent estimator of (a scaled version of) the realized portfolio risk, which is minimized by optimizing online the shrinkage intensity. Our portfolio optimization method is shown via simulations to outperform existing methods both for synthetic and real market data.
-
Directory of Open Access Journals (Sweden)
Claudia M Rivera-Hoyos
Full Text Available Lacasses are multicopper oxidases that can catalyze aromatic and non-aromatic compounds concomitantly with reduction of molecular oxygen to water. Fungal laccases have generated a growing interest due to their biotechnological potential applications, such as lignocellulosic material delignification, biopulping and biobleaching, wastewater treatment, and transformation of toxic organic pollutants. In this work we selected fungal genes encoding for laccase enzymes GlLCC1 in Ganoderma lucidum and POXA 1B in Pleurotus ostreatus. These genes were optimized for codon use, GC content, and regions generating secondary structures. Laccase proposed computational models, and their interaction with ABTS [2, 2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid] substrate was evaluated by molecular docking. Synthetic genes were cloned under the control of Pichia pastoris glyceraldehyde-3-phosphate dehydrogenase (GAP constitutive promoter. P. pastoris X-33 was transformed with pGAPZαA-LaccGluc-Stop and pGAPZαA-LaccPost-Stop constructs. Optimization reduced GC content by 47 and 49% for LaccGluc-Stop and LaccPost-Stop genes, respectively. A codon adaptation index of 0.84 was obtained for both genes. 3D structure analysis using SuperPose revealed LaccGluc-Stop is similar to the laccase crystallographic structure 1GYC of Trametes versicolor. Interaction analysis of the 3D models validated through ABTS, demonstrated higher substrate affinity for LaccPost-Stop, in agreement with our experimental results with enzymatic activities of 451.08 ± 6.46 UL-1 compared to activities of 0.13 ± 0.028 UL-1 for LaccGluc-Stop. This study demonstrated that G. lucidum GlLCC1 and P. ostreatus POXA 1B gene optimization resulted in constitutive gene expression under GAP promoter and α-factor leader in P. pastoris. These are important findings in light of recombinant enzyme expression system utility for environmentally friendly designed expression systems, because of the wide range
-
Grzegorczyk, Marco; Husmeier, Dirk
2012-07-12
An important and challenging problem in systems biology is the inference of gene regulatory networks from short non-stationary time series of transcriptional profiles. A popular approach that has been widely applied to this end is based on dynamic Bayesian networks (DBNs), although traditional homogeneous DBNs fail to model the non-stationarity and time-varying nature of the gene regulatory processes. Various authors have therefore recently proposed combining DBNs with multiple changepoint processes to obtain time varying dynamic Bayesian networks (TV-DBNs). However, TV-DBNs are not without problems. Gene expression time series are typically short, which leaves the model over-flexible, leading to over-fitting or inflated inference uncertainty. In the present paper, we introduce a Bayesian regularization scheme that addresses this difficulty. Our approach is based on the rationale that changes in gene regulatory processes appear gradually during an organism's life cycle or in response to a changing environment, and we have integrated this notion in the prior distribution of the TV-DBN parameters. We have extensively tested our regularized TV-DBN model on synthetic data, in which we have simulated short non-homogeneous time series produced from a system subject to gradual change. We have then applied our method to real-world gene expression time series, measured during the life cycle of Drosophila melanogaster, under artificially generated constant light condition in Arabidopsis thaliana, and from a synthetically designed strain of Saccharomyces cerevisiae exposed to a changing environment.
-
PREditOR: a synthetic biology approach to removing heterochromatin from cells.
Molina, Oscar; Carmena, Mar; Maudlin, Isabella E; Earnshaw, William C
2016-12-01
It is widely accepted that heterochromatin is necessary to maintain genomic stability. However, direct experimental evidence supporting this is slim. Previous studies using either enzyme inhibitors, gene knockout or knockdown studies all are subject to the caveat that drugs may have off-target effects and enzymes that modify chromatin proteins to support heterochromatin formation may also have numerous other cellular targets as well. Here, we describe PREditOR (protein reading and editing of residues), a synthetic biology approach that allows us to directly remove heterochromatin from cells without either drugs or global interference with gene function. We find that removal of heterochromatin perturbs mitotic progression and causes a dramatic increase in chromosome segregation defects, possibly as a result of interfering with the normal centromeric localization of the chromosomal passenger complex.
-
Yan, Yue
2018-03-01
A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.
-
Impact of synthetic biology and metabolic engineering on industrial production of fine chemicals
DEFF Research Database (Denmark)
Jullesson, David; David, Florian; Pfleger, Brian
2015-01-01
Industrial bio-processes for fine chemical production are increasingly relying on cell factories developed through metabolic engineering and synthetic biology. The use of high throughput techniques and automation for the design of cell factories, and especially platform strains, has played...... chemicals that have reached the market, key metabolic engineering tools that have allowed this to happen and some of the companies that are currently utilizing these technologies for developing industrial production processes....... an important role in the transition from laboratory research to industrial production. Model organisms such as Saccharomyces cerevisiae and Escherichia coli remain widely used host strains for industrial production due to their robust and desirable traits. This review describes some of the bio-based fine...
-
Meeting Report: Synthetic Biology Jamboree for Undergraduates
Campbell, A. Malcolm
2005-01-01
The field of synthetic biology (the name is derived from an analogy to synthetic chemistry) has recognized itself as a "field" only since about 2002. Synthetic biology has gotten some high-profile attention recently, but most people are not aware the field even exists. Synthetic biologists apply engineering principles to genomic circuits to…
-
21 CFR 73.1200 - Synthetic iron oxide.
2010-04-01
... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Synthetic iron oxide. 73.1200 Section 73.1200 Food... COLOR ADDITIVES EXEMPT FROM CERTIFICATION Drugs § 73.1200 Synthetic iron oxide. (a) Identity. (1) The color additive synthetic iron oxide consists of any one or any combination of synthetically prepared...
-
21 CFR 73.200 - Synthetic iron oxide.
2010-04-01
... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Synthetic iron oxide. 73.200 Section 73.200 Food... COLOR ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.200 Synthetic iron oxide. (a) Identity. (1) The color additive synthetic iron oxide consists of any one or any combination of synthetically prepared...
-
21 CFR 172.888 - Synthetic petroleum wax.
2010-04-01
... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Synthetic petroleum wax. 172.888 Section 172.888... CONSUMPTION Multipurpose Additives § 172.888 Synthetic petroleum wax. Synthetic petroleum wax may be safely used in or on foods in accordance with the following conditions: (a) Synthetic petroleum wax is a...
-
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2008-01-01
This paper describes the background of the robustness requirements implemented in the Danish Code of Practice for Safety of Structures and in the Danish National Annex to the Eurocode 0, see (DS-INF 146, 2003), (DS 409, 2006), (EN 1990 DK NA, 2007) and (Sørensen and Christensen, 2006). More...... frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new structures essential....... According to Danish design rules robustness shall be documented for all structures in high consequence class. The design procedure to document sufficient robustness consists of: 1) Review of loads and possible failure modes / scenarios and determination of acceptable collapse extent; 2) Review...
-
Dynamics robustness of cascading systems.
Directory of Open Access Journals (Sweden)
Jonathan T Young
2017-03-01
Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it
-
Sohoni, Sujata Vijay; Fazio, Alessandro; Workman, Christopher T.; Mijakovic, Ivan; Lantz, Anna Eliasson
2014-01-01
The objective of this study was the application of the synthetic promoter library (SPL) technology for modulation of actinorhodin production in Streptomyces coelicolor A3(2). The SPL technology was used to optimize the expression of a pathway specific positive transcriptional regulator ActII orf4, which activates the transcription of the S. coelicolor actinorhodin biosynthetic gene cluster. The native actII orf4 promoter was replaced with synthetic promoters, generating a S. coelicolor library with a broad range of expression levels of actII orf4. The resulting library was screened based on the yield of actinorhodin. Selected strains were further physiologically characterized. One of the strains from the library, ScoSPL20, showed considerably higher yield of actinorhodin and final actinorhodin titer, compared to S. coelicolor wild type and S. coelicolor with actII orf4 expressed from a strong constitutive promoter. ScoSPL20 demonstrated exceptional productivity despite having a comparatively weak expression from the promoter. Interestingly, the ScoSPL20 promoter was activated at a much earlier stage of growth compared to the wild type, demonstrating the advantage of fine-tuning and temporal tuning of gene expression in metabolic engineering. Transcriptome studies were performed in exponential and actinorhodin-producing phase of growth to compare gene expression between ScoSPL20 and the wild type. To our knowledge, this is the first successful application of the SPL technology for secondary metabolite production in filamentous bacteria. PMID:24963940
-
Robust and distributed hypothesis testing
Gül, Gökhan
2017-01-01
This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...
-
Robustness Property of Robust-BD Wald-Type Test for Varying-Dimensional General Linear Models
Directory of Open Access Journals (Sweden)
Xiao Guo
2018-03-01
Full Text Available An important issue for robust inference is to examine the stability of the asymptotic level and power of the test statistic in the presence of contaminated data. Most existing results are derived in finite-dimensional settings with some particular choices of loss functions. This paper re-examines this issue by allowing for a diverging number of parameters combined with a broader array of robust error measures, called “robust- BD ”, for the class of “general linear models”. Under regularity conditions, we derive the influence function of the robust- BD parameter estimator and demonstrate that the robust- BD Wald-type test enjoys the robustness of validity and efficiency asymptotically. Specifically, the asymptotic level of the test is stable under a small amount of contamination of the null hypothesis, whereas the asymptotic power is large enough under a contaminated distribution in a neighborhood of the contiguous alternatives, thus lending supports to the utility of the proposed robust- BD Wald-type test.
-
Synthetic biology: programming cells for biomedical applications.
Hörner, Maximilian; Reischmann, Nadine; Weber, Wilfried
2012-01-01
The emerging field of synthetic biology is a novel biological discipline at the interface between traditional biology, chemistry, and engineering sciences. Synthetic biology aims at the rational design of complex synthetic biological devices and systems with desired properties by combining compatible, modular biological parts in a systematic manner. While the first engineered systems were mainly proof-of-principle studies to demonstrate the power of the modular engineering approach of synthetic biology, subsequent systems focus on applications in the health, environmental, and energy sectors. This review describes recent approaches for biomedical applications that were developed along the synthetic biology design hierarchy, at the level of individual parts, of devices, and of complex multicellular systems. It describes how synthetic biological parts can be used for the synthesis of drug-delivery tools, how synthetic biological devices can facilitate the discovery of novel drugs, and how multicellular synthetic ecosystems can give insight into population dynamics of parasites and hosts. These examples demonstrate how this new discipline could contribute to novel solutions in the biopharmaceutical industry.
-
DEFF Research Database (Denmark)
Ek, Pramod Kumar
This thesis investigated the role of amphiphilic triblock copolymer micelle nanomaterials in nanosensors, with emphasis on the synthesis of micelle particle sensors. The thesis is focused on the role of synthetic and dimensional synthetic organic chemistry in amphiphilic triblock core-shellcorona...
-
"Clicking" Gene Therapeutics: A Successful Union of Chemistry and Biomedicine for New Solutions
DEFF Research Database (Denmark)
Astakhova, Kira; Ray, Roslyn; Taskova, Maria
2018-01-01
The use of nucleic acid, DNA and RNA, based strategies to disrupt gene expression as a therapeutic is quickly emerging. Indeed, synthetic oligonucleotides represent a major component of modern gene therapeutics. However, the efficiency and specificity of intracellular uptake for nonmodified oligo...
-
Word selection affects perceptions of synthetic biology
Directory of Open Access Journals (Sweden)
Tonidandel Scott
2011-07-01
Full Text Available Abstract Members of the synthetic biology community have discussed the significance of word selection when describing synthetic biology to the general public. In particular, many leaders proposed the word "create" was laden with negative connotations. We found that word choice and framing does affect public perception of synthetic biology. In a controlled experiment, participants perceived synthetic biology more negatively when "create" was used to describe the field compared to "construct" (p = 0.008. Contrary to popular opinion among synthetic biologists, however, low religiosity individuals were more influenced negatively by the framing manipulation than high religiosity people. Our results suggest that synthetic biologists directly influence public perception of their field through avoidance of the word "create".
-
Libraries of Synthetic TALE-Activated Promoters: Methods and Applications.
Schreiber, T; Tissier, A
2016-01-01
The discovery of proteins with programmable DNA-binding specificities triggered a whole array of applications in synthetic biology, including genome editing, regulation of transcription, and epigenetic modifications. Among those, transcription activator-like effectors (TALEs) due to their natural function as transcription regulators, are especially well-suited for the development of orthogonal systems for the control of gene expression. We describe here the construction and testing of libraries of synthetic TALE-activated promoters which are under the control of a single TALE with a given DNA-binding specificity. These libraries consist of a fixed DNA-binding element for the TALE, a TATA box, and variable sequences of 19 bases upstream and 43 bases downstream of the DNA-binding element. These libraries were cloned using a Golden Gate cloning strategy making them usable as standard parts in a modular cloning system. The broad range of promoter activities detected and the versatility of these promoter libraries make them valuable tools for applications in the fine-tuning of expression in metabolic engineering projects or in the design and implementation of regulatory circuits. © 2016 Elsevier Inc. All rights reserved.
-
Confidence from uncertainty - A multi-target drug screening method from robust control theory
Directory of Open Access Journals (Sweden)
Petzold Linda R
2010-11-01
Full Text Available Abstract Background Robustness is a recognized feature of biological systems that evolved as a defence to environmental variability. Complex diseases such as diabetes, cancer, bacterial and viral infections, exploit the same mechanisms that allow for robust behaviour in healthy conditions to ensure their own continuance. Single drug therapies, while generally potent regulators of their specific protein/gene targets, often fail to counter the robustness of the disease in question. Multi-drug therapies offer a powerful means to restore disrupted biological networks, by targeting the subsystem of interest while preventing the diseased network from reconciling through available, redundant mechanisms. Modelling techniques are needed to manage the high number of combinatorial possibilities arising in multi-drug therapeutic design, and identify synergistic targets that are robust to system uncertainty. Results We present the application of a method from robust control theory, Structured Singular Value or μ- analysis, to identify highly effective multi-drug therapies by using robustness in the face of uncertainty as a new means of target discrimination. We illustrate the method by means of a case study of a negative feedback network motif subject to parametric uncertainty. Conclusions The paper contributes to the development of effective methods for drug screening in the context of network modelling affected by parametric uncertainty. The results have wide applicability for the analysis of different sources of uncertainty like noise experienced in the data, neglected dynamics, or intrinsic biological variability.
-
Sun, Haiyan; Pattnaik, Asit K; Osorio, Fernando A; Vu, Hiep L X
2016-12-01
We recently generated a fully synthetic porcine reproductive and respiratory syndrome virus strain (designated as PRRSV-CON), which confers unprecedented levels of heterologous protection. We report herein that the synthetic PRRSV-CON possesses a unique phenotype in that it induces type-I interferons (IFNs) instead of suppressing these cytokines as most of the naturally occurring PRRSV isolates do. Through gain- and loss- of-function studies, the IFN-inducing phenotype of PRRSV-CON was mapped to the 3.3kb genomic fragment encoding three viral nonstructural proteins: nsp1α, nsp1β and the N-terminal part of nsp2. Further studies indicated that a cooperation among these 3 proteins was required for effective induction of IFNs. Collectively, this study constitutes the first step toward understanding the mechanisms by which the synthetic PRRSV-CON confers heterologous protection. Copyright © 2016 Elsevier Inc. All rights reserved.
-
Synthetic Biology for Specialty Chemicals.
Markham, Kelly A; Alper, Hal S
2015-01-01
In this review, we address recent advances in the field of synthetic biology and describe how those tools have been applied to produce a wide variety of chemicals in microorganisms. Here we classify the expansion of the synthetic biology toolbox into three different categories based on their primary function in strain engineering-for design, for construction, and for optimization. Next, focusing on recent years, we look at how chemicals have been produced using these new synthetic biology tools. Advances in producing fuels are briefly described, followed by a more thorough treatment of commodity chemicals, specialty chemicals, pharmaceuticals, and nutraceuticals. Throughout this review, an emphasis is placed on how synthetic biology tools are applied to strain engineering. Finally, we discuss organism and host strain diversity and provide a future outlook in the field.
-
Gerasymenko, I M; Sheludko, Y V
2017-07-01
To exploit cold-inducible biochemical processes beneficial for foreign mRNA transcription, translation and storage, as well as protein product stability, during Agrobacterium-mediated transient expression. The efficiency of three different 5'-regulatory sequences to achieve transient expression of the GFP-based reporter gene under chilling conditions (6-8 °C since the 3rd day post inoculation) was compared. We studied the upstream sequences of a cold-inducible Arabidopsis thaliana cor15a gene, the core element of 35S CaMV promoter fused to the TMV omega 5'-UTR, and the synthetic promoter including the 35S core sequence and two binding sites for cold-inducible CBF transcription factors (P_DRE::35S). Cultivation of plants transiently expressing reporter gene under control of the synthetic P_DRE::35S promoter under chilling conditions since the 3rd dpi led to the reliably higher reporter accumulation as compared to the other tested regulatory sequences under chilling or greenhouse conditions. Reporter protein fluorescence under chilling conditions using P_DRE::35S reached 160% as compared to the transient expression in the greenhouse. Period of transient expression considerably extended if plants were cultivated at chilling temperature since the 3rd dpi: reporter protein fluorescence reached its maximum at the 20th dpi and was detected in leaves up to the 65th dpi. The enhanced protein accumulation at low temperature was accompanied by the prolonged period of corresponding mRNA accumulation. Transient expression under chilling conditions using synthetic cold-inducible promoter enhances target protein accumulation and may decrease greenhouse heating expenses.
-
Protease-sensitive synthetic prions.
Directory of Open Access Journals (Sweden)
David W Colby
2010-01-01
Full Text Available Prions arise when the cellular prion protein (PrP(C undergoes a self-propagating conformational change; the resulting infectious conformer is designated PrP(Sc. Frequently, PrP(Sc is protease-resistant but protease-sensitive (s prions have been isolated in humans and other animals. We report here that protease-sensitive, synthetic prions were generated in vitro during polymerization of recombinant (rec PrP into amyloid fibers. In 22 independent experiments, recPrP amyloid preparations, but not recPrP monomers or oligomers, transmitted disease to transgenic mice (n = 164, denoted Tg9949 mice, that overexpress N-terminally truncated PrP. Tg9949 control mice (n = 174 did not spontaneously generate prions although they were prone to late-onset spontaneous neurological dysfunction. When synthetic prion isolates from infected Tg9949 mice were serially transmitted in the same line of mice, they exhibited sPrP(Sc and caused neurodegeneration. Interestingly, these protease-sensitive prions did not shorten the life span of Tg9949 mice despite causing extensive neurodegeneration. We inoculated three synthetic prion isolates into Tg4053 mice that overexpress full-length PrP; Tg4053 mice are not prone to developing spontaneous neurological dysfunction. The synthetic prion isolates caused disease in 600-750 days in Tg4053 mice, which exhibited sPrP(Sc. These novel synthetic prions demonstrate that conformational changes in wild-type PrP can produce mouse prions composed exclusively of sPrP(Sc.
-
Learning gene regulatory networks from gene expression data using weighted consensus
Fujii, Chisato; Kuwahara, Hiroyuki; Yu, Ge; Guo, Lili; Gao, Xin
2016-01-01
An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.
-
Learning gene regulatory networks from gene expression data using weighted consensus
Fujii, Chisato
2016-08-25
An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.
-
Robustness Beamforming Algorithms
Directory of Open Access Journals (Sweden)
Sajad Dehghani
2014-04-01
Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.
-
Synergistic Synthetic Biology: Units in Concert
Trosset, Jean-Yves; Carbonell, Pablo
2013-01-01
Synthetic biology aims at translating the methods and strategies from engineering into biology in order to streamline the design and construction of biological devices through standardized parts. Modular synthetic biology devices are designed by means of an adequate elimination of cross-talk that makes circuits orthogonal and specific. To that end, synthetic constructs need to be adequately optimized through in silico modeling by choosing the right complement of genetic parts and by experimental tuning through directed evolution and craftsmanship. In this review, we consider an additional and complementary tool available to the synthetic biologist for innovative design and successful construction of desired circuit functionalities: biological synergies. Synergy is a prevalent emergent property in biological systems that arises from the concerted action of multiple factors producing an amplification or cancelation effect compared with individual actions alone. Synergies appear in domains as diverse as those involved in chemical and protein activity, polypharmacology, and metabolic pathway complementarity. In conventional synthetic biology designs, synergistic cross-talk between parts and modules is generally attenuated in order to verify their orthogonality. Synergistic interactions, however, can induce emergent behavior that might prove useful for synthetic biology applications, like in functional circuit design, multi-drug treatment, or in sensing and delivery devices. Synergistic design principles are therefore complementary to those coming from orthogonal design and may provide added value to synthetic biology applications. The appropriate modeling, characterization, and design of synergies between biological parts and units will allow the discovery of yet unforeseeable, novel synthetic biology applications. PMID:25022769
-
Synergistic Synthetic Biology: Units in Concert
International Nuclear Information System (INIS)
Trosset, Jean-Yves; Carbonell, Pablo
2013-01-01
Synthetic biology aims at translating the methods and strategies from engineering into biology in order to streamline the design and construction of biological devices through standardized parts. Modular synthetic biology devices are designed by means of an adequate elimination of cross-talk that makes circuits orthogonal and specific. To that end, synthetic constructs need to be adequately optimized through in silico modeling by choosing the right complement of genetic parts and by experimental tuning through directed evolution and craftsmanship. In this review, we consider an additional and complementary tool available to the synthetic biologist for innovative design and successful construction of desired circuit functionalities: biological synergies. Synergy is a prevalent emergent property in biological systems that arises from the concerted action of multiple factors producing an amplification or cancelation effect compared with individual actions alone. Synergies appear in domains as diverse as those involved in chemical and protein activity, polypharmacology, and metabolic pathway complementarity. In conventional synthetic biology designs, synergistic cross-talk between parts and modules is generally attenuated in order to verify their orthogonality. Synergistic interactions, however, can induce emergent behavior that might prove useful for synthetic biology applications, like in functional circuit design, multi-drug treatment, or in sensing and delivery devices. Synergistic design principles are therefore complementary to those coming from orthogonal design and may provide added value to synthetic biology applications. The appropriate modeling, characterization, and design of synergies between biological parts and units will allow the discovery of yet unforeseeable, novel synthetic biology applications.
-
Multiclass gene selection using Pareto-fronts.
Rajapakse, Jagath C; Mundra, Piyushkumar A
2013-01-01
Filter methods are often used for selection of genes in multiclass sample classification by using microarray data. Such techniques usually tend to bias toward a few classes that are easily distinguishable from other classes due to imbalances of strong features and sample sizes of different classes. It could therefore lead to selection of redundant genes while missing the relevant genes, leading to poor classification of tissue samples. In this manuscript, we propose to decompose multiclass ranking statistics into class-specific statistics and then use Pareto-front analysis for selection of genes. This alleviates the bias induced by class intrinsic characteristics of dominating classes. The use of Pareto-front analysis is demonstrated on two filter criteria commonly used for gene selection: F-score and KW-score. A significant improvement in classification performance and reduction in redundancy among top-ranked genes were achieved in experiments with both synthetic and real-benchmark data sets.
-
Bayesian assignment of gene ontology terms to gene expression experiments
Sykacek, P.
2012-01-01
Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488
-
Bayesian assignment of gene ontology terms to gene expression experiments.
Sykacek, P
2012-09-15
Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.
-
Structure and chromosomal localization of the human lymphotoxin gene
International Nuclear Information System (INIS)
Nedwin, G.E.; Jarrett-Nedwin, J.; Smith, D.H.; Naylor, S.L.; Sakaguchi, A.Y.; Goeddel, D.V.; Gray, P.W.
1987-01-01
The authors have isolated, sequenced, and determined the chromosomal localization of the gene encoding human lymphotoxin (LT). The single copy gene was isolated from a human genomic library using a /sup 32/P-labeled 116 bp synthetic DNA fragment whose sequence was based on the NH/sub 2/-terminal amino acid sequence of LT. The gene spans 3 kb of DNA and is interrupted by three intervening sequences. The LT gene is located on human chromosome 6, as determined by Southern blot analysis of human-murine hybrid DNA. Putative transcriptional control regions and areas of homology with the promoters of interferon and other genes are identified
-
Akbari, Omar S; Chen, Chun-Hong; Marshall, John M; Huang, Haixia; Antoshechkin, Igor; Hay, Bruce A
2014-12-19
Insects act as vectors for diseases of plants, animals, and humans. Replacement of wild insect populations with genetically modified individuals unable to transmit disease provides a potentially self-perpetuating method of disease prevention. Population replacement requires a gene drive mechanism in order to spread linked genes mediating disease refractoriness through wild populations. We previously reported the creation of synthetic Medea selfish genetic elements able to drive population replacement in Drosophila. These elements use microRNA-mediated silencing of myd88, a maternally expressed gene required for embryonic dorso-ventral pattern formation, coupled with early zygotic expression of a rescuing transgene, to bring about gene drive. Medea elements that work through additional mechanisms are needed in order to be able to carry out cycles of population replacement and/or remove existing transgenes from the population, using second-generation elements that spread while driving first-generation elements out of the population. Here we report the synthesis and population genetic behavior of two new synthetic Medea elements that drive population replacement through manipulation of signaling pathways involved in cellular blastoderm formation or Notch signaling, demonstrating that in Drosophila Medea elements can be generated through manipulation of diverse signaling pathways. We also describe the mRNA and small RNA changes in ovaries and early embryos associated from Medea-bearing females. Finally, we use modeling to illustrate how Medea elements carrying genes that result in diapause-dependent female lethality could be used to bring about population suppression.
-
Synthetic biology, metaphors and responsibility.
McLeod, Carmen; Nerlich, Brigitte
2017-08-29
Metaphors are not just decorative rhetorical devices that make speech pretty. They are fundamental tools for thinking about the world and acting on the world. The language we use to make a better world matters; words matter; metaphors matter. Words have consequences - ethical, social and legal ones, as well as political and economic ones. They need to be used 'responsibly'. They also need to be studied carefully - this is what we want to do through this editorial and the related thematic collection. In the context of synthetic biology, natural and social scientists have become increasingly interested in metaphors, a wave of interest that we want to exploit and amplify. We want to build on emerging articles and books on synthetic biology, metaphors of life and the ethical and moral implications of such metaphors. This editorial provides a brief introduction to synthetic biology and responsible innovation, as well as a comprehensive review of literature on the social, cultural and ethical impacts of metaphor use in genomics and synthetic biology. Our aim is to stimulate an interdisciplinary and international discussion on the impact that metaphors can have on science, policy and publics in the context of synthetic biology.
-
International Nuclear Information System (INIS)
Nicolin, A.
2009-01-01
The project has been focusing on molecular mechanisms determining the rate of RNA degradation eventually important to regulate gene expression and phenotype at post transcription level. Exogenous synthetic oligonucleotides targeting the relevant domains of b- RNA degradation could stabilize the transcript, efficiently enhance gene expression and alter the cellular phenotype accordingly. The experimental model was the bcl2 RNA (b-RNA), its molecular mechanisms of degradation and the functional effects of turnover modifications by exogenous means
-
Approaches to chemical synthetic biology.
Chiarabelli, Cristiano; Stano, Pasquale; Anella, Fabrizio; Carrara, Paolo; Luisi, Pier Luigi
2012-07-16
Synthetic biology is first represented in terms of two complementary aspects, the bio-engineering one, based on the genetic manipulation of extant microbial forms in order to obtain forms of life which do not exist in nature; and the chemical synthetic biology, an approach mostly based on chemical manipulation for the laboratory synthesis of biological structures that do not exist in nature. The paper is mostly devoted to shortly review chemical synthetic biology projects currently carried out in our laboratory. In particular, we describe: the minimal cell project, then the "Never Born Proteins" and lastly the Never Born RNAs. We describe and critically analyze the main results, emphasizing the possible relevance of chemical synthetic biology for the progress in basic science and biotechnology. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
-
Control of gene expression by CRISPR-Cas systems
2013-01-01
Clustered regularly interspaced short palindromic repeats (CRISPR) loci and their associated cas (CRISPR-associated) genes provide adaptive immunity against viruses (phages) and other mobile genetic elements in bacteria and archaea. While most of the early work has largely been dominated by examples of CRISPR-Cas systems directing the cleavage of phage or plasmid DNA, recent studies have revealed a more complex landscape where CRISPR-Cas loci might be involved in gene regulation. In this review, we summarize the role of these loci in the regulation of gene expression as well as the recent development of synthetic gene regulation using engineered CRISPR-Cas systems. PMID:24273648
-
Towards evolution-guided microbial engineering - tools development and applications
DEFF Research Database (Denmark)
Genee, Hans Jasper
is thedevelopment of highly robust biosensor-based synthetic selection systemsthat enable high-throughput functional interrogation of complexphenotypic libraries. Using the model organism Escherichia coli as a host, Ideploy these systems to i) perform metagenome wide sequenceindependentidentification of novel...... for microbial engineering anddemonstrates direct applications to gene discovery, protein engineering andcell factory development....
-
Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong
2015-01-01
Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.
-
Robustness Analyses of Timber Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Hald, Frederik
2013-01-01
The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many mo...... with respect to robustness of timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many...... modern building codes consider the need for the robustness of structures and provide strategies and methods to obtain robustness. Therefore, a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues...
-
Synthetic Aperture Sequential Beamforming
DEFF Research Database (Denmark)
Kortbek, Jacob; Jensen, Jørgen Arendt; Gammelmark, Kim Løkke
2008-01-01
A synthetic aperture focusing (SAF) technique denoted Synthetic Aperture Sequential Beamforming (SASB) suitable for 2D and 3D imaging is presented. The technique differ from prior art of SAF in the sense that SAF is performed on pre-beamformed data contrary to channel data. The objective is to im......A synthetic aperture focusing (SAF) technique denoted Synthetic Aperture Sequential Beamforming (SASB) suitable for 2D and 3D imaging is presented. The technique differ from prior art of SAF in the sense that SAF is performed on pre-beamformed data contrary to channel data. The objective...... is to improve and obtain a more range independent lateral resolution compared to conventional dynamic receive focusing (DRF) without compromising frame rate. SASB is a two-stage procedure using two separate beamformers. First a set of Bmode image lines using a single focal point in both transmit and receive...... is stored. The second stage applies the focused image lines from the first stage as input data. The SASB method has been investigated using simulations in Field II and by off-line processing of data acquired with a commercial scanner. The performance of SASB with a static image object is compared with DRF...
-
Towards a synthetic chloroplast.
Directory of Open Access Journals (Sweden)
Christina M Agapakis
2011-04-01
Full Text Available The evolution of eukaryotic cells is widely agreed to have proceeded through a series of endosymbiotic events between larger cells and proteobacteria or cyanobacteria, leading to the formation of mitochondria or chloroplasts, respectively. Engineered endosymbiotic relationships between different species of cells are a valuable tool for synthetic biology, where engineered pathways based on two species could take advantage of the unique abilities of each mutualistic partner.We explored the possibility of using the photosynthetic bacterium Synechococcus elongatus PCC 7942 as a platform for studying evolutionary dynamics and for designing two-species synthetic biological systems. We observed that the cyanobacteria were relatively harmless to eukaryotic host cells compared to Escherichia coli when injected into the embryos of zebrafish, Danio rerio, or taken up by mammalian macrophages. In addition, when engineered with invasin from Yersinia pestis and listeriolysin O from Listeria monocytogenes, S. elongatus was able to invade cultured mammalian cells and divide inside macrophages.Our results show that it is possible to engineer photosynthetic bacteria to invade the cytoplasm of mammalian cells for further engineering and applications in synthetic biology. Engineered invasive but non-pathogenic or immunogenic photosynthetic bacteria have great potential as synthetic biological devices.
-
Yu, Zheng; Krause, Sascha M B; Beck, David A C; Chistoserdova, Ludmila
2016-01-01
In this perspective article, we question how well model organisms, the ones that are easy to cultivate in the laboratory and that show robust growth and biomass accumulation, reflect the dynamics and interactions of microbial communities observed in nature. Today's -omics toolbox allows assessing the genomic potential of microbes in natural environments in a high-throughput fashion and at a strain-level resolution. However, understanding of the details of microbial activities and of the mechanistic bases of community function still requires experimental validation in simplified and fully controlled systems such as synthetic communities. We have studied methane utilization in Lake Washington sediment for a few decades and have identified a number of species genetically equipped for this activity. We have also identified co-occurring satellite species that appear to form functional communities together with the methanotrophs. Here, we compare experimental findings from manipulation of natural communities involved in metabolism of methane in this niche with findings from manipulation of synthetic communities assembled in the laboratory of species originating from the same study site, from very simple (two-species) to rather complex (50-species) synthetic communities. We observe some common trends in community dynamics between the two types of communities, toward representation of specific functional guilds. However, we also identify strong discrepancies between the dominant methane oxidizers in synthetic communities compared to natural communities, under similar incubation conditions. These findings highlight the challenges that exist in using the synthetic community approach to modeling dynamics and species interactions in natural communities.
-
Siade, Adam J.; Hall, Joel; Karelse, Robert N.
2017-11-01
Regional groundwater flow models play an important role in decision making regarding water resources; however, the uncertainty embedded in model parameters and model assumptions can significantly hinder the reliability of model predictions. One way to reduce this uncertainty is to collect new observation data from the field. However, determining where and when to obtain such data is not straightforward. There exist a number of data-worth and experimental design strategies developed for this purpose. However, these studies often ignore issues related to real-world groundwater models such as computational expense, existing observation data, high-parameter dimension, etc. In this study, we propose a methodology, based on existing methods and software, to efficiently conduct such analyses for large-scale, complex regional groundwater flow systems for which there is a wealth of available observation data. The method utilizes the well-established d-optimality criterion, and the minimax criterion for robust sampling strategies. The so-called Null-Space Monte Carlo method is used to reduce the computational burden associated with uncertainty quantification. And, a heuristic methodology, based on the concept of the greedy algorithm, is proposed for developing robust designs with subsets of the posterior parameter samples. The proposed methodology is tested on a synthetic regional groundwater model, and subsequently applied to an existing, complex, regional groundwater system in the Perth region of Western Australia. The results indicate that robust designs can be obtained efficiently, within reasonable computational resources, for making regional decisions regarding groundwater level sampling.
-
Synthetic Biology: Advancing Biological Frontiers by Building Synthetic Systems
Chen, Yvonne Yu-Hsuan; Galloway, Kate E; Smolke, Christina D
2012-01-01
Advances in synthetic biology are contributing to diverse research areas, from basic biology to biomanufacturing and disease therapy. We discuss the theoretical foundation, applications, and potential of this emerging field.
-
Synthetic biology: an emerging engineering discipline.
Cheng, Allen A; Lu, Timothy K
2012-01-01
Over the past decade, synthetic biology has emerged as an engineering discipline for biological systems. Compared with other substrates, biology poses a unique set of engineering challenges resulting from an incomplete understanding of natural biological systems and tools for manipulating them. To address these challenges, synthetic biology is advancing from developing proof-of-concept designs to focusing on core platforms for rational and high-throughput biological engineering. These platforms span the entire biological design cycle, including DNA construction, parts libraries, computational design tools, and interfaces for manipulating and probing synthetic circuits. The development of these enabling technologies requires an engineering mindset to be applied to biology, with an emphasis on generalizable techniques in addition to application-specific designs. This review aims to discuss the progress and challenges in synthetic biology and to illustrate areas where synthetic biology may impact biomedical engineering and human health.
-
Synthetic peptides for antibody production
N.D. Zegers (Netty)
1995-01-01
textabstractSynthetic peptides are useful tools for the generation of antibodies. The use of antibodies as specific reagents in inununochemical assays is widely applied. In this chapter, the application of synthetic peptides for the generation of antibodies is described. The different steps
-
Synthetic LDL as targeted drug delivery vehicle
Forte, Trudy M [Berkeley, CA; Nikanjam, Mina [Richmond, CA
2012-08-28
The present invention provides a synthetic LDL nanoparticle comprising a lipid moiety and a synthetic chimeric peptide so as to be capable of binding the LDL receptor. The synthetic LDL nanoparticle of the present invention is capable of incorporating and targeting therapeutics to cells expressing the LDL receptor for diseases associated with the expression of the LDL receptor such as central nervous system diseases. The invention further provides methods of using such synthetic LDL nanoparticles.
-
Programming languages for synthetic biology.
Umesh, P; Naveen, F; Rao, Chanchala Uma Maheswara; Nair, Achuthsankar S
2010-12-01
In the backdrop of accelerated efforts for creating synthetic organisms, the nature and scope of an ideal programming language for scripting synthetic organism in-silico has been receiving increasing attention. A few programming languages for synthetic biology capable of defining, constructing, networking, editing and delivering genome scale models of cellular processes have been recently attempted. All these represent important points in a spectrum of possibilities. This paper introduces Kera, a state of the art programming language for synthetic biology which is arguably ahead of similar languages or tools such as GEC, Antimony and GenoCAD. Kera is a full-fledged object oriented programming language which is tempered by biopart rule library named Samhita which captures the knowledge regarding the interaction of genome components and catalytic molecules. Prominent feature of the language are demonstrated through a toy example and the road map for the future development of Kera is also presented.
-
Synthetic biology as red herring.
Preston, Beth
2013-12-01
It has become commonplace to say that with the advent of technologies like synthetic biology the line between artifacts and living organisms, policed by metaphysicians since antiquity, is beginning to blur. But that line began to blur 10,000 years ago when plants and animals were first domesticated; and has been thoroughly blurred at least since agriculture became the dominant human subsistence pattern many millennia ago. Synthetic biology is ultimately only a late and unexceptional offshoot of this prehistoric development. From this perspective, then, synthetic biology is a red herring, distracting us from more thorough philosophical consideration of the most truly revolutionary human practice-agriculture. In the first section of this paper I will make this case with regard to ontology, arguing that synthetic biology crosses no ontological lines that were not crossed already in the Neolithic. In the second section I will construct a parallel case with regard to cognition, arguing that synthetic biology as biological engineering represents no cognitive advance over what was required for domestication and the new agricultural subsistence pattern it grounds. In the final section I will make the case with regard to human existence, arguing that synthetic biology, even if wildly successful, is not in a position to cause significant existential change in what it is to be human over and above the massive existential change caused by the transition to agriculture. I conclude that a longer historical perspective casts new light on some important issues in philosophy of technology and environmental philosophy. Copyright © 2013 Elsevier Ltd. All rights reserved.
-
US Competitiveness in Synthetic Biology.
Gronvall, Gigi Kwik
2015-01-01
Synthetic biology is an emerging technical field that aims to make biology easier to engineer; the field has applications in strategically important sectors for the US economy. While the United States currently leads in synthetic biology R&D, other nations are heavily investing in order to boost their economies, which will inevitably diminish the US leadership position. This outcome is not entirely negative--additional investments will expand markets--but it is critical that the US government take steps to remain competitive: There are applications from which the US population and economy may benefit; there are specific applications with importance for national defense; and US technical leadership will ensure that US experts have a leading role in synthetic biology governance, regulation, and oversight. Measures to increase competitiveness in S&T generally are broadly applicable for synthetic biology and should be pursued. However, the US government will also need to take action on fundamental issues that will affect the field's development, such as countering anti-GMO (genetically modified organism) sentiments and anti-GMO legislation. The United States should maintain its regulatory approach so that it is the product that is regulated, not the method used to create a product. At the same time, the United States needs to ensure that the regulatory framework is updated so that synthetic biology products do not fall into regulatory gaps. Finally, the United States needs to pay close attention to how synthetic biology applications may be governed internationally, such as through the Nagoya Protocol of the Convention on Biological Diversity, so that beneficial applications may be realized.
-
Synthetic Biology: Mapping the Scientific Landscape
Oldham, Paul; Hall, Stephen; Burton, Geoff
2012-01-01
This article uses data from Thomson Reuters Web of Science to map and analyse the scientific landscape for synthetic biology. The article draws on recent advances in data visualisation and analytics with the aim of informing upcoming international policy debates on the governance of synthetic biology by the Subsidiary Body on Scientific, Technical and Technological Advice (SBSTTA) of the United Nations Convention on Biological Diversity. We use mapping techniques to identify how synthetic biology can best be understood and the range of institutions, researchers and funding agencies involved. Debates under the Convention are likely to focus on a possible moratorium on the field release of synthetic organisms, cells or genomes. Based on the empirical evidence we propose that guidance could be provided to funding agencies to respect the letter and spirit of the Convention on Biological Diversity in making research investments. Building on the recommendations of the United States Presidential Commission for the Study of Bioethical Issues we demonstrate that it is possible to promote independent and transparent monitoring of developments in synthetic biology using modern information tools. In particular, public and policy understanding and engagement with synthetic biology can be enhanced through the use of online interactive tools. As a step forward in this process we make existing data on the scientific literature on synthetic biology available in an online interactive workbook so that researchers, policy makers and civil society can explore the data and draw conclusions for themselves. PMID:22539946
-
Impact of synthetic biology and metabolic engineering on industrial production of fine chemicals.
Jullesson, David; David, Florian; Pfleger, Brian; Nielsen, Jens
2015-11-15
Industrial bio-processes for fine chemical production are increasingly relying on cell factories developed through metabolic engineering and synthetic biology. The use of high throughput techniques and automation for the design of cell factories, and especially platform strains, has played an important role in the transition from laboratory research to industrial production. Model organisms such as Saccharomyces cerevisiae and Escherichia coli remain widely used host strains for industrial production due to their robust and desirable traits. This review describes some of the bio-based fine chemicals that have reached the market, key metabolic engineering tools that have allowed this to happen and some of the companies that are currently utilizing these technologies for developing industrial production processes. Copyright © 2015 Elsevier Inc. All rights reserved.
-
Good genes, complementary genes and human mate preferences.
Roberts, S Craig; Little, Anthony C
2008-09-01
The past decade has witnessed a rapidly growing interest in the biological basis of human mate choice. Here we review recent studies that demonstrate preferences for traits which might reveal genetic quality to prospective mates, with potential but still largely unknown influence on offspring fitness. These include studies assessing visual, olfactory and auditory preferences for potential good-gene indicator traits, such as dominance or bilateral symmetry. Individual differences in these robust preferences mainly arise through within and between individual variation in condition and reproductive status. Another set of studies have revealed preferences for traits indicating complementary genes, focussing on discrimination of dissimilarity at genes in the major histocompatibility complex (MHC). As in animal studies, we are only just beginning to understand how preferences for specific traits vary and inter-relate, how consideration of good and compatible genes can lead to substantial variability in individual mate choice decisions and how preferences expressed in one sensory modality may reflect those in another. Humans may be an ideal model species in which to explore these interesting complexities.
-
International Nuclear Information System (INIS)
Wu Dianxing; Ye Qingfu; Wang Zhonghua; Xia Yingwu
2004-01-01
The effects of gamma irradiation on the transgenic rice containing a synthetic cry1Ab gene from Bacillus thuringiensis were investigated. There was almost no difference in the content of the major nutritional components, i.e. crude protein, crude lipid, eight essential amino acids and total ash between the irradiated grains and the non-irradiated transgenic rice. However, the amounts of Cry1Ab protein and apparent amylose in the irradiated transgenic rice were reduced significantly by the doses higher than 200 Gy. In vivo observation showed that Cry1Ab protein contents also decreased in the fresh leaf tissues of survival seedlings after irradiation with 200 Gy or higher doses and showed inhibition of seedling growth. The results indicate that gamma irradiation might improve the quality of transgenic rice due to removal of the toxic Cry1Ab protein
-
Synthetic peptides for antibody production
Zegers, N.D.
1995-01-01
Synthetic peptides are useful tools for the generation of antibodies. The use of antibodies as specific reagents in inununochemical assays is widely applied. In this chapter, the application of synthetic peptides for the generation of antibodies is described. The different steps that lead to the
-
The Ethics of Synthetic Biology
DEFF Research Database (Denmark)
Christiansen, Andreas
The dissertation analyses and discusses a number of ethical issues that have been raised in connection with the development of synthetic biology. Synthetic biology is a set of new techniques for DNA-level design and construction of living beings with useful properties. The dissertation especially...
-
Differential Gene Expression and Aging
Directory of Open Access Journals (Sweden)
Laurent Seroude
2002-01-01
Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.
-
Content metamorphosis in synthetic holography
International Nuclear Information System (INIS)
Desbiens, Jacques
2013-01-01
A synthetic hologram is an optical system made of hundreds of images amalgamated in a structure of holographic cells. Each of these images represents a point of view on a three-dimensional space which makes us consider synthetic holography as a multiple points of view perspective system. In the composition of a computer graphics scene for a synthetic hologram, the field of view of the holographic image can be divided into several viewing zones. We can attribute these divisions to any object or image feature independently and operate different transformations on image content. In computer generated holography, we tend to consider content variations as a continuous animation much like a short movie. However, by composing sequential variations of image features in relation with spatial divisions, we can build new narrative forms distinct from linear cinematographic narration. When observers move freely and change their viewing positions, they travel from one field of view division to another. In synthetic holography, metamorphoses of image content are within the observer's path. In all imaging Medias, the transformation of image features in synchronisation with the observer's position is a rare occurrence. However, this is a predominant characteristic of synthetic holography. This paper describes some of my experimental works in the development of metamorphic holographic images.
-
Veiga, Tânia; Gombert, Andreas K; Landes, Nils; Verhoeven, Maarten D; Kiel, Jan A K W; Krikken, Arjen M; Nijland, Jeroen G; Touw, Hesselien; Luttik, Marijke A H; van der Toorn, John C; Driessen, Arnold J M; Bovenberg, Roel A L; van den Berg, Marco A; van der Klei, Ida J; Pronk, Jack T; Daran, Jean-Marc
2012-07-01
Industrial production of semi-synthetic cephalosporins by Penicillium chrysogenum requires supplementation of the growth media with the side-chain precursor adipic acid. In glucose-limited chemostat cultures of P. chrysogenum, up to 88% of the consumed adipic acid was not recovered in cephalosporin-related products, but used as an additional carbon and energy source for growth. This low efficiency of side-chain precursor incorporation provides an economic incentive for studying and engineering the metabolism of adipic acid in P. chrysogenum. Chemostat-based transcriptome analysis in the presence and absence of adipic acid confirmed that adipic acid metabolism in this fungus occurs via β-oxidation. A set of 52 adipate-responsive genes included six putative genes for acyl-CoA oxidases and dehydrogenases, enzymes responsible for the first step of β-oxidation. Subcellular localization of the differentially expressed acyl-CoA oxidases and dehydrogenases revealed that the oxidases were exclusively targeted to peroxisomes, while the dehydrogenases were found either in peroxisomes or in mitochondria. Deletion of the genes encoding the peroxisomal acyl-CoA oxidase Pc20g01800 and the mitochondrial acyl-CoA dehydrogenase Pc20g07920 resulted in a 1.6- and 3.7-fold increase in the production of the semi-synthetic cephalosporin intermediate adipoyl-6-APA, respectively. The deletion strains also showed reduced adipate consumption compared to the reference strain, indicating that engineering of the first step of β-oxidation successfully redirected a larger fraction of adipic acid towards cephalosporin biosynthesis. Copyright © 2012 Elsevier Inc. All rights reserved.
-
DEFF Research Database (Denmark)
Sohoni, Sujata Vijay; Fazio, Alessandro; Workman, Christopher
2014-01-01
The objective of this study was the application of the synthetic promoter library (SPL) technology for modulation of actinorhodin production in Streptomyces coelicolor A3(2). The SPL technology was used to optimize the expression of a pathway specific positive transcriptional regulator Actll orf4...... constitutive promoter. ScoSPL20 demonstrated exceptional productivity despite having a comparatively weak expression from the promoter. Interestingly, the ScoSPL20 promoter was activated at a much earlier stage of growth compared to the wild type, demonstrating the advantage of fine-tuning and temporal tuning......, which activates the transcription of the S. coelicolor actinorhodin biosynthetic gene cluster. The native actll orf4 promoter was replaced with synthetic promoters, generating a S. coelicolor library with a broad range of expression levels of actll orf4. The resulting library was screened based...
-
International Conference on Robust Statistics
Filzmoser, Peter; Gather, Ursula; Rousseeuw, Peter
2003-01-01
Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.
-
DEFF Research Database (Denmark)
Gorm Hansen, Birgitte
their core i nterests, 2) developing a selfsupply of industry interests by becoming entrepreneurs and thus creating their own compliant industry partner and 3) balancing resources within a larger collective of researchers, thus countering changes in the influx of funding caused by shifts in political...... knowledge", Danish research policy seems to have helped develop politically and economically "robust scientists". Scientific robustness is acquired by way of three strategies: 1) tasting and discriminating between resources so as to avoid funding that erodes academic profiles and push scientists away from...
-
Benedito, V.A.; Visser, P.B.; Angenent, G.C.; Krens, F.A.
2004-01-01
Virus-induced gene silencing (VIGS) has been shown to be of great potential in plant reverse genetics. Advantages of VIGS over other approaches, such as T-DNA or transposon tagging, include the circumvention of plant transformation, methodological simplicity and robustness, and speedy results. These
-
Multiply-Imputed Synthetic Data: Advice to the Imputer
Directory of Open Access Journals (Sweden)
Loong Bronwyn
2017-12-01
Full Text Available Several statistical agencies have started to use multiply-imputed synthetic microdata to create public-use data in major surveys. The purpose of doing this is to protect the confidentiality of respondents’ identities and sensitive attributes, while allowing standard complete-data analyses of microdata. A key challenge, faced by advocates of synthetic data, is demonstrating that valid statistical inferences can be obtained from such synthetic data for non-confidential questions. Large discrepancies between observed-data and synthetic-data analytic results for such questions may arise because of uncongeniality; that is, differences in the types of inputs available to the imputer, who has access to the actual data, and to the analyst, who has access only to the synthetic data. Here, we discuss a simple, but possibly canonical, example of uncongeniality when using multiple imputation to create synthetic data, which specifically addresses the choices made by the imputer. An initial, unanticipated but not surprising, conclusion is that non-confidential design information used to impute synthetic data should be released with the confidential synthetic data to allow users of synthetic data to avoid possible grossly conservative inferences.
-
Akbari, Omar S.; Chen, Chun-Hong; Marshall, John M.; Huang, Haixia; Antoshechkin, Igor; Hay, Bruce A.
2013-01-01
Insects act as vectors for diseases of plants, animals and humans. Replacement of wild insect populations with genetically modified individuals unable to transmit disease provides a potentially self-perpetuating method of disease prevention. Population replacement requires a gene drive mechanism in order to spread linked genes mediating disease refractoriness through wild populations. We previously reported the creation of synthetic Medea selfish genetic elements able to drive population replacement in Drosophila. These elements use microRNA-mediated silencing of myd88, a maternally expressed gene required for embryonic dorso-ventral pattern formation, coupled with early zygotic expression of a rescuing transgene, to bring about gene drive. Medea elements that work through additional mechanisms are needed in order to be able to carry out cycles of population replacement and/or remove existing transgenes from the population, using second-generation elements that spread while driving first-generation elements out of the population. Here we report the synthesis and population genetic behavior of two new synthetic Medea elements that drive population replacement through manipulation of signaling pathways involved in cellular blastoderm formation or Notch signaling, demonstrating that in Drosophila Medea elements can be generated through manipulation of diverse signaling pathways. We also describe the mRNA and small RNA changes in ovaries and early embryos associated from Medea-bearing females. Finally, we use modeling to illustrate how Medea elements carrying genes that result in diapause-dependent female lethality could be used to bring about population suppression. PMID:23654248
-
Is synthetic biology mechanical biology?
Holm, Sune
2015-12-01
A widespread and influential characterization of synthetic biology emphasizes that synthetic biology is the application of engineering principles to living systems. Furthermore, there is a strong tendency to express the engineering approach to organisms in terms of what seems to be an ontological claim: organisms are machines. In the paper I investigate the ontological and heuristic significance of the machine analogy in synthetic biology. I argue that the use of the machine analogy and the aim of producing rationally designed organisms does not necessarily imply a commitment to mechanical biology. The ideal of applying engineering principles to biology is best understood as expressing recognition of the machine-unlikeness of natural organisms and the limits of human cognition. The paper suggests an interpretation of the identification of organisms with machines in synthetic biology according to which it expresses a strategy for representing, understanding, and constructing living systems that are more machine-like than natural organisms.
-
Synthetic cannabis and acute ischemic stroke.
Bernson-Leung, Miya E; Leung, Lester Y; Kumar, Sandeep
2014-01-01
An association between marijuana use and stroke has been previously reported. However, the health risks of newer synthetic cannabinoid compounds are less well known. We describe 2 cases that introduce a previously unreported association between synthetic cannabis use and ischemic stroke in young adults. A 22-year-old woman presented with dysarthria, left hemiplegia, and left hemianesthesia within hours of first use of synthetic cannabis. She was healthy and without identified stroke risk factors other than oral contraceptive use and a patent foramen ovale without venous thromboses. A 26-year-old woman presented with nonfluent aphasia, left facial droop, and left hemianesthesia approximately 12 hours after first use of synthetic cannabis. Her other stroke risk factors included migraine with aura, oral contraceptive use, smoking, and a family history of superficial thrombophlebitis. Both women were found to have acute, large-territory infarctions of the right middle cerebral artery. Our 2 cases had risk factors for ischemic stroke but were otherwise young and healthy and the onset of their deficits occurred within hours after first-time exposure to synthetic cannabis. Synthetic cannabis use is an important consideration in the investigation of stroke in young adults. Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.
-
Robust Trust in Expert Testimony
Directory of Open Access Journals (Sweden)
Christian Dahlman
2015-05-01
Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.
-
Directory of Open Access Journals (Sweden)
Stinus Lindgreen
2014-10-01
Full Text Available Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of new technologies for characterizing transcriptome outputs, notably RNA-seq, are improving noncoding RNA identification and expression quantification. However, a major challenge is to robustly distinguish functional outputs from transcriptional noise. To establish whether annotation of existing transcriptome data has effectively captured all functional outputs, we analysed over 400 publicly available RNA-seq datasets spanning 37 different Archaea and Bacteria. Using comparative tools, we identify close to a thousand highly-expressed candidate noncoding RNAs. However, our analyses reveal that capacity to identify noncoding RNA outputs is strongly dependent on phylogenetic sampling. Surprisingly, and in stark contrast to protein-coding genes, the phylogenetic window for effective use of comparative methods is perversely narrow: aggregating public datasets only produced one phylogenetic cluster where these tools could be used to robustly separate unannotated noncoding RNAs from a null hypothesis of transcriptional noise. Our results show that for the full potential of transcriptomics data to be realized, a change in experimental design is paramount: effective transcriptomics requires phylogeny-aware sampling.
-
Non-electrostatic complexes with DNA: towards novel synthetic gene delivery systems.
Soto, J; Bessodes, M; Pitard, B; Mailhe, P; Scherman, D; Byk, G
2000-05-01
We have developed new DNA complexing amphiphile based on Hoechst 33258 interaction with DNA grooves. The synthesis and physicochemical characterisation of lipid/DNA complexes, as compared to that of classical lipopolyamine for gene delivery, are described and discussed.
-
Robustness Analysis of Timber Truss Structure
DEFF Research Database (Denmark)
Rajčić, Vlatka; Čizmar, Dean; Kirkegaard, Poul Henning
2010-01-01
The present paper discusses robustness of structures in general and the robustness requirements given in the codes. Robustness of timber structures is also an issues as this is closely related to Working group 3 (Robustness of systems) of the COST E55 project. Finally, an example of a robustness...... evaluation of a widespan timber truss structure is presented. This structure was built few years ago near Zagreb and has a span of 45m. Reliability analysis of the main members and the system is conducted and based on this a robustness analysis is preformed....
-
[Melatonin, synthetic analogs, and the sleep/wake rhythm].
Escames, G; Acuña-Castroviejo, D
Melatonin, a widespread hormone in the animal kingdom, is produced by several organs and tissues besides the pineal gland. Whilst extrapineal melatonin behaves as a cytoprotective molecule, the pineal produces the hormone in a rhythmic manner. The discovery of melatonin in 1958, and the characterization of its synthesis somewhat later, let to the description of its photoperiodic regulation and its relationship with the biological rhythms such as the sleep/wake rhythm. The suprachiasmatic nuclei are the anatomical seat of the biological clock, represented by the clock genes, which code for the period and frequency of the rhythms. The photoperiod synchronizes the activity of the auprachiasmatic biological clock, which in turn induces the melatonin's rhythm. The rhythm of melatonin, peaking at 2-3 am, acts as an endogenous synchronizer that translates the environmental photoperiodic signal in chemical information for the cells. The sleep/wake cycle is a typical biological rhythm synchronized by melatonin, and the sleep/wake cycle alterations of chronobiological origin, are very sensitive to melatonin treatment. Taking advantage of the chronobiotic and antidepressive properties of melatonin, a series of synthetic analogs of this hormone, with high interest in insomnia, are now available. Melatonin is a highly effective chronobiotic in the treatment of chronobiological alterations of the sleep/wake cycle. From a pharmacokinetic point of view, the synthetic drugs derived from melatonin are interesting tools in the therapy of these alterations.
-
A TAD further: exogenous control of gene activation.
Mapp, Anna K; Ansari, Aseem Z
2007-01-23
Designer molecules that can be used to impose exogenous control on gene transcription, artificial transcription factors (ATFs), are highly desirable as mechanistic probes of gene regulation, as potential therapeutic agents, and as components of cell-based devices. Recently, several advances have been made in the design of ATFs that activate gene transcription (activator ATFs), including reports of small-molecule-based systems and ATFs that exhibit potent activity. However, the many open mechanistic questions about transcriptional activators, in particular, the structure and function of the transcriptional activation domain (TAD), have hindered rapid development of synthetic ATFs. A compelling need thus exists for chemical tools and insights toward a more detailed portrait of the dynamic process of gene activation.
-
Qualitative Robustness in Estimation
Directory of Open Access Journals (Sweden)
Mohammed Nasser
2012-07-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif";} Qualitative robustness, influence function, and breakdown point are three main concepts to judge an estimator from the viewpoint of robust estimation. It is important as well as interesting to study relation among them. This article attempts to present the concept of qualitative robustness as forwarded by first proponents and its later development. It illustrates intricacies of qualitative robustness and its relation with consistency, and also tries to remove commonly believed misunderstandings about relation between influence function and qualitative robustness citing some examples from literature and providing a new counter-example. At the end it places a useful finite and a simulated version of qualitative robustness index (QRI. In order to assess the performance of the proposed measures, we have compared fifteen estimators of correlation coefficient using simulated as well as real data sets.
-
Saavedra, Lucila; Minahk, Carlos; de Ruiz Holgado, Aída P.; Sesma, Fernando
2004-01-01
The enterocin CRL35 biosynthetic gene cluster was cloned and sequenced. The sequence was revealed to be highly identical to that of the mundticin KS gene cluster (S. Kawamoto, J. Shima, R. Sato, T. Eguchi, S. Ohmomo, J. Shibato, N. Horikoshi, K. Takeshita, and T. Sameshima, Appl. Environ. Microbiol. 68:3830-3840, 2002). Short synthetic peptides were designed based on the bacteriocin sequence and were evaluated in antimicrobial competitive assays. The peptide KYYGNGVSCNKKGCS produced an enhancement of enterocin CRL35 antimicrobial activity in a buffer system. PMID:15215149
-
Sriboonchitta, Songsak; Huynh, Van-Nam
2017-01-01
This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
-
Imaging with Synthetic Aperture Radar
Massonnet, Didier
2008-01-01
Describing a field that has been transformed by the recent availability of data from a new generation of space and airborne systems, the authors offer a synthetic geometrical approach to the description of synthetic aperture radar, one that addresses physicists, radar specialists, as well as experts in image processing.
-
Bishop , Matt; Elliott , Chip
2011-01-01
Part 2: WISE 7; International audience; Robust programming lies at the heart of the type of coding called “secure programming”. Yet it is rarely taught in academia. More commonly, the focus is on how to avoid creating well-known vulnerabilities. While important, that misses the point: a well-structured, robust program should anticipate where problems might arise and compensate for them. This paper discusses one view of robust programming and gives an example of how it may be taught.
-
DEFF Research Database (Denmark)
Kemmler, S.; Eifler, Tobias; Bertsche, B.
2015-01-01
products are and vice versa. For a comprehensive understanding and to use existing synergies between both domains, this paper discusses the basic principles of Reliability- and Robust Design theory. The development of a comprehensive model will enable an integrated consideration of both domains...
-
Inferring Gene Regulatory Networks Using Conditional Regulation Pattern to Guide Candidate Genes.
Directory of Open Access Journals (Sweden)
Fei Xiao
Full Text Available Combining path consistency (PC algorithms with conditional mutual information (CMI are widely used in reconstruction of gene regulatory networks. CMI has many advantages over Pearson correlation coefficient in measuring non-linear dependence to infer gene regulatory networks. It can also discriminate the direct regulations from indirect ones. However, it is still a challenge to select the conditional genes in an optimal way, which affects the performance and computation complexity of the PC algorithm. In this study, we develop a novel conditional mutual information-based algorithm, namely RPNI (Regulation Pattern based Network Inference, to infer gene regulatory networks. For conditional gene selection, we define the co-regulation pattern, indirect-regulation pattern and mixture-regulation pattern as three candidate patterns to guide the selection of candidate genes. To demonstrate the potential of our algorithm, we apply it to gene expression data from DREAM challenge. Experimental results show that RPNI outperforms existing conditional mutual information-based methods in both accuracy and time complexity for different sizes of gene samples. Furthermore, the robustness of our algorithm is demonstrated by noisy interference analysis using different types of noise.
-
A modular positive feedback-based gene amplifier
Directory of Open Access Journals (Sweden)
Bhalerao Kaustubh D
2010-02-01
Full Text Available Abstract Background Positive feedback is a common mechanism used in the regulation of many gene circuits as it can amplify the response to inducers and also generate binary outputs and hysteresis. In the context of electrical circuit design, positive feedback is often considered in the design of amplifiers. Similar approaches, therefore, may be used for the design of amplifiers in synthetic gene circuits with applications, for example, in cell-based sensors. Results We developed a modular positive feedback circuit that can function as a genetic signal amplifier, heightening the sensitivity to inducer signals as well as increasing maximum expression levels without the need for an external cofactor. The design utilizes a constitutively active, autoinducer-independent variant of the quorum-sensing regulator LuxR. We experimentally tested the ability of the positive feedback module to separately amplify the output of a one-component tetracycline sensor and a two-component aspartate sensor. In each case, the positive feedback module amplified the response to the respective inducers, both with regards to the dynamic range and sensitivity. Conclusions The advantage of our design is that the actual feedback mechanism depends only on a single gene and does not require any other modulation. Furthermore, this circuit can amplify any transcriptional signal, not just one encoded within the circuit or tuned by an external inducer. As our design is modular, it can potentially be used as a component in the design of more complex synthetic gene circuits.
-
[Treatment approaches for synthetic drug addiction].
Kobayashi, Ohji
2015-09-01
In Japan, synthetic drugs have emerged since late 2000s, and cases of emergency visits and fatal traffic accidents due to acute intoxication have rapidly increased. The synthetic drugs gained popularity mainly because they were cheap and thought to be "legal". The Japanese government restricted not only production and distribution, but also its possession and use in April 2014. As the synthetic drug dependent patients have better social profiles compared to methamphetamine abusers, this legal sanction may have triggered the decrease in the number of synthetic drug dependent patient visits observed at Kanagawa Psychiatric Center since July 2014. Treatment of the synthetic drug dependent patients should begin with empathic inquiry into the motives and positive psychological effects of the drug use. In the maintenance phase, training patients to trust others and express their hidden negative emotions through verbal communications is essential. The recovery is a process of understanding the relationship between psychological isolation and drug abuse, and gaining trust in others to cope with negative emotions that the patients inevitably would face in their subsequent lives.
-
[Synthetic biology and rearrangements of microbial genetic material].
Liang, Quan-Feng; Wang, Qian; Qi, Qing-Sheng
2011-10-01
As an emerging discipline, synthetic biology has shown great scientific values and application prospects. Although there have been many reviews of various aspects on synthetic biology over the last years, this article, for the first time, attempted to discuss the relationship and difference between microbial genetics and synthetic biology. We summarized the recent development of synthetic biology in rearranging microbial genetic materials, including synthesis, design and reduction of genetic materials, standardization of genetic parts and modularization of genetic circuits. The relationship between synthetic biology and microbial genetic engineering was also discussed in the paper.
-
In-silico human genomics with GeneCards
Directory of Open Access Journals (Sweden)
Stelzer Gil
2011-10-01
Full Text Available Abstract Since 1998, the bioinformatics, systems biology, genomics and medical communities have enjoyed a synergistic relationship with the GeneCards database of human genes (http://www.genecards.org. This human gene compendium was created to help to introduce order into the increasing chaos of information flow. As a consequence of viewing details and deep links related to specific genes, users have often requested enhanced capabilities, such that, over time, GeneCards has blossomed into a suite of tools (including GeneDecks, GeneALaCart, GeneLoc, GeneNote and GeneAnnot for a variety of analyses of both single human genes and sets thereof. In this paper, we focus on inhouse and external research activities which have been enabled, enhanced, complemented and, in some cases, motivated by GeneCards. In turn, such interactions have often inspired and propelled improvements in GeneCards. We describe here the evolution and architecture of this project, including examples of synergistic applications in diverse areas such as synthetic lethality in cancer, the annotation of genetic variations in disease, omics integration in a systems biology approach to kidney disease, and bioinformatics tools.
-
Synthetic Biology and the Translational Imperative.
Heidari Feidt, Raheleh; Ienca, Marcello; Elger, Bernice Simone; Folcher, Marc
2017-12-18
Advances at the interface between the biological sciences and engineering are giving rise to emerging research fields such as synthetic biology. Harnessing the potential of synthetic biology requires timely and adequate translation into clinical practice. However, the translational research enterprise is currently facing fundamental obstacles that slow down the transition of scientific discoveries from the laboratory to the patient bedside. These obstacles including scarce financial resources and deficiency of organizational and logistic settings are widely discussed as primary impediments to translational research. In addition, a number of socio-ethical considerations inherent in translational research need to be addressed. As the translational capacity of synthetic biology is tightly linked to its social acceptance and ethical approval, ethical limitations may-together with financial and organizational problems-be co-determinants of suboptimal translation. Therefore, an early assessment of such limitations will contribute to proactively favor successful translation and prevent the promising potential of synthetic biology from remaining under-expressed. Through the discussion of two case-specific inventions in synthetic biology and their associated ethical implications, we illustrate the socio-ethical challenges ahead in the process of implementing synthetic biology into clinical practice. Since reducing the translational lag is essential for delivering the benefits of basic biomedical research to society at large and promoting global health, we advocate a moral obligation to accelerating translational research: the "translational imperative."
-
Kis, Mihaly; Burbridge, Emma; Brock, Ian W; Heggie, Laura; Dix, Philip J; Kavanagh, Tony A
2004-03-01
Native horseradish (Armoracia rusticana) peroxidase, HRP (EC 1.11.1.7), isoenzyme C is synthesized with N-terminal and C-terminal peptide extensions, believed to be associated with protein targeting. This study aimed to explore the specific functions of these extensions, and to generate transgenic plants with expression patterns suitable for exploring the role of peroxidase in plant development and defence. Transgenic Nicotiana tabacum (tobacco) plants expressing different versions of a synthetic horseradish peroxidase, HRP, isoenzyme C gene were constructed. The gene was engineered to include additional sequences coding for either the natural N-terminal or the C-terminal extension or both. These constructs were placed under the control of a constitutive promoter (CaMV-35S) or the tobacco RUBISCO-SSU light inducible promoter (SSU) and introduced into tobacco using Agrobacterium-mediated transformation. To study the effects of the N- and C-terminal extensions, the localization of recombinant peroxidase was determined using biochemical and molecular techniques. Transgenic tobacco plants can exhibit a ten-fold increase in peroxidase activity compared with wild-type tobacco levels, and the majority of this activity is located in the symplast. The N-terminal extension is essential for the production of high levels of recombinant protein, while the C-terminal extension has little effect. Differences in levels of enzyme activity and recombinant protein are reflected in transcript levels. There is no evidence to support either preferential secretion or vacuolar targeting of recombinant peroxidase in this heterologous expression system. This leads us to question the postulated targeting roles of these peptide extensions. The N-terminal extension is essential for high level expression and appears to influence transcript stability or translational efficiency. Plants have been generated with greatly elevated cytosolic peroxidase activity, and smaller increases in apoplastic