Sample records for robust synthetic genetic
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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
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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
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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.
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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
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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
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[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.
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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.
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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
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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
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Modularization of genetic elements promotes synthetic metabolic engineering.
Qi, Hao; Li, Bing-Zhi; Zhang, Wen-Qian; Liu, Duo; Yuan, Ying-Jin
2015-11-15
In the context of emerging synthetic biology, metabolic engineering is moving to the next stage powered by new technologies. Systematical modularization of genetic elements makes it more convenient to engineer biological systems for chemical production or other desired purposes. In the past few years, progresses were made in engineering metabolic pathway using synthetic biology tools. Here, we spotlighted the topic of implementation of modularized genetic elements in metabolic engineering. First, we overviewed the principle developed for modularizing genetic elements and then discussed how the genetic modules advanced metabolic engineering studies. Next, we picked up some milestones of engineered metabolic pathway achieved in the past few years. Last, we discussed the rapid raised synthetic biology field of "building a genome" and the potential in metabolic engineering. Copyright © 2015 Elsevier Inc. All rights reserved.
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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
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Engineering genetic circuit interactions within and between synthetic minimal cells
Adamala, Katarzyna P.; Martin-Alarcon, Daniel A.; Guthrie-Honea, Katriona R.; Boyden, Edward S.
2017-05-01
Genetic circuits and reaction cascades are of great importance for synthetic biology, biochemistry and bioengineering. An open question is how to maximize the modularity of their design to enable the integration of different reaction networks and to optimize their scalability and flexibility. One option is encapsulation within liposomes, which enables chemical reactions to proceed in well-isolated environments. Here we adapt liposome encapsulation to enable the modular, controlled compartmentalization of genetic circuits and cascades. We demonstrate that it is possible to engineer genetic circuit-containing synthetic minimal cells (synells) to contain multiple-part genetic cascades, and that these cascades can be controlled by external signals as well as inter-liposomal communication without crosstalk. We also show that liposomes that contain different cascades can be fused in a controlled way so that the products of incompatible reactions can be brought together. Synells thus enable a more modular creation of synthetic biology cascades, an essential step towards their ultimate programmability.
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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.
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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.
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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).
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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.
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Robust reactor power control system design by genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1998-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
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Robust reactor power control system design by genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1997-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
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Adaptive logical stochastic resonance in time-delayed synthetic genetic networks
Zhang, Lei; Zheng, Wenbin; Song, Aiguo
2018-04-01
In the paper, the concept of logical stochastic resonance is applied to implement logic operation and latch operation in time-delayed synthetic genetic networks derived from a bacteriophage λ. Clear logic operation and latch operation can be obtained when the network is tuned by modulated periodic force and time-delay. In contrast with the previous synthetic genetic networks based on logical stochastic resonance, the proposed system has two advantages. On one hand, adding modulated periodic force to the background noise can increase the length of the optimal noise plateau of obtaining desired logic response and make the system adapt to varying noise intensity. On the other hand, tuning time-delay can extend the optimal noise plateau to larger range. The result provides possible help for designing new genetic regulatory networks paradigm based on logical stochastic resonance.
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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.
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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.
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Wagner, James M; Alper, Hal S
2016-04-01
Coupling the tools of synthetic biology with traditional molecular genetic techniques can enable the rapid prototyping and optimization of yeast strains. While the era of yeast synthetic biology began in the well-characterized model organism Saccharomyces cerevisiae, it is swiftly expanding to include non-conventional yeast production systems such as Hansenula polymorpha, Kluyveromyces lactis, Pichia pastoris, and Yarrowia lipolytica. These yeasts already have roles in the manufacture of vaccines, therapeutic proteins, food additives, and biorenewable chemicals, but recent synthetic biology advances have the potential to greatly expand and diversify their impact on biotechnology. In this review, we summarize the development of synthetic biological tools (including promoters and terminators) and enabling molecular genetics approaches that have been applied in these four promising alternative biomanufacturing platforms. An emphasis is placed on synthetic parts and genome editing tools. Finally, we discuss examples of synthetic tools developed in other organisms that can be adapted or optimized for these hosts in the near future. Copyright © 2015 Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Johan Soewanda
2007-01-01
Full Text Available This paper discusses the application of Robust Hybrid Genetic Algorithm to solve a flow-shop scheduling problem. The proposed algorithm attempted to reach minimum makespan. PT. FSCM Manufacturing Indonesia Plant 4's case was used as a test case to evaluate the performance of the proposed algorithm. The proposed algorithm was compared to Ant Colony, Genetic-Tabu, Hybrid Genetic Algorithm, and the company's algorithm. We found that Robust Hybrid Genetic produces statistically better result than the company's, but the same as Ant Colony, Genetic-Tabu, and Hybrid Genetic. In addition, Robust Hybrid Genetic Algorithm required less computational time than Hybrid Genetic Algorithm
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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
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Alternative Watson-Crick Synthetic Genetic Systems.
Benner, Steven A; Karalkar, Nilesh B; Hoshika, Shuichi; Laos, Roberto; Shaw, Ryan W; Matsuura, Mariko; Fajardo, Diego; Moussatche, Patricia
2016-11-01
In its "grand challenge" format in chemistry, "synthesis" as an activity sets out a goal that is substantially beyond current theoretical and technological capabilities. In pursuit of this goal, scientists are forced across uncharted territory, where they must answer unscripted questions and solve unscripted problems, creating new theories and new technologies in ways that would not be created by hypothesis-directed research. Thus, synthesis drives discovery and paradigm changes in ways that analysis cannot. Described here are the products that have arisen so far through the pursuit of one grand challenge in synthetic biology: Recreate the genetics, catalysis, evolution, and adaptation that we value in life, but using genetic and catalytic biopolymers different from those that have been delivered to us by natural history on Earth. The outcomes in technology include new diagnostic tools that have helped personalize the care of hundreds of thousands of patients worldwide. In science, the effort has generated a fundamentally different view of DNA, RNA, and how they work. Copyright © 2016 Cold Spring Harbor Laboratory Press; all rights reserved.
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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.
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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.
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Molecular analysis of genetic diversity in elite II synthetic hexaploid ...
African Journals Online (AJOL)
The present study was conducted to assess the genetic diversity of Elite-II synthetic hexaploid (SH) wheat by genome DNA fingerprinting as revealed by random amplified polymorphic DNA (RAPD) analysis. Ten decamer RAPD primers (OPG-1, OPG-2, OPG-3, OPG-4, OPG-5, OPA-3, OPA-4, OPA-5, OPA-8, and OPA-15) ...
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Genetic and Environmental Control of Neurodevelopmental Robustness in Drosophila.
Directory of Open Access Journals (Sweden)
David J Mellert
Full Text Available Interindividual differences in neuronal wiring may contribute to behavioral individuality and affect susceptibility to neurological disorders. To investigate the causes and potential consequences of wiring variation in Drosophila melanogaster, we focused on a hemilineage of ventral nerve cord interneurons that exhibits morphological variability. We find that late-born subclasses of the 12A hemilineage are highly sensitive to genetic and environmental variation. Neurons in the second thoracic segment are particularly variable with regard to two developmental decisions, whereas its segmental homologs are more robust. This variability "hotspot" depends on Ultrabithorax expression in the 12A neurons, indicating variability is cell-intrinsic and under genetic control. 12A development is more variable and sensitive to temperature in long-established laboratory strains than in strains recently derived from the wild. Strains with a high frequency of one of the 12A variants also showed a high frequency of animals with delayed spontaneous flight initiation, whereas other wing-related behaviors did not show such a correlation and were thus not overtly affected by 12A variation. These results show that neurodevelopmental robustness is variable and under genetic control in Drosophila and suggest that the fly may serve as a model for identifying conserved gene pathways that stabilize wiring in stressful developmental environments. Moreover, some neuronal lineages are variation hotspots and thus may be more amenable to evolutionary change.
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Directory of Open Access Journals (Sweden)
Dominik Müller
2017-03-01
Full Text Available Recurrent selection (RS has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents ( Np , but little is known about how Np affects genomic selection (GS in RS, especially the persistency of prediction accuracy (rg , g ^ and genetic gain. Synthetics were simulated by intermating Np= 2–32 parent lines from an ancestral population with short- or long-range linkage disequilibrium (LDA and subjected to multiple cycles of GS. We determined rg , g ^ and genetic gain across 30 cycles for different training set (TS sizes, marker densities, and generations of recombination before model training. Contributions to rg , g ^ and genetic gain from pedigree relationships, as well as from cosegregation and LDA between QTL and markers, were analyzed via four scenarios differing in (i the relatedness between TS and selection candidates and (ii whether selection was based on markers or pedigree records. Persistency of rg , g ^ was high for small Np , where predominantly cosegregation contributed to rg , g ^ , but also for large Np , where LDA replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing Np > 4, given long-range LDA in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to rg , g ^ for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size (NTS and higher marker density improved persistency of rg , g ^ and hence genetic gain, but additional recombinations could not increase genetic gain.
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Tomazou, Marios; Barahona, Mauricio; Polizzi, Karen M; Stan, Guy-Bart
2018-04-25
To perform well in biotechnology applications, synthetic genetic oscillators must be engineered to allow independent modulation of amplitude and period. This need is currently unmet. Here, we demonstrate computationally how two classic genetic oscillators, the dual-feedback oscillator and the repressilator, can be re-designed to provide independent control of amplitude and period and improve tunability-that is, a broad dynamic range of periods and amplitudes accessible through the input "dials." Our approach decouples frequency and amplitude modulation by incorporating an orthogonal "sink module" where the key molecular species are channeled for enzymatic degradation. This sink module maintains fast oscillation cycles while alleviating the translational coupling between the oscillator's transcription factors and output. We characterize the behavior of our re-designed oscillators over a broad range of physiologically reasonable parameters, explain why this facilitates broader function and control, and provide general design principles for building synthetic genetic oscillators that are more precisely controllable. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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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
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Müller, Dominik; Schopp, Pascal; Melchinger, Albrecht E
2017-03-10
Recurrent selection (RS) has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents [Formula: see text] but little is known about how [Formula: see text] affects genomic selection (GS) in RS, especially the persistency of prediction accuracy ([Formula: see text]) and genetic gain. Synthetics were simulated by intermating [Formula: see text]= 2-32 parent lines from an ancestral population with short- or long-range linkage disequilibrium ([Formula: see text]) and subjected to multiple cycles of GS. We determined [Formula: see text] and genetic gain across 30 cycles for different training set ( TS ) sizes, marker densities, and generations of recombination before model training. Contributions to [Formula: see text] and genetic gain from pedigree relationships, as well as from cosegregation and [Formula: see text] between QTL and markers, were analyzed via four scenarios differing in (i) the relatedness between TS and selection candidates and (ii) whether selection was based on markers or pedigree records. Persistency of [Formula: see text] was high for small [Formula: see text] where predominantly cosegregation contributed to [Formula: see text], but also for large [Formula: see text] where [Formula: see text] replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing [Formula: see text] > 4, given long-range LD A in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to [Formula: see text] for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size ([Formula: see text]) and higher marker density improved persistency of
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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.
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Bio-Inspired Microsystem for Robust Genetic Assay Recognition
Directory of Open Access Journals (Sweden)
Jaw-Chyng Lue
2008-01-01
Full Text Available A compact integrated system-on-chip (SoC architecture solution for robust, real-time, and on-site genetic analysis has been proposed. This microsystem solution is noise-tolerable and suitable for analyzing the weak fluorescence patterns from a PCR prepared dual-labeled DNA microchip assay. In the architecture, a preceding VLSI differential logarithm microchip is designed for effectively computing the logarithm of the normalized input fluorescence signals. A posterior VLSI artificial neural network (ANN processor chip is used for analyzing the processed signals from the differential logarithm stage. A single-channel logarithmic circuit was fabricated and characterized. A prototype ANN chip with unsupervised winner-take-all (WTA function was designed, fabricated, and tested. An ANN learning algorithm using a novel sigmoid-logarithmic transfer function based on the supervised backpropagation (BP algorithm is proposed for robustly recognizing low-intensity patterns. Our results show that the trained new ANN can recognize low-fluorescence patterns better than an ANN using the conventional sigmoid function.
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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.
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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.
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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
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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.
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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.
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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...
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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.
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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.
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Directory of Open Access Journals (Sweden)
Wing Kam Fung
2010-02-01
Full Text Available The case-control study is an important design for testing association between genetic markers and a disease. The Cochran-Armitage trend test (CATT is one of the most commonly used statistics for the analysis of case-control genetic association studies. The asymptotically optimal CATT can be used when the underlying genetic model (mode of inheritance is known. However, for most complex diseases, the underlying genetic models are unknown. Thus, tests robust to genetic model misspecification are preferable to the model-dependant CATT. Two robust tests, MAX3 and the genetic model selection (GMS, were recently proposed. Their asymptotic null distributions are often obtained by Monte-Carlo simulations, because they either have not been fully studied or involve multiple integrations. In this article, we study how components of each robust statistic are correlated, and find a linear dependence among the components. Using this new finding, we propose simple algorithms to calculate asymptotic null distributions for MAX3 and GMS, which greatly reduce the computing intensity. Furthermore, we have developed the R package Rassoc implementing the proposed algorithms to calculate the empirical and asymptotic p values for MAX3 and GMS as well as other commonly used tests in case-control association studies. For illustration, Rassoc is applied to the analysis of case-control data of 17 most significant SNPs reported in four genome-wide association studies.
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Robust PD Sway Control of a Lifted Load for a Crane Using a Genetic Algorithm
Kawada, Kazuo; Sogo, Hiroyuki; Yamamoto, Toru; Mada, Yasuhiro
PID control schemes still continue to be widely used for most industrial control systems. This is mainly because PID controllers have simple control structures, and are simple to maintain and tune. However, it is difficult to find a set of suitable control parameters in the case of time-varying and/or nonlinear systems. For such a problem, the robust controller has been proposed.Although it is important to choose the suitable nominal model in designing the robust controller, it is not usually easy.In this paper, a new robust PD controller design scheme is proposed, which utilizes a genetic algorithm.
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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.
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Genome complexity, robustness and genetic interactions in digital organisms
Lenski, Richard E.; Ofria, Charles; Collier, Travis C.; Adami, Christoph
1999-08-01
Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined `metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.
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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.
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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
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Loads Bias Genetic and Signaling Switches in Synthetic and Natural Systems
Medford, June; Prasad, Ashok
2014-01-01
Biological protein interactions networks such as signal transduction or gene transcription networks are often treated as modular, allowing motifs to be analyzed in isolation from the rest of the network. Modularity is also a key assumption in synthetic biology, where it is similarly expected that when network motifs are combined together, they do not lose their essential characteristics. However, the interactions that a network module has with downstream elements change the dynamical equations describing the upstream module and thus may change the dynamic and static properties of the upstream circuit even without explicit feedback. In this work we analyze the behavior of a ubiquitous motif in gene transcription and signal transduction circuits: the switch. We show that adding an additional downstream component to the simple genetic toggle switch changes its dynamical properties by changing the underlying potential energy landscape, and skewing it in favor of the unloaded side, and in some situations adding loads to the genetic switch can also abrogate bistable behavior. We find that an additional positive feedback motif found in naturally occurring toggle switches could tune the potential energy landscape in a desirable manner. We also analyze autocatalytic signal transduction switches and show that a ubiquitous positive feedback switch can lose its switch-like properties when connected to a downstream load. Our analysis underscores the necessity of incorporating the effects of downstream components when understanding the physics of biochemical network motifs, and raises the question as to how these effects are managed in real biological systems. This analysis is particularly important when scaling synthetic networks to more complex organisms. PMID:24676102
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Multilayer perceptron for robust nonlinear interval regression analysis using genetic algorithms.
Hu, Yi-Chung
2014-01-01
On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets.
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A robust controller design method for feedback substitution schemes using genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Trujillo, Mirsha M; Hadjiloucas, Sillas; Becerra, Victor M, E-mail: s.hadjiloucas@reading.ac.uk [Cybernetics, School of Systems Engineering, University of Reading, RG6 6AY (United Kingdom)
2011-08-17
Controllers for feedback substitution schemes demonstrate a trade-off between noise power gain and normalized response time. Using as an example the design of a controller for a radiometric transduction process subjected to arbitrary noise power gain and robustness constraints, a Pareto-front of optimal controller solutions fulfilling a range of time-domain design objectives can be derived. In this work, we consider designs using a loop shaping design procedure (LSDP). The approach uses linear matrix inequalities to specify a range of objectives and a genetic algorithm (GA) to perform a multi-objective optimization for the controller weights (MOGA). A clonal selection algorithm is used to further provide a directed search of the GA towards the Pareto front. We demonstrate that with the proposed methodology, it is possible to design higher order controllers with superior performance in terms of response time, noise power gain and robustness.
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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.
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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
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Rewiring protein synthesis: From natural to synthetic amino acids.
Fan, Yongqiang; Evans, Christopher R; Ling, Jiqiang
2017-11-01
The protein synthesis machinery uses 22 natural amino acids as building blocks that faithfully decode the genetic information. Such fidelity is controlled at multiple steps and can be compromised in nature and in the laboratory to rewire protein synthesis with natural and synthetic amino acids. This review summarizes the major quality control mechanisms during protein synthesis, including aminoacyl-tRNA synthetases, elongation factors, and the ribosome. We will discuss evolution and engineering of such components that allow incorporation of natural and synthetic amino acids at positions that deviate from the standard genetic code. The protein synthesis machinery is highly selective, yet not fixed, for the correct amino acids that match the mRNA codons. Ambiguous translation of a codon with multiple amino acids or complete reassignment of a codon with a synthetic amino acid diversifies the proteome. Expanding the genetic code with synthetic amino acids through rewiring protein synthesis has broad applications in synthetic biology and chemical biology. Biochemical, structural, and genetic studies of the translational quality control mechanisms are not only crucial to understand the physiological role of translational fidelity and evolution of the genetic code, but also enable us to better design biological parts to expand the proteomes of synthetic organisms. This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue. Copyright © 2017 Elsevier B.V. All rights reserved.
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The emerging age of cell-free synthetic biology.
Smith, Mark Thomas; Wilding, Kristen M; Hunt, Jeremy M; Bennett, Anthony M; Bundy, Bradley C
2014-08-25
The engineering of and mastery over biological parts has catalyzed the emergence of synthetic biology. This field has grown exponentially in the past decade. As increasingly more applications of synthetic biology are pursued, more challenges are encountered, such as delivering genetic material into cells and optimizing genetic circuits in vivo. An in vitro or cell-free approach to synthetic biology simplifies and avoids many of the pitfalls of in vivo synthetic biology. In this review, we describe some of the innate features that make cell-free systems compelling platforms for synthetic biology and discuss emerging improvements of cell-free technologies. We also select and highlight recent and emerging applications of cell-free synthetic biology. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
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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.
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Synthetic Biology Parts for the Storage of Increased Genetic Information in Cells.
Morris, Sydney E; Feldman, Aaron W; Romesberg, Floyd E
2017-10-20
To bestow cells with novel forms and functions, the goal of synthetic biology, we have developed the unnatural nucleoside triphosphates dNaMTP and dTPT3TP, which form an unnatural base pair (UBP) and expand the genetic alphabet. While the UBP may be retained in the DNA of a living cell, its retention is sequence-dependent. We now report a steady-state kinetic characterization of the rate with which the Klenow fragment of E. coli DNA polymerase I synthesizes the UBP and its mispairs in a variety of sequence contexts. Correct UBP synthesis is as efficient as for a natural base pair, except in one sequence context, and in vitro performance is correlated with in vivo performance. The data elucidate the determinants of efficient UBP synthesis, show that the dNaM-dTPT3 UBP is the first generally recognized natural-like base pair, and importantly, demonstrate that dNaMTP and dTPT3TP are well optimized and standardized parts for the expansion of the genetic alphabet.
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Czajka, Jeffrey; Wang, Qinhong; Wang, Yechun; Tang, Yinjie J
2017-10-01
Genetically modified microbes have had much industrial success producing protein-based products (such as antibodies and enzymes). However, engineering microbial workhorses for biomanufacturing of commodity compounds remains challenging. First, microbes cannot afford burdens with both overexpression of multiple enzymes and metabolite drainage for product synthesis. Second, synthetic circuits and introduced heterologous pathways are not yet as "robust and reliable" as native pathways due to hosts' innate regulations, especially under suboptimal fermentation conditions. Third, engineered enzymes may lack channeling capabilities for cascade-like transport of metabolites to overcome diffusion barriers or to avoid intermediate toxicity in the cytoplasmic environment. Fourth, moving engineered hosts from laboratory to industry is unreliable because genetic mutations and non-genetic cell-to-cell variations impair the large-scale fermentation outcomes. Therefore, synthetic biology strains often have unsatisfactory industrial performance (titer/yield/productivity). To overcome these problems, many different species are being explored for their metabolic strengths that can be leveraged to synthesize specific compounds. Here, we provide examples of non-conventional and genetically amenable species for industrial manufacturing, including the following: Corynebacterium glutamicum for its TCA cycle-derived biosynthesis, Yarrowia lipolytica for its biosynthesis of fatty acids and carotenoids, cyanobacteria for photosynthetic production from its sugar phosphate pathways, and Rhodococcus for its ability to biotransform recalcitrant feedstock. Finally, we discuss emerging technologies (e.g., genome-to-phenome mapping, single cell methods, and knowledge engineering) that may facilitate the development of novel cell factories.
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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
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Design and construction of "synthetic species".
Directory of Open Access Journals (Sweden)
Eduardo Moreno
Full Text Available Synthetic biology is an area of biological research that combines science and engineering. Here, I merge the principles of synthetic biology and regulatory evolution to create a new species with a minimal set of known elements. Using preexisting transgenes and recessive mutations of Drosophila melanogaster, a transgenic population arises with small eyes and a different venation pattern that fulfils the criteria of a new species according to Mayr's Biological Species Concept. The population described here is the first transgenic organism that cannot hybridize with the original wild type population but remains fertile when crossed with other identical transgenic animals. I therefore propose the term "synthetic species" to distinguish it from "natural species", not only because it has been created by genetic manipulation, but also because it may never be able to survive outside the laboratory environment. The use of genetic engineering to design artificial species barriers could help us understand natural speciation and may have practical applications. For instance, the transition from transgenic organisms towards synthetic species could constitute a safety mechanism to avoid the hybridization of genetically modified animals with wild type populations, preserving biodiversity.
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pBAM1: an all-synthetic genetic tool for analysis and construction of complex bacterial phenotypes
Directory of Open Access Journals (Sweden)
Arévalo-Rodríguez Miguel
2011-02-01
Full Text Available Abstract Background Since publication in 1977 of plasmid pBR322, many breakthroughs in Biology have depended on increasingly sophisticated vector platforms for analysis and engineering of given bacterial strains. Although restriction sites impose a certain format in the procedures for assembling cloned genes, every attempt thus far to standardize vector architecture and nomenclature has ended up in failure. While this state of affairs may still be tolerable for traditional one-at-a-time studies of single genes, the onset of systems and synthetic biology calls for a simplification -along with an optimization- of the currently unwieldy pool of genetic tools. Results The functional DNA sequences present in the natural bacterial transposon Tn5 have been methodically edited and refactored for the production of a multi-purpose genetic tool named pBAM1, which allows a range of manipulations in the genome of Gram-negative bacteria. This all-synthetic construct enhances the power of mini-transposon vectors for either de-construction or re-construction of phenotypes á la carte by incorporating features inspired in systems engineering: modularity, re-usability, minimization, and compatibility with other genetic tools. pBAM1 bears an streamlined, restriction site-freed and narrow-host range replication frame bearing the sequences of R6K oriV, oriT and an ampicillin resistance marker. These go along with a business module that contains a host-independent and hyperactive transposition platform for in vivo or in vitro insertion of desired DNA into the genome of the target bacterium. All functional sequences were standardized for a straightforward replacement by equivalent counterparts, if required. pBAM1 can be delivered into recipient cells by either mating or electroporation, producing transposon insertion frequencies of 1.8 × 10-3 and 1.02 × 10-7, respectively in the soil bacterium Pseudomonas putida. Analyses of the resulting clones revealed a 100% of
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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.
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Mammalian synthetic biology for studying the cell.
Mathur, Melina; Xiang, Joy S; Smolke, Christina D
2017-01-02
Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.
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Synthetic multicellular oscillatory systems: controlling protein dynamics with genetic circuits
International Nuclear Information System (INIS)
Koseska, Aneta; Volkov, Evgenii; Kurths, Juergen
2011-01-01
Synthetic biology is a relatively new research discipline that combines standard biology approaches with the constructive nature of engineering. Thus, recent efforts in the field of synthetic biology have given a perspective to consider cells as 'programmable matter'. Here, we address the possibility of using synthetic circuits to control protein dynamics. In particular, we show how intercellular communication and stochasticity can be used to manipulate the dynamical behavior of a population of coupled synthetic units and, in this manner, finely tune the expression of specific proteins of interest, e.g. in large bioreactors.
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A standard-enabled workflow for synthetic biology
Myers, Chris J.
2017-06-15
A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications.
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A standard-enabled workflow for synthetic biology
Myers, Chris J.; Beal, Jacob; Gorochowski, Thomas E.; Kuwahara, Hiroyuki; Madsen, Curtis; McLaughlin, James Alastair; Mısırlı, Gö ksel; Nguyen, Tramy; Oberortner, Ernst; Samineni, Meher; Wipat, Anil; Zhang, Michael; Zundel, Zach
2017-01-01
A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select
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Yeast synthetic biology for the production of recombinant therapeutic proteins.
Kim, Hyunah; Yoo, Su Jin; Kang, Hyun Ah
2015-02-01
The production of recombinant therapeutic proteins is one of the fast-growing areas of molecular medicine and currently plays an important role in treatment of several diseases. Yeasts are unicellular eukaryotic microbial host cells that offer unique advantages in producing biopharmaceutical proteins. Yeasts are capable of robust growth on simple media, readily accommodate genetic modifications, and incorporate typical eukaryotic post-translational modifications. Saccharomyces cerevisiae is a traditional baker's yeast that has been used as a major host for the production of biopharmaceuticals; however, several nonconventional yeast species including Hansenula polymorpha, Pichia pastoris, and Yarrowia lipolytica have gained increasing attention as alternative hosts for the industrial production of recombinant proteins. In this review, we address the established and emerging genetic tools and host strains suitable for recombinant protein production in various yeast expression systems, particularly focusing on current efforts toward synthetic biology approaches in developing yeast cell factories for the production of therapeutic recombinant proteins. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.
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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.
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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
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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
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Two synthetic tandem repetitive DNA probes were used to compare genetic variation at variable-number-tandem-repeat (VNTR) loci among Rubus idaeus L. var. strigosus (Michx.) Maxim. (Rosaceae) individuals sampled at eight sites contaminated by pollutants (N = 39) and eight adjacent...
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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.
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A standard-enabled workflow for synthetic biology.
Myers, Chris J; Beal, Jacob; Gorochowski, Thomas E; Kuwahara, Hiroyuki; Madsen, Curtis; McLaughlin, James Alastair; Mısırlı, Göksel; Nguyen, Tramy; Oberortner, Ernst; Samineni, Meher; Wipat, Anil; Zhang, Michael; Zundel, Zach
2017-06-15
A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.
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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
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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.
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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.
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Sanders, Barbara P; Edo-Matas, Diana; Papic, Natasa; Schuitemaker, Hanneke; Custers, Jerome H H V
2015-10-13
Safety of vaccines can be compromised by contamination with adventitious agents. One potential source of adventitious agents is a vaccine seed, typically derived from historic clinical isolates with poorly defined origins. Here we generated synthetic poliovirus seeds derived from chemically synthesized DNA plasmids encoding the sequence of wild-type poliovirus strains used in marketed inactivated poliovirus vaccines. The synthetic strains were phenotypically identical to wild-type polioviruses as shown by equivalent infectious titers in culture supernatant and antigenic content, even when infection cultures are scaled up to 10-25L bioreactors. Moreover, the synthetic seeds were genetically stable upon extended passaging on the PER.C6 cell culture platform. Use of synthetic seeds produced on the serum-free PER.C6 cell platform ensures a perfectly documented seed history and maximum control over starting materials. It provides an opportunity to maximize vaccine safety which increases the prospect of a vaccine end product that is free from adventitious agents. Copyright © 2015 Elsevier Ltd. All rights reserved.
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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.
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Synthetic Biology Open Language (SBOL) Version 2.2.0.
Cox, Robert Sidney; Madsen, Curtis; McLaughlin, James Alastair; Nguyen, Tramy; Roehner, Nicholas; Bartley, Bryan; Beal, Jacob; Bissell, Michael; Choi, Kiri; Clancy, Kevin; Grünberg, Raik; Macklin, Chris; Misirli, Goksel; Oberortner, Ernst; Pocock, Matthew; Samineni, Meher; Zhang, Michael; Zhang, Zhen; Zundel, Zach; Gennari, John H; Myers, Chris; Sauro, Herbert; Wipat, Anil
2018-04-02
Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year's JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.
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Synthetic Biology Open Language (SBOL) Version 2.2.0
Cox, Robert Sidney
2018-04-04
Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year\\'s JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.
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Synthetic Biology Open Language (SBOL Version 2.2.0
Directory of Open Access Journals (Sweden)
Cox Robert Sidney
2018-04-01
Full Text Available Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year’s JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.
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Synthetic Biology Open Language (SBOL) Version 2.2.0
Cox, Robert Sidney; Madsen, Curtis; McLaughlin, James Alastair; Nguyen, Tramy; Roehner, Nicholas; Bartley, Bryan; Beal, Jacob; Bissell, Michael; Choi, Kiri; Clancy, Kevin; Grunberg, Raik; Macklin, Chris; Misirli, Goksel; Oberortner, Ernst; Pocock, Matthew; Samineni, Meher; Zhang, Michael; Zhang, Zhen; Zundel, Zach; Gennari, John H.; Myers, Chris; Sauro, Herbert; Wipat, Anil
2018-01-01
Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year's JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.
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A Novel Evolutionary Algorithm for Designing Robust Analog Filters
Directory of Open Access Journals (Sweden)
Shaobo Li
2018-03-01
Full Text Available Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness achievable through parameter tuning. This paper proposes a new evolutionary algorithm for robust design that exploits the open-ended topological search capability of genetic programming (GP coupled with bond graph modeling. We applied our GP-based robust design (GPRD algorithm to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on a state-of-the-art real-parameter genetic algorithm (GA, our GPRD algorithm with a fitness criterion rewarding robustness, with respect to parameter perturbations, can evolve more robust filters than what was achieved through parameter tuning alone. We also find that inappropriate GA tuning may mislead the search process and that multiple-simulation and perturbed fitness evaluation methods for evolving robustness have complementary behaviors with no absolute advantage of one over the other.
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Faisal, Mohammad; Alatar, Abdulrahman A; Ahmad, Naseem; Anis, Mohammad; Hegazy, Ahmad K
2012-05-03
An efficient method was developed for plant regeneration and establishment from alginate encapsulated synthetic seeds of Rauvolfia serpentina. Synthetic seeds were produced using in vitro proliferated microshoots upon complexation of 3% sodium alginate prepared in Llyod and McCown woody plant medium (WPM) and 100 mM calcium chloride. Re-growth ability of encapsulated nodal segments was evaluated after storage at 4 °C for 0, 1, 2, 4, 6 and 8 weeks and compared with non-encapsulated buds. Effects of different media viz; Murashige and Skoog medium; Lloyd and McCown woody Plant medium, Gamborg’s B5 medium and Schenk and Hildebrandt medium was also investigated for conversion into plantlets. The maximum frequency of conversion into plantlets from encapsulated nodal segments stored at 4 °C for 4 weeks was achieved on woody plant medium supplement with 5.0 μM BA and 1.0 μM NAA. Rooting in plantlets was achieved in half-strength Murashige and Skoog liquid medium containing 0.5 μM indole-3-acetic acid (IAA) on filter paper bridges. Plantlets obtained from stored synseeds were hardened, established successfully ex vitro and were morphologically similar to each other as well as their mother plant. The genetic fidelity of Rauvolfia clones raised from synthetic seeds following four weeks of storage at 4 °C were assessed by using random amplified polymorphic DNA (RAPD) and inter-simple sequence repeat (ISSR) markers. All the RAPD and ISSR profiles from generated plantlets were monomorphic and comparable to the mother plant, which confirms the genetic stability among the clones. This synseed protocol could be useful for establishing a particular system for conservation, short-term storage and production of genetically identical and stable plants before it is released for commercial purposes.
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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.
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International Nuclear Information System (INIS)
Demirhan, Haydar; Kayhan Atilgan, Yasemin
2015-01-01
Highlights: • Precise horizontal global solar radiation estimation models are proposed for Turkey. • Genetic programming technique is used to construct the models. • Robust coplot analysis is applied to reduce the impact of outlier observations. • Better estimation and prediction properties are observed for the models. - Abstract: Renewable energy sources have been attracting more and more attention of researchers due to the diminishing and harmful nature of fossil energy sources. Because of the importance of solar energy as a renewable energy source, an accurate determination of significant covariates and their relationships with the amount of global solar radiation reaching the Earth is a critical research problem. There are numerous meteorological and terrestrial covariates that can be used in the analysis of horizontal global solar radiation. Some of these covariates are highly correlated with each other. It is possible to find a large variety of linear or non-linear models to explain the amount of horizontal global solar radiation. However, models that explain the amount of global solar radiation with the smallest set of covariates should be obtained. In this study, use of the robust coplot technique to reduce the number of covariates before going forward with advanced modelling techniques is considered. After reducing the dimensionality of model space, yearly and monthly mean daily horizontal global solar radiation estimation models for Turkey are built by using the genetic programming technique. It is observed that application of robust coplot analysis is helpful for building precise models that explain the amount of global solar radiation with the minimum number of covariates without suffering from outlier observations and the multicollinearity problem. Consequently, over a dataset of Turkey, precise yearly and monthly mean daily global solar radiation estimation models are introduced using the model spaces obtained by robust coplot technique and
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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
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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.
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A Blueprint for a Synthetic Genetic Feedback Controller to Reprogram Cell Fate.
Del Vecchio, Domitilla; Abdallah, Hussein; Qian, Yili; Collins, James J
2017-01-25
To artificially reprogram cell fate, experimentalists manipulate the gene regulatory networks (GRNs) that maintain a cell's phenotype. In practice, reprogramming is often performed by constant overexpression of specific transcription factors (TFs). This process can be unreliable and inefficient. Here, we address this problem by introducing a new approach to reprogramming based on mathematical analysis. We demonstrate that reprogramming GRNs using constant overexpression may not succeed in general. Instead, we propose an alternative reprogramming strategy: a synthetic genetic feedback controller that dynamically steers the concentration of a GRN's key TFs to any desired value. The controller works by adjusting TF expression based on the discrepancy between desired and actual TF concentrations. Theory predicts that this reprogramming strategy is guaranteed to succeed, and its performance is independent of the GRN's structure and parameters, provided that feedback gain is sufficiently high. As a case study, we apply the controller to a model of induced pluripotency in stem cells. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
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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.
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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.
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Philosophy of Systems and Synthetic Biology
DEFF Research Database (Denmark)
Green, Sara
2017-01-01
This entry aims to clarify how systems and synthetic biology contribute to and extend discussions within philosophy of science. Unlike fields such as developmental biology or molecular biology, systems and synthetic biology are not easily demarcated by a focus on a specific subject area or level...... of organization. Rather, they are characterized by the development and application of mathematical, computational, and synthetic modeling strategies in response to complex problems and challenges within the life sciences. Proponents of systems and synthetic biology often stress the necessity of a perspective...... that goes beyond the scope of molecular biology and genetic engineering, respectively. With the emphasis on systems and interaction networks, the approaches explicitly engage in one of the oldest philosophical discussions on the relationship between parts and wholes, or between reductionism and holism...
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Chromatin regulators, phenotypic robustness and autism risk
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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.
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Boehm, Christian R; Pollak, Bernardo; Purswani, Nuri; Patron, Nicola; Haseloff, Jim
2017-07-05
Plants are attractive platforms for synthetic biology and metabolic engineering. Plants' modular and plastic body plans, capacity for photosynthesis, extensive secondary metabolism, and agronomic systems for large-scale production make them ideal targets for genetic reprogramming. However, efforts in this area have been constrained by slow growth, long life cycles, the requirement for specialized facilities, a paucity of efficient tools for genetic manipulation, and the complexity of multicellularity. There is a need for better experimental and theoretical frameworks to understand the way genetic networks, cellular populations, and tissue-wide physical processes interact at different scales. We highlight new approaches to the DNA-based manipulation of plants and the use of advanced quantitative imaging techniques in simple plant models such as Marchantia polymorpha. These offer the prospects of improved understanding of plant dynamics and new approaches to rational engineering of plant traits. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.
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Directory of Open Access Journals (Sweden)
Zhenyu Shi
2016-12-01
Full Text Available Molecular Cloning Designer Simulator (MCDS is a powerful new all-in-one cloning and genetic engineering design, simulation and management software platform developed for complex synthetic biology and metabolic engineering projects. In addition to standard functions, it has a number of features that are either unique, or are not found in combination in any one software package: (1 it has a novel interactive flow-chart user interface for complex multi-step processes, allowing an integrated overview of the whole project; (2 it can perform a user-defined workflow of cloning steps in a single execution of the software; (3 it can handle multiple types of genetic recombineering, a technique that is rapidly replacing classical cloning for many applications; (4 it includes experimental information to conveniently guide wet lab work; and (5 it can store results and comments to allow the tracking and management of the whole project in one platform. MCDS is freely available from https://mcds.codeplex.com. Keywords: BioCAD, Genetic engineering software, Molecular cloning software, Synthetic biology, Workflow simulation and management
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Super-Resolution for Synthetic Zooming
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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.
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Synthetic biology for pharmaceutical drug discovery
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Trosset JY
2015-12-01
Full Text Available Jean-Yves Trosset,1 Pablo Carbonell2,3 1Bioinformation Research Laboratory, Sup’Biotech, Villejuif, France; 2Faculty of Life Sciences, SYNBIOCHEM Centre, Manchester Institute of Biotechnology, University of Manchester, Manchester, UK; 3Department of Experimental and Health Sciences (DCEXS, Research Programme on Biomedical Informatics (GRIB, Hospital del Mar Medical Research Institute (IMIM, Universitat Pompeu Fabra (UPF, Barcelona, Spain Abstract: Synthetic biology (SB is an emerging discipline, which is slowly reorienting the field of drug discovery. For thousands of years, living organisms such as plants were the major source of human medicines. The difficulty in resynthesizing natural products, however, often turned pharmaceutical industries away from this rich source for human medicine. More recently, progress on transformation through genetic manipulation of biosynthetic units in microorganisms has opened the possibility of in-depth exploration of the large chemical space of natural products derivatives. Success of SB in drug synthesis culminated with the bioproduction of artemisinin by microorganisms, a tour de force in protein and metabolic engineering. Today, synthetic cells are not only used as biofactories but also used as cell-based screening platforms for both target-based and phenotypic-based approaches. Engineered genetic circuits in synthetic cells are also used to decipher disease mechanisms or drug mechanism of actions and to study cell–cell communication within bacteria consortia. This review presents latest developments of SB in the field of drug discovery, including some challenging issues such as drug resistance and drug toxicity. Keywords: metabolic engineering, plant synthetic biology, natural products, synthetic quorum sensing, drug resistance
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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.
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Pose estimation for augmented reality applications using genetic algorithm.
Yu, Ying Kin; Wong, Kin Hong; Chang, Michael Ming Yuen
2005-12-01
This paper describes a genetic algorithm that tackles the pose-estimation problem in computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the three-dimensional structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose as in the existing work, our algorithm, at the same time, searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to the existing algorithms. Our approach outperformed the Lowe's method and the other two genetic algorithms under the presence of point mismatches and outliers. In addition, it has been used to estimate the pose of a real object. It is shown that the proposed method is applicable to augmented reality applications.
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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.
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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.
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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.
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Genetic architecture promotes the evolution and maintenance of cooperation.
Directory of Open Access Journals (Sweden)
Antoine Frénoy
Full Text Available When cooperation has a direct cost and an indirect benefit, a selfish behavior is more likely to be selected for than an altruistic one. Kin and group selection do provide evolutionary explanations for the stability of cooperation in nature, but we still lack the full understanding of the genomic mechanisms that can prevent cheater invasion. In our study we used Aevol, an agent-based, in silico genomic platform to evolve populations of digital organisms that compete, reproduce, and cooperate by secreting a public good for tens of thousands of generations. We found that cooperating individuals may share a phenotype, defined as the amount of public good produced, but have very different abilities to resist cheater invasion. To understand the underlying genetic differences between cooperator types, we performed bio-inspired genomics analyses of our digital organisms by recording and comparing the locations of metabolic and secretion genes, as well as the relevant promoters and terminators. Association between metabolic and secretion genes (promoter sharing, overlap via frame shift or sense-antisense encoding was characteristic for populations with robust cooperation and was more likely to evolve when secretion was costly. In mutational analysis experiments, we demonstrated the potential evolutionary consequences of the genetic association by performing a large number of mutations and measuring their phenotypic and fitness effects. The non-cooperating mutants arising from the individuals with genetic association were more likely to have metabolic deleterious mutations that eventually lead to selection eliminating such mutants from the population due to the accompanying fitness decrease. Effectively, cooperation evolved to be protected and robust to mutations through entangled genetic architecture. Our results confirm the importance of second-order selection on evolutionary outcomes, uncover an important genetic mechanism for the evolution and
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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
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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
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Misconceptions of Synthetic Biology: Lessons from an Interdisciplinary Summer School
Verseux, Cyprien; Acevedo-Rocha, Carlos G.; Chizzolini, Fabio; Rothschild, Lynn J.
2016-01-01
In 2014, an international group of scholars from various fields analysed the "societal dimensions" of synthetic biology in an interdisciplinary summer school. Here, we report and discuss the biologists' observations on the general perception of synthetic biology by non-biologists who took part in this event. Most attendees mainly associated synthetic biology with contributions from the best-known public figures of the field, rarely mentioning other scientists. Media extrapolations of those contributions appeared to have created unrealistic expectations and irrelevant fears that were widely disconnected from the current research in synthetic biology. Another observation was that when debating developments in synthetic biology, semantics strongly mattered: depending on the terms used to present an application of synthetic biology, attendees reacted in radically different ways. For example, using the term "GMOs" (genetically modified organisms) rather than the term "genetic engineering" led to very different reactions. Stimulating debates also happened with participants having unanticipated points of view, for instance biocentrist ethicists who argued that engineered microbes should not be used for human purposes. Another communication challenge emerged from the connotations and inaccuracies surrounding the word "life", which impaired constructive debates, thus leading to misconceptions about the abilities of scientists to engineer or even create living organisms. Finally, it appeared that synthetic biologists tend to overestimate the knowledge of non-biologists, further affecting communication. The motivation and ability of synthetic biologists to communicate their work outside their research field needs to be fostered, notably towards policymakers who need a more accurate and technical understanding of the field to make informed decisions. Interdisciplinary events gathering scholars working in and around synthetic biology are an effective tool in addressing those
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Synthetic Phage for Tissue Regeneration
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So Young Yoo
2014-01-01
Full Text Available Controlling structural organization and signaling motif display is of great importance to design the functional tissue regenerating materials. Synthetic phage, genetically engineered M13 bacteriophage has been recently introduced as novel tissue regeneration materials to display a high density of cell-signaling peptides on their major coat proteins for tissue regeneration purposes. Structural advantages of their long-rod shape and monodispersity can be taken together to construct nanofibrous scaffolds which support cell proliferation and differentiation as well as direct orientation of their growth in two or three dimensions. This review demonstrated how functional synthetic phage is designed and subsequently utilized for tissue regeneration that offers potential cell therapy.
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Synthetic Biology of Cyanobacteria: Unique Challenges and Opportunities
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Bertram M Berla
2013-08-01
Full Text Available Photosynthetic organisms, and especially cyanobacteria, hold great promise as sources of renewably-produced fuels, bulk and specialty chemicals, and nutritional products. Synthetic biology tools can help unlock cyanobacteria’s potential for these functions, but unfortunately tool development for these organisms has lagged behind that for S. cerevisiae and E. coli. While these organisms may in many cases be more difficult to work with as ‘chassis’ strains for synthetic biology than certain heterotrophs, the unique advantages of autotrophs in biotechnology applications as well as the scientific importance of improved understanding of photosynthesis warrant the development of these systems into something akin to a ‘green E. coli’. In this review, we highlight unique challenges and opportunities for development of synthetic biology approaches in cyanobacteria. We review classical and recently developed methods for constructing targeted mutants in various cyanobacterial strains, and offer perspective on what genetic tools might most greatly expand the ability to engineer new functions in such strains. Similarly, we review what genetic parts are most needed for the development of cyanobacterial synthetic biology. Finally, we highlight recent methods to construct genome-scale models of cyanobacterial metabolism and to use those models to measure properties of autotrophic metabolism. Throughout this paper, we discuss some of the unique challenges of a diurnal, autotrophic lifestyle along with how the development of synthetic biology and biotechnology in cyanobacteria must fit within those constraints.
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Toni, Tina; Tidor, Bruce
2013-01-01
Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA – for example, on the same transcript – was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady
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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.
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On the Interplay between Entropy and Robustness of Gene Regulatory Networks
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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.
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On the possible role of robustness in the evolution of infectious diseases
Ogbunugafor, C. Brandon; Pease, James B.; Turner, Paul E.
2010-06-01
Robustness describes the capacity for a biological system to remain canalized despite perturbation. Genetic robustness affords maintenance of phenotype despite mutational input, necessarily involving the role of epistasis. Environmental robustness is phenotypic constancy in the face of environmental variation, where epistasis may be uninvolved. Here we discuss genetic and environmental robustness, from the standpoint of infectious disease evolution, and suggest that robustness may be a unifying principle for understanding how different disease agents evolve. We focus especially on viruses with RNA genomes due to their importance in the evolution of emerging diseases and as model systems to test robustness theory. We present new data on adaptive constraints for a model RNA virus challenged to evolve in response to UV radiation. We also draw attention to other infectious disease systems where robustness theory may prove useful for bridging evolutionary biology and biomedicine, especially the evolution of antibiotic resistance in bacteria, immune evasion by influenza, and malaria parasite infections.
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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.
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Design Automation in Synthetic Biology.
Appleton, Evan; Madsen, Curtis; Roehner, Nicholas; Densmore, Douglas
2017-04-03
Design automation refers to a category of software tools for designing systems that work together in a workflow for designing, building, testing, and analyzing systems with a target behavior. In synthetic biology, these tools are called bio-design automation (BDA) tools. In this review, we discuss the BDA tools areas-specify, design, build, test, and learn-and introduce the existing software tools designed to solve problems in these areas. We then detail the functionality of some of these tools and show how they can be used together to create the desired behavior of two types of modern synthetic genetic regulatory networks. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.
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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.
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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
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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.
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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
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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.
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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
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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.
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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.
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Lee, Kyung-Ho; Kim, Dong-Myung
2013-11-01
Synthetic biology is built on the synthesis, engineering, and assembly of biological parts. Proteins are the first components considered for the construction of systems with designed biological functions because proteins carry out most of the biological functions and chemical reactions inside cells. Protein synthesis is considered to comprise the most basic levels of the hierarchical structure of synthetic biology. Cell-free protein synthesis has emerged as a powerful technology that can potentially transform the concept of bioprocesses. With the ability to harness the synthetic power of biology without many of the constraints of cell-based systems, cell-free protein synthesis enables the rapid creation of protein molecules from diverse sources of genetic information. Cell-free protein synthesis is virtually free from the intrinsic constraints of cell-based methods and offers greater flexibility in system design and manipulability of biological synthetic machinery. Among its potential applications, cell-free protein synthesis can be combined with various man-made devices for rapid functional analysis of genomic sequences. This review covers recent efforts to integrate cell-free protein synthesis with various reaction devices and analytical platforms. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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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
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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.
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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.
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Directory of Open Access Journals (Sweden)
Lihong Jiang
2018-06-01
Full Text Available Advances in metabolic engineering and synthetic biology have facilitated the manufacturing of many valuable-added compounds and commodity chemicals using microbial cell factories in the past decade. However, due to complexity of cellular metabolism, the optimization of metabolic pathways for maximal production represents a grand challenge and an unavoidable barrier for metabolic engineering. Recently, cell-free protein synthesis system (CFPS has been emerging as an enabling alternative to address challenges in biomanufacturing. This review summarizes the recent progresses of CFPS in rapid prototyping of biosynthetic pathways and genetic circuits (biosensors to speed up design-build-test (DBT cycles of metabolic engineering and synthetic biology. Keywords: Cell-free protein synthesis, Metabolic pathway optimization, Genetic circuits, Metabolic engineering, Synthetic biology
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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.
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International Nuclear Information System (INIS)
Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor
2017-01-01
Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the
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Synthetic genetic polymers capable of heredity and evolution
DEFF Research Database (Denmark)
Pinheiro, Vitor B; Taylor, Alexander I; Cozens, Christopher
2012-01-01
in and recovered from six alternative genetic polymers based on simple nucleic acid architectures not found in nature [xeno-nucleic acids (XNAs)]. We also select XNA aptamers, which bind their targets with high affinity and specificity, demonstrating that beyond heredity, specific XNAs have the capacity......Genetic information storage and processing rely on just two polymers, DNA and RNA, yet whether their role reflects evolutionary history or fundamental functional constraints is currently unknown. With the use of polymerase evolution and design, we show that genetic information can be stored...... for Darwinian evolution and folding into defined structures. Thus, heredity and evolution, two hallmarks of life, are not limited to DNA and RNA but are likely to be emergent properties of polymers capable of information storage....
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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
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Space Synthetic Biology Project
Howard, David; Roman, Monsi; Mansell, James (Matt)
2015-01-01
Synthetic biology is an effort to make genetic engineering more useful by standardizing sections of genetic code. By standardizing genetic components, biological engineering will become much more similar to traditional fields of engineering, in which well-defined components and subsystems are readily available in markets. Specifications of the behavior of those components and subsystems can be used to model a system which incorporates them. Then, the behavior of the novel system can be simulated and optimized. Finally, the components and subsystems can be purchased and assembled to create the optimized system, which most often will exhibit behavior similar to that indicated by the model. The Space Synthetic Biology project began in 2012 as a multi-Center effort. The purpose of this project was to harness Synthetic Biology principals to enable NASA's missions. A central target for application was to Environmental Control & Life Support (ECLS). Engineers from NASA Marshall Space Flight Center's (MSFC's) ECLS Systems Development Branch (ES62) were brought into the project to contribute expertise in operational ECLS systems. Project lead scientists chose to pursue the development of bioelectrochemical technologies to spacecraft life support. Therefore, the ECLS element of the project became essentially an effort to develop a bioelectrochemical ECLS subsystem. Bioelectrochemical systems exploit the ability of many microorganisms to drive their metabolisms by direct or indirect utilization of electrical potential gradients. Whereas many microorganisms are capable of deriving the energy required for the processes of interest (such as carbon dioxide (CO2) fixation) from sunlight, it is believed that subsystems utilizing electrotrophs will exhibit smaller mass, volume, and power requirements than those that derive their energy from sunlight. In the first 2 years of the project, MSFC personnel conducted modeling, simulation, and conceptual design efforts to assist the
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Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.
Roehner, Nicholas; Zhang, Zhen; Nguyen, Tramy; Myers, Chris J
2015-08-21
In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).
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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.
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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.
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Synthetic Biology and the U.S. Biotechnology Regulatory System: Challenges and Options
Energy Technology Data Exchange (ETDEWEB)
Carter, Sarah R. [J. Craig Venter Inst., Rockville, MD (United States); Rodemeyer, Michael [Univ. of Virginia, Charlottesville, VA (United States); Garfinkel, Michele S. [EMBO, Heidelberg (Germany); Friedman, Robert M. [J. Craig Venter Inst., Rockville, MD (United States)
2014-05-01
Synthetic Biology and the U.S. Biotechnology Regulatory System: Challenges and Options Sarah R. Carter, Ph.D., J. Craig Venter Institute; Michael Rodemeyer, J.D., University of Virginia; Michele S. Garfinkel, Ph.D., EMBO; Robert M. Friedman, Ph.D., J. Craig Venter Institute In recent years, a range of genetic engineering techniques referred to as “synthetic biology” has significantly expanded the tool kit available to scientists and engineers, providing them with far greater capabilities to engineer organisms than previous techniques allowed. The field of synthetic biology includes the relatively new ability to synthesize long pieces of DNA from chemicals, as well as improved methods for genetic manipulation and design of genetic pathways to achieve more precise control of biological systems. These advances will help usher in a new generation of genetically engineered microbes, plants, and animals. The JCVI Policy Center team, along with researchers at the University of Virginia and EMBO, examined how well the current U.S. regulatory system for genetically engineered products will handle the near-term introduction of organisms engineered using synthetic biology. In particular, the focus was on those organisms intended to be used or grown directly in the environment, outside of a contained facility. The study concludes that the U.S. regulatory agencies have adequate legal authority to address most, but not all, potential environmental, health and safety concerns posed by these organisms. Such near-term products are likely to represent incremental changes rather than a marked departure from previous genetically engineered organisms. However, the study also identified two key challenges for the regulatory system, which are detailed in the report. First, USDA’s authority over genetically engineered plants depends on the use of an older engineering technique that is no longer necessary for many applications. The shift to synthetic biology and other newer genetic
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APPLICATION OF GENETIC ALGORITHMS FOR ROBUST PARAMETER OPTIMIZATION
Directory of Open Access Journals (Sweden)
N. Belavendram
2010-12-01
Full Text Available Parameter optimization can be achieved by many methods such as Monte-Carlo, full, and fractional factorial designs. Genetic algorithms (GA are fairly recent in this respect but afford a novel method of parameter optimization. In GA, there is an initial pool of individuals each with its own specific phenotypic trait expressed as a ‘genetic chromosome’. Different genes enable individuals with different fitness levels to reproduce according to natural reproductive gene theory. This reproduction is established in terms of selection, crossover and mutation of reproducing genes. The resulting child generation of individuals has a better fitness level akin to natural selection, namely evolution. Populations evolve towards the fittest individuals. Such a mechanism has a parallel application in parameter optimization. Factors in a parameter design can be expressed as a genetic analogue in a pool of sub-optimal random solutions. Allowing this pool of sub-optimal solutions to evolve over several generations produces fitter generations converging to a pre-defined engineering optimum. In this paper, a genetic algorithm is used to study a seven factor non-linear equation for a Wheatstone bridge as the equation to be optimized. A comparison of the full factorial design against a GA method shows that the GA method is about 1200 times faster in finding a comparable solution.
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PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN
Institute of Scientific and Technical Information of China (English)
HU Jie; PENG Yinghong; XIONG Guangleng
2006-01-01
A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.
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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
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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.
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BISRU: Synthetic Microbes for Moon, Mars and Beyond
Cumbers, J.; Rothchild, L.
2010-04-01
Synthetic biology and genomics will bring a new range of designer organisms into being and give us new tools for the manipulation and control of these organisms. BISRU or biological in situ resource utilization is the use of such genetically modified organisms in space.
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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).
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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.
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Selection platforms for directed evolution in synthetic biology.
Tizei, Pedro A G; Csibra, Eszter; Torres, Leticia; Pinheiro, Vitor B
2016-08-15
Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules-gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function-be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code. © 2016 The Author(s).
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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.
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Robust Image Analysis of Faces for Genetic Applications
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2010-01-01
Roč. 6, č. 2 (2010), s. 95-102 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : object localization * template matching * eye or mouth detection * robust correlation analysis * image denoising Subject RIV: BB - Applied Statistics, Operational Research http://www.ejbi.cz/articles/201012/47/1.html
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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.
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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.
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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.
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A Realistic Model under which the Genetic Code is Optimal
Buhrman, H.; van der Gulik, P.T.S.; Klau, G.W.; Schaffner, C.; Speijer, D.; Stougie, L.
2013-01-01
The genetic code has a high level of error robustness. Using values of hydrophobicity scales as a proxy for amino acid character, and the mean square measure as a function quantifying error robustness, a value can be obtained for a genetic code which reflects the error robustness of that code. By
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Rettinger, A; Broeckl, S; Fink, M; Prodinger, W M; Blum, H; Krebs, S; Domogalla, J; Just, F; Gellert, S; Straubinger, R K; Büttner, M
2017-06-01
Alpine Mycobacterium caprae isolates found in cattle and red deer display at least three genetic variations in the region of difference four (RD4) that can be used for further differentiation of the isolates into the subtypes 'Allgäu', 'Karwendel' and 'Lechtal'. Each genomic subtype is thereby characterized by a specific nucleotide deletion pattern in the 12.7-kb RD4 region. Even though M. caprae infections are frequently documented in cattle and red deer, little is known about the transmission routes. Hence, robust markers for M. caprae subtyping are needed to gain insight into the molecular epidemiology. For this reason, a rapid and robust multiplex PCR was developed for the simultaneous detection of three M. caprae RD4 subtypes and was used to subtype a total number of 241 M. caprae isolates from animals (145 cattle, 95 red deer and one fox) from Bavaria and Austria. All three subtypes occur spatially distributed and are found in cattle and in red deer suggesting transmission between the two species. As subtypes are genetically stable in both species it is hypothesized that the described genetic variations developed within the host due to 'within-host replication'. The results of this study recommend the genomic RD4 region as a reliable diagnostic marker for M. caprae subtype differentiation. © 2015 Blackwell Verlag GmbH.
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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
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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
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Vecchioni, Simon; Toomey, Emily; Capece, Mark C.; Rothschild, Lynn; Wind, Shalom
2017-01-01
DNA is an ideal template for a biological nanowire-it has a linear structure several atoms thick; it possesses addressable nucleobase geometry that can be precisely defined; and it is massively scalable into branched networks. Until now, the drawback of DNA as a conducting nanowire been, simply put, its low conductance. To address this deficiency, we extensively characterize a chemical variant of canonical DNA that exploits the affinity of natural cytosine bases for silver ions. We successfully construct chains of single silver ions inside double-stranded DNA, confirm the basic dC-Ag+-dC bond geometry and kinetics, and show length-tunability dependent on mismatch distribution, ion availability and enzyme activity. An analysis of the absorbance spectra of natural DNA and silver-binding, poly-cytosine DNA demonstrates the heightened thermostability of the ion chain and its resistance to aqueous stresses such as precipitation, dialysis and forced reduction. These chemically critical traits lend themselves to an increase in electrical conductivity of over an order of magnitude for 11-base silver-paired duplexes over natural strands when assayed by STM break junction. We further construct and implement a genetic pathway in the E. coli bacterium for the biosynthesis of highly ionizable DNA sequences. Toward future circuits, we construct a model of transcription network architectures to determine the most efficient and robust connectivity for cell-based fabrication, and we perform sequence optimization with a genetic algorithm to identify oligonucleotides robust to changes in the base-pairing energy landscape. We propose that this system will serve as a synthetic biological fabrication platform for more complex DNA nanotechnology and nanoelectronics with applications to deep space and low resource environments.
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Plant synthetic biology: a new platform for industrial biotechnology.
Fesenko, Elena; Edwards, Robert
2014-05-01
Thirty years after the production of the first generation of genetically modified plants we are now set to move into a new era of recombinant crop technology through the application of synthetic biology to engineer new and complex input and output traits. The use of synthetic biology technologies will represent more than incremental additions of transgenes, but rather the directed design of completely new metabolic pathways, physiological traits, and developmental control strategies. The need to enhance our ability to improve crops through new engineering capability is now increasingly pressing as we turn to plants not just for food, but as a source of renewable feedstocks for industry. These accelerating and diversifying demands for new output traits coincide with a need to reduce inputs and improve agricultural sustainability. Faced with such challenges, existing technologies will need to be supplemented with new and far-more-directed approaches to turn valuable resources more efficiently into usable agricultural products. While these objectives are challenging enough, the use of synthetic biology in crop improvement will face public acceptance issues as a legacy of genetically modified technologies in many countries. Here we review some of the potential benefits of adopting synthetic biology approaches in improving plant input and output traits for their use as industrial chemical feedstocks, as linked to the rapidly developing biorefining industry. Several promising technologies and biotechnological targets are identified along with some of the key regulatory and societal challenges in the safe and acceptable introduction of such technology.
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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.
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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
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[How to be prudent with synthetic biology. Synthetic Biology and the precautionary principle].
Rodríguez López, Blanca
2014-01-01
Synthetic biology is a new discipline that is twofold: firstly it offers the promise to pay benefits that can alleviate some of the ills that plague mankind; On the other hand, like all technologies, holds risks. Given these, the most critical and concerned about the risks, invoke the application of the precautionary principle, common in cases where an activity or new technology creates risks to the environment and/or human health, but far from universally accepted happens to be currently one of the most controversial principles. In this paper the question of the risks and benefits of synthetic biology and the relevance of applying the precautionary principle are analyzed. To do this we proceed as follows. The first part focuses on synthetic biology. At first, this discipline is characterized, with special attention to what is novel compared to the known as "genetic engineering". In the second stage both the benefits and the risks associated with it are discussed. The first part concludes with a review of the efforts currently being made to control or minimize the risks. The second part aims to analyze the precautionary principle and its possible relevance to the case of Synthetic Biology. At first, the different versions and interpretations of the principle and the various criticisms of which has been the subject are reviewed. Finally, after discarding the Precautionary Principle as an useful tool, it is seen as more appropriate some recent proposals to treat technologies that take into account not only risks but also their benefits.
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Synthetic Biology and the Argument from Continuity with Established Technologies
DEFF Research Database (Denmark)
Christiansen, Andreas
2015-01-01
) that it ignores the distinction between what reasons we have and what we should do all things considered. I then illustrate the Continuity Argument and its problems in the case where human manipulation of organisms’ genetic makeup is a suggested reason for finding synthetic biology problematic. Finally, I suggest......Defenders of synthetic biology commonly make reference to the fact that established technologies, such as domestication or selective breeding, share some of the features of synthetic biology that critics argue make it ethically problematic. In this chapter, I reconstruct such references...... as instances of a type of argument which I dub the Continuity Argument. Roughly, the Continuity Argument seeks to show that if we are not disposed to reject the established technology, then features that this technology share with synthetic biology cannot provide reasons to find it ethically problematic. I...
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Synthetic biology in cell-based cancer immunotherapy.
Chakravarti, Deboki; Wong, Wilson W
2015-08-01
The adoptive transfer of genetically engineered T cells with cancer-targeting receptors has shown tremendous promise for eradicating tumors in clinical trials. This form of cellular immunotherapy presents a unique opportunity to incorporate advanced systems and synthetic biology approaches to create cancer therapeutics with novel functions. We first review the development of synthetic receptors, switches, and circuits to control the location, duration, and strength of T cell activity against tumors. In addition, we discuss the cellular engineering and genome editing of host cells (or the chassis) to improve the efficacy of cell-based cancer therapeutics, and to reduce the time and cost of manufacturing. Copyright © 2015 Elsevier Ltd. All rights reserved.
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A Synthetic Biology Framework for Programming Eukaryotic Transcription Functions
Khalil, Ahmad S.; Lu, Timothy K.; Bashor, Caleb J.; Ramirez, Cherie L.; Pyenson, Nora C.; Joung, J. Keith; Collins, James J.
2013-01-01
SUMMARY Eukaryotic transcription factors (TFs) perform complex and combinatorial functions within transcriptional networks. Here, we present a synthetic framework for systematically constructing eukaryotic transcription functions using artificial zinc fingers, modular DNA-binding domains found within many eukaryotic TFs. Utilizing this platform, we construct a library of orthogonal synthetic transcription factors (sTFs) and use these to wire synthetic transcriptional circuits in yeast. We engineer complex functions, such as tunable output strength and transcriptional cooperativity, by rationally adjusting a decomposed set of key component properties, e.g., DNA specificity, affinity, promoter design, protein-protein interactions. We show that subtle perturbations to these properties can transform an individual sTF between distinct roles (activator, cooperative factor, inhibitory factor) within a transcriptional complex, thus drastically altering the signal processing behavior of multi-input systems. This platform provides new genetic components for synthetic biology and enables bottom-up approaches to understanding the design principles of eukaryotic transcriptional complexes and networks. PMID:22863014
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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 ...
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Attraction Basins as Gauges of Robustness against Boundary Conditions in Biological Complex Systems
Demongeot, Jacques; Goles, Eric; Morvan, Michel; Noual, Mathilde; Sené, Sylvain
2010-01-01
One fundamental concept in the context of biological systems on which researches have flourished in the past decade is that of the apparent robustness of these systems, i.e., their ability to resist to perturbations or constraints induced by external or boundary elements such as electromagnetic fields acting on neural networks, micro-RNAs acting on genetic networks and even hormone flows acting both on neural and genetic networks. Recent studies have shown the importance of addressing the question of the environmental robustness of biological networks such as neural and genetic networks. In some cases, external regulatory elements can be given a relevant formal representation by assimilating them to or modeling them by boundary conditions. This article presents a generic mathematical approach to understand the influence of boundary elements on the dynamics of regulation networks, considering their attraction basins as gauges of their robustness. The application of this method on a real genetic regulation network will point out a mathematical explanation of a biological phenomenon which has only been observed experimentally until now, namely the necessity of the presence of gibberellin for the flower of the plant Arabidopsis thaliana to develop normally. PMID:20700525
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Attraction basins as gauges of robustness against boundary conditions in biological complex systems.
Directory of Open Access Journals (Sweden)
Jacques Demongeot
Full Text Available One fundamental concept in the context of biological systems on which researches have flourished in the past decade is that of the apparent robustness of these systems, i.e., their ability to resist to perturbations or constraints induced by external or boundary elements such as electromagnetic fields acting on neural networks, micro-RNAs acting on genetic networks and even hormone flows acting both on neural and genetic networks. Recent studies have shown the importance of addressing the question of the environmental robustness of biological networks such as neural and genetic networks. In some cases, external regulatory elements can be given a relevant formal representation by assimilating them to or modeling them by boundary conditions. This article presents a generic mathematical approach to understand the influence of boundary elements on the dynamics of regulation networks, considering their attraction basins as gauges of their robustness. The application of this method on a real genetic regulation network will point out a mathematical explanation of a biological phenomenon which has only been observed experimentally until now, namely the necessity of the presence of gibberellin for the flower of the plant Arabidopsis thaliana to develop normally.
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Robust modified GA based multi-stage fuzzy LFC
International Nuclear Information System (INIS)
Shayeghi, H.; Jalili, A.; Shayanfar, H.A.
2007-01-01
In this paper, a robust genetic algorithm (GA) based multi-stage fuzzy (MSF) controller is proposed for solution of the load frequency control (LFC) problem in a restructured power system that operates under deregulation based on the bilateral policy scheme. In this strategy, the control signal is tuned online from the knowledge base and the fuzzy inference, which request fewer sources and has two rule base sets. In the proposed method, for achieving the desired level of robust performance, exact tuning of the membership functions is very important. Thus, to reduce the design effort and find a better fuzzy system control, membership functions are designed automatically by modified genetic algorithms. The classical genetic algorithms are powerful search techniques to find the global optimal area. However, the global optimum value is not guaranteed using this method, and the speed of the algorithm's convergence is extremely reduced too. To overcome this drawback, a modified genetic algorithm is being used to tune the membership functions of the proposed MSF controller. The effectiveness of the proposed method is demonstrated on a three area restructured power system with possible contracted scenarios under large load demand and area disturbances in comparison with the multi-stage fuzzy and classical fuzzy PID controllers through FD and ITAE performance indices. The results evaluation shows that the proposed control strategy achieves good robust performance for a wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other controllers. Moreover, this newly developed control strategy has a simple structure, does not require an accurate model of the plant and is fairly easy to implement, which can be useful for the real world complex power systems
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Robust modified GA based multi-stage fuzzy LFC
Energy Technology Data Exchange (ETDEWEB)
Shayeghi, H. [Technical Engineering Department, The University of Mohaghegh Ardebili, Daneshkah St., Ardebil (Iran); Jalili, A. [Electrical Engineering Group, Islamic Azad University, Ardebil Branch, Ardebil (Iran); Shayanfar, H.A. [Electrical Engineering Department, Iran University of Science and Technology, Tehran (Iran)
2007-05-15
In this paper, a robust genetic algorithm (GA) based multi-stage fuzzy (MSF) controller is proposed for solution of the load frequency control (LFC) problem in a restructured power system that operates under deregulation based on the bilateral policy scheme. In this strategy, the control signal is tuned online from the knowledge base and the fuzzy inference, which request fewer sources and has two rule base sets. In the proposed method, for achieving the desired level of robust performance, exact tuning of the membership functions is very important. Thus, to reduce the design effort and find a better fuzzy system control, membership functions are designed automatically by modified genetic algorithms. The classical genetic algorithms are powerful search techniques to find the global optimal area. However, the global optimum value is not guaranteed using this method, and the speed of the algorithm's convergence is extremely reduced too. To overcome this drawback, a modified genetic algorithm is being used to tune the membership functions of the proposed MSF controller. The effectiveness of the proposed method is demonstrated on a three area restructured power system with possible contracted scenarios under large load demand and area disturbances in comparison with the multi-stage fuzzy and classical fuzzy PID controllers through FD and ITAE performance indices. The results evaluation shows that the proposed control strategy achieves good robust performance for a wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other controllers. Moreover, this newly developed control strategy has a simple structure, does not require an accurate model of the plant and is fairly easy to implement, which can be useful for the real world complex power systems. (author)
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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...
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Basic science through engineering? Synthetic modeling and the idea of biology-inspired engineering.
Knuuttila, Tarja; Loettgers, Andrea
2013-06-01
Synthetic biology is often understood in terms of the pursuit for well-characterized biological parts to create synthetic wholes. Accordingly, it has typically been conceived of as an engineering dominated and application oriented field. We argue that the relationship of synthetic biology to engineering is far more nuanced than that and involves a sophisticated epistemic dimension, as shown by the recent practice of synthetic modeling. Synthetic models are engineered genetic networks that are implanted in a natural cell environment. Their construction is typically combined with experiments on model organisms as well as mathematical modeling and simulation. What is especially interesting about this combinational modeling practice is that, apart from greater integration between these different epistemic activities, it has also led to the questioning of some central assumptions and notions on which synthetic biology is based. As a result synthetic biology is in the process of becoming more "biology inspired." Copyright © 2013 Elsevier Ltd. All rights reserved.
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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...
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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.
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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.
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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.
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Synthetic Biology to Engineer Bacteriophage Genomes.
Rita Costa, Ana; Milho, Catarina; Azeredo, Joana; Pires, Diana Priscila
2018-01-01
Recent advances in the synthetic biology field have enabled the development of new molecular biology techniques used to build specialized bacteriophages with new functionalities. Bacteriophages have been engineered towards a wide range of applications including pathogen control and detection, targeted drug delivery, or even assembly of new materials.In this chapter, two strategies that have been successfully used to genetically engineer bacteriophage genomes are addressed: a yeast-based platform and bacteriophage recombineering of electroporated DNA.
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Molecular analysis of genetic diversity in elite II synthetic hexaploid ...
African Journals Online (AJOL)
STORAGESEVER
2009-07-20
Jul 20, 2009 ... The presence of sufficient genetic diversity in the germplam is an important ..... Figure 1. PCR amplification profile of Elite-II SH Wheat using the primer OPG-2. .... genetic relationships among cowpea breeding lines and local.
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Robust Optimization for Time-Cost Tradeoff Problem in Construction Projects
Directory of Open Access Journals (Sweden)
Ming Li
2014-01-01
Full Text Available Construction projects are generally subject to uncertainty, which influences the realization of time-cost tradeoff in project management. This paper addresses a time-cost tradeoff problem under uncertainty, in which activities in projects can be executed in different construction modes corresponding to specified time and cost with interval uncertainty. Based on multiobjective robust optimization method, a robust optimization model for time-cost tradeoff problem is developed. In order to illustrate the robust model, nondominated sorting genetic algorithm-II (NSGA-II is modified to solve the project example. The results show that, by means of adjusting the time and cost robust coefficients, the robust Pareto sets for time-cost tradeoff can be obtained according to different acceptable risk level, from which the decision maker could choose the preferred construction alternative.
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Evaluation of cytoplasmic genetic effects for production and ...
African Journals Online (AJOL)
uvp
2014-12-03
Dec 3, 2014 ... Cytoplasmic genetic effects are transmitted directly only from mother to offspring through mitochondrial DNA. Normal genetic .... inheritance in three synthetic lines of beef cattle differing in mature size. J. Anim. Sci. 69, 745.
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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
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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)
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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.
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Preparing Synthetic Biology for the World
Directory of Open Access Journals (Sweden)
Gerd H.G. Moe-Behrens
2013-01-01
Full Text Available Synthetic Biology promises low-cost, exponentially scalable products and global health solutions in the form of self-replicating organisms, or living devices. As these promises are realized, proof-of-concept systems will gradually migrate from tightly regulated laboratory or industrial environments into private spaces as, for instance, probiotic health products, food, and even do-it-yourself bioengineered systems. What additional steps, if any, should be taken before releasing engineered self-replicating organisms into a broader user space? In this review, we explain how studies of genetically modified organisms lay groundwork for the future landscape of biosafety. Early in the design process, biological engineers are anticipating potential hazards and developing innovative tools to mitigate risk. Here, we survey lessons learned, ongoing efforts to engineer intrinsic biocontainment, and how different stakeholders in synthetic biology can act to accomplish best practices for biosafety.
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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
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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...
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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
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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.
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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.
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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.
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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.
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Is there anything unique in the ethics of synthetic biology?
Heyd, David
2012-01-01
Synthetic biology does not create any ethical dilemmas that have not already been raised in the development of practices such as genetic screening, genetic engineering, and other interventions in the evolutionary processes. The issue is, nevertheless, ethically serious. Two different angles are examined: the philosophical legitimacy of human intervention in the shaping of human nature, and the more pragmatic (though by no means less important) question of the risks involved in such a novel line of research. As for the first, the claim made here is that in principle there is no constraint in human intervention in the world, since ultimately the source of any value lies in human interests, welfare, and values. This is an approach that is opposite to Habermas's. As for the practical problem of risk, research in synthetic biology calls for particular caution, since in at least the first stages of a new research or program, there is no social regulation, and society is wholly dependent on the scientist's ethical integrity.
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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.
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Synthetic biology approaches in drug discovery and pharmaceutical biotechnology.
Neumann, Heinz; Neumann-Staubitz, Petra
2010-06-01
Synthetic biology is the attempt to apply the concepts of engineering to biological systems with the aim to create organisms with new emergent properties. These organisms might have desirable novel biosynthetic capabilities, act as biosensors or help us to understand the intricacies of living systems. This approach has the potential to assist the discovery and production of pharmaceutical compounds at various stages. New sources of bioactive compounds can be created in the form of genetically encoded small molecule libraries. The recombination of individual parts has been employed to design proteins that act as biosensors, which could be used to identify and quantify molecules of interest. New biosynthetic pathways may be designed by stitching together enzymes with desired activities, and genetic code expansion can be used to introduce new functionalities into peptides and proteins to increase their chemical scope and biological stability. This review aims to give an insight into recently developed individual components and modules that might serve as parts in a synthetic biology approach to pharmaceutical biotechnology.
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Cell-free synthetic biology for environmental sensing and remediation.
Karig, David K
2017-06-01
The fields of biosensing and bioremediation leverage the phenomenal array of sensing and metabolic capabilities offered by natural microbes. Synthetic biology provides tools for transforming these fields through complex integration of natural and novel biological components to achieve sophisticated sensing, regulation, and metabolic function. However, the majority of synthetic biology efforts are conducted in living cells, and concerns over releasing genetically modified organisms constitute a key barrier to environmental applications. Cell-free protein expression systems offer a path towards leveraging synthetic biology, while preventing the spread of engineered organisms in nature. Recent efforts in the areas of cell-free approaches for sensing, regulation, and metabolic pathway implementation, as well as for preserving and deploying cell-free expression components, embody key steps towards realizing the potential of cell-free systems for environmental sensing and remediation. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.
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RAPD and SSR based genetic diversity analysis of elite-2 set of ...
African Journals Online (AJOL)
Background: Synthetic hexaploid wheats are artificially reconstituted hexaploid wheats that possess high genetic variation which could be utilized for the development of new improved wheat varieties. One such group of synthetic wheats is called the Elite-II set of synthetic wheats that are derived from crossing durum wheat ...
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Synthetic Biology and Ethics: Past, Present, and Future.
Häyry, Matti
2017-04-01
This article explores the ethical issues that have been identified in emerging technologies, from early genetic engineering to synthetic biology. The scientific advances in the field form a continuum, and some ethical considerations can be raised time and again when new developments occur. An underlying concern is the cumulative effect of scientific advances and ensuing technological innovation that can change our understanding of life and humanity.
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An Evolutionary Approach for Robust Layout Synthesis of MEMS
DEFF Research Database (Denmark)
Fan, Zhun; Wang, Jiachuan; Goodman, Erik
2005-01-01
The paper introduces a robust design method for layout synthesis of MEM resonators subject to inherent geometric uncertainties such as the fabrication error on the sidewall of the structure. The robust design problem is formulated as a multi-objective constrained optimisation problem after certain...... assumptions and treated with multiobjective genetic algorithm (MOGA), a special type of evolutionary computing approaches. Case study based on layout synthesis of a comb-driven MEM resonator shows that the approach proposed in this paper can lead to design results that meet the target performance and are less...
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Directory of Open Access Journals (Sweden)
Mohammad Anis
2012-05-01
Full Text Available An efficient method was developed for plant regeneration and establishment from alginate encapsulated synthetic seeds of Rauvolfia serpentina. Synthetic seeds were produced using in vitro proliferated microshoots upon complexation of 3% sodium alginate prepared in Llyod and McCown woody plant medium (WPM and 100 mM calcium chloride. Re-growth ability of encapsulated nodal segments was evaluated after storage at 4 °C for 0, 1, 2, 4, 6 and 8 weeks and compared with non-encapsulated buds. Effects of different media viz; Murashige and Skoog medium; Lloyd and McCown woody Plant medium, Gamborg’s B5 medium and Schenk and Hildebrandt medium was also investigated for conversion into plantlets. The maximum frequency of conversion into plantlets from encapsulated nodal segments stored at 4 °C for 4 weeks was achieved on woody plant medium supplement with 5.0 μM BA and 1.0 μM NAA. Rooting in plantlets was achieved in half-strength Murashige and Skoog liquid medium containing 0.5 μM indole-3-acetic acid (IAA on filter paper bridges. Plantlets obtained from stored synseeds were hardened, established successfully ex vitro and were morphologically similar to each other as well as their mother plant. The genetic fidelity of Rauvolfia clones raised from synthetic seeds following four weeks of storage at 4 °C were assessed by using random amplified polymorphic DNA (RAPD and inter-simple sequence repeat (ISSR markers. All the RAPD and ISSR profiles from generated plantlets were monomorphic and comparable to the mother plant, which confirms the genetic stability among the clones. This synseed protocol could be useful for establishing a particular system for conservation, short-term storage and production of genetically identical and stable plants before it is released for commercial purposes.
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Beach, Dale L.; Alvarez, Consuelo J.
2015-01-01
Synthetic biology offers an ideal opportunity to promote undergraduate laboratory courses with research-style projects, immersing students in an inquiry-based program that enhances the experience of the scientific process. We designed a semester-long, project-based laboratory curriculum using synthetic biology principles to develop a novel sensory device. Students develop subject matter knowledge of molecular genetics and practical skills relevant to molecular biology, recombinant DNA techniq...
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A multiobjective approach to the genetic code adaptability problem.
de Oliveira, Lariza Laura; de Oliveira, Paulo S L; Tinós, Renato
2015-02-19
The organization of the canonical code has intrigued researches since it was first described. If we consider all codes mapping the 64 codes into 20 amino acids and one stop codon, there are more than 1.51×10(84) possible genetic codes. The main question related to the organization of the genetic code is why exactly the canonical code was selected among this huge number of possible genetic codes. Many researchers argue that the organization of the canonical code is a product of natural selection and that the code's robustness against mutations would support this hypothesis. In order to investigate the natural selection hypothesis, some researches employ optimization algorithms to identify regions of the genetic code space where best codes, according to a given evaluation function, can be found (engineering approach). The optimization process uses only one objective to evaluate the codes, generally based on the robustness for an amino acid property. Only one objective is also employed in the statistical approach for the comparison of the canonical code with random codes. We propose a multiobjective approach where two or more objectives are considered simultaneously to evaluate the genetic codes. In order to test our hypothesis that the multiobjective approach is useful for the analysis of the genetic code adaptability, we implemented a multiobjective optimization algorithm where two objectives are simultaneously optimized. Using as objectives the robustness against mutation with the amino acids properties polar requirement (objective 1) and robustness with respect to hydropathy index or molecular volume (objective 2), we found solutions closer to the canonical genetic code in terms of robustness, when compared with the results using only one objective reported by other authors. Using more objectives, more optimal solutions are obtained and, as a consequence, more information can be used to investigate the adaptability of the genetic code. The multiobjective approach
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A Parvovirus B19 synthetic genome: sequence features and functional competence.
Manaresi, Elisabetta; Conti, Ilaria; Bua, Gloria; Bonvicini, Francesca; Gallinella, Giorgio
2017-08-01
Central to genetic studies for Parvovirus B19 (B19V) is the availability of genomic clones that may possess functional competence and ability to generate infectious virus. In our study, we established a new model genetic system for Parvovirus B19. A synthetic approach was followed, by design of a reference genome sequence, by generation of a corresponding artificial construct and its molecular cloning in a complete and functional form, and by setup of an efficient strategy to generate infectious virus, via transfection in UT7/EpoS1 cells and amplification in erythroid progenitor cells. The synthetic genome was able to generate virus with biological properties paralleling those of native virus, its infectious activity being dependent on the preservation of self-complementarity and sequence heterogeneity within the terminal regions. A virus of defined genome sequence, obtained from controlled cell culture conditions, can constitute a reference tool for investigation of the structural and functional characteristics of the virus. Copyright © 2017 Elsevier Inc. All rights reserved.
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Robust Parameter Coordination for Multidisciplinary Design
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
This paper introduced a robust parameter coordination method to analyze parameter uncertainties so as to predict conflicts and coordinate parameters in multidisciplinary design. The proposed method is based on constraints network, which gives a formulated model to analyze the coupling effects between design variables and product specifications. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. To solve this constraint network model, a general consistent algorithm framework is designed and implemented with interval arithmetic and the genetic algorithm, which can deal with both algebraic and ordinary differential equations. With the help of this method, designers could infer the consistent solution space from the given specifications. A case study involving the design of a bogie dumping system demonstrates the usefulness of this approach.
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Reverse engineering large-scale genetic networks: synthetic versus ...
Indian Academy of Sciences (India)
2010-04-19
Apr 19, 2010 ... process computationally to describe the structure of the sys- tem and ... to the different mathematical formalisms used to model net-. Keywords. gene ..... All the algorithms were implemented in MATLAB 7.0 and run on all the 'gold ..... De Jong H. 2002 Medeling and simulation of genetic regulatory systems: a ...
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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.
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Robust Optimization of Fourth Party Logistics Network Design under Disruptions
Directory of Open Access Journals (Sweden)
Jia Li
2015-01-01
Full Text Available The Fourth Party Logistics (4PL network faces disruptions of various sorts under the dynamic and complex environment. In order to explore the robustness of the network, the 4PL network design with consideration of random disruptions is studied. The purpose of the research is to construct a 4PL network that can provide satisfactory service to customers at a lower cost when disruptions strike. Based on the definition of β-robustness, a robust optimization model of 4PL network design under disruptions is established. Based on the NP-hard characteristic of the problem, the artificial fish swarm algorithm (AFSA and the genetic algorithm (GA are developed. The effectiveness of the algorithms is tested and compared by simulation examples. By comparing the optimal solutions of the 4PL network for different robustness level, it is indicated that the robust optimization model can evade the market risks effectively and save the cost in the maximum limit when it is applied to 4PL network design.
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Genetic improvement of vegetables
International Nuclear Information System (INIS)
Jaramillo Vasquez, J.G.
2001-01-01
Some genetic bases of the improvement of vegetables are given. The objectives of the genetic improvement and the fundamental stages of this process are done. The sources of genetic variation are indicated and they are related the reproduction systems of the main horticultural species. It is analyzed the concept of genetic inheritance like base to determine the procedures more appropriate of improvement. The approaches are discussed, has more than enough phenotypic value, genetic action and genotypic variance; Equally the heredability concepts and value of improvement. The conventional methods of improvement are described, like they are: the introduction of species or varieties, the selection, the pure line, the pedigree method, the selection for families, the recurrent selection, the selection for unique seed, the haploids method, the selection for heterosis and the synthetic varieties
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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 ...
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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....
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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
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The SBOL Stack: A Platform for Storing, Publishing, and Sharing Synthetic Biology Designs.
Madsen, Curtis; McLaughlin, James Alastair; Mısırlı, Göksel; Pocock, Matthew; Flanagan, Keith; Hallinan, Jennifer; Wipat, Anil
2016-06-17
Recently, synthetic biologists have developed the Synthetic Biology Open Language (SBOL), a data exchange standard for descriptions of genetic parts, devices, modules, and systems. The goals of this standard are to allow scientists to exchange designs of biological parts and systems, to facilitate the storage of genetic designs in repositories, and to facilitate the description of genetic designs in publications. In order to achieve these goals, the development of an infrastructure to store, retrieve, and exchange SBOL data is necessary. To address this problem, we have developed the SBOL Stack, a Resource Description Framework (RDF) database specifically designed for the storage, integration, and publication of SBOL data. This database allows users to define a library of synthetic parts and designs as a service, to share SBOL data with collaborators, and to store designs of biological systems locally. The database also allows external data sources to be integrated by mapping them to the SBOL data model. The SBOL Stack includes two Web interfaces: the SBOL Stack API and SynBioHub. While the former is designed for developers, the latter allows users to upload new SBOL biological designs, download SBOL documents, search by keyword, and visualize SBOL data. Since the SBOL Stack is based on semantic Web technology, the inherent distributed querying functionality of RDF databases can be used to allow different SBOL stack databases to be queried simultaneously, and therefore, data can be shared between different institutes, centers, or other users.
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Robust Layout Synthesis of a MEM Crab-Leg Resonator Using a Constrained Genetic Algorithm
DEFF Research Database (Denmark)
Fan, Zhun; Achiche, Sofiane
2007-01-01
The research work carried out in this paper introduces a robust design method for layout synthesis of MEM resonator subject to inherent geometric uncertainties such as the fabrication error on the sidewall of the structure. The robust design problem is formulated as a multi-objective constrained...
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The power and robustness of maximum LOD score statistics.
Yoo, Y J; Mendell, N R
2008-07-01
The maximum LOD score statistic is extremely powerful for gene mapping when calculated using the correct genetic parameter value. When the mode of genetic transmission is unknown, the maximum of the LOD scores obtained using several genetic parameter values is reported. This latter statistic requires higher critical value than the maximum LOD score statistic calculated from a single genetic parameter value. In this paper, we compare the power of maximum LOD scores based on three fixed sets of genetic parameter values with the power of the LOD score obtained after maximizing over the entire range of genetic parameter values. We simulate family data under nine generating models. For generating models with non-zero phenocopy rates, LOD scores maximized over the entire range of genetic parameters yielded greater power than maximum LOD scores for fixed sets of parameter values with zero phenocopy rates. No maximum LOD score was consistently more powerful than the others for generating models with a zero phenocopy rate. The power loss of the LOD score maximized over the entire range of genetic parameters, relative to the maximum LOD score calculated using the correct genetic parameter value, appeared to be robust to the generating models.
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Introduction to focus issue: quantitative approaches to genetic networks.
Albert, Réka; Collins, James J; Glass, Leon
2013-06-01
All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks
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Experiential Engineering through iGEM--An Undergraduate Summer Competition in Synthetic Biology
Mitchell, Rudolph; Dori, Yehudit Judy; Kuldell, Natalie H.
2011-01-01
Unlike students in other engineering disciplines, undergraduates in biological engineering typically have limited opportunity to develop design competencies, and even fewer chances to implement their designed projects. The international Genetically Engineered Machines (iGEM) competition is a student Synthetic Biology competition that, in 2009,…
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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.
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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).
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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.
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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.
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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…
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Beach, Dale L; Alvarez, Consuelo J
2015-12-01
Synthetic biology offers an ideal opportunity to promote undergraduate laboratory courses with research-style projects, immersing students in an inquiry-based program that enhances the experience of the scientific process. We designed a semester-long, project-based laboratory curriculum using synthetic biology principles to develop a novel sensory device. Students develop subject matter knowledge of molecular genetics and practical skills relevant to molecular biology, recombinant DNA techniques, and information literacy. During the spring semesters of 2014 and 2015, the Synthetic Biology Laboratory Project was delivered to sophomore genetics courses. Using a cloning strategy based on standardized BioBrick genetic "parts," students construct a "reporter plasmid" expressing a reporter gene (GFP) controlled by a hybrid promoter regulated by the lac-repressor protein (lacI). In combination with a "sensor plasmid," the production of the reporter phenotype is inhibited in the presence of a target environmental agent, arabinose. When arabinose is absent, constitutive GFP expression makes cells glow green. But the presence of arabinose activates a second promoter (pBAD) to produce a lac-repressor protein that will inhibit GFP production. Student learning was assessed relative to five learning objectives, using a student survey administered at the beginning (pre-survey) and end (post-survey) of the course, and an additional 15 open-ended questions from five graded Progress Report assignments collected throughout the course. Students demonstrated significant learning gains (p Biology Laboratory Project enhanced their understanding of molecular genetics. The laboratory project is highly adaptable for both introductory and advanced courses.
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Synthetic review on the genetic relatedness between North Africa ...
African Journals Online (AJOL)
... genetic markers are associated with certain aspects of human culture like languages, ... In the Middle East, the predominant categories of Y chromosomes are ... less frequency than the Middle Eastern ones, showing an important paternal ...
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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.
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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
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VisBOL: Web-Based Tools for Synthetic Biology Design Visualization.
McLaughlin, James Alastair; Pocock, Matthew; Mısırlı, Göksel; Madsen, Curtis; Wipat, Anil
2016-08-19
VisBOL is a Web-based application that allows the rendering of genetic circuit designs, enabling synthetic biologists to visually convey designs in SBOL visual format. VisBOL designs can be exported to formats including PNG and SVG images to be embedded in Web pages, presentations and publications. The VisBOL tool enables the automated generation of visualizations from designs specified using the Synthetic Biology Open Language (SBOL) version 2.0, as well as a range of well-known bioinformatics formats including GenBank and Pigeoncad notation. VisBOL is provided both as a user accessible Web site and as an open-source (BSD) JavaScript library that can be used to embed diagrams within other content and software.
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Wan, Y.
2013-06-01
Brainbow is a genetic engineering technique that randomly colorizes cells. Biological samples processed with this technique and imaged with confocal microscopy have distinctive colors for individual cells. Complex cellular structures can then be easily visualized. However, the complexity of the Brainbow technique limits its applications. In practice, most confocal microscopy scans use different florescence staining with typically at most three distinct cellular structures. These structures are often packed and obscure each other in rendered images making analysis difficult. In this paper, we leverage a process known as GPU framebuffer feedback loops to synthesize Brainbow-like images. In addition, we incorporate ID shuffing and Monte-Carlo sampling into our technique, so that it can be applied to single-channel confocal microscopy data. The synthesized Brainbow images are presented to domain experts with positive feedback. A user survey demonstrates that our synthetic Brainbow technique improves visualizations of volume data with complex structures for biologists.
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Hiemstra, H S; van Veelen, P A; Schloot, N C; Geluk, A; van Meijgaarden, K E; Willemen, S J; Leunissen, J A; Benckhuijsen, W E; Amons, R; de Vries, R R; Roep, B O; Ottenhoff, T H; Drijfhout, J W
1998-10-15
Progress has recently been made in the use of synthetic peptide libraries for the identification of T cell-stimulating ligands. T cell epitopes identified from synthetic libraries are mimics of natural epitopes. Here we show how the mimicry epitopes obtained from synthetic peptide libraries enable unambiguous identification of natural T cell Ags. Synthetic peptide libraries were screened with Mycobacterium tuberculosis-reactive and -autoreactive T cell clones. In two cases, database homology searches with mimicry epitopes isolated from a dedicated synthetic peptide library allowed immediate identification of the natural antigenic protein. In two other cases, an amino acid pattern that reflected the epitope requirements of the T cell was determined by substitution and omission mixture analysis. Subsequently, the natural Ag was identified from databases using this refined pattern. This approach opens new perspectives for rapid and reliable Ag definition, representing a feasible alternative to the biochemical and genetic approaches described thus far.
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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.
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Promoting microbiology education through the iGEM synthetic biology competition.
Kelwick, Richard; Bowater, Laura; Yeoman, Kay H; Bowater, Richard P
2015-08-01
Synthetic biology has developed rapidly in the 21st century. It covers a range of scientific disciplines that incorporate principles from engineering to take advantage of and improve biological systems, often applied to specific problems. Methods important in this subject area include the systematic design and testing of biological systems and, here, we describe how synthetic biology projects frequently develop microbiology skills and education. Synthetic biology research has huge potential in biotechnology and medicine, which brings important ethical and moral issues to address, offering learning opportunities about the wider impact of microbiological research. Synthetic biology projects have developed into wide-ranging training and educational experiences through iGEM, the International Genetically Engineered Machines competition. Elements of the competition are judged against specific criteria and teams can win medals and prizes across several categories. Collaboration is an important element of iGEM, and all DNA constructs synthesized by iGEM teams are made available to all researchers through the Registry for Standard Biological Parts. An overview of microbiological developments in the iGEM competition is provided. This review is targeted at educators that focus on microbiology and synthetic biology, but will also be of value to undergraduate and postgraduate students with an interest in this exciting subject area. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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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.
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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.
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Cryptic Genetic Variation in Evolutionary Developmental Genetics
Directory of Open Access Journals (Sweden)
Annalise B. Paaby
2016-06-01
Full Text Available Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes—processes that cannot be fully observed in continuously varying visible traits.
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Tian, Li-Ping; Wang, Jianxin; Wu, Fang-Xiang
2012-09-01
The study of stability is essential for designing or controlling genetic regulatory networks, which can be described by nonlinear differential equations with time delays. Much attention has been paid to the study of delay-independent stability of genetic regulatory networks and as a result, many sufficient conditions have been derived for delay-independent stability. Although it might be more interesting in practice, delay-dependent stability of genetic regulatory networks has been studied insufficiently. Based on the linear matrix inequality (LMI) approach, in this study we will present some delay-dependent stability conditions for genetic regulatory networks. Then we extend these results to genetic regulatory networks with parameter uncertainties. To illustrate the effectiveness of our theoretical results, gene repressilatory networks are analyzed .
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Directory of Open Access Journals (Sweden)
Othman M. K. Alsmadi
2015-01-01
Full Text Available A robust computational technique for model order reduction (MOR of multi-time-scale discrete systems (single input single output (SISO and multi-input multioutput (MIMO is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.
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Shi, Zhenyu; Vickers, Claudia E
2016-12-01
Molecular Cloning Designer Simulator (MCDS) is a powerful new all-in-one cloning and genetic engineering design, simulation and management software platform developed for complex synthetic biology and metabolic engineering projects. In addition to standard functions, it has a number of features that are either unique, or are not found in combination in any one software package: (1) it has a novel interactive flow-chart user interface for complex multi-step processes, allowing an integrated overview of the whole project; (2) it can perform a user-defined workflow of cloning steps in a single execution of the software; (3) it can handle multiple types of genetic recombineering, a technique that is rapidly replacing classical cloning for many applications; (4) it includes experimental information to conveniently guide wet lab work; and (5) it can store results and comments to allow the tracking and management of the whole project in one platform. MCDS is freely available from https://mcds.codeplex.com.
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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
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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.
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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.
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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
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Hybrid Robust Optimization for the Design of a Smartphone Metal Frame Antenna
Directory of Open Access Journals (Sweden)
Sungwoo Lee
2018-01-01
Full Text Available Hybrid robust optimization that combines a genetical swarm optimization (GSO scheme with an orthogonal array (OA is proposed to design an antenna robust to the tolerances arising during the fabrication process of the antenna in this paper. An inverted-F antenna with a metal frame serves as an example to explain the procedure of the proposed method. GSO is adapted to determine the design variables of the antenna, which operates on the GSM850 band (824–894 MHz. The robustness of the antenna is evaluated through a noise test using the OA. The robustness of the optimized antenna is improved by approximately 61.3% relative to that of a conventional antenna. Conventional and optimized antennas are fabricated and measured to validate the experimental results.
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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.
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[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.
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Synthetic Biology: Engineering, Evolution and Design (SEED) Conference 2014
Energy Technology Data Exchange (ETDEWEB)
Voigt, Christopher [Massachusetts Institute of Technology
2014-07-01
SEED2014 focused on advances in the science and technology emerging from the field of synthetic biology. We broadly define this as technologies that accelerate the process of genetic engineering. It highlighted new tool development, as well as the application of these tools to diverse problems in biotechnology, including therapeutics, industrial chemicals and fuels, natural products, and agriculture. Systems spanned from in vitro experiments and viruses, through diverse bacteria, to eukaryotes (yeast, mammalian cells, plants).
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Improving microalgae for biotechnology - From genetics to synthetic biology
Czech Academy of Sciences Publication Activity Database
Hlavová, Monika; Turóczy, Zoltán; Bišová, Kateřina
2015-01-01
Roč. 33, č. 6 (2015), s. 1194-1203 ISSN 0734-9750 R&D Projects: GA MŠk EE2.3.30.0059; GA MŠk ED2.1.00/03.0110 Institutional support: RVO:61388971 Keywords : Microalgae * Genetics * Mutagenesis Subject RIV: EE - Microbiology, Virology Impact factor: 9.848, year: 2015
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Robust optimization of a tandem grating solar thermal absorber
Choi, Jongin; Kim, Mingeon; Kang, Kyeonghwan; Lee, Ikjin; Lee, Bong Jae
2018-04-01
Ideal solar thermal absorbers need to have a high value of the spectral absorptance in the broad solar spectrum to utilize the solar radiation effectively. Majority of recent studies about solar thermal absorbers focus on achieving nearly perfect absorption using nanostructures, whose characteristic dimension is smaller than the wavelength of sunlight. However, precise fabrication of such nanostructures is not easy in reality; that is, unavoidable errors always occur to some extent in the dimension of fabricated nanostructures, causing an undesirable deviation of the absorption performance between the designed structure and the actually fabricated one. In order to minimize the variation in the solar absorptance due to the fabrication error, the robust optimization can be performed during the design process. However, the optimization of solar thermal absorber considering all design variables often requires tremendous computational costs to find an optimum combination of design variables with the robustness as well as the high performance. To achieve this goal, we apply the robust optimization using the Kriging method and the genetic algorithm for designing a tandem grating solar absorber. By constructing a surrogate model through the Kriging method, computational cost can be substantially reduced because exact calculation of the performance for every combination of variables is not necessary. Using the surrogate model and the genetic algorithm, we successfully design an effective solar thermal absorber exhibiting a low-level of performance degradation due to the fabrication uncertainty of design variables.
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Schmidt, Markus; de Lorenzo, Víctor
2012-07-16
The plausible release of deeply engineered or even entirely synthetic/artificial microorganisms raises the issue of their intentional (e.g. bioremediation) or accidental interaction with the Environment. Containment systems designed in the 1980s-1990s for limiting the spread of genetically engineered bacteria and their recombinant traits are still applicable to contemporary Synthetic Biology constructs. Yet, the ease of DNA synthesis and the uncertainty on how non-natural properties and strains could interplay with the existing biological word poses yet again the challenge of designing safe and efficacious firewalls to curtail possible interactions. Such barriers may include xeno-nucleic acids (XNAs) instead of DNA as information-bearing molecules, rewriting the genetic code to make it non-understandable by the existing gene expression machineries, and/or making growth dependent on xenobiotic chemicals. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
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Reprint of Design of synthetic microbial communities for biotechnological production processes.
Jagmann, Nina; Philipp, Bodo
2014-12-20
In their natural habitats microorganisms live in multi-species communities, in which the community members exhibit complex metabolic interactions. In contrast, biotechnological production processes catalyzed by microorganisms are usually carried out with single strains in pure cultures. A number of production processes, however, may be more efficiently catalyzed by the concerted action of microbial communities. This review will give an overview of organismic interactions between microbial cells and of biotechnological applications of microbial communities. It focuses on synthetic microbial communities that consist of microorganisms that have been genetically engineered. Design principles for such synthetic communities will be exemplified based on plausible scenarios for biotechnological production processes. These design principles comprise interspecific metabolic interactions via cross-feeding, regulation by interspecific signaling processes via metabolites and autoinducing signal molecules, and spatial structuring of synthetic microbial communities. In particular, the implementation of metabolic interdependencies, of positive feedback regulation and of inducible cell aggregation and biofilm formation will be outlined. Synthetic microbial communities constitute a viable extension of the biotechnological application of metabolically engineered single strains and enlarge the scope of microbial production processes. Copyright © 2014 Elsevier B.V. All rights reserved.
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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.
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Kang, Zhen; Huang, Hao; Zhang, Yunfeng; Du, Guocheng; Chen, Jian
2017-01-01
Pichia pastoris: (reclassified as Komagataella phaffii), a methylotrophic yeast strain has been widely used for heterologous protein production because of its unique advantages, such as readily achievable high-density fermentation, tractable genetic modifications and typical eukaryotic post-translational modifications. More recently, P. pastoris as a metabolic pathway engineering platform has also gained much attention. In this mini-review, we addressed recent advances of molecular toolboxes, including synthetic promoters, signal peptides, and genome engineering tools that established for P. pastoris. Furthermore, the applications of P. pastoris towards synthetic biology were also discussed and prospected especially in the context of genome-scale metabolic pathway analysis.
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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...
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Complex and unexpected dynamics in simple genetic regulatory networks
Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey
2014-03-01
One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.
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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
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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
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Kesselmeier, Miriam; Lorenzo Bermejo, Justo
2017-11-01
Logistic regression is the most common technique used for genetic case-control association studies. A disadvantage of standard maximum likelihood estimators of the genotype relative risk (GRR) is their strong dependence on outlier subjects, for example, patients diagnosed at unusually young age. Robust methods are available to constrain outlier influence, but they are scarcely used in genetic studies. This article provides a non-intimidating introduction to robust logistic regression, and investigates its benefits and limitations in genetic association studies. We applied the bounded Huber and extended the R package 'robustbase' with the re-descending Hampel functions to down-weight outlier influence. Computer simulations were carried out to assess the type I error rate, mean squared error (MSE) and statistical power according to major characteristics of the genetic study and investigated markers. Simulations were complemented with the analysis of real data. Both standard and robust estimation controlled type I error rates. Standard logistic regression showed the highest power but standard GRR estimates also showed the largest bias and MSE, in particular for associated rare and recessive variants. For illustration, a recessive variant with a true GRR=6.32 and a minor allele frequency=0.05 investigated in a 1000 case/1000 control study by standard logistic regression resulted in power=0.60 and MSE=16.5. The corresponding figures for Huber-based estimation were power=0.51 and MSE=0.53. Overall, Hampel- and Huber-based GRR estimates did not differ much. Robust logistic regression may represent a valuable alternative to standard maximum likelihood estimation when the focus lies on risk prediction rather than identification of susceptibility variants. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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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
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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
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Energy Technology Data Exchange (ETDEWEB)
Madhavan, Aravind [Biotechnology Division, National Institute for Interdisciplinary Science and Technology, Council of Scientific and Industrial Research, Trivandrum (India); Rajiv Gandhi Centre for Biotechnology, Trivandrum (India); Jose, Anju Alphonsa; Binod, Parameswaran; Sindhu, Raveendran, E-mail: sindhurgcb@gmail.com; Sukumaran, Rajeev K. [Biotechnology Division, National Institute for Interdisciplinary Science and Technology, Council of Scientific and Industrial Research, Trivandrum (India); Pandey, Ashok [Biotechnology Division, National Institute for Interdisciplinary Science and Technology, Council of Scientific and Industrial Research, Trivandrum (India); Center for Innovative and Applied Bioprocessing, Mohali, Punjab (India); Castro, Galliano Eulogio [Dpt. Ingeniería Química, Ambiental y de los Materiales Edificio, Universidad de Jaén, Jaén (Spain)
2017-04-25
The increasing fossil fuel scarcity has led to an urgent need to develop alternative fuels. Currently microorganisms have been extensively used for the production of first-generation biofuels from lignocellulosic biomass. Yeast is the efficient producer of bioethanol among all existing biofuels option. Tools of synthetic biology have revolutionized the field of microbial cell factories especially in the case of ethanol and fatty acid production. Most of the synthetic biology tools have been developed for the industrial workhorse Saccharomyces cerevisiae. The non-conventional yeast systems have several beneficial traits like ethanol tolerance, thermotolerance, inhibitor tolerance, genetic diversity, etc., and synthetic biology have the power to expand these traits. Currently, synthetic biology is slowly widening to the non-conventional yeasts like Hansenula polymorpha, Kluyveromyces lactis, Pichia pastoris, and Yarrowia lipolytica. Herein, we review the basic synthetic biology tools that can apply to non-conventional yeasts. Furthermore, we discuss the recent advances employed to develop efficient biofuel-producing non-conventional yeast strains by metabolic engineering and synthetic biology with recent examples. Looking forward, future synthetic engineering tools’ development and application should focus on unexplored non-conventional yeast species.
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Directory of Open Access Journals (Sweden)
Raveendran Sindhu
2017-04-01
Full Text Available The increasing fossil fuel scarcity has led to an urgent need to develop alternative fuels. Currently microorganisms have been extensively used for the production of first-generation biofuels from lignocellulosic biomass. Yeast is the efficient producer of bioethanol among all existing biofuels option. Tools of synthetic biology have revolutionized the field of microbial cell factories especially in the case of ethanol and fatty acid production. Most of the synthetic biology tools have been developed for the industrial workhorse Saccharomyces cerevisiae. The non-conventional yeast systems have several beneficial traits like ethanol tolerance, thermotolerance, inhibitor tolerance, genetic diversity, etc., and synthetic biology have the power to expand these traits. Currently, synthetic biology is slowly widening to the non-conventional yeasts like Hansenula polymorpha, Kluyveromyces lactis, Pichia pastoris, and Yarrowia lipolytica. Herein, we review the basic synthetic biology tools that can apply to non-conventional yeasts. Furthermore, we discuss the recent advances employed to develop efficient biofuel-producing non-conventional yeast strains by metabolic engineering and synthetic biology with recent examples. Looking forward, future synthetic engineering tools’ development and application should focus on unexplored non-conventional yeast species.
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International Nuclear Information System (INIS)
Madhavan, Aravind; Jose, Anju Alphonsa; Binod, Parameswaran; Sindhu, Raveendran; Sukumaran, Rajeev K.; Pandey, Ashok; Castro, Galliano Eulogio
2017-01-01
The increasing fossil fuel scarcity has led to an urgent need to develop alternative fuels. Currently microorganisms have been extensively used for the production of first-generation biofuels from lignocellulosic biomass. Yeast is the efficient producer of bioethanol among all existing biofuels option. Tools of synthetic biology have revolutionized the field of microbial cell factories especially in the case of ethanol and fatty acid production. Most of the synthetic biology tools have been developed for the industrial workhorse Saccharomyces cerevisiae. The non-conventional yeast systems have several beneficial traits like ethanol tolerance, thermotolerance, inhibitor tolerance, genetic diversity, etc., and synthetic biology have the power to expand these traits. Currently, synthetic biology is slowly widening to the non-conventional yeasts like Hansenula polymorpha, Kluyveromyces lactis, Pichia pastoris, and Yarrowia lipolytica. Herein, we review the basic synthetic biology tools that can apply to non-conventional yeasts. Furthermore, we discuss the recent advances employed to develop efficient biofuel-producing non-conventional yeast strains by metabolic engineering and synthetic biology with recent examples. Looking forward, future synthetic engineering tools’ development and application should focus on unexplored non-conventional yeast species.
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Genetic Constructor: An Online DNA Design Platform.
Bates, Maxwell; Lachoff, Joe; Meech, Duncan; Zulkower, Valentin; Moisy, Anaïs; Luo, Yisha; Tekotte, Hille; Franziska Scheitz, Cornelia Johanna; Khilari, Rupal; Mazzoldi, Florencio; Chandran, Deepak; Groban, Eli
2017-12-15
Genetic Constructor is a cloud Computer Aided Design (CAD) application developed to support synthetic biologists from design intent through DNA fabrication and experiment iteration. The platform allows users to design, manage, and navigate complex DNA constructs and libraries, using a new visual language that focuses on functional parts abstracted from sequence. Features like combinatorial libraries and automated primer design allow the user to separate design from construction by focusing on functional intent, and design constraints aid iterative refinement of designs. A plugin architecture enables contributions from scientists and coders to leverage existing powerful software and connect to DNA foundries. The software is easily accessible and platform agnostic, free for academics, and available in an open-source community edition. Genetic Constructor seeks to democratize DNA design, manufacture, and access to tools and services from the synthetic biology community.
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Closed-Loop and Robust Control of Quantum Systems
Directory of Open Access Journals (Sweden)
Chunlin Chen
2013-01-01
Full Text Available For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA, and reinforcement learning (RL methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H∞ control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention.
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Closed-loop and robust control of quantum systems.
Chen, Chunlin; Wang, Lin-Cheng; Wang, Yuanlong
2013-01-01
For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control) have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA), and reinforcement learning (RL) methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H(∞) control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention.
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Selection Transforms the Landscape of Genetic Variation Interacting with Hsp90.
Geiler-Samerotte, Kerry A; Zhu, Yuan O; Goulet, Benjamin E; Hall, David W; Siegal, Mark L
2016-10-01
The protein-folding chaperone Hsp90 has been proposed to buffer the phenotypic effects of mutations. The potential for Hsp90 and other putative buffers to increase robustness to mutation has had major impact on disease models, quantitative genetics, and evolutionary theory. But Hsp90 sometimes contradicts expectations for a buffer by potentiating rapid phenotypic changes that would otherwise not occur. Here, we quantify Hsp90's ability to buffer or potentiate (i.e., diminish or enhance) the effects of genetic variation on single-cell morphological features in budding yeast. We corroborate reports that Hsp90 tends to buffer the effects of standing genetic variation in natural populations. However, we demonstrate that Hsp90 tends to have the opposite effect on genetic variation that has experienced reduced selection pressure. Specifically, Hsp90 tends to enhance, rather than diminish, the effects of spontaneous mutations and recombinations. This result implies that Hsp90 does not make phenotypes more robust to the effects of genetic perturbation. Instead, natural selection preferentially allows buffered alleles to persist and thereby creates the false impression that Hsp90 confers greater robustness.
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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.
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Demongeot, Jacques; Ben Amor, Hedi; Elena, Adrien; Gillois, Pierre; Noual, Mathilde; Sené, Sylvain
2009-01-01
Regulatory interaction networks are often studied on their dynamical side (existence of attractors, study of their stability). We focus here also on their robustness, that is their ability to offer the same spatiotemporal patterns and to resist to external perturbations such as losses of nodes or edges in the networks interactions architecture, changes in their environmental boundary conditions as well as changes in the update schedule (or updating mode) of the states of their elements (e.g., if these elements are genes, their synchronous coexpression mode versus their sequential expression). We define the generic notions of boundary, core, and critical vertex or edge of the underlying interaction graph of the regulatory network, whose disappearance causes dramatic changes in the number and nature of attractors (e.g., passage from a bistable behaviour to a unique periodic regime) or in the range of their basins of stability. The dynamic transition of states will be presented in the framework of threshold Boolean automata rules. A panorama of applications at different levels will be given: brain and plant morphogenesis, bulbar cardio-respiratory regulation, glycolytic/oxidative metabolic coupling, and eventually cell cycle and feather morphogenesis genetic control. PMID:20057955
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Directory of Open Access Journals (Sweden)
Sylvain Sené
2009-10-01
Full Text Available Regulatory interaction networks are often studied on their dynamical side (existence of attractors, study of their stability. We focus here also on their robustness, that is their ability to offer the same spatiotemporal patterns and to resist to external perturbations such as losses of nodes or edges in the networks interactions architecture, changes in their environmental boundary conditions as well as changes in the update schedule (or updating mode of the states of their elements (e.g., if these elements are genes, their synchronous coexpression mode versus their sequential expression. We define the generic notions of boundary, core, and critical vertex or edge of the underlying interaction graph of the regulatory network, whose disappearance causes dramatic changes in the number and nature of attractors (e.g., passage from a bistable behaviour to a unique periodic regime or in the range of their basins of stability. The dynamic transition of states will be presented in the framework of threshold Boolean automata rules. A panorama of applications at different levels will be given: brain and plant morphogenesis, bulbar cardio-respiratory regulation, glycolytic/oxidative metabolic coupling, and eventually cell cycle and feather morphogenesis genetic control.
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Directory of Open Access Journals (Sweden)
Madsen Per
2007-07-01
Full Text Available Abstract In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.
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Transcription control engineering and applications in synthetic biology
Directory of Open Access Journals (Sweden)
Michael D. Engstrom
2017-09-01
Full Text Available In synthetic biology, researchers assemble biological components in new ways to produce systems with practical applications. One of these practical applications is control of the flow of genetic information (from nucleic acid to protein, a.k.a. gene regulation. Regulation is critical for optimizing protein (and therefore activity levels and the subsequent levels of metabolites and other cellular properties. The central dogma of molecular biology posits that information flow commences with transcription, and accordingly, regulatory tools targeting transcription have received the most attention in synthetic biology. In this mini-review, we highlight many past successes and summarize the lessons learned in developing tools for controlling transcription. In particular, we focus on engineering studies where promoters and transcription terminators (cis-factors were directly engineered and/or isolated from DNA libraries. We also review several well-characterized transcription regulators (trans-factors, giving examples of how cis- and trans-acting factors have been combined to create digital and analogue switches for regulating transcription in response to various signals. Last, we provide examples of how engineered transcription control systems have been used in metabolic engineering and more complicated genetic circuits. While most of our mini-review focuses on the well-characterized bacterium Escherichia coli, we also provide several examples of the use of transcription control engineering in non-model organisms. Similar approaches have been applied outside the bacterial kingdom indicating that the lessons learned from bacterial studies may be generalized for other organisms.
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Transcription control engineering and applications in synthetic biology.
Engstrom, Michael D; Pfleger, Brian F
2017-09-01
In synthetic biology, researchers assemble biological components in new ways to produce systems with practical applications. One of these practical applications is control of the flow of genetic information (from nucleic acid to protein), a.k.a. gene regulation. Regulation is critical for optimizing protein (and therefore activity) levels and the subsequent levels of metabolites and other cellular properties. The central dogma of molecular biology posits that information flow commences with transcription, and accordingly, regulatory tools targeting transcription have received the most attention in synthetic biology. In this mini-review, we highlight many past successes and summarize the lessons learned in developing tools for controlling transcription. In particular, we focus on engineering studies where promoters and transcription terminators ( cis -factors) were directly engineered and/or isolated from DNA libraries. We also review several well-characterized transcription regulators ( trans- factors), giving examples of how cis- and trans -acting factors have been combined to create digital and analogue switches for regulating transcription in response to various signals. Last, we provide examples of how engineered transcription control systems have been used in metabolic engineering and more complicated genetic circuits. While most of our mini-review focuses on the well-characterized bacterium Escherichia coli , we also provide several examples of the use of transcription control engineering in non-model organisms. Similar approaches have been applied outside the bacterial kingdom indicating that the lessons learned from bacterial studies may be generalized for other organisms.
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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.
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Design of synthetic biological logic circuits based on evolutionary algorithm.
Chuang, Chia-Hua; Lin, Chun-Liang; Chang, Yen-Chang; Jennawasin, Tanagorn; Chen, Po-Kuei
2013-08-01
The construction of an artificial biological logic circuit using systematic strategy is recognised as one of the most important topics for the development of synthetic biology. In this study, a real-structured genetic algorithm (RSGA), which combines general advantages of the traditional real genetic algorithm with those of the structured genetic algorithm, is proposed to deal with the biological logic circuit design problem. A general model with the cis-regulatory input function and appropriate promoter activity functions is proposed to synthesise a wide variety of fundamental logic gates such as NOT, Buffer, AND, OR, NAND, NOR and XOR. The results obtained can be extended to synthesise advanced combinational and sequential logic circuits by topologically distinct connections. The resulting optimal design of these logic gates and circuits are established via the RSGA. The in silico computer-based modelling technology has been verified showing its great advantages in the purpose.
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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.
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A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.
Nguyen, Tramy; Roehner, Nicholas; Zundel, Zach; Myers, Chris J
2016-06-17
Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.
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Design of uav robust autopilot based on adaptive neuro-fuzzy inference system
Directory of Open Access Journals (Sweden)
Mohand Achour Touat
2008-04-01
Full Text Available This paper is devoted to the application of adaptive neuro-fuzzy inference systems to the robust control of the UAV longitudinal motion. The adaptive neore-fuzzy inference system model needs to be trained by input/output data. This data were obtained from the modeling of a ”crisp” robust control system. The synthesis of this system is based on the separation theorem, which defines the structure and parameters of LQG-optimal controller, and further - robust optimization of this controller, based on the genetic algorithm. Such design procedure can define the rule base and parameters of fuzzyfication and defuzzyfication algorithms of the adaptive neore-fuzzy inference system controller, which ensure the robust properties of the control system. Simulation of the closed loop control system of UAV longitudinal motion with adaptive neore-fuzzy inference system controller demonstrates high efficiency of proposed design procedure.
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Robust H∞ output-feedback control for path following of autonomous ground vehicles
Hu, Chuan; Jing, Hui; Wang, Rongrong; Yan, Fengjun; Chadli, Mohammed
2016-03-01
This paper presents a robust H∞ output-feedback control strategy for the path following of autonomous ground vehicles (AGVs). Considering the vehicle lateral velocity is usually hard to measure with low cost sensor, a robust H∞ static output-feedback controller based on the mixed genetic algorithms (GA)/linear matrix inequality (LMI) approach is proposed to realize the path following without the information of the lateral velocity. The proposed controller is robust to the parametric uncertainties and external disturbances, with the parameters including the tire cornering stiffness, vehicle longitudinal velocity, yaw rate and road curvature. Simulation results based on CarSim-Simulink joint platform using a high-fidelity and full-car model have verified the effectiveness of the proposed control approach.
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A reconfigurable NAND/NOR genetic logic gate.
Goñi-Moreno, Angel; Amos, Martyn
2012-09-18
Engineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations. We describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs. We present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications.
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Genetic analyses of agronomic and seed quality traits of synthetic ...
Indian Academy of Sciences (India)
As for protein content, similar results were found in the F2 plants and their maternal parents. ... doubled haploid; genetic analysis; gene interaction; agronomic traits; seed ..... Han J. Q. and Liu H. L. 1993 Principal component analysis for main.
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Göttert, Hendrikje; Mattiazzi Usaj, Mojca; Rosebrock, Adam P; Andrews, Brenda J
2018-01-01
Fluorescent reporter genes have long been used to quantify various cell features such as transcript and protein abundance. Here, we describe a method, reporter synthetic genetic array (R-SGA) analysis, which allows for the simultaneous quantification of any fluorescent protein readout in thousands of yeast strains using an automated pipeline. R-SGA combines a fluorescent reporter system with standard SGA analysis and can be used to examine any array-based strain collection available to the yeast community. This protocol describes the R-SGA methodology for screening different arrays of yeast mutants including the deletion collection, a collection of temperature-sensitive strains for the assessment of essential yeast genes and a collection of inducible overexpression strains. We also present an alternative pipeline for the analysis of R-SGA output strains using flow cytometry of cells in liquid culture. Data normalization for both pipelines is discussed.
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Pulse Detecting Genetic Circuit – A New Design Approach
Inniss, Mara; Iba, Hitoshi; Way, Jeffrey C.
2016-01-01
A robust cellular counter could enable synthetic biologists to design complex circuits with diverse behaviors. The existing synthetic-biological counters, responsive to the beginning of the pulse, are sensitive to the pulse duration. Here we present a pulse detecting circuit that responds only at the falling edge of a pulse–analogous to negative edge triggered electric circuits. As biological events do not follow precise timing, use of such a pulse detector would enable the design of robust asynchronous counters which can count the completion of events. This transcription-based pulse detecting circuit depends on the interaction of two co-expressed lambdoid phage-derived proteins: the first is unstable and inhibits the regulatory activity of the second, stable protein. At the end of the pulse the unstable inhibitor protein disappears from the cell and the second protein triggers the recording of the event completion. Using stochastic simulation we showed that the proposed design can detect the completion of the pulse irrespective to the pulse duration. In our simulation we also showed that fusing the pulse detector with a phage lambda memory element we can construct a counter which can be extended to count larger numbers. The proposed design principle is a new control mechanism for synthetic biology which can be integrated in different circuits for identifying the completion of an event. PMID:27907045
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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.
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Directory of Open Access Journals (Sweden)
Ya-Tang Yang
2016-10-01
Full Text Available One goal of metabolic engineering and synthetic biology for cyanobacteria and microalgae is to engineer strains that can optimally produce biofuels and commodity chemicals. However, the current workflow is slow and labor intensive with respect to assembly of genetic parts and characterization of production yields because of the slow growth rates of these organisms. Here, we review recent progress in the microfluidic photobioreactors and identify opportunities and unmet needs in metabolic engineering and synthetic biology. Because of the unprecedented experimental resolution down to the single cell level, long-term real-time monitoring capability, and high throughput with low cost, microfluidic photobioreactor technology will be an indispensible tool to speed up the development process, advance fundamental knowledge, and realize the full potential of metabolic engineering and synthetic biology for cyanobacteria and microalgae.
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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)
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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.
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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.
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Schopp, Pascal; Müller, Dominik; Technow, Frank; Melchinger, Albrecht E
2017-01-01
Synthetics play an important role in quantitative genetic research and plant breeding, but few studies have investigated the application of genomic prediction (GP) to these populations. Synthetics are generated by intermating a small number of parents ([Formula: see text] and thereby possess unique genetic properties, which make them especially suited for systematic investigations of factors contributing to the accuracy of GP. We generated synthetics in silico from [Formula: see text]2 to 32 maize (Zea mays L.) lines taken from an ancestral population with either short- or long-range linkage disequilibrium (LD). In eight scenarios differing in relatedness of the training and prediction sets and in the types of data used to calculate the relationship matrix (QTL, SNPs, tag markers, and pedigree), we investigated the prediction accuracy (PA) of Genomic best linear unbiased prediction (GBLUP) and analyzed contributions from pedigree relationships captured by SNP markers, as well as from cosegregation and ancestral LD between QTL and SNPs. The effects of training set size [Formula: see text] and marker density were also studied. Sampling few parents ([Formula: see text]) generates substantial sample LD that carries over into synthetics through cosegregation of alleles at linked loci. For fixed [Formula: see text], [Formula: see text] influences PA most strongly. If the training and prediction set are related, using [Formula: see text] parents yields high PA regardless of ancestral LD because SNPs capture pedigree relationships and Mendelian sampling through cosegregation. As [Formula: see text] increases, ancestral LD contributes more information, while other factors contribute less due to lower frequencies of closely related individuals. For unrelated prediction sets, only ancestral LD contributes information and accuracies were poor and highly variable for [Formula: see text] due to large sample LD. For large [Formula: see text], achieving moderate accuracy requires
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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
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Directory of Open Access Journals (Sweden)
Abdulqader Jighly
2018-02-01
Full Text Available Whole genome duplication (WGD is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents (Triticum turgidum; 2n = 4x = 28, AABB subgenomes with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii; 2n = 2x = 14, DD subgenome. The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy
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A synthetic system links FeFe-hydrogenases to essential E. coli sulfur metabolism
Directory of Open Access Journals (Sweden)
Grandl Gerald
2011-05-01
Full Text Available Abstract Background FeFe-hydrogenases are the most active class of H2-producing enzymes known in nature and may have important applications in clean H2 energy production. Many potential uses are currently complicated by a crucial weakness: the active sites of all known FeFe-hydrogenases are irreversibly inactivated by O2. Results We have developed a synthetic metabolic pathway in E. coli that links FeFe-hydrogenase activity to the production of the essential amino acid cysteine. Our design includes a complementary host strain whose endogenous redox pool is insulated from the synthetic metabolic pathway. Host viability on a selective medium requires hydrogenase expression, and moderate O2 levels eliminate growth. This pathway forms the basis for a genetic selection for O2 tolerance. Genetically selected hydrogenases did not show improved stability in O2 and in many cases had lost H2 production activity. The isolated mutations cluster significantly on charged surface residues, suggesting the evolution of binding surfaces that may accelerate hydrogenase electron transfer. Conclusions Rational design can optimize a fully heterologous three-component pathway to provide an essential metabolic flux while remaining insulated from the endogenous redox pool. We have developed a number of convenient in vivo assays to aid in the engineering of synthetic H2 metabolism. Our results also indicate a H2-independent redox activity in three different FeFe-hydrogenases, with implications for the future directed evolution of H2-activating catalysts.
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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.
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CRISPR/Cas9 gene drives in genetically variable and nonrandomly mating wild populations.
Drury, Douglas W; Dapper, Amy L; Siniard, Dylan J; Zentner, Gabriel E; Wade, Michael J
2017-05-01
Synthetic gene drives based on CRISPR/Cas9 have the potential to control, alter, or suppress populations of crop pests and disease vectors, but it is unclear how they will function in wild populations. Using genetic data from four populations of the flour beetle Tribolium castaneum , we show that most populations harbor genetic variants in Cas9 target sites, some of which would render them immune to drive (ITD). We show that even a rare ITD allele can reduce or eliminate the efficacy of a CRISPR/Cas9-based synthetic gene drive. This effect is equivalent to and accentuated by mild inbreeding, which is a characteristic of many disease-vectoring arthropods. We conclude that designing such drives will require characterization of genetic variability and the mating system within and among targeted populations.
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Directory of Open Access Journals (Sweden)
Gina M. Zastrow-Hayes
2015-03-01
Full Text Available Molecular characterization of events is an integral part of the advancement process during genetically modified (GM crop product development. Assessment of these events is traditionally accomplished by polymerase chain reaction (PCR and Southern blot analyses. Southern blot analysis can be time-consuming and comparatively expensive and does not provide sequence-level detail. We have developed a sequence-based application, Southern-by-Sequencing (SbS, utilizing sequence capture coupled with next-generation sequencing (NGS technology to replace Southern blot analysis for event selection in a high-throughput molecular characterization environment. SbS is accomplished by hybridizing indexed and pooled whole-genome DNA libraries from GM plants to biotinylated probes designed to target the sequence of transformation plasmids used to generate events within the pool. This sequence capture process enriches the sequence data obtained for targeted regions of interest (transformation plasmid DNA. Taking advantage of the DNA adjacent to the targeted bases (referred to as next-to-target sequence that accompanies the targeted transformation plasmid sequence, the data analysis detects plasmid-to-genome and plasmid-to-plasmid junctions introduced during insertion into the plant genome. Analysis of these junction sequences provides sequence-level information as to the following: the number of insertion loci including detection of unlinked, independently segregating, small DNA fragments; copy number; rearrangements, truncations, or deletions of the intended insertion DNA; and the presence of transformation plasmid backbone sequences. This molecular evidence from SbS analysis is used to characterize and select GM plants meeting optimal molecular characterization criteria. SbS technology has proven to be a robust event screening tool for use in a high-throughput molecular characterization environment.
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Burkholderia thailandensis: Genetic Manipulation.
Garcia, Erin C
2017-05-16
Burkholderia thailandensis is a Gram-negative bacterium endemic to Southeast Asian and northern Australian soils. It is non-pathogenic; therefore, it is commonly used as a model organism for the related human pathogens Burkholderia mallei and Burkholderia pseudomallei. B. thailandensis is relatively easily genetically manipulated and a variety of robust genetic tools can be used in this organism. This unit describes protocols for conjugation, natural transformation, mini-Tn7 insertion, and allelic exchange in B. thailandensis. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.
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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
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Genetic architecture of rainbow trout survival from egg to adult
Vehvilainen, H.; Kause, A.; Quiton, C.; Kuukka-Anttila, H.; Koskinen, H.; Paananen, T.
2010-01-01
Survival from birth to a reproductive adult is a challenge that only robust individuals resistant to a variety of mortality factors will overcome. To assess whether survival traits share genetic architecture throughout the life cycle, we estimated genetic correlations for survival within fingerling
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The bacterial nanorecorder: engineering E. coli to function as a chemical recording device.
Bhomkar, Prasanna; Materi, Wayne; Wishart, David S
2011-01-01
Synthetic biology is an emerging branch of molecular biology that uses synthetic genetic constructs to create man-made cells or organisms that are capable of performing novel and/or useful applications. Using a synthetic chemically sensitive genetic toggle switch to activate appropriate fluorescent protein indicators (GFP, RFP) and a cell division inhibitor (minC), we have created a novel E. coli strain that can be used as a highly specific, yet simple and inexpensive chemical recording device. This biological "nanorecorder" can be used to determine both the type and the time at which a brief chemical exposure event has occurred. In particular, we show that the short-term exposure (15-30 min) of cells harboring this synthetic genetic circuit to small molecule signals (anhydrotetracycline or IPTG) triggered long-term and uniform cell elongation, with cell length being directly proportional to the time elapsed following a brief chemical exposure. This work demonstrates that facile modification of an existing genetic toggle switch can be exploited to generate a robust, biologically-based "nanorecorder" that could potentially be adapted to detect, respond and record a wide range of chemical stimuli that may vary over time and space.
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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...
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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.
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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.
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Sequence robust association test for familial data.
Dai, Wei; Yang, Ming; Wang, Chaolong; Cai, Tianxi
2017-09-01
Genome-wide association studies (GWAS) and next generation sequencing studies (NGSS) are often performed in family studies to improve power in identifying genetic variants that are associated with clinical phenotypes. Efficient analysis of genome-wide studies with familial data is challenging due to the difficulty in modeling shared but unmeasured genetic and/or environmental factors that cause dependencies among family members. Existing genetic association testing procedures for family studies largely rely on generalized estimating equations (GEE) or linear mixed-effects (LME) models. These procedures may fail to properly control for type I errors when the imposed model assumptions fail. In this article, we propose the Sequence Robust Association Test (SRAT), a fully rank-based, flexible approach that tests for association between a set of genetic variants and an outcome, while accounting for within-family correlation and adjusting for covariates. Comparing to existing methods, SRAT has the advantages of allowing for unknown correlation structures and weaker assumptions about the outcome distribution. We provide theoretical justifications for SRAT and show that SRAT includes the well-known Wilcoxon rank sum test as a special case. Extensive simulation studies suggest that SRAT provides better protection against type I error rate inflation, and could be much more powerful for settings with skewed outcome distribution than existing methods. For illustration, we also apply SRAT to the familial data from the Framingham Heart Study and Offspring Study to examine the association between an inflammatory marker and a few sets of genetic variants. © 2017, The International Biometric Society.
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Genetic interaction network of the Saccharomyces cerevisiae type 1 phosphatase Glc7
Directory of Open Access Journals (Sweden)
Neszt Michael
2008-07-01
Full Text Available Abstract Background Protein kinases and phosphatases regulate protein phosphorylation, a critical means of modulating protein function, stability and localization. The identification of functional networks for protein phosphatases has been slow due to their redundant nature and the lack of large-scale analyses. We hypothesized that a genome-scale analysis of genetic interactions using the Synthetic Genetic Array could reveal protein phosphatase functional networks. We apply this approach to the conserved type 1 protein phosphatase Glc7, which regulates numerous cellular processes in budding yeast. Results We created a novel glc7 catalytic mutant (glc7-E101Q. Phenotypic analysis indicates that this novel allele exhibits slow growth and defects in glucose metabolism but normal cell cycle progression and chromosome segregation. This suggests that glc7-E101Q is a hypomorphic glc7 mutant. Synthetic Genetic Array analysis of glc7-E101Q revealed a broad network of 245 synthetic sick/lethal interactions reflecting that many processes are required when Glc7 function is compromised such as histone modification, chromosome segregation and cytokinesis, nutrient sensing and DNA damage. In addition, mitochondrial activity and inheritance and lipid metabolism were identified as new processes involved in buffering Glc7 function. An interaction network among 95 genes genetically interacting with GLC7 was constructed by integration of genetic and physical interaction data. The obtained network has a modular architecture, and the interconnection among the modules reflects the cooperation of the processes buffering Glc7 function. Conclusion We found 245 genes required for the normal growth of the glc7-E101Q mutant. Functional grouping of these genes and analysis of their physical and genetic interaction patterns bring new information on Glc7-regulated processes.
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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.
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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.
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Delay-independent stability of genetic regulatory networks.
Wu, Fang-Xiang
2011-11-01
Genetic regulatory networks can be described by nonlinear differential equations with time delays. In this paper, we study both locally and globally delay-independent stability of genetic regulatory networks, taking messenger ribonucleic acid alternative splicing into consideration. Based on nonnegative matrix theory, we first develop necessary and sufficient conditions for locally delay-independent stability of genetic regulatory networks with multiple time delays. Compared to the previous results, these conditions are easy to verify. Then we develop sufficient conditions for global delay-independent stability for genetic regulatory networks. Compared to the previous results, this sufficient condition is less conservative. To illustrate theorems developed in this paper, we analyze delay-independent stability of two genetic regulatory networks: a real-life repressilatory network with three genes and three proteins, and a synthetic gene regulatory network with five genes and seven proteins. The simulation results show that the theorems developed in this paper can effectively determine the delay-independent stability of genetic regulatory networks.
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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...
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DEFF Research Database (Denmark)
Rennig, Maja; Martinez, Virginia; Mirzadeh, Kiavash
2018-01-01
Evolution can be harnessed to optimize synthetic biology designs. A prominent example is recombinant protein production-a dominating theme in biotechnology for more than three decades. Typically, a protein coding sequence (cds) is recombined with genetic elements, such as promoters, ribosome...... and allows expression levels in large clone libraries to be probed using a simple cell survival assay on the respective antibiotic. The power of the approach is demonstrated by substantially increasing production of two commercially interesting proteins, a Nanobody and an Affibody. The method is a simple......-level expression-an example of synthetic evolution. However, manual screening limits the ability to assay expression levels of all putative sequences in the libraries. Here we have solved this bottleneck by designing a collection of translational coupling devices based on a RNA secondary structure. Exchange...
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Directory of Open Access Journals (Sweden)
Sam F Greenbury
2016-03-01
Full Text Available Mutational neighbourhoods in genotype-phenotype (GP maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps-a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure-to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i If a particular (non-neutral phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected; ii If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar; iii If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i and ii reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii may instead facilitate evolutionary exploration
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Greenbury, Sam F.; Schaper, Steffen; Ahnert, Sebastian E.; Louis, Ard A.
2016-01-01
Mutational neighbourhoods in genotype-phenotype (GP) maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps—a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure—to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i) If a particular (non-neutral) phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected; ii) If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar; iii) If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i) and ii) reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii) may instead facilitate evolutionary exploration and so
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Adaptive sensor fusion using genetic algorithms
International Nuclear Information System (INIS)
Fitzgerald, D.S.; Adams, D.G.
1994-01-01
Past attempts at sensor fusion have used some form of Boolean logic to combine the sensor information. As an alteniative, an adaptive ''fuzzy'' sensor fusion technique is described in this paper. This technique exploits the robust capabilities of fuzzy logic in the decision process as well as the optimization features of the genetic algorithm. This paper presents a brief background on fuzzy logic and genetic algorithms and how they are used in an online implementation of adaptive sensor fusion
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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.
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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
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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.
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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
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A case study of a multiobjective recombinative genetic algorithm with coevolutionary sharing
Neef, R.M.; Thierens, D.; Arciszewski, H.F.R.
1999-01-01
We present a multiobjective genetic algorithm that incorporates various genetic algorithm techniques that have been proven to be efficient and robust in their problem domain. More specifically, we integrate rank based selection, adaptive niching through coevolutionary sharing, elitist recombination,
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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.
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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.
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Using Genetic Algorithms for Building Metrics of Collaborative Systems
Directory of Open Access Journals (Sweden)
Cristian CIUREA
2011-01-01
Full Text Available he paper objective is to reveal the importance of genetic algorithms in building robust metrics of collaborative systems. The main types of collaborative systems in economy are presented and some characteristics of genetic algorithms are described. A genetic algorithm was implemented in order to determine the local maximum and minimum points of the relative complexity function associated to a collaborative banking system. The intelligent collaborative systems based on genetic algorithms, representing the new generation of collaborative systems, are analyzed and the implementation of auto-adaptive interfaces in a banking application is described.
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Robust transient dynamics and brain functions
Directory of Open Access Journals (Sweden)
Mikhail I Rabinovich
2011-06-01
Full Text Available In the last few decades several concepts of Dynamical Systems Theory (DST have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc. have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework -heteroclinic sequential dynamics- to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i within the same modality, (ii among different modalities from the same family (like perception, and (iii among modalities from different families (like emotion and cognition. The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory -a vital cognitive function-, and to find specific dynamical signatures -different kinds of instabilities- of several brain functions and mental diseases.
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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
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Ischemic stroke after use of the synthetic marijuana "spice".
Freeman, Melissa J; Rose, David Z; Myers, Martin A; Gooch, Clifton L; Bozeman, Andrea C; Burgin, W Scott
2013-12-10
To report and associate acute cerebral infarctions in 2 young, previously healthy siblings with use of the street drug known as "spice" (a synthetic marijuana product, also known as "K2"), which they independently smoked before experiencing acute embolic-appearing ischemic strokes. We present history, physical examination, laboratory data, cerebrovascular imaging, echocardiogram, ECG, and hospital course of these patients. We found that in both siblings spice was obtained from the same source. The drug was found to contain the schedule I synthetic cannabinoid JWH-018. Full stroke workup was unrevealing of a stroke etiology; urine drug screen was positive for marijuana. We found that our 2 patients who smoked the street drug spice had a temporal association with symptoms of acute cerebral infarction. This association may be confounded by contaminants in the product consumed (i.e., marijuana or an unidentified toxin) or by an unknown genetic mechanism. The imaging of both patients suggests an embolic etiology, which is consistent with reports of serious adverse cardiac events with spice use, including tachyarrhythmias and myocardial infarctions.
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Insulated transcriptional elements enable precise design of genetic circuits.
Zong, Yeqing; Zhang, Haoqian M; Lyu, Cheng; Ji, Xiangyu; Hou, Junran; Guo, Xian; Ouyang, Qi; Lou, Chunbo
2017-07-03
Rational engineering of biological systems is often complicated by the complex but unwanted interactions between cellular components at multiple levels. Here we address this issue at the level of prokaryotic transcription by insulating minimal promoters and operators to prevent their interaction and enable the biophysical modeling of synthetic transcription without free parameters. This approach allows genetic circuit design with extraordinary precision and diversity, and consequently simplifies the design-build-test-learn cycle of circuit engineering to a mix-and-match workflow. As a demonstration, combinatorial promoters encoding NOT-gate functions were designed from scratch with mean errors of 96% using our insulated transcription elements. Furthermore, four-node transcriptional networks with incoherent feed-forward loops that execute stripe-forming functions were obtained without any trial-and-error work. This insulation-based engineering strategy improves the resolution of genetic circuit technology and provides a simple approach for designing genetic circuits for systems and synthetic biology.Unwanted interactions between cellular components can complicate rational engineering of biological systems. Here the authors design insulated minimal promoters and operators that enable biophysical modeling of bacterial transcription without free parameters for precise circuit design.
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International Nuclear Information System (INIS)
Masood, R.M.; Bibi, K.; Jamil, M.
2016-01-01
The current study evaluates genetic penetrance and expressivity of an alien genome introgression in a set of 117 primary synthetic hexaploid wheat (SHW) accessions. These SHW have originated from durum wheat /accessions with three sets of durum wheat cultivars ALTAR 84, D67.2 and CERCETA as the female and diverse Ae. tauschii accessions as the pollen parents. Diversity of the 12 important traits (Growth habit, pigmentation, chlorophyll content, leaf area index, crop digital ground cover, awn size, awn length, and several seed digital imaging parameters)revealed significant variation for the respective traits, leading to the conclusion that Ae. tauschii accessions have tremendous diversity than the durum controls. Further, the value deviations within each attribute had a range of being lower or higher than their durum wheat female parents and these observations allowed us to use the variations as selective sieves and narrow down the desirable SHW that would be advantageous to exploit for wheat breeding and cultivar improvement programs. Selections were made and a group of 41SHW accessions were identified that will after an intermediate DNA diversity evaluation form a crisper final set for user friendly utilization. The range of selections shows multiple trait advantages for exploitation in both irrigated and rain-fed conditions. This pivotal study sets the foundation to better define the D genome SHW for efficient utilization in future research investigations. Our results have implications in widening the genetic base of hexaploid bread wheat and may facilitate the development of agronomically desirable wheat cultivars. (author)
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Cell-free synthetic biology: thinking outside the cell.
Hodgman, C Eric; Jewett, Michael C
2012-05-01
Cell-free synthetic biology is emerging as a powerful approach aimed to understand, harness, and expand the capabilities of natural biological systems without using intact cells. Cell-free systems bypass cell walls and remove genetic regulation to enable direct access to the inner workings of the cell. The unprecedented level of control and freedom of design, relative to in vivo systems, has inspired the rapid development of engineering foundations for cell-free systems in recent years. These efforts have led to programmed circuits, spatially organized pathways, co-activated catalytic ensembles, rational optimization of synthetic multi-enzyme pathways, and linear scalability from the micro-liter to the 100-liter scale. It is now clear that cell-free systems offer a versatile test-bed for understanding why nature's designs work the way they do and also for enabling biosynthetic routes to novel chemicals, sustainable fuels, and new classes of tunable materials. While challenges remain, the emergence of cell-free systems is poised to open the way to novel products that until now have been impractical, if not impossible, to produce by other means. Copyright © 2011 Elsevier Inc. All rights reserved.
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Genetic diversity in Trichomonas vaginalis.
Meade, John C; Carlton, Jane M
2013-09-01
Recent advances in genetic characterisation of Trichomonas vaginalis isolates show that the extensive clinical variability in trichomoniasis and its disease sequelae are matched by significant genetic diversity in the organism itself, suggesting a connection between the genetic identity of isolates and their clinical manifestations. Indeed, a high degree of genetic heterogeneity in T vaginalis isolates has been observed using multiple genotyping techniques. A unique two-type population structure that is both local and global in distribution has been identified, and there is evidence of recombination within each group, although sexual recombination between the groups appears to be constrained. There is conflicting evidence in these studies for correlations between T vaginalis genetic identity and clinical presentation, metronidazole susceptibility, and the presence of T vaginalis virus, underscoring the need for adoption of a common standard for genotyping the parasite. Moving forward, microsatellite genotyping and multilocus sequence typing are the most robust techniques for future investigations of T vaginalis genotype-phenotype associations.
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Han, Lide; Yang, Jian; Zhu, Jun
2007-06-01
A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.
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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.
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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.
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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...
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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.
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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.
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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...
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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
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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.
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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...
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Genetic Algorithm Based Economic Dispatch with Valve Point Effect
Energy Technology Data Exchange (ETDEWEB)
Park, Jong Nam; Park, Kyung Won; Kim, Ji Hong; Kim, Jin O [Hanyang University (Korea, Republic of)
1999-03-01
This paper presents a new approach on genetic algorithm to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through improved death penalty method, generation-apart elitism, atavism and sexual selection with sexual distinction. Numerical results on a test system consisting of 13 thermal units show that the proposed approach is faster, more robust and powerful than conventional genetic algorithms. (author). 8 refs., 10 figs.
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Maize Genetic Resources Collections – Utilizing a Treasure Trove
The maize genetic resource collection managed by the USDA-ARS's National Plant Germplasm System is heavily utilized by researchers and educators. A collection of landraces, inbred lines from public and private sector sources, synthetics and key populations, it serves both as a living snapshot of th...
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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."
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A Case Study of a Multiobjective Elitist Recombinative Genetic Algorithm with Coevolutionary Sharing
Neef, R.M.; Thierens, D.; Arciszewski, H.F.R.
1999-01-01
We present a multiobjective genetic algorithm that incorporates various genetic algorithm techniques that have been proven to be efficient and robust in their problem domain. More specifically, we integrate rank based selection, adaptive niching through coevolutionary sharing, elitist recombination,
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Application of Genetic Algorithms in Seismic Tomography
Soupios, Pantelis; Akca, Irfan; Mpogiatzis, Petros; Basokur, Ahmet; Papazachos, Constantinos
2010-05-01
application of hybrid genetic algorithms in seismic tomography is examined and the efficiency of least squares and genetic methods as representative of the local and global optimization, respectively, is presented and evaluated. The robustness of both optimization methods has been tested and compared for the same source-receiver geometry and characteristics of the model structure (anomalies, etc.). A set of seismic refraction synthetic (noise free) data was used for modeling. Specifically, cross-well, down-hole and typical refraction studies using 24 geophones and 5 shoots were used to confirm the applicability of the genetic algorithms in seismic tomography. To solve the forward modeling and estimate the traveltimes, the revisited ray bending method was used supplemented by an approximate computation of the first Fresnel volume. The root mean square (rms) error as the misfit function was used and calculated for the entire random velocity model for each generation. After the end of each generation and based on the misfit of the individuals (velocity models), the selection, crossover and mutation (typical process steps of genetic algorithms) were selected continuing the evolution theory and coding the new generation. To optimize the computation time, since the whole procedure is quite time consuming, the Matlab Distributed Computing Environment (MDCE) was used in a multicore engine. During the tests, we noticed that the fast convergence that the algorithm initially exhibits (first 5 generations) is followed by progressively slower improvements of the reconstructed velocity models. Thus, to improve the final tomographic models, a hybrid genetic algorithm (GA) approach was adopted by combining the GAs with a local optimization method after several generations, on the basis of the convergence of the resulting models. This approach is shown to be efficient, as it directs the solution search towards a model region close to the global minimum solution.
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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.
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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
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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.
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Denoising of genetic switches based on Parrondo's paradox
Fotoohinasab, Atiyeh; Fatemizadeh, Emad; Pezeshk, Hamid; Sadeghi, Mehdi
2018-03-01
Random decision making in genetic switches can be modeled as tossing a biased coin. In other word, each genetic switch can be considered as a game in which the reactive elements compete with each other to increase their molecular concentrations. The existence of a very small number of reactive element molecules has caused the neglect of effects of noise to be inevitable. Noise can lead to undesirable cell fate in cellular differentiation processes. In this paper, we study the robustness to noise in genetic switches by considering another switch to have a new gene regulatory network (GRN) in which both switches have been affected by the same noise and for this purpose, we will use Parrondo's paradox. We introduce two networks of games based on possible regulatory relations between genes. Our results show that the robustness to noise can increase by combining these noisy switches. We also describe how one of the switches in network II can model lysis/lysogeny decision making of bacteriophage lambda in Escherichia coli and we change its fate by another switch.
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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)
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Robustness to Faults Promotes Evolvability: Insights from Evolving Digital Circuits.
Milano, Nicola; Nolfi, Stefano
2016-01-01
We demonstrate how the need to cope with operational faults enables evolving circuits to find more fit solutions. The analysis of the results obtained in different experimental conditions indicates that, in absence of faults, evolution tends to select circuits that are small and have low phenotypic variability and evolvability. The need to face operation faults, instead, drives evolution toward the selection of larger circuits that are truly robust with respect to genetic variations and that have a greater level of phenotypic variability and evolvability. Overall our results indicate that the need to cope with operation faults leads to the selection of circuits that have a greater probability to generate better circuits as a result of genetic variation with respect to a control condition in which circuits are not subjected to faults.
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Pathological Bases for a Robust Application of Cancer Molecular Classification
Directory of Open Access Journals (Sweden)
Salvador J. Diaz-Cano
2015-04-01
Full Text Available Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes, and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors.
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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.
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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.
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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.
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Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J
2012-01-01
Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.
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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.
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Robust Optimization on Regional WCO-for-Biodiesel Supply Chain under Supply and Demand Uncertainties
Directory of Open Access Journals (Sweden)
Yong Zhang
2016-01-01
Full Text Available This paper aims to design a robust waste cooking oil- (WCO- for-biodiesel supply chain under WCO supply and price as well as biodiesel demand and price uncertainties, so as to improve biorefineries’ ability to cope with the poor environment. A regional supply chain is firstly introduced based on the biggest WCO-for-biodiesel company in Changzhou, Jiangsu province, and it comprises three components: WCO supplier, biorefinery, and demand zone. And then a robust mixed integer linear model with multiple objectives (economic, environmental, and social objectives is proposed for both biorefinery location and transportation plans. After that, a heuristic algorithm based on genetic algorithm is proposed to solve this model. Finally, the 27 cities in Yangtze River delta are adopted to verify the proposed models and methods, and the sustainability and robustness of biodiesel supply are discussed.
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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)
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Genetic Engineering In BioButanol Production And Tolerance
Directory of Open Access Journals (Sweden)
Ashok Rao
Full Text Available ABSTRACT The growing need to address current energy and environmental problems has sparked an interest in developing improved biological methods to produce liquid fuels from renewable sources. Higher-chain alcohols possess chemical properties that are more similar to gasoline. Ethanol and butanol are two products which are used as biofuel. Butanol production was more concerned than ethanol because of its high octane number. Unfortunately, these alcohols are not produced efficiently in natural microorganisms, and thus economical production in industrial volumes remains a challenge. The synthetic biology, however, offers additional tools to engineer synthetic pathways in user-friendly hosts to help increase titers and productivity of bio-butanol. Knock out and over-expression of genes is the major approaches towards genetic manipulation and metabolic engineering of microbes. Yet there are TargeTron Technology, Antisense RNA and CRISPR technology has a vital role in genome manipulation of C.acetobutylicum. This review concentrates on the recent developments for efficient production of butanol and butanol tolerance by various genetically engineered microbes.
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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.
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The effects of ecology and evolutionary history on robust capuchin morphological diversity.
Wright, Kristin A; Wright, Barth W; Ford, Susan M; Fragaszy, Dorothy; Izar, Patricia; Norconk, Marilyn; Masterson, Thomas; Hobbs, David G; Alfaro, Michael E; Lynch Alfaro, Jessica W
2015-01-01
Recent molecular work has confirmed the long-standing morphological hypothesis that capuchins are comprised of two distinct clades, the gracile (untufted) capuchins (genus Cebus, Erxleben, 1777) and the robust (tufted) capuchins (genus Sapajus Kerr, 1792). In the past, the robust group was treated as a single, undifferentiated and cosmopolitan species, with data from all populations lumped together in morphological and ecological studies, obscuring morphological differences that might exist across this radiation. Genetic evidence suggests that the modern radiation of robust capuchins began diversifying ∼2.5 Ma, with significant subsequent geographic expansion into new habitat types. In this study we use a morphological sample of gracile and robust capuchin craniofacial and postcranial characters to examine how ecology and evolutionary history have contributed to morphological diversity within the robust capuchins. We predicted that if ecology is driving robust capuchin variation, three distinct robust morphotypes would be identified: (1) the Atlantic Forest species (Sapajus xanthosternos, S. robustus, and S. nigritus), (2) the Amazonian rainforest species (S. apella, S. cay and S. macrocephalus), and (3) the Cerrado-Caatinga species (S. libidinosus). Alternatively, if diversification time between species pairs predicts degree of morphological difference, we predicted that the recently diverged S. apella, S. macrocephalus, S. libidinosus, and S. cay would be morphologically comparable, with greater variation among the more ancient lineages of S. nigritus, S. xanthosternos, and S. robustus. Our analyses suggest that S. libidinosus has the most derived craniofacial and postcranial features, indicative of inhabiting a more terrestrial niche that includes a dependence on tool use for the extraction of imbedded foods. We also suggest that the cranial robusticity of S. macrocephalus and S. apella are indicative of recent competition with sympatric gracile capuchin
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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.
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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)
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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.
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Genetic noise control via protein oligomerization
Energy Technology Data Exchange (ETDEWEB)
Ghim, C; Almaas, E
2008-06-12
Gene expression in a cell entails random reaction events occurring over disparate time scales. Thus, molecular noise that often results in phenotypic and population-dynamic consequences sets a fundamental limit to biochemical signaling. While there have been numerous studies correlating the architecture of cellular reaction networks with noise tolerance, only a limited effort has been made to understand the dynamical role of protein-protein associations. We have developed a fully stochastic model for the positive feedback control of a single gene, as well as a pair of genes (toggle switch), integrating quantitative results from previous in vivo and in vitro studies. In particular, we explicitly account for the fast protein binding-unbinding kinetics, RNA polymerases, and the promoter/operator sequences of DNA. We find that the overall noise-level is reduced and the frequency content of the noise is dramatically shifted to the physiologically irrelevant high-frequency regime in the presence of protein dimerization. This is independent of the choice of monomer or dimer as transcription factor and persists throughout the multiple model topologies considered. For the toggle switch, we additionally find that the presence of a protein dimer, either homodimer or heterodimer, may significantly reduce its intrinsic switching rate. Hence, the dimer promotes the robust function of bistable switches by preventing the uninduced (induced) state from randomly being induced (uninduced). The specific binding between regulatory proteins provides a buffer that may prevent the propagation of fluctuations in genetic activity. The capacity of the buffer is a non-monotonic function of association-dissociation rates. Since the protein oligomerization per se does not require extra protein components to be expressed, it provides a basis for the rapid control of intrinsic or extrinsic noise. The stabilization of phenotypically important toggle switches, and nested positive feedback loops in
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Genetic noise control via protein oligomerization
Directory of Open Access Journals (Sweden)
Almaas Eivind
2008-11-01
Full Text Available Abstract Background Gene expression in a cell entails random reaction events occurring over disparate time scales. Thus, molecular noise that often results in phenotypic and population-dynamic consequences sets a fundamental limit to biochemical signaling. While there have been numerous studies correlating the architecture of cellular reaction networks with noise tolerance, only a limited effort has been made to understand the dynamic role of protein-protein interactions. Results We have developed a fully stochastic model for the positive feedback control of a single gene, as well as a pair of genes (toggle switch, integrating quantitative results from previous in vivo and in vitro studies. In particular, we explicitly account for the fast binding-unbinding kinetics among proteins, RNA polymerases, and the promoter/operator sequences of DNA. We find that the overall noise-level is reduced and the frequency content of the noise is dramatically shifted to the physiologically irrelevant high-frequency regime in the presence of protein dimerization. This is independent of the choice of monomer or dimer as transcription factor and persists throughout the multiple model topologies considered. For the toggle switch, we additionally find that the presence of a protein dimer, either homodimer or heterodimer, may significantly reduce its random switching rate. Hence, the dimer promotes the robust function of bistable switches by preventing the uninduced (induced state from randomly being induced (uninduced. Conclusion The specific binding between regulatory proteins provides a buffer that may prevent the propagation of fluctuations in genetic activity. The capacity of the buffer is a non-monotonic function of association-dissociation rates. Since the protein oligomerization per se does not require extra protein components to be expressed, it provides a basis for the rapid control of intrinsic or extrinsic noise. The stabilization of regulatory circuits
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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.
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Ischemic stroke after use of the synthetic marijuana “spice”
Freeman, Melissa J.; Rose, David Z.; Myers, Martin A.; Gooch, Clifton L.; Bozeman, Andrea C.
2013-01-01
Objectives: To report and associate acute cerebral infarctions in 2 young, previously healthy siblings with use of the street drug known as “spice” (a synthetic marijuana product, also known as “K2”), which they independently smoked before experiencing acute embolic-appearing ischemic strokes. Methods: We present history, physical examination, laboratory data, cerebrovascular imaging, echocardiogram, ECG, and hospital course of these patients. Results: We found that in both siblings spice was obtained from the same source. The drug was found to contain the schedule I synthetic cannabinoid JWH-018. Full stroke workup was unrevealing of a stroke etiology; urine drug screen was positive for marijuana. Conclusions: We found that our 2 patients who smoked the street drug spice had a temporal association with symptoms of acute cerebral infarction. This association may be confounded by contaminants in the product consumed (i.e., marijuana or an unidentified toxin) or by an unknown genetic mechanism. The imaging of both patients suggests an embolic etiology, which is consistent with reports of serious adverse cardiac events with spice use, including tachyarrhythmias and myocardial infarctions. PMID:24212384
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Directory of Open Access Journals (Sweden)
Schalk Cloete
2013-05-01
Full Text Available It is a difficult task to improve animal production by means of genetic selection, if the environment does not allow full expression of the animal’s genetic potential. This concept may well be the future for animal welfare, because it highlights the need to incorporate traits related to production and robustness, simultaneously, to reach sustainable breeding goals. This review explores the identification of potential genetic markers for robustness within the hypothalamic-pituitary-adrenal axis (HPAA, since this axis plays a vital role in the stress response. If genetic selection for superior HPAA responses to stress is possible, then it ought to be possible to breed robust and easily managed genotypes that might be able to adapt to a wide range of environmental conditions whilst expressing a high production potential. This approach is explored in this review by means of lessons learnt from research on Merino sheep, which were divergently selected for their multiple rearing ability. These two selection lines have shown marked differences in reproduction, production and welfare, which makes this breeding programme ideal to investigate potential genetic markers of robustness. The HPAA function is explored in detail to elucidate where such genetic markers are likely to be found.
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Bacteriophage-based synthetic biology for the study of infectious diseases
Lu, Timothy K.
2014-01-01
Since their discovery, bacteriophages have contributed enormously to our understanding of molecular biology as model systems. Furthermore, bacteriophages have provided many tools that have advanced the fields of genetic engineering and synthetic biology. Here, we discuss bacteriophage-based technologies and their application to the study of infectious diseases. New strategies for engineering genomes have the potential to accelerate the design of novel phages as therapies, diagnostics, and tools. Though almost a century has elapsed since their discovery, bacteriophages continue to have a major impact on modern biological sciences, especially with the growth of multidrug-resistant bacteria and interest in the microbiome. PMID:24997401
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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...
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Integrated genetic analysis microsystems
International Nuclear Information System (INIS)
Lagally, Eric T; Mathies, Richard A
2004-01-01
With the completion of the Human Genome Project and the ongoing DNA sequencing of the genomes of other animals, bacteria, plants and others, a wealth of new information about the genetic composition of organisms has become available. However, as the demand for sequence information grows, so does the workload required both to generate this sequence and to use it for targeted genetic analysis. Microfabricated genetic analysis systems are well poised to assist in the collection and use of these data through increased analysis speed, lower analysis cost and higher parallelism leading to increased assay throughput. In addition, such integrated microsystems may point the way to targeted genetic experiments on single cells and in other areas that are otherwise very difficult. Concomitant with these advantages, such systems, when fully integrated, should be capable of forming portable systems for high-speed in situ analyses, enabling a new standard in disciplines such as clinical chemistry, forensics, biowarfare detection and epidemiology. This review will discuss the various technologies available for genetic analysis on the microscale, and efforts to integrate them to form fully functional robust analysis devices. (topical review)
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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.
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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.
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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.
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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.
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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
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Do species conservation assessments capture genetic diversity?
Directory of Open Access Journals (Sweden)
Malin C. Rivers
2014-12-01
Full Text Available The best known system for classifying threat status of species, the IUCN Red List, currently lacks explicit considerations of genetic diversity, and consequently may not account for potential adaptation of species to future environmental change. To address this gap, we integrate range-wide genetic analysis with IUCN Red List assessments.We calculated the loss of genetic diversity under simulated range loss for species of Delonix (Leguminosae. Simulated range loss involved random loss of populations and was intended to model ongoing habitat destruction. We found a strong relationship between loss of genetic diversity and range. Moreover, we found correspondence between levels of genetic diversity and thresholds for ‘non-threatened’ versus ‘threatened’ IUCN Red List categories.Our results support the view that current threat thresholds of the IUCN Red List criteria reflect genetic diversity, and hence evolutionary potential; although the genetic diversity distinction between threatened categories was less evident. Thus, by supplementing conventional conservation assessments with genetic data, new insights into the biological robustness of IUCN Red List assessments for targeted conservation initiatives can be achieved. Keywords: Conservation assessment, Conservation genetics, Extinction risk, Genetic diversity, IUCN Red List, Range
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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/ ...
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DEFF Research Database (Denmark)
Lawlor, Debbie A; Harbord, Roger M; Tybjærg-Hansen, Anne
2011-01-01
We used genetic variants that are robustly associated with adiposity to examine the causal association of adiposity with psychological distress.......We used genetic variants that are robustly associated with adiposity to examine the causal association of adiposity with psychological distress....
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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...
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Robust Circle Detection Using Harmony Search
Directory of Open Access Journals (Sweden)
Jaco Fourie
2017-01-01
Full Text Available Automatic circle detection is an important element of many image processing algorithms. Traditionally the Hough transform has been used to find circular objects in images but more modern approaches that make use of heuristic optimisation techniques have been developed. These are often used in large complex images where the presence of noise or limited computational resources make the Hough transform impractical. Previous research on the use of the Harmony Search (HS in circle detection showed that HS is an attractive alternative to many of the modern circle detectors based on heuristic optimisers like genetic algorithms and simulated annealing. We propose improvements to this work that enables our algorithm to robustly find multiple circles in larger data sets and still work on realistic images that are heavily corrupted by noisy edges.
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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.
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Bashor, Caleb J; Horwitz, Andrew A; Peisajovich, Sergio G; Lim, Wendell A
2010-01-01
The living cell is an incredibly complex entity, and the goal of predictively and quantitatively understanding its function is one of the next great challenges in biology. Much of what we know about the cell concerns its constituent parts, but to a great extent we have yet to decode how these parts are organized to yield complex physiological function. Classically, we have learned about the organization of cellular networks by disrupting them through genetic or chemical means. The emerging discipline of synthetic biology offers an additional, powerful approach to study systems. By rearranging the parts that comprise existing networks, we can gain valuable insight into the hierarchical logic of the networks and identify the modular building blocks that evolution uses to generate innovative function. In addition, by building minimal toy networks, one can systematically explore the relationship between network structure and function. Here, we outline recent work that uses synthetic biology approaches to investigate the organization and function of cellular networks, and describe a vision for a synthetic biology toolkit that could be used to interrogate the design principles of diverse systems.
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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.
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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...
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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...
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Musah, Samira
Human pluripotent stem (hPS) cells have the remarkable capacity to self-renew indefinitely and differentiate into desired cell types. They can serve as a virtually unlimited supply of cells for applications ranging from drug screening to cell therapies to understanding human development. Reaping the promise of hPS cells hinges on effective defined culture and differentiation conditions. Efforts to generate chemically-defined environments for hPS cell propagation and directed differentiation have been hindered by access to only a handful of ligands to target hPS cells. Additionally, progress has been limited also by lack of knowledge regarding the relevant functional properties of the cell culture substratum. To address these problems, I first employed forward-chemical-genetics coupled with self-assembled monolayer technology to identify novel peptides that bind to hPS cell-surface receptors. I then developed a controlled synthesis of hydrogels with tailored peptide display and mechanical properties. This approach yielded synthetic hydrogels with specific mechanical properties that function in a defined medium to robustly support hPS cell self-renewal. Finally, by starting from molecular level understanding that matrix elasticity regulates developmental pathways, I generated a highly efficient hydrogel platform that restricts hPS cell differentiation to neurons, even without soluble inductive factors. These results indicate that insoluble cues can be important information conduits to guide hPS cell fate decisions. I envision that the blueprint provided by this work can be utilized to devise new materials to guide hPS cell fate.
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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.
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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.
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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.
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3D-QSAR Investigation of Synthetic Antioxidant Chromone Derivatives by Molecular Field Analysis
Directory of Open Access Journals (Sweden)
Jiraporn Ungwitayatorn
2008-02-01
Full Text Available A series of 7-hydroxy, 8-hydroxy and 7,8-dihydroxy synthetic chromone derivatives was evaluated for their DPPH free radical scavenging activities. A training set of 30 synthetic chromone derivatives was subject to three-dimensional quantitative structure-activity relationship (3D-QSAR studies using molecular field analysis (MFA. The substitutional requirements for favorable antioxidant activity were investigated and a predictive model that could be used for the design of novel antioxidants was derived. Regression analysis was carried out using genetic partial least squares (G/PLS method. A highly predictive and statistically significant model was generated. The predictive ability of the developed model was assessed using a test set of 5 compounds (r2pred = 0.924. The analyzed MFA model demonstrated a good fit, having r2 value of 0.868 and crossvalidated coefficient r2cv value of 0.771.
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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.
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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.
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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)
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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.
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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.
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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.
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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.
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Analysis of the Threat of Genetically Modified Organisms for Biological Warfare
2011-05-01
biological warfare. The primary focus of the framework are those aspects of the technology directly affecting humans by inducing virulent infectious disease...applications. Simple organisms such as fruit flies have been used to study the effects of genetic changes across generations. Transgenic mice are...Analysis * Multi-cell pathogens * Toxins (Chemical products of living cells.) * Fungi (Robust organism; no genetic manipulation needed
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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
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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.
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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
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Roehner, Nicholas; Myers, Chris J
2014-02-21
Recently, we have begun to witness the potential of synthetic biology, noted here in the form of bacteria and yeast that have been genetically engineered to produce biofuels, manufacture drug precursors, and even invade tumor cells. The success of these projects, however, has often failed in translation and application to new projects, a problem exacerbated by a lack of engineering standards that combine descriptions of the structure and function of DNA. To address this need, this paper describes a methodology to connect the systems biology markup language (SBML) to the synthetic biology open language (SBOL), existing standards that describe biochemical models and DNA components, respectively. Our methodology involves first annotating SBML model elements such as species and reactions with SBOL DNA components. A graph is then constructed from the model, with vertices corresponding to elements within the model and edges corresponding to the cause-and-effect relationships between these elements. Lastly, the graph is traversed to assemble the annotating DNA components into a composite DNA component, which is used to annotate the model itself and can be referenced by other composite models and DNA components. In this way, our methodology can be used to build up a hierarchical library of models annotated with DNA components. Such a library is a useful input to any future genetic technology mapping algorithm that would automate the process of composing DNA components to satisfy a behavioral specification. Our methodology for SBML-to-SBOL annotation is implemented in the latest version of our genetic design automation (GDA) software tool, iBioSim.
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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.
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Directory of Open Access Journals (Sweden)
Elto Eugenio Gomes e Gama
2003-08-01
Full Text Available O objetivo deste estudo foi determinar através das estimativas de parâmetros genéticos o potencial de um sintético de milho de grãos duros e de ciclo semiprecoce, para a formação de híbridos e/ou melhoramento intrapopulacional. Foram utilizadas 142 progênies endogâmicas S2 do Sin EEL Flint, em cruzamentos topcrosses com um Sintético heteroticamente contrastante. Essas progênies topcrosses foram avaliadas utilizando-se o delineamento em látice simples 12 x 12, e em dois locais de teste. Os maiores valores médios para PED foram observados para os topcrosses n.º 101 (12069kg ha-1 e nº 72 (11068Kg ha-1, tendo o primeiro apresentado comportamento específico para Londrina, e o segunda demonstrado comportamento superior nos dois ambientes. Os valores das estimativas dos parâmetros estudados foram semelhantes aos encontrados em alguns estudos conduzidos em condições tropicais. O grupo de progênies S2 da Sin EEL Flint conduziu a valores médios de , CVg e h² similares aos encontrados na literatura para outros genótipos. Observa-se que esse Sintético possui suficiente variabilidade genética e potencial para extração de linhagens para formação de híbridos e como germoplasma em programas de melhoramento.The objective of this study was to determine the genetic potential of a semi-early maize synthetic with flint type kernel (Sin EEL Flint. The estimation of genetic parameters was obtained with S2 progenies, and the performance of the progenies in hybrid combinations were evaluated. One hundred fourty-two S2 progenies of Sin EEL Flint were used. They were obtained by top crossings with a contrasting heterotic synthetic of dent type kernel. These topcross progenies were tested in a lattice design 12 x 12 with two replications in two locations, Sete Lagoas and Londrina. The selected topcross nº 101, with specific adaptation for Londrina. and nº72, being adapted to both locations, were the best yieldings (PED with 12069Kg ha-1 and
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TMTI Task 1.6 Genetic Engineering Methods and Detection
Energy Technology Data Exchange (ETDEWEB)
Slezak, T; Lenhoff, R; Allen, J; Borucki, M; Vitalis, E; Gardner, S
2009-12-04
A large number of GE techniques can be adapted from other microorganisms to biothreat bacteria and viruses. Detection of GE in a microorganism increases in difficulty as the size of the genetic change decreases. In addition to the size of the engineered change, the consensus genomic sequence of the microorganism can impact the difficulty of detecting an engineered change in genomes that are highly variable from strain to strain. This problem will require comprehensive databases of whole genome sequences for more genetically variable biothreat bacteria and viruses. Preliminary work with microarrays for detecting synthetic elements or virulence genes and analytic bioinformatic approaches for whole genome sequence comparison to detect genetic engineering show promise for attacking this difficult problem but a large amount of future work remains.
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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
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Growth-rate-dependent dynamics of a bacterial genetic oscillator
Osella, Matteo; Lagomarsino, Marco Cosentino
2013-01-01
Gene networks exhibiting oscillatory dynamics are widespread in biology. The minimal regulatory designs giving rise to oscillations have been implemented synthetically and studied by mathematical modeling. However, most of the available analyses generally neglect the coupling of regulatory circuits with the cellular “chassis” in which the circuits are embedded. For example, the intracellular macromolecular composition of fast-growing bacteria changes with growth rate. As a consequence, important parameters of gene expression, such as ribosome concentration or cell volume, are growth-rate dependent, ultimately coupling the dynamics of genetic circuits with cell physiology. This work addresses the effects of growth rate on the dynamics of a paradigmatic example of genetic oscillator, the repressilator. Making use of empirical growth-rate dependencies of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed. The physical support of the circuit (type of plasmid or gene positions on the chromosome) also plays an important role in determining the oscillation stability and the growth-rate dependence of period and amplitude. This analysis has potential application in the field of synthetic biology, and suggests that the coupling between endogenous genetic oscillators and cell physiology can have substantial consequences for their functionality.
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Proceedings of Synthetic Biology: Engineering, Evolution and Design (SEED) Conference 2015
Energy Technology Data Exchange (ETDEWEB)
Silver, Pamela [Harvard Univ., Cambridge, MA (United States); SEED 2015 Conference Chair; Flach, Evan [American Institute of Chemical Engineers; SEED 2015 Conference Organizer
2016-10-27
Synthetic Biology is an emerging discipline that seeks to accelerate the process of engineering biology. As such, the tools are broadly applicable to application areas, including chemicals and biofuels, materials, medicine and agriculture. A characteristic of the field is to look holistically at cellular design, from sensing and genetic circuitry to the manipulation of cellular processes and actuators, to controlling metabolism, to programming multicellular behaviors. Further, the types of cells that are manipulated are broad, from in vitro systems to microbes and fungi to mammalian and plant cells and living animals. Many of the projects in synthetic biology seek to move biochemical functions across organisms. The field is highly interdisciplinary with faculty and students spread across departments that focus on engineering (biological, chemical, electrical, mechanical, civil, computer science) and basic science (biology and systems biology, chemistry, physics). While there have been many one-off workshops and meeting on synthetic biology, the 2014 Synthetic Biology: Engineering, Evolution and Design (SEED) was the first of an annual conference series that serves as a reliable place to pull together the involved disciplines in order to organize and exchange advances in the science and technology in the field. Further, the SEED conferences have a strong focus on industry, with many companies represented and actively participating. A number of these companies have started major efforts in synthetic biology including large companies (e.g., Pfizer, Novartis, Dow, Dupont, BP, Total), smaller companies have recently gone public (e.g., Amyris, Gevo, Intrexon), and many start-ups (e.g., Teslagen, Refactored Materials, Pivot, Genomatica). There are a number of loosely affiliated Synthetic Biology Centers, including ones at MIT, Boston University, UCSD, UCSF, UC-Berkeley, Imperial College, Oxford, and ETH. SEED 2015 will serve as the primary meeting at which international
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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 ...
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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.
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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)
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The Genetics, Neurogenetics and Pharmacogenetics of Addiction.
Demers, Catherine H; Bogdan, Ryan; Agrawal, Arpana
2014-03-01
Addictions are prevalent psychiatric disorders that confer remarkable personal and social burden. Despite substantial evidence for their moderate, yet robust, heritability (approx. 50%), specific genetic mechanisms underlying their development and maintenance remain unclear. The goal of this selective review is to highlight progress in unveiling the genetic underpinnings of addiction. First, we revisit the basis for heritable variation in addiction before reviewing the most replicable candidate gene findings and emerging signals from genomewide association studies for alcohol, nicotine and cannabis addictions. Second, we survey the modest but growing field of neurogenetics examining how genetic variation influences corticostriatal structure, function, and connectivity to identify neural mechanisms that may underlie associations between genetic variation and addiction. Third, we outline how extant genomic findings are being used to develop and refine pharmacotherapies. Finally, as sample sizes for genetically informed studies of addiction approach critical mass, we posit five exciting possibilities that may propel further discovery (improved phenotyping, rare variant discovery, gene-environment interplay, epigenetics, and novel neuroimaging designs).
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Utilization of genetic algorithm in on-line tuning of fluid power servos
Energy Technology Data Exchange (ETDEWEB)
Halme, J.
1997-12-31
This study describes a robust and plausible method based on genetic algorithms suitable for tuning a regulator. The main advantages of the method presented is its robustness and easy-to-use feature. In this thesis the method is demonstrated by searching for appropriate control parameters of a state-feedback controller in a fluid power environment. To corroborate the robustness of the tuning method, two earlier studies are also presented in the appendix, where the presented tuning method is used in different kinds of regulator tuning situations. (orig.) 33 refs.
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Utilization of genetic algorithm in on-line tuning of fluid power servos
Energy Technology Data Exchange (ETDEWEB)
Halme, J
1998-12-31
This study describes a robust and plausible method based on genetic algorithms suitable for tuning a regulator. The main advantages of the method presented is its robustness and easy-to-use feature. In this thesis the method is demonstrated by searching for appropriate control parameters of a state-feedback controller in a fluid power environment. To corroborate the robustness of the tuning method, two earlier studies are also presented in the appendix, where the presented tuning method is used in different kinds of regulator tuning situations. (orig.) 33 refs.
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Methods and Tools for the Analysis, Verification and Synthesis of Genetic Logic Circuits,
DEFF Research Database (Denmark)
Baig, Hasan
2017-01-01
. This usually requires simulating the mathematical models of these genetic circuits and perceive whether or not the circuit behaves appropriately. Furthermore, synthetic biology utilizes the concepts from electronic design automation (EDA) of abstraction and automated construction to generate genetic circuits...... that the proposed approach is effective to determine the variation in the behavior of genetic circuits when the circuit’s parameters are changed. In addition, the thesis also attempts to propose a synthesis and technology mapping tool, called GeneTech, for genetic circuits. It allows users to construct a genetic...... important design characteristics. This thesis also introduces an automated approach to analyze the behavior of genetic logic circuits from the simulation data. With this capability, the boolean logic of complex genetic circuits can be analyzed and/or verified automatically. It is also shown in this thesis...
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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)
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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)
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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...
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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.
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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
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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....
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Genetic architecture and the evolution of sex.
Lohaus, Rolf; Burch, Christina L; Azevedo, Ricardo B R
2010-01-01
Theoretical investigations of the advantages of sex have tended to treat the genetic architecture of organisms as static and have not considered that genetic architecture might coevolve with reproductive mode. As a result, some potential advantages of sex may have been missed. Using a gene network model, we recently showed that recombination imposes selection for robustness to mutation and that negative epistasis can evolve as a by-product of this selection. These results motivated a detailed exploration of the mutational deterministic hypothesis, a hypothesis in which the advantage of sex depends critically on epistasis. We found that sexual populations do evolve higher mean fitness and lower genetic load than asexual populations at equilibrium, and, under moderate stabilizing selection and large population size, these equilibrium sexual populations resist invasion by asexuals. However, we found no evidence that these long- and short-term advantages to sex were explained by the negative epistasis that evolved in our experiments. The long-term advantage of sex was that sexual populations evolved a lower deleterious mutation rate, but this property was not sufficient to account for the ability of sexual populations to resist invasion by asexuals. The ability to resist asexual invasion was acquired simultaneously with an increase in recombinational robustness that minimized the cost of sex. These observations provide the first direct evidence that sexual reproduction does indeed select for conditions that favor its own maintenance. Furthermore, our results highlight the importance of considering a dynamic view of the genetic architecture to understand the evolution of sex and recombination.
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Recoding aminoacyl-tRNA synthetases for synthetic biology by rational protein-RNA engineering.
Hadd, Andrew; Perona, John J
2014-12-19
We have taken a rational approach to redesigning the amino acid binding and aminoacyl-tRNA pairing specificities of bacterial glutaminyl-tRNA synthetase. The four-stage engineering incorporates generalizable design principles and improves the pairing efficiency of noncognate glutamate with tRNA(Gln) by over 10(5)-fold compared to the wild-type enzyme. Better optimized designs of the protein-RNA complex include substantial reengineering of the globular core region of the tRNA, demonstrating a role for specific tRNA nucleotides in specifying the identity of the genetically encoded amino acid. Principles emerging from this engineering effort open new prospects for combining rational and genetic selection approaches to design novel aminoacyl-tRNA synthetases that ligate noncanonical amino acids onto tRNAs. This will facilitate reconstruction of the cellular translation apparatus for applications in synthetic biology.
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Statistics for Learning Genetics
Charles, Abigail Sheena
, although the necessity for infusing these quantitative subjects with genetics and, overall, the biological sciences is growing (topics including synthetic biology, molecular systems biology and phylogenetics) there remains little time in the semester to be dedicated to the consolidation of learning and understanding.
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Genetic activity of plant growth regulators, cartolin and benzilandenin, under ionizing radiation
International Nuclear Information System (INIS)
Vilenskij, E.P.
1987-01-01
Protective effects of a new cytokinin-type growth regulator cartolin (CRT) are established on a genetic test system of waxy-changes in pollen barley grains under acute irradiation of growing plants. It is shown that the CRT effect is similar to that of synthetic cytokinin benziladenin
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Translation and Adaptation of the Genetic Counselling Outcome Scale (GCOS-24) for Use in Denmark
DEFF Research Database (Denmark)
Diness, Birgitte Rode; Overbeck, Gritt; Hjortshøj, Tina Duelund
2017-01-01
Outcome measurement in clinical genetics is challenging. Robust outcome measures are needed to provide evidence to support service development within genetic counseling. The Genetic Counselling Outcome Scale (GCOS-24), a Patient Reported Outcome Measure (PROM), was developed in English...... and validated with clinical genetics patients in the British NHS. This study reports the translation and adaptation of the GCOS-24 for use in Denmark. GCOS-24 was translated and back translated, supervised by an expert committee. Feedback on the first version was collected from genetic counseling patients...
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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.
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International Nuclear Information System (INIS)
Nambu, Yohsuke; Takashima, Toshihide; Inagaki, Akiya
2015-01-01
This paper examines the effects of connecting multiplexing shunt circuits composed of inductors and resistors to piezoelectric transducers so as to improve the robustness of a piezoelectric vibration absorber (PVA). PVAs are well known to be effective at suppressing the vibration of an adaptive structure; their weakness is low robustness to changes in the dynamic parameters of the system, including the main structure and the absorber. In the application to space structures, the temperature-dependency of capacitance of piezoelectric ceramics is the factor that causes performance reduction. To improve robustness to the temperature-dependency of the capacitance, this paper proposes a multiple-PVA system that is composed of distributed piezoelectric transducers and several shunt circuits. The optimization problems that determine both the frequencies and the damping ratios of the PVAs are multi-objective problems, which are solved using a real-coded genetic algorithm in this paper. A clamped aluminum beam with four groups of piezoelectric ceramics attached was considered in simulations and experiments. Numerical simulations revealed that the PVA systems designed using the proposed method had tolerance to changes in the capacitances. Furthermore, experiments using a thermostatic bath were conducted to reveal the effectiveness and robustness of the PVA systems. The maximum peaks of the transfer functions of the beam with the open circuit, the single-PVA system, the double-PVA system, and the quadruple-PVA system at 20 °C were 14.3 dB, −6.91 dB, −7.47 dB, and −8.51 dB, respectively. The experimental results also showed that the multiple-PVA system is more robust than a single PVA in a variable temperature environment from −10 °C to 50 °C. In conclusion, the use of multiple PVAs results in an effective, robust vibration control method for adaptive structures. (paper)
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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.
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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...
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Wong, Brian J F; Karimi, Koohyar; Devcic, Zlatko; McLaren, Christine E; Chen, Wen-Pin
2008-06-01
similar collection of morphometric measures. No correlation with more commonly accepted measures such as the length facial thirds or fifths were identified. When images are examined as a montage (by generation), clear distinct trends are identified: oval shaped faces, distinct arched eyebrows, and full lips predominate. Faces evolve to approximate the guidelines suggested by classical canons. F3 and F4 generation faces look profoundly similar. The statistical and qualitative analysis indicates that the algorithm and methodology succeeds in generating successively more attractive faces. The use of genetic algorithms in combination with a morphing software and traditional focus-group derived attractiveness scores can be used to evolve attractive synthetic faces. We have demonstrated that the evolution of attractive faces can be mimicked in software. Genetic algorithms and morphing provide a robust alternative to traditional approaches rooted in comparing attractiveness scores with a series of morphometric measurements in human subjects.
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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…
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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...
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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...
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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...
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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...
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Application of genetic algorithms for parameter estimation in liquid chromatography
International Nuclear Information System (INIS)
Hernandez Torres, Reynier; Irizar Mesa, Mirtha; Tavares Camara, Leoncio Diogenes
2012-01-01
In chromatography, complex inverse problems related to the parameters estimation and process optimization are presented. Metaheuristics methods are known as general purpose approximated algorithms which seek and hopefully find good solutions at a reasonable computational cost. These methods are iterative process to perform a robust search of a solution space. Genetic algorithms are optimization techniques based on the principles of genetics and natural selection. They have demonstrated very good performance as global optimizers in many types of applications, including inverse problems. In this work, the effectiveness of genetic algorithms is investigated to estimate parameters in liquid chromatography
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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
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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...
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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.
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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.
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A model for improving microbial biofuel production using a synthetic feedback loop
Energy Technology Data Exchange (ETDEWEB)
Dunlop, Mary; Keasling, Jay; Mukhopadhyay, Aindrila
2011-07-14
Cells use feedback to implement a diverse range of regulatory functions. Building synthetic feedback control systems may yield insight into the roles that feedback can play in regulation since it can be introduced independently of native regulation, and alternative control architectures can be compared. We propose a model for microbial biofuel production where a synthetic control system is used to increase cell viability and biofuel yields. Although microbes can be engineered to produce biofuels, the fuels are often toxic to cell growth, creating a negative feedback loop that limits biofuel production. These toxic effects may be mitigated by expressing efflux pumps that export biofuel from the cell. We developed a model for cell growth and biofuel production and used it to compare several genetic control strategies for their ability to improve biofuel yields. We show that controlling efflux pump expression directly with a biofuel-responsive promoter is a straight forward way of improving biofuel production. In addition, a feed forward loop controller is shown to be versatile at dealing with uncertainty in biofuel production rates.
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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...
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Ortholog prediction of the Aspergillus genus applicable for synthetic biology
DEFF Research Database (Denmark)
Rasmussen, Jane Lind Nybo; Vesth, Tammi Camilla; Theobald, Sebastian
of genotype-to-phenotype. To achieve this, we have developed orthologous protein prediction software that utilizes genus-wide genetic diversity. The approach is optimized for large data sets, based on BLASTp considering protein identity and alignment coverage, and clustering using single linkage of bi......The Aspergillus genus contains leading industrial microorganisms, excelling in producing bioactive compounds and enzymes. Using synthetic biology and bioinformatics, we aim to re-engineer these organisms for applications within human health, pharmaceuticals, environmental engineering, and food......-directional hits. The result is orthologous protein families describing the genomic and functional features of individual species, clades and the core/pan genome of Aspergillus; and applicable to genotype-to-phenotype analyses in other microbial genera....
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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".
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Metformin is synthetically lethal with glucose withdrawal in cancer cells.
Menendez, Javier A; Oliveras-Ferraros, Cristina; Cufí, Sílvia; Corominas-Faja, Bruna; Joven, Jorge; Martin-Castillo, Begoña; Vazquez-Martin, Alejandro
2012-08-01
Glucose deprivation is a distinctive feature of the tumor microecosystem caused by the imbalance between poor supply and an extraordinarily high consumption rate. The metabolic reprogramming from mitochondrial respiration to aerobic glycolysis in cancer cells (the "Warburg effect") is linked to oncogenic transformation in a manner that frequently implies the inactivation of metabolic checkpoints such as the energy rheostat AMP-activated protein kinase (AMPK). Because the concept of synthetic lethality in oncology can be applied not only to genetic and epigenetic intrinsic differences between normal and cancer cells but also to extrinsic ones such as altered microenvironment, we recently hypothesized that stress-energy mimickers such as the AMPK agonist metformin should produce metabolic synthetic lethality in a glucose-starved cell culture milieu imitating the adverse tumor growth conditions in vivo. Under standard high-glucose conditions, metformin supplementation mostly caused cell cycle arrest without signs of apoptotic cell death. Under glucose withdrawal stress, metformin supplementation circumvented the ability of oncogenes (e.g., HER2) to protect breast cancer cells from glucose-deprivation apoptosis. Significantly, representative cell models of breast cancer heterogeneity underwent massive apoptosis (by >90% in some cases) when glucose-starved cell cultures were supplemented with metformin. Our current findings may uncover crucial issues regarding the cell-autonomous metformin's anti-cancer actions: (1) The offently claimed clinically irrelevant, non-physiological concentrations needed to observe the metformin's anti-cancer effects in vitro merely underlie the artifactual interference of erroneous glucose-rich experimental conditions that poorly reflect glucose-starved in vivo conditions; (2) the preferential killing of cancer stem cells (CSC) by metformin may simply expose the best-case scenario for its synthetically lethal activity because an increased
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Directed genetic modification of African horse sickness virus by reverse genetics
Directory of Open Access Journals (Sweden)
Elaine Vermaak
2015-07-01
Full Text Available African horse sickness virus (AHSV, a member of the Orbivirus genus in the family Reoviridae, is an arthropod-transmitted pathogen that causes a devastating disease in horses with a mortality rate greater than 90%. Fundamental research on AHSV and the development of safe, efficacious vaccines could benefit greatly from an uncomplicated genetic modification method to generate recombinant AHSV. We demonstrate that infectious AHSV can be recovered by transfection of permissive mammalian cells with transcripts derived in vitro from purified AHSV core particles. These findings were expanded to establish a genetic modification system for AHSV that is based on transfection of the cells with a mixture of purified core transcripts and a synthetic T7 transcript. This approach was applied successfully to recover a directed cross-serotype reassortant AHSV and to introduce a marker sequence into the viral genome. The ability to manipulate the AHSV genome and engineer specific mutants will increase understanding of AHSV replication and pathogenicity, as well as provide a tool for generating designer vaccine strains.
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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.
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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.
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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.
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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.
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[Genetic factors in myocardial infarction].
Hara, Masahiko; Sakata, Yasuhiko; Sato, Hiroshi
2013-02-01
One of the main mechanisms of acute myocardial infarction (AMI) is plaque rupture or erosion followed by intraluminal thrombus formation and occlusion of the coronary arteries. Thus far, many underlying conditions or environmental factors, such as hypertension, diabetes, dyslipidemia, smoking or obesity, as well as a family history of coronary artery diseases have been identified as risks for the onset of AMI. These risks suggest that AMI occurs due to interactions between underlying conditions and multiple genetic susceptibilities. For this reason, many target gene-disease association studies have been performed with the recent introduction of genome-wide association studies (GWAS) that have further revealed new genetic susceptibilities for AMI. GWAS is a way to examine many common genetic variants in different individuals to see if any variant is associated with a trait in a case-control fashion, and typically focuses on associations between single-nucleotide polymorphisms (SNP) and traits. SNP on chromosome 9p21 is one of the robust susceptibility variants for AMI which has been identified by many GWAS. In this review, we overview the methodology of GWAS, introduce genetic variants identified by GWAS as those with susceptibility for AMI, and describe the foresight of using GWAS to investigate genetic susceptibility to AMI.
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Robust design of broadband EUV multilayer beam splitters based on particle swarm optimization
International Nuclear Information System (INIS)
Jiang, Hui; Michette, Alan G.
2013-01-01
A robust design idea for broadband EUV multilayer beam splitters is introduced that achieves the aim of decreasing the influence of layer thickness errors on optical performances. Such beam splitters can be used in interferometry to determine the quality of EUVL masks by comparing with a reference multilayer. In the optimization, particle swarm techniques were used for the first time in such designs. Compared to conventional genetic algorithms, particle swarm optimization has stronger ergodicity, simpler processing and faster convergence
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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.
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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.
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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
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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...
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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...
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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.
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Numeral eddy current sensor modelling based on genetic neural network
International Nuclear Information System (INIS)
Yu Along
2008-01-01
This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method
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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.
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A Hybrid Genetic Algorithm Approach for Optimal Power Flow
Directory of Open Access Journals (Sweden)
Sydulu Maheswarapu
2011-08-01
Full Text Available This paper puts forward a reformed hybrid genetic algorithm (GA based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA, adaptive genetic algorithm (AGA, differential evolution (DE, particle swarm optimization (PSO and music based harmony search (MBHS on a IEEE30 bus test bed, with a total load of 283.4 MW. Its found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.
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Design Optimization of Tilting-Pad Journal Bearing Using a Genetic Algorithm
Directory of Open Access Journals (Sweden)
Hamit Saruhan
2004-01-01
Full Text Available This article focuses on the use of genetic algorithms in developing an efficient optimum design method for tilting pad bearings. The approach optimizes based on minimum film thickness, power loss, maximum film temperature, and a global objective. Results for a five tilting-pad preloaded bearing are presented to provide a comparison with more traditional optimum design methods such as the gradient-based global criterion method, and also to provide insight into the potential of genetic algorithms in the design of rotor bearings. Genetic algorithms are efficient search techniques based on the idea of natural selection and genetics. These robust methods have gained recognition as general problem solving techniques in many applications.
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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.
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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.
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Rahman, M M; Baker, G; Powis, K J; Roush, R T; Schmidt, O
2010-08-01
Field surveys of pest insect pest populations in agroecosystems reveal low but significant levels of tolerance to synthetic and biological pesticides but fail to uncover resistance alleles in test crosses. To study the potential of inducible mechanisms to generate tolerance to synthetic pesticides, we performed baseline susceptibility studies in field and laboratory populations of diamondback moth, Plutella xylostella (L.), to commercial formulations of emamectin benzoate. Pesticide exposure in the field caused elevated levels of tolerance, which decreased in field-collected populations after maintaining insects with pesticide-free diet in the laboratory. Because no significant resistance alleles were identified in back-crossed individuals, the observed increase in tolerance was probably not based on preexisting recessive resistance mechanisms in the population. Instead, the genetic analysis after five and 12 generations is compatible with a transient up-regulation of an immune and metabolic status in tolerant insects that can be transmitted to offspring by a maternal effect. Although the epigenetic effects contributed to incremental increases in tolerance in the first five generations, other resistance mechanisms that are transmitted genetically predominate after 12 generations of increased exposure to the pesticide.
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Synthetic biology routes to bio-artificial intelligence
Zaikin, Alexey; Saka, Yasushi; Romano, M. Carmen; Giuraniuc, Claudiu V.; Kanakov, Oleg; Laptyeva, Tetyana
2016-01-01
The design of synthetic gene networks (SGNs) has advanced to the extent that novel genetic circuits are now being tested for their ability to recapitulate archetypal learning behaviours first defined in the fields of machine and animal learning. Here, we discuss the biological implementation of a perceptron algorithm for linear classification of input data. An expansion of this biological design that encompasses cellular ‘teachers’ and ‘students’ is also examined. We also discuss implementation of Pavlovian associative learning using SGNs and present an example of such a scheme and in silico simulation of its performance. In addition to designed SGNs, we also consider the option to establish conditions in which a population of SGNs can evolve diversity in order to better contend with complex input data. Finally, we compare recent ethical concerns in the field of artificial intelligence (AI) and the future challenges raised by bio-artificial intelligence (BI). PMID:27903825
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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
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Cell Factory Stability and Genetic Circuits for Improved Strain Development
DEFF Research Database (Denmark)
Rugbjerg, Peter
. However, all synthetic gene systems - including the target metabolic pathways themselves - represent a possible fitness burden to the cell and thus constitute a threat to strain stability. In this thesis, several studies served to develop genetic systems for optimizing cell factory development...... systems can challenge the stability of strain designs. A metabolite-producing Escherichia coli strain was long-term cultured to study production stability and the dynamic effects of mutations within the cell population. A genetic error landscape of pathway disruptions was identified including particular......Development of new chemical-‐producing microbial cell factories is an iterative trial-and-error process, and to screen candidate cells at high throughput, genetic biosensor systems are appealing. Each biosensor has distinct biological parameters, making modular tuning networks attractive...
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BacillOndex: An Integrated Data Resource for Systems and Synthetic Biology
Directory of Open Access Journals (Sweden)
Misirli Goksel
2013-06-01
Full Text Available BacillOndex is an extension of the Ondex data integration system, providing a semantically annotated, integrated knowledge base for the model Gram-positive bacterium Bacillus subtilis. This application allows a user to mine a variety of B. subtilis data sources, and analyse the resulting integrated dataset, which contains data about genes, gene products and their interactions. The data can be analysed either manually, by browsing using Ondex, or computationally via a Web services interface. We describe the process of creating a BacillOndex instance, and describe the use of the system for the analysis of single nucleotide polymorphisms in B. subtilis Marburg. The Marburg strain is the progenitor of the widely-used laboratory strain B. subtilis 168. We identified 27 SNPs with predictable phenotypic effects, including genetic traits for known phenotypes. We conclude that BacillOndex is a valuable tool for the systems-level investigation of, and hypothesis generation about, this important biotechnology workhorse. Such understanding contributes to our ability to construct synthetic genetic circuits in this organism.
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BacillOndex: An Integrated Data Resource for Systems and Synthetic Biology.
Misirli, Goksel; Wipat, Anil; Mullen, Joseph; James, Katherine; Pocock, Matthew; Smith, Wendy; Allenby, Nick; Hallinan, Jennifer S
2013-06-01
BacillOndex is an extension of the Ondex data integration system, providing a semantically annotated, integrated knowledge base for the model Gram-positive bacterium Bacillus subtilis. This application allows a user to mine a variety of B. subtilis data sources, and analyse the resulting integrated dataset, which contains data about genes, gene products and their interactions. The data can be analysed either manually, by browsing using Ondex, or computationally via a Web services interface. We describe the process of creating a BacillOndex instance, and describe the use of the system for the analysis of single nucleotide polymorphisms in B. subtilis Marburg. The Marburg strain is the progenitor of the widely-used laboratory strain B. subtilis 168. We identified 27 SNPs with predictable phenotypic effects, including genetic traits for known phenotypes. We conclude that BacillOndex is a valuable tool for the systems-level investigation of, and hypothesis generation about, this important biotechnology workhorse. Such understanding contributes to our ability to construct synthetic genetic circuits in this organism.
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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.
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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.
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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.
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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
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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.
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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
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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...
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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.
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Recent advances in antisense oligonucleotide therapy in genetic neuromuscular diseases
Directory of Open Access Journals (Sweden)
Ashok Verma
2018-01-01
Full Text Available Genetic neuromuscular diseases are caused by defective expression of nuclear or mitochondrial genes. Mutant genes may reduce expression of wild-type proteins, and strategies to activate expression of the wild-type proteins might provide therapeutic benefits. Also, a toxic mutant protein may cause cell death, and strategies that reduce mutant gene expression may provide therapeutic benefit. Synthetic antisense oligonucleotide (ASO can recognize cellular RNA and control gene expression. In recent years, advances in ASO chemistry, creation of designer ASO molecules to enhance their safety and target delivery, and scientific controlled clinical trials to ascertain their therapeutic safety and efficacy have led to an era of plausible application of ASO technology to treat currently incurable neuromuscular diseases. Over the past 1 year, for the first time, the United States Food and Drug Administration has approved two ASO therapies in genetic neuromuscular diseases. This overview summarizes the recent advances in ASO technology, evolution and use of synthetic ASOs as a therapeutic platform, and the mechanism of ASO action by exon-skipping in Duchenne muscular dystrophy and exon-inclusion in spinal muscular atrophy, with comments on their advantages and limitations.
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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.
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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
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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...
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Tien, Shin-Ming; Hsu, Chih-Yuan; Chen, Bor-Sen
2016-01-01
Bacteria navigate environments full of various chemicals to seek favorable places for survival by controlling the flagella's rotation using a complicated signal transduction pathway. By influencing the pathway, bacteria can be engineered to search for specific molecules, which has great potential for application to biomedicine and bioremediation. In this study, genetic circuits were constructed to make bacteria search for a specific molecule at particular concentrations in their environment through a synthetic biology method. In addition, by replacing the "brake component" in the synthetic circuit with some specific sensitivities, the bacteria can be engineered to locate areas containing specific concentrations of the molecule. Measured by the swarm assay qualitatively and microfluidic techniques quantitatively, the characteristics of each "brake component" were identified and represented by a mathematical model. Furthermore, we established another mathematical model to anticipate the characteristics of the "brake component". Based on this model, an abundant component library can be established to provide adequate component selection for different searching conditions without identifying all components individually. Finally, a systematic design procedure was proposed. Following this systematic procedure, one can design a genetic circuit for bacteria to rapidly search for and locate different concentrations of particular molecules by selecting the most adequate "brake component" in the library. Moreover, following simple procedures, one can also establish an exclusive component library suitable for other cultivated environments, promoter systems, or bacterial strains.
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Directory of Open Access Journals (Sweden)
Shin-Ming Tien
Full Text Available Bacteria navigate environments full of various chemicals to seek favorable places for survival by controlling the flagella's rotation using a complicated signal transduction pathway. By influencing the pathway, bacteria can be engineered to search for specific molecules, which has great potential for application to biomedicine and bioremediation. In this study, genetic circuits were constructed to make bacteria search for a specific molecule at particular concentrations in their environment through a synthetic biology method. In addition, by replacing the "brake component" in the synthetic circuit with some specific sensitivities, the bacteria can be engineered to locate areas containing specific concentrations of the molecule. Measured by the swarm assay qualitatively and microfluidic techniques quantitatively, the characteristics of each "brake component" were identified and represented by a mathematical model. Furthermore, we established another mathematical model to anticipate the characteristics of the "brake component". Based on this model, an abundant component library can be established to provide adequate component selection for different searching conditions without identifying all components individually. Finally, a systematic design procedure was proposed. Following this systematic procedure, one can design a genetic circuit for bacteria to rapidly search for and locate different concentrations of particular molecules by selecting the most adequate "brake component" in the library. Moreover, following simple procedures, one can also establish an exclusive component library suitable for other cultivated environments, promoter systems, or bacterial strains.
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Directory of Open Access Journals (Sweden)
Riaan A.L. Rheeder
2014-10-01
Full Text Available On 20 May 2010, the Venter Institute in America announced that they have fully synthesised the genome of the organism Mycoplasma mycoides whilst in vitro by using a computer connected to a machine that synthesises genes. Thereafter, the genome was placed back into the casing of another organism (Mycoplasma capricolum and it was reported that the synthesised organism and the genome functioned normally. This synthesised organism was reconstructed to function as a minute little factory with the aim of producing and secreting fuel and medicine − something that is not the natural function of this organism. There are certain potential dangers inherent in this kind of technology. Scientists fear that this technology may contaminate or infect humans, animals or the environment, and that it can as such be extremely harmful, or even lead to the destruction of humans. Other scientists are concerned that terrorists can use this technology to kill innocent citizens. Some ethicists are of the opinion that the consequences of synthetic biology is currently unpredictable and that it is therefore risky. In opposition to the potential dangers, one has to mention that synthetic biology indeed can result in far-reaching positive outcomes such as the manufacturing of biofuel and medication. Most scientists and ethicists are of the opinion that the potential dangers involved in synthetic biology should be evaluated in light of the fact that genetic manipulation has not caused any biological devastation over the last 30 years. From a Christian point of departure, the opinion is currently that synthetic biology is not an irresponsible science and technology.
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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.
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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.
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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.
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Optimization Design by Genetic Algorithm Controller for Trajectory Control of a 3-RRR Parallel Robot
Directory of Open Access Journals (Sweden)
Lianchao Sheng
2018-01-01
Full Text Available In order to improve the control precision and robustness of the existing proportion integration differentiation (PID controller of a 3-Revolute–Revolute–Revolute (3-RRR parallel robot, a variable PID parameter controller optimized by a genetic algorithm controller is proposed in this paper. Firstly, the inverse kinematics model of the 3-RRR parallel robot was established according to the vector method, and the motor conversion matrix was deduced. Then, the error square integral was chosen as the fitness function, and the genetic algorithm controller was designed. Finally, the control precision of the new controller was verified through the simulation model of the 3-RRR planar parallel robot—built in SimMechanics—and the robustness of the new controller was verified by adding interference. The results show that compared with the traditional PID controller, the new controller designed in this paper has better control precision and robustness, which provides the basis for practical application.
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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.
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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....
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Model-based problem solving through symbolic regression via pareto genetic programming
Vladislavleva, E.
2008-01-01
Pareto genetic programming methodology is extended by additional generic model selection and generation strategies that (1) drive the modeling engine to creation of models of reduced non-linearity and increased generalization capabilities, and (2) improve the effectiveness of the search for robust
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Microorganism Utilization for Synthetic Milk
Morford, Megan A.; Khodadad, Christina L.; Caro, Janicce I.; Spencer, LaShelle E.; Richards, Jeffery T.; Strayer, Richard F.; Birmele, Michele N.; Wheeler, Raymond M.
2014-01-01
A desired architecture for long duration spaceflight, like aboard the International Space Station or for future missions to Mars, is to provide a supply of fresh food crops for the astronauts. However, some crops can create a high proportion of inedible plant waste. The main goal of the Synthetic Biology project, Cow in a Column, was to produce the components of milk (sugar, lipid, protein) from inedible plant waste by utilizing microorganisms (fungi, yeast, bacteria). Of particular interest was utilizing the valuable polysaccharide, cellulose, found in plant waste, to naturally fuel-through microorganism cellular metabolism- the creation of sugar (glucose), lipid (milk fat), and protein (casein) in order to produce a synthetic edible food product. Environmental conditions such as pH, temperature, carbon source, aeration, and choice microorganisms were optimized in the laboratory and the desired end-products, sugars and lipids, were analyzed. Trichoderma reesei, a known cellulolytic fungus, was utilized to drive the production of glucose, with the intent that the produced glucose would serve as the carbon source for milk fat production and be a substitute for the milk sugar lactose. Lipid production would be carried out by Rhodosporidium toruloides, yeast known to accumulate those lipids that are typically found in milk fat. Results showed that glucose and total lipid content were below what was expected during this phase of experimentation. In addition, individual analysis of six fatty acids revealed that the percentage of each fatty acid was lower than naturally produced bovine milk. Overall, this research indicates that microorganisms could be utilized to breakdown inedible solid waste to produce useable products. For future work, the production of the casein protein for milk would require the development of a genetically modified organism, which was beyond the scope of the original project. Additional trials would be needed to further refine the required
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A robust PSSs design using PSO in a multi-machine environment
Energy Technology Data Exchange (ETDEWEB)
Shayeghi, H., E-mail: hshayeghi@gmail.co [Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil (Iran, Islamic Republic of); Shayanfar, H.A. [Center of Excellence for Power Automation and Operation, Electrical Engineering Department, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Safari, A.; Aghmasheh, R. [Technical Engineering Department, Zanjan University, Zanjan (Iran, Islamic Republic of)
2010-04-15
In this paper, multi-objective design of multi-machine power system stabilizers (PSSs) using particle swarm optimization (PSO) is proposed. The potential of the proposed approach for optimal setting of the widely used conventional lead-lag PSSs has been investigated. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electromechanical modes of all machines to a prescribed zone in the s-plane. The PSSs parameters tuning problem is converted to an optimization problem with the eigenvalue-based multi-objective function comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes, which is solved by a PSO algorithm which has a strong ability to find the most optimistic results. The robustness of the proposed PSO-based PSSs (PSOPSS) is verified on a multi-machine power system under different operating conditions and disturbances. The results of the proposed PSOPSS are compared with the genetic algorithm based tuned PSS and classical PSSs through eigenvalue analysis, nonlinear time-domain simulation and some performance indices to illustrate its robust performance for a wide range of loading conditions.
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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.
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Robust and flexible mapping for real-time distributed applications during the early design phases
DEFF Research Database (Denmark)
Gan, Junhe; Pop, Paul; Gruian, Flavius
2012-01-01
has a high chance of being schedulable, considering the wcet uncertainties, whereas a flexible mapping has a high chance to successfully accommodate the future scenarios. We propose a Genetic Algorithm-based approach to solve this optimization problem. Extensive experiments show the importance......We are interested in mapping hard real-time applications on distributed heterogeneous architectures. An application is modeled as a set of tasks, and we consider a fixed-priority preemptive scheduling policy. We target the early design phases, when decisions have a high impact on the subsequent...... in the functionality requirements are captured using “future scenarios”, which are task sets that model functionality likely to be added in the future. In this context, we derive a mapping of tasks in the application, such that the resulted implementation is both robust and flexible. Robust means that the application...
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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.
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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.
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Development of Next Generation Synthetic Biology Tools for Use in Streptomyces venezuelae
Energy Technology Data Exchange (ETDEWEB)
Phelan, Ryan M. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Univ. of California, Berkeley, CA (United States). QB3 Inst.; Sachs, Daniel [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Petkiewicz, Shayne J. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Barajas, Jesus F. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Blake-Hedges, Jacquelyn M. [Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Thompson, Mitchell G. [Univ. of California, Berkeley, CA (United States). Dept. of Plant & Microbial Biology; Reider Apel, Amanda [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Rasor, Blake J. [Miami Univ., Oxford, Ohio (United States). Dept. of Biology; Katz, Leonard [Univ. of California, Berkeley, CA (United States). QB3 Inst.; Keasling, Jay D. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Univ. of California, Berkeley, CA (United States). QB3 Inst.; Univ. of California, Berkeley, CA (United States). Dept. of Chemical and Biomolecular Engineering and Department of Bioengineering; Technical Univ. of Denmark, Kogle Alle (Denmark). Novo Nordisk Foundation Center for Biosustainability
2016-09-07
Streptomyces have a rich history as producers of important natural products and this genus of bacteria has recently garnered attention for its potential applications in the broader context of synthetic biology. However, the dearth of genetic tools available to control and monitor protein production precludes rapid and predictable metabolic engineering that is possible in hosts such as Escherichia coli or Saccharomyces cerevisiae. In an effort to improve genetic tools for Streptomyces venezuelae, we developed a suite of standardized, orthogonal integration vectors and an improved method to monitor protein production in this host. These tools were applied to characterize heterologous promoters and various attB chromosomal integration sites. A final study leveraged the characterized toolset to demonstrate its use in producing the biofuel precursor bisabolene using a chromosomally integrated expression system. In conclusion, these tools advance S. venezuelae to be a practical host for future metabolic engineering efforts.
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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.
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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...
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A synthetic maternal-effect selfish genetic element drives population replacement in Drosophila.
Chen, Chun-Hong; Huang, Haixia; Ward, Catherine M; Su, Jessica T; Schaeffer, Lorian V; Guo, Ming; Hay, Bruce A
2007-04-27
One proposed strategy for controlling the transmission of insect-borne pathogens uses a drive mechanism to ensure the rapid spread of transgenes conferring disease refractoriness throughout wild populations. Here, we report the creation of maternal-effect selfish genetic elements in Drosophila that drive population replacement and are resistant to recombination-mediated dissociation of drive and disease refractoriness functions. These selfish elements use microRNA-mediated silencing of a maternally expressed gene essential for embryogenesis, which is coupled with early zygotic expression of a rescuing transgene.
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[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.
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Mechanical design in embryos: mechanical signalling, robustness and developmental defects.
Davidson, Lance A
2017-05-19
Embryos are shaped by the precise application of force against the resistant structures of multicellular tissues. Forces may be generated, guided and resisted by cells, extracellular matrix, interstitial fluids, and how they are organized and bound within the tissue's architecture. In this review, we summarize our current thoughts on the multiple roles of mechanics in direct shaping, mechanical signalling and robustness of development. Genetic programmes of development interact with environmental cues to direct the composition of the early embryo and endow cells with active force production. Biophysical advances now provide experimental tools to measure mechanical resistance and collective forces during morphogenesis and are allowing integration of this field with studies of signalling and patterning during development. We focus this review on concepts that highlight this integration, and how the unique contributions of mechanical cues and gradients might be tested side by side with conventional signalling systems. We conclude with speculation on the integration of large-scale programmes of development, and how mechanical responses may ensure robust development and serve as constraints on programmes of tissue self-assembly.This article is part of the themed issue 'Systems morphodynamics: understanding the development of tissue hardware'. © 2017 The Author(s).
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Directory of Open Access Journals (Sweden)
Ashutosh K. AGARWAL
2011-10-01
Full Text Available Genetic algorithms are robust search techniques based on the principles of evolution. A genetic algorithm maintains a population of encoded solutions and guides the population towards the optimum solution. This important property of genetic algorithm is used in this paper to stabilize the Inverted pendulum system. This paper highlights the application and stability of inverted pendulum using PID controller with fuzzy logic genetic algorithm supervisor . There are a large number of well established search techniques in use within the information technology industry. We propose a method to control inverted pendulum steady state error and overshoot using genetic algorithm technique.
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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."