Gavasso, Sonia; Gullaksen, Stein-Erik; Skavland, Jørn; Gjertsen, Bjørn T
Single-cell proteomics in cancer is evolving and promises to provide more accurate diagnoses based on detailed molecular features of cells within tumors. This review focuses on technologies that allow for collection of complex data from single cells, but also highlights methods that are adaptable to routine cancer diagnostics. Current diagnostics rely on histopathological analysis, complemented by mutational detection and clinical imaging. Though crucial, the information gained is often not directly transferable to defined therapeutic strategies, and predicting therapy response in a patient is difficult. In cancer, cellular states revealed through perturbed intracellular signaling pathways can identify functional mutations recurrent in cancer subsets. Single-cell proteomics remains to be validated in clinical trials where serial samples before and during treatment can reveal excessive clonal evolution and therapy failure; its use in clinical trials is anticipated to ignite a diagnostic revolution that will better align diagnostics with the current biological understanding of cancer.
Su, Yapeng; Shi, Qihui; Wei, Wei
New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Full Text Available Microbiologists traditionally study population rather than individual cells, as it is generally assumed that the status of individual cells will be similar to that observed in the population. However, the recent studies have shown that the individual behavior of each single cell could be quite different from that of the whole population, suggesting the importance of extending traditional microbiology studies to single-cell level. With recent technological advances, such as flow cytometry, next-generation sequencing (NGS, and microspectroscopy, single-cell microbiology has greatly enhanced the understanding of individuality and heterogeneity of microbes in many biological systems. Notably, the application of multiple ‘omics’ in single-cell analysis has shed light on how individual cells perceive, respond, and adapt to the environment, how heterogeneity arises under external stress and finally determines the fate of the whole population, and how microbes survive under natural conditions. As single-cell analysis involves no axenic cultivation of target microorganism, it has also been demonstrated as a valuable tool for dissecting the microbial ‘dark matter.’ In this review, current state-of-the-art tools and methods for genomic and transcriptomic analysis of microbes at single-cell level were critically summarized, including single-cell isolation methods and experimental strategies of single-cell analysis with NGS. In addition, perspectives on the future trends of technology development in the field of single-cell analysis was also presented.
Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin
Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.
Stanford University's Steve Quake on "Sequencing Single Cell Microbial Genomes with Microfluidic Amplification Tools" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.
Zolg, Daniel P.; Wilhelm, Mathias; Schnatbaum, Karsten; Zerweck, Johannes; Knaute, Tobias; Delanghe, Bernard; Bailey, Derek J.; Gessulat, Siegfried; Ehrlich, Hans-Christian; Weininger, Maximilian; Yu, Peng; Schlegl, Judith; Kramer, Karl; Schmidt, Tobias; Kusebauch, Ulrike; Deutsch, Eric W.; Aebersold, Ruedi; Moritz, Robert L.; Wenschuh, Holger; Moehring, Thomas; Aiche, Stephan; Huhmer, Andreas; Reimer, Ulf; Kuster, Bernhard
The ProteomeTools project builds molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we report the generation and multimodal LC-MS/MS analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products and exemplify the utility of this data. The resource will be extended to >1 million peptides and all data will be shared with the community via ProteomicsDB and proteomeXchange. PMID:28135259
Schizophrenia is likely to be a multifactorial disorder, consequence of alterations in gene and protein expression since the neurodevelopment that together to environmental factors will trigger the establishment of the disease. In the post-genomic era, proteomics has emerged as a promising strategy for revealing disease and treatment biomarkers as well as a tool for the comprehension of the mechanisms of schizophrenia pathobiology. Here, there is a discussion of the potential pathways and str...
Li, Jiayao; Kim, Yeonuk; Liu, Boyin; Qin, Ruwen; Li, Jian; Fu, Jing
The nano-manipulation approach that combines Focused Ion Beam (FIB) milling and various imaging and probing techniques enables researchers to investigate the cellular structures in three dimensions. Such fusion approach, however, requires extensive effort on locating and examining randomly-distributed targets due to limited Field of View (FOV) when high magnification is desired. In the present study, we present the development that automates 'pattern and probe' particularly for single-cell analysis, achieved by computer aided tools including feature recognition and geometric planning algorithms. Scheduling of serial FOVs for imaging and probing of multiple cells was considered as a rectangle covering problem, and optimal or near-optimal solutions were obtained with the heuristics developed. FIB milling was then employed automatically followed by downstream analysis using Atomic Force Microscopy (AFM) to probe the cellular interior. Our strategy was applied to examine bacterial cells (Klebsiella pneumoniae) and achieved high efficiency with limited human interference. The developed algorithms can be easily adapted and integrated with different imaging platforms towards high-throughput imaging analysis of single cells. Copyright © 2017 Elsevier Ltd. All rights reserved.
Full Text Available A sharp decline in the availability of arable land and sufficient supply of irrigation water along with a continuous steep increase in food demands have exerted a pressure on farmers to produce more with fewer resources. A viable solution to release this pressure is to speed up the plant breeding process by employing biotechnology in breeding programs. The majority of biotechnological applications rely on information generated from various -omic technologies. The latest outstanding improvements in proteomic platforms and many other but related advances in plant biotechnology techniques offer various new ways to encourage the usage of these technologies by plant scientists for crop improvement programs. A combinatorial approach of accelerated gene discovery through genomics, proteomics, and other associated -omic branches of biotechnology, as an applied approach, is proving to be an effective way to speed up the crop improvement programs worldwide. In the near future, swift improvements in -omic databases are becoming critical and demand immediate attention for the effective utilization of these techniques to produce next-generation crops for the progressive farmers. Here, we have reviewed the recent advances in proteomics, as tools of biotechnology, which are offering great promise and leading the path towards crop improvement for sustainable agriculture.
Yip, Shun H; Sham, Pak Chung; Wang, Junwen
Traditional RNA sequencing (RNA-seq) allows the detection of gene expression variations between two or more cell populations through differentially expressed gene (DEG) analysis. However, genes that contribute to cell-to-cell differences are not discoverable with RNA-seq because RNA-seq samples are obtained from a mixture of cells. Single-cell RNA-seq (scRNA-seq) allows the detection of gene expression in each cell. With scRNA-seq, highly variable gene (HVG) discovery allows the detection of genes that contribute strongly to cell-to-cell variation within a homogeneous cell population, such as a population of embryonic stem cells. This analysis is implemented in many software packages. In this study, we compare seven HVG methods from six software packages, including BASiCS, Brennecke, scLVM, scran, scVEGs and Seurat. Our results demonstrate that reproducibility in HVG analysis requires a larger sample size than DEG analysis. Discrepancies between methods and potential issues in these tools are discussed and recommendations are made.
Márcio S. Rocha
Full Text Available We present a review on two new tools to study biophysical properties of single molecules and single cells. A laser incident through a high numerical aperture microscope objective can trap small dielectric particles near the focus. This arrangement is named optical tweezers. This technique has the advantage to permit manipulation of a single individual object. We use optical tweezers to measure the entropic elasticity of a single DNA molecule and its interaction with the drug Psoralen. Optical tweezers are also used to hold a kidney cell MDCK away from the substrate to allow precise volume measurements of this single cell during an osmotic shock. This procedure allows us to obtain information about membrane water permeability and regulatory volume increase. Defocusing microscopy is a recent technique invented in our laboratory, which allows the observation of transparent objects, by simply defocusing the microscope in a controlled way. Our physical model of a defocused microscope shows that the image contrast observed in this case is proportional to the defocus distance and to the curvature of the transparent object. Defocusing microscopy is very useful to study motility and mechanical properties of cells. We show here the application of defocusing microscopy to measurements of macrophage surface fluctuations and their influence on phagocytosis.Apresentamos uma revisão de duas novas técnicas para estudar propriedades biofísicas de moléculas únicas e células únicas. Um laser incidindo em uma objetiva de microscópio de grande abertura numérica é capaz de aprisionar pequenas partículas dielétricas na região próxima ao foco. Este aparato é chamado de pinça óptica. Esta técnica tem a grande vantagem de permitir a manipulação de um objeto individual. Usamos a pinça óptica para medir a elasticidade entrópica de uma molécula única de DNA em sua interação com o fármaco Psoralen. A pinça óptica também é usada para segurar
Barkla, Bronwyn J; Vera-Estrella, Rosario; Raymond, Carolyn
Epidermal bladder cells (EBC) are large single-celled, specialized, and modified trichomes found on the aerial parts of the halophyte Mesembryanthemum crystallinum. Recent development of a simple but high throughput technique to extract the contents from these cells has provided an opportunity to conduct detailed single-cell-type analyses of their molecular characteristics at high resolution to gain insight into the role of these cells in the salt tolerance of the plant. In this study, we carry out large-scale complementary quantitative proteomic studies using both a label (DIGE) and label-free (GeLC-MS) approach to identify salt-responsive proteins in the EBC extract. Additionally we perform an ionomics analysis (ICP-MS) to follow changes in the amounts of 27 different elements. Using these methods, we were able to identify 54 proteins and nine elements that showed statistically significant changes in the EBC from salt-treated plants. GO enrichment analysis identified a large number of transport proteins but also proteins involved in photosynthesis, primary metabolism and Crassulacean acid metabolism (CAM). Validation of results by western blot, confocal microscopy and enzyme analysis helped to strengthen findings and further our understanding into the role of these specialized cells. As expected EBC accumulated large quantities of sodium, however, the most abundant element was chloride suggesting the sequestration of this ion into the EBC vacuole is just as important for salt tolerance. This single-cell type omics approach shows that epidermal bladder cells of M. crystallinum are metabolically active modified trichomes, with primary metabolism supporting cell growth, ion accumulation, compatible solute synthesis and CAM. Data are available via ProteomeXchange with identifier PXD004045.
Offermann, Sascha; Friso, Giulia; Doroshenk, Kelly A; Sun, Qi; Sharpe, Richard M; Okita, Thomas W; Wimmer, Diana; Edwards, Gerald E; van Wijk, Klaas J
Kranz C4 species strictly depend on separation of primary and secondary carbon fixation reactions in different cell types. In contrast, the single-cell C4 (SCC4) species Bienertia sinuspersici utilizes intracellular compartmentation including two physiologically and biochemically different chloroplast types; however, information on identity, localization, and induction of proteins required for this SCC4 system is currently very limited. In this study, we determined the distribution of photosynthesis-related proteins and the induction of the C4 system during development by label-free proteomics of subcellular fractions and leaves of different developmental stages. This was enabled by inferring a protein sequence database from 454 sequencing of Bienertia cDNAs. Large-scale proteome rearrangements were observed as C4 photosynthesis developed during leaf maturation. The proteomes of the two chloroplasts are different with differential accumulation of linear and cyclic electron transport components, primary and secondary carbon fixation reactions, and a triose-phosphate shuttle that is shared between the two chloroplast types. This differential protein distribution pattern suggests the presence of a mRNA or protein-sorting mechanism for nuclear-encoded, chloroplast-targeted proteins in SCC4 species. The combined information was used to provide a comprehensive model for NAD-ME type carbon fixation in SCC4 species.
Ray, Sandipan; Koshy, Nicole Rachel; Reddy, Panga Jaipal; Srivastava, Sanjeeva
Web-based educational resources have gained enormous popularity recently and are increasingly becoming a part of modern educational systems. Virtual Labs are E-learning platforms where learners can gain the experience of practical experimentation without any direct physical involvement on real bench work. They use computerized simulations, models, videos, animations and other instructional technologies to create interactive content. Proteomics being one of the most rapidly growing fields of the biological sciences is now an important part of college and university curriculums. Consequently, many E-learning programs have started incorporating the theoretical and practical aspects of different proteomic techniques as an element of their course work in the form of Video Lectures and Virtual Labs. To this end, recently we have developed a Virtual Proteomics Lab at the Indian Institute of Technology Bombay, which demonstrates different proteomics techniques, including basic and advanced gel and MS-based protein separation and identification techniques, bioinformatics tools and molecular docking methods, and their applications in different biological samples. This Tutorial will discuss the prominent Virtual Labs featuring proteomics content, including the Virtual Proteomics Lab of IIT-Bombay, and E-resources available for proteomics study that are striving to make proteomic techniques and concepts available and accessible to the student and research community. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 14). Details can be found at: http://www.proteomicstutorials.org/. Copyright © 2012 Elsevier B.V. All rights reserved.
Meyer, S; López-Serrano, A; Mitze, H; Jakubowski, N; Schwerdtle, T
Single-cell inductively coupled plasma mass spectrometry (SC-ICP-MS) has become a powerful and fast tool to evaluate the elemental composition at a single-cell level. In this study, the cellular bioavailability of arsenite (incubation of 25 and 50 μM for 0-48 h) has been successfully assessed by SC-ICP-MS/MS for the first time directly after re-suspending the cells in water. This procedure avoids the normally arising cell membrane permeabilization caused by cell fixation methods (e.g. methanol fixation). The reliability and feasibility of this SC-ICP-MS/MS approach with a limit of detection of 0.35 fg per cell was validated by conventional bulk ICP-MS/MS analysis after cell digestion and parallel measurement of sulfur and phosphorus.
Santella, Anthony; Catena, Raúl; Kovacevic, Ismar; Shah, Pavak; Yu, Zidong; Marquina-Solis, Javier; Kumar, Abhishek; Wu, Yicong; Schaff, James; Colón-Ramos, Daniel; Shroff, Hari; Mohler, William A; Bao, Zhirong
Imaging and image analysis advances are yielding increasingly complete and complicated records of cellular events in tissues and whole embryos. The ability to follow hundreds to thousands of cells at the individual level demands a spatio-temporal data infrastructure: tools to assemble and collate knowledge about development spatially in a manner analogous to geographic information systems (GIS). Just as GIS indexes items or events based on their spatio-temporal or 4D location on the Earth these tools would organize knowledge based on location within the tissues or embryos. Developmental processes are highly context-specific, but the complexity of the 4D environment in which they unfold is a barrier to assembling an understanding of any particular process from diverse sources of information. In the same way that GIS aids the understanding and use of geo-located large data sets, software can, with a proper frame of reference, allow large biological data sets to be understood spatially. Intuitive tools are needed to navigate the spatial structure of complex tissue, collate large data sets and existing knowledge with this spatial structure and help users derive hypotheses about developmental mechanisms. Toward this goal we have developed WormGUIDES, a mobile application that presents a 4D developmental atlas for Caenorhabditis elegans. The WormGUIDES mobile app enables users to navigate a 3D model depicting the nuclear positions of all cells in the developing embryo. The identity of each cell can be queried with a tap, and community databases searched for available information about that cell. Information about ancestry, fate and gene expression can be used to label cells and craft customized visualizations that highlight cells as potential players in an event of interest. Scenes are easily saved, shared and published to other WormGUIDES users. The mobile app is available for Android and iOS platforms. WormGUIDES provides an important tool for examining developmental
Full Text Available Abstract Background Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA approaches have emerged as an alternative to the traditional data dependent acquisition (DDA in shotgun proteomics experiments. MSE is the term used to name one of the DIA approaches used in QTOF instruments. MSE data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MSE data. Results In this paper we present PAnalyzer, a software tool focused on the protein inference process of shotgun proteomics. Our approach considers all the identified proteins and groups them when necessary indicating their confidence using different evidence categories. PAnalyzer can read protein identification files in the XML output format of the ProteinLynx Global Server (PLGS software provided by Waters Corporation for their MSE data, and also in the mzIdentML format recently standardized by HUPO-PSI. Multiple files can also be read simultaneously and are considered as technical replicates. Results are saved to CSV, HTML and mzIdentML (in the case of a single mzIdentML input file files. An MSE analysis of a real sample is presented to compare the results of PAnalyzer and ProteinLynx Global Server. Conclusions We present a software tool to deal with the ambiguities that arise in the protein inference process. Key contributions are support for MSE data analysis by ProteinLynx Global Server and technical replicates
Saeed Alexander I
Full Text Available Abstract Background Mass spectrometry (MS based label-free protein quantitation has mainly focused on analysis of ion peak heights and peptide spectral counts. Most analyses of tandem mass spectrometry (MS/MS data begin with an enzymatic digestion of a complex protein mixture to generate smaller peptides that can be separated and identified by an MS/MS instrument. Peptide spectral counting techniques attempt to quantify protein abundance by counting the number of detected tryptic peptides and their corresponding MS spectra. However, spectral counting is confounded by the fact that peptide physicochemical properties severely affect MS detection resulting in each peptide having a different detection probability. Lu et al. (2007 described a modified spectral counting technique, Absolute Protein Expression (APEX, which improves on basic spectral counting methods by including a correction factor for each protein (called Oi value that accounts for variable peptide detection by MS techniques. The technique uses machine learning classification to derive peptide detection probabilities that are used to predict the number of tryptic peptides expected to be detected for one molecule of a particular protein (Oi. This predicted spectral count is compared to the protein's observed MS total spectral count during APEX computation of protein abundances. Results The APEX Quantitative Proteomics Tool, introduced here, is a free open source Java application that supports the APEX protein quantitation technique. The APEX tool uses data from standard tandem mass spectrometry proteomics experiments and provides computational support for APEX protein abundance quantitation through a set of graphical user interfaces that partition thparameter controls for the various processing tasks. The tool also provides a Z-score analysis for identification of significant differential protein expression, a utility to assess APEX classifier performance via cross validation, and a
Amantonico, Andrea; Urban, Pawel L; Fagerer, Stephan R; Balabin, Roman M; Zenobi, Renato
Heterogeneity is a characteristic feature of all populations of living organisms. Here we make an attempt to validate a single-cell mass spectrometric method for detection of changes in metabolite levels occurring in populations of unicellular organisms. Selected metabolites involved in central metabolism (ADP, ATP, GTP, and UDP-Glucose) could readily be detected in single cells of Closterium acerosum by means of negative-mode matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS). The analytical capabilities of this approach were characterized using standard compounds. The method was then used to study populations of individual cells with different levels of the chosen metabolites. With principal component analysis and support vector machine algorithms, it was possible to achieve a clear separation of individual C. acerosum cells in different metabolic states. This study demonstrates the suitability of mass spectrometric analysis of metabolites in single cells to measure cell-population heterogeneity.
Barkla, Bronwyn J.; Vera-Estrella, Rosario; Raymond, Carolyn
Background Epidermal bladder cells (EBC) are large single-celled, specialized, and modified trichomes found on the aerial parts of the halophyte Mesembryanthemum crystallinum. Recent development of a simple but high throughput technique to extract the contents from these cells has provided an opportunity to conduct detailed single-cell-type analyses of their molecular characteristics at high resolution to gain insight into the role of these cells in the salt tolerance of the plant. Results In...
Rakszewska, A.; Tel, J.; Chokkalingam, V.; Huck, W.T.
Miniaturization has been the key driver for many remarkable technological developments in recent decades. Miniaturization has now also extended into biology, thereby setting the stage for high-throughput single-cell analysis. This advancement is important because, despite detailed molecular
Findeisen, Peter; Neumaier, Michael
Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.
MASS SPECTROMETRY PROTEOMICS METHOD AS A RAPID SCREENING TOOL FOR BACTERIAL CONTAMINATION OF FOOD ECBC-TR...TITLE AND SUBTITLE Mass Spectrometry Proteomics Method as a Rapid Screening Tool for Bacterial Contamination of Food 5a. CONTRACT NUMBER 5b...the MSPM to correctly classify whether or not food samples were contaminated with Salmonella enterica serotype Newport in this blinded pilot study
Yates John R
Full Text Available Abstract Background A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu et al. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen et al. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired. Results To address the open issues above, we present a program termed PatternLab for proteomics. This program implements existing strategies and adds two new methods to pinpoint differences in protein profiles. The first method, ACFold, addresses experiments with less than three replicates from each state or having assays acquired by different protocols as described by Chen et al. ACFold uses a combined criterion based on expression fold changes, the AC test, and the false-discovery rate, and can supply a "bird's-eye view" of differentially expressed proteins. The other method addresses experimental designs having multiple readings from each state and is referred to as nSVM (natural support vector machine because of its roots in evolutionary computing and in statistical learning theory. Our observations suggest that nSVM's niche comprises projects that select a minimum set of proteins for classification purposes; for example, the development of an early detection kit for a given pathology. We demonstrate the effectiveness of each method on experimental data and confront them with existing strategies
García-Berrocoso, Teresa; Llombart, Víctor; Colàs-Campàs, Laura; Hainard, Alexandre; Licker, Virginie; Penalba, Anna; Ramiro, Laura; Simats, Alba; Bustamante, Alejandro; Martínez-Saez, Elena; Canals, Francesc; Sanchez, Jean-Charles; Montaner, Joan
Cerebral ischemia entails rapid tissue damage in the affected brain area causing devastating neurological dysfunction. How each component of the neurovascular unit contributes or responds to the ischemic insult in the context of the human brain has not been solved yet. Thus, the analysis of the proteome is a straightforward approach to unraveling these cell proteotypes. In this study, post-mortem brain slices from ischemic stroke patients were obtained corresponding to infarcted (IC) and contralateral (CL) areas. By means of laser microdissection, neurons and blood brain barrier structures (BBB) were isolated and analyzed using label-free quantification. MS data are available via ProteomeXchange with identifier PXD003519. Ninety proteins were identified only in neurons, 260 proteins only in the BBB and 261 proteins in both cell types. Bioinformatics analyses revealed that repair processes, mainly related to synaptic plasticity, are outlined in microdissected neurons, with nonexclusive important functions found in the BBB. A total of 30 proteins showing p 2 between IC and CL areas were considered meaningful in this study: 13 in neurons, 14 in the BBB and 3 in both cell types. Twelve of these proteins were selected as candidates and analyzed by immunohistofluorescence in independent brains. The MS findings were completely verified for neuronal SAHH2 and SRSF1 whereas the presence in both cell types of GABT and EAA2 was only validated in neurons. In addition, SAHH2 showed its potential as a prognostic biomarker of neurological improvement when analyzed early in the plasma of ischemic stroke patients. Therefore, the quantitative proteomes of neurons and the BBB (or proteotypes) after human brain ischemia presented here contribute to increasing the knowledge regarding the molecular mechanisms of ischemic stroke pathology and highlight new proteins that might represent putative biomarkers of brain ischemia or therapeutic targets. © 2018 by The American Society for
A comprehensive range of mass spectrometric tools is required to investigate todays life science applications and a strong focus is on addressing the needs of functional proteomics. Application examples are given showing the streamlined process of protein identification from low femtomole amounts of digests. Sample preparation is achieved with a convertible robot for automated 2D gel picking, and MALDI target dispensing. MALDI-TOF or ESI-MS subsequent to enzymatic digestion. A choice of mass spectrometers including Q-q-TOF with multipass capability, MALDI-MS/MS with unsegmented PSD, Ion Trap and FT-MS are discussed for their respective strengths and applications. Bioinformatics software that allows both database work and novel peptide mass spectra interpretation is reviewed. The automated database searching uses either entire digest LC-MS n ESI Ion Trap data or MALDI MS and MS/MS spectra. It is shown how post translational modifications are interactively uncovered and de-novo sequencing of peptides is facilitated
Misra, Biswapriya B
Proteomics data processing, annotation, and analysis can often lead to major hurdles in large-scale high-throughput bottom-up proteomics experiments. Given the recent rise in protein-based big datasets being generated, efforts in in silico tool development occurrences have had an unprecedented increase; so much so, that it has become increasingly difficult to keep track of all the advances in a particular academic year. However, these tools benefit the plant proteomics community in circumventing critical issues in data analysis and visualization, as these continually developing open-source and community-developed tools hold potential in future research efforts. This review will aim to introduce and summarize more than 50 software tools, databases, and resources developed and published during 2016-2017 under the following categories: tools for data pre-processing and analysis, statistical analysis tools, peptide identification tools, databases and spectral libraries, and data visualization and interpretation tools. Intended for a well-informed proteomics community, finally, efforts in data archiving and validation datasets for the community will be discussed as well. Additionally, the author delineates the current and most commonly used proteomics tools in order to introduce novice readers to this -omics discovery platform. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Sison-Young, Rowena L C; Mitsa, Dimitra; Jenkins, Rosalind E; Mottram, David; Alexandre, Eliane; Richert, Lysiane; Aerts, Hélène; Weaver, Richard J; Jones, Robert P; Johann, Esther; Hewitt, Philip G; Ingelman-Sundberg, Magnus; Goldring, Christopher E P; Kitteringham, Neil R; Park, B Kevin
In vitro preclinical models for the assessment of drug-induced liver injury (DILI) are usually based on cryopreserved primary human hepatocytes (cPHH) or human hepatic tumor-derived cell lines; however, it is unclear how well such cell models reflect the normal function of liver cells. The physiological, pharmacological, and toxicological phenotyping of available cell-based systems is necessary in order to decide the testing purpose for which they are fit. We have therefore undertaken a global proteomic analysis of 3 human-derived hepatic cell lines (HepG2, Upcyte, and HepaRG) in comparison with cPHH with a focus on drug metabolizing enzymes and transport proteins (DMETs), as well as Nrf2-regulated proteins. In total, 4946 proteins were identified, of which 2722 proteins were common across all cell models, including 128 DMETs. Approximately 90% reduction in expression of cytochromes P450 was observed in HepG2 and Upcyte cells, and approximately 60% in HepaRG cells relative to cPHH. Drug transporter expression was also lower compared with cPHH with the exception of MRP3 and P-gp (MDR1) which appeared to be significantly expressed in HepaRG cells. In contrast, a high proportion of Nrf2-regulated proteins were more highly expressed in the cell lines compared with cPHH. The proteomic database derived here will provide a rational basis for the context-specific selection of the most appropriate 'hepatocyte-like' cell for the evaluation of particular cellular functions associated with DILI and, at the same time, assist in the construction of a testing paradigm which takes into account the in vivo disposition of a new drug. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology.
To understand the inhomogeneity of cells in biological systems, there is a growing demand for the capability to characterize the properties of individual single cells. Since single cell studies require continuous monitoring of the cell behaviors instead of a snapshot test at a single time point, an effective single-cell assay that can support time lapsed studies in a high throughput manner is desired. Most currently available single-cell technologies cannot provide proper environments to sustain cell growth and cannot provide, for appropriate cell types, proliferation of single cells and convenient, non-invasive tests of single cell behaviors from molecular markers. In this dissertation, I present a highly versatile single-cell assay that can accommodate different cellular types, enable easy and efficient single cell loading and culturing, and be suitable for the study of effects of in-vitro environmental factors in combination with drug screening. The salient features of the assay are the non-invasive collection and surveying of single cell secretions at different time points and massively parallel translocation of single cells by user defined criteria, producing very high compatibility to the downstream process such as single cell qPCR and sequencing. Above all, the acquired information is quantitative -- for example, one of the studies is measured by the number of exosomes each single cell secretes for a given time period. Therefore, our single-cell assay provides a convenient, low-cost, and enabling tool for quantitative, time lapsed studies of single cell properties.
Martínez-Bartolomé, Salvador; Medina-Aunon, J Alberto; López-García, Miguel Ángel; González-Tejedo, Carmen; Prieto, Gorka; Navajas, Rosana; Salazar-Donate, Emilio; Fernández-Costa, Carolina; Yates, John R; Albar, Juan Pablo
Mass-spectrometry-based proteomics has evolved into a high-throughput technology in which numerous large-scale data sets are generated from diverse analytical platforms. Furthermore, several scientific journals and funding agencies have emphasized the storage of proteomics data in public repositories to facilitate its evaluation, inspection, and reanalysis. (1) As a consequence, public proteomics data repositories are growing rapidly. However, tools are needed to integrate multiple proteomics data sets to compare different experimental features or to perform quality control analysis. Here, we present a new Java stand-alone tool, Proteomics Assay COMparator (PACOM), that is able to import, combine, and simultaneously compare numerous proteomics experiments to check the integrity of the proteomic data as well as verify data quality. With PACOM, the user can detect source of errors that may have been introduced in any step of a proteomics workflow and that influence the final results. Data sets can be easily compared and integrated, and data quality and reproducibility can be visually assessed through a rich set of graphical representations of proteomics data features as well as a wide variety of data filters. Its flexibility and easy-to-use interface make PACOM a unique tool for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom .
Domont Gilberto B
Full Text Available Abstract Background Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Results Here we present a new algorithm, termed GO Explorer (GOEx, that leverages the gene ontology (GO to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172. We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. Conclusion GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.
Carvalho, Paulo C; Fischer, Juliana Sg; Chen, Emily I; Domont, Gilberto B; Carvalho, Maria Gc; Degrave, Wim M; Yates, John R; Barbosa, Valmir C
Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge. Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few. GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at http://pcarvalho.com/patternlab.
Pang, Chi Nam Ignatius; Aya, Carlos; Tay, Aidan
data generated from protein mass spectrometry. We are developing a set of tools which allow users to: •Co-visualise genomics, transcriptomics, and proteomics data using the Integrated Genomics Viewer (IGV).1 •Validate the existence of genes and mRNAs using peptides identified from mass spectrometry...
Rasinger, J D; Marbaix, H; Dieu, M; Fumière, O; Mauro, S; Palmblad, M; Raes, M; Berntssen, M H G
The rapidly growing aquaculture industry drives the search for sustainable protein sources in fish feed. In the European Union (EU) since 2013 non-ruminant processed animal proteins (PAP) are again permitted to be used in aquafeeds. To ensure that commercial fish feeds do not contain PAP from prohibited species, EU reference methods were established. However, due to the heterogeneous and complex nature of PAP complementary methods are required to guarantee the safe use of this fish feed ingredient. In addition, there is a need for tissue specific PAP detection to identify the sources (i.e. bovine carcass, blood, or meat) of illegal PAP use. In the present study, we investigated and compared different protein extraction, solubilisation and digestion protocols on different proteomics platforms for the detection and differentiation of prohibited PAP. In addition, we assessed if tissue specific PAP detection was feasible using proteomics tools. All work was performed independently in two different laboratories. We found that irrespective of sample preparation gel-based proteomics tools were inappropriate when working with PAP. Gel-free shotgun proteomics approaches in combination with direct spectral comparison were able to provide quality species and tissue specific data to complement and refine current methods of PAP detection and identification. To guarantee the safe use of processed animal protein (PAP) in aquafeeds efficient PAP detection and monitoring tools are required. The present study investigated and compared various proteomics workflows and shows that the application of shotgun proteomics in combination with direct comparison of spectral libraries provides for the desired species and tissue specific classification of this heat sterilized and pressure treated (≥133°C, at 3bar for 20min) protein feed ingredient. Copyright © 2016 Elsevier B.V. All rights reserved.
Hartwig, Sonja; Czibere, Akos; Kotzka, Jorg; Passlack, Waltraud; Haas, Rainer; Eckel, Jürgen; Lehr, Stefan
Blood serum samples are the major source for clinical proteomics approaches, which aim to identify diagnostically relevant or treatment-response related proteins. But, the presence of very high-abundance proteins and the enormous dynamic range of protein distribution hinders whole serum analysis. An innovative tool to overcome these limitations, utilizes combinatorial hexapeptide ligand libraries (ProteoMiner). Here, we demonstrate that ProteoMiner can be used for comparative and quantitative analysis of complex proteomes. We spiked serum samples with increasing amounts (3 microg to 300 microg) of whole E. coli lysate, processed it with ProteoMiner and performed quantitative analyses of 2D-gels. We found, that the concentration of the spiked bacteria proteome, reflected by the maintained proportional spot intensities, was not altered by ProteoMiner treatment. Therefore, we conclude that the ProteoMiner technology can be used for quantitative analysis of low abundant proteins in complex biological samples.
It is believed that cancer originates from a single cell that has gone through generations of evolution of genetic and epigenetic changes that associate with the hallmarks of cancer. In some cancers such as various types of leukemia, cancer is clonal. Yet in other cancers like glioblastoma (GBM), there is tremendous tumor heterogeneity that is likely to be caused by simultaneous evolution of multiple subclones within the same tissue. It is obvious that understanding how a single cell develops into a clonal tumor upon genetic alterations, at molecular and cellular levels, holds the key to the real appreciation of tumor etiology and ultimate solution for therapeutics. Surprisingly very little is known about the process of spontaneous tumorigenesis from single cells in human or vertebrate animal models. The main reason is the lack of technology to track the natural process of single cell changes from a homeostatic state to a progressively cancerous state. Recently, we developed a patented compound, photoactivatable (''caged'') tamoxifen analogue 4-OHC and associated technique called optochemogenetic switch (OCG switch), which we believe opens the opportunity to address this urgent biological as well as clinical question about cancer. We propose to combine OCG switch with genetically engineered mouse models of head and neck squamous cell carcinoma and high grade astrocytoma (including GBM) to study how single cells, when transformed through acute loss of tumor suppressor genes PTEN and TP53 and gain of oncogenic KRAS, can develop into tumor colonies with cellular and molecular heterogeneity in these tissues. The abstract is for my invited talk in session ``Beyond Darwin: Evolution in Single Cells'' 3/18/2016 11:15 AM.
Kessner, Darren; Chambers, Matt; Burke, Robert; Agus, David; Mallick, Parag
The ProteoWizard software project provides a modular and extensible set of open-source, cross-platform tools and libraries. The tools perform proteomics data analyses; the libraries enable rapid tool creation by providing a robust, pluggable development framework that simplifies and unifies data file access, and performs standard proteomics and LCMS dataset computations. The library contains readers and writers of the mzML data format, which has been written using modern C++ techniques and design principles and supports a variety of platforms with native compilers. The software has been specifically released under the Apache v2 license to ensure it can be used in both academic and commercial projects. In addition to the library, we also introduce a rapidly growing set of companion tools whose implementation helps to illustrate the simplicity of developing applications on top of the ProteoWizard library. Cross-platform software that compiles using native compilers (i.e. GCC on Linux, MSVC on Windows and XCode on OSX) is available for download free of charge, at http://proteowizard.sourceforge.net. This website also provides code examples, and documentation. It is our hope the ProteoWizard project will become a standard platform for proteomics development; consequently, code use, contribution and further development are strongly encouraged.
Tennessen, Kristin [Lawrence Berkeley National Lab. (LBNL), Walnut Creek, CA (United States). Dept. of Energy Joint Genome Inst.; Pati, Amrita [Lawrence Berkeley National Lab. (LBNL), Walnut Creek, CA (United States). Dept. of Energy Joint Genome Inst.
Recent technological advancements in single-cell genomics have encouraged the classification and functional assessment of microorganisms from a wide span of the biospheres phylogeny.1,2 Environmental processes of interest to the DOE, such as bioremediation and carbon cycling, can be elucidated through the genomic lens of these unculturable microbes. However, contamination can occur at various stages of the single-cell sequencing process. Contaminated data can lead to wasted time and effort on meaningless analyses, inaccurate or erroneous conclusions, and pollution of public databases. A fully automated decontamination tool is necessary to prevent these instances and increase the throughput of the single-cell sequencing process
The CPTAC program develops new approaches to elucidate aspects of the molecular complexity of cancer made from large-scale proteogenomic datasets, and advance them toward precision medicine. Part of the CPTAC mission is to make data and tools available and accessible to the greater research community to accelerate the discovery process.
Deng, Ning; Li, Zhenye; Pan, Chao; Duan, Huilong
Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.
Arrais, Joel P; Rosa, Nuno; Melo, José; Coelho, Edgar D; Amaral, Diana; Correia, Maria José; Barros, Marlene; Oliveira, José Luís
The molecular complexity of the human oral cavity can only be clarified through identification of components that participate within it. However current proteomic techniques produce high volumes of information that are dispersed over several online databases. Collecting all of this data and using an integrative approach capable of identifying unknown associations is still an unsolved problem. This is the main motivation for this work. We present the online bioinformatic tool OralCard, which comprises results from 55 manually curated articles reflecting the oral molecular ecosystem (OralPhysiOme). It comprises experimental information available from the oral proteome both of human (OralOme) and microbial origin (MicroOralOme) structured in protein, disease and organism. This tool is a key resource for researchers to understand the molecular foundations implicated in biology and disease mechanisms of the oral cavity. The usefulness of this tool is illustrated with the analysis of the oral proteome associated with diabetes melitus type 2. OralCard is available at http://bioinformatics.ua.pt/oralcard. Copyright © 2013 Elsevier Ltd. All rights reserved.
Gillet, Ludovic C; Bernhardt, Oliver M.; MacLean, Brendan; Röst, Hannes L.; Tate, Stephen A.; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I.; Aebersold, Ruedi; Tenzer, Stefan
The consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra), a method that uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test datasets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation windows setups. For consistent evaluation we developed LFQbench, an R-package to calculate metrics of precision and accuracy in label-free quantitative MS, and report the identification performance, robustness and specificity of each software tool. Our reference datasets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics. PMID:27701404
Navarro, Pedro; Kuharev, Jörg; Gillet, Ludovic C; Bernhardt, Oliver M; MacLean, Brendan; Röst, Hannes L; Tate, Stephen A; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I; Aebersold, Ruedi; Tenzer, Stefan
Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.
Gao, Liang; Wang, Lidai; Li, Chiye; Liu, Yan; Ke, Haixin; Zhang, Chi
Abstract. A novel photoacoustic thermometric method is presented for simultaneously imaging cells and sensing their temperature. With three-seconds-per-frame imaging speed, a temperature resolution of 0.2°C was achieved in a photo-thermal cell heating experiment. Compared to other approaches, the photoacoustic thermometric method has the advantage of not requiring custom-developed temperature-sensitive biosensors. This feature should facilitate the conversion of single-cell thermometry into a routine lab tool and make it accessible to a much broader biological research community. PMID:23377004
Pascovici, Dana; Handler, David C L; Wu, Jemma X; Haynes, Paul A
Multiple testing corrections are a useful tool for restricting the FDR, but can be blunt in the context of low power, as we demonstrate by a series of simple simulations. Unfortunately, in proteomics experiments low power can be common, driven by proteomics-specific issues like small effects due to ratio compression, and few replicates due to reagent high cost, instrument time availability and other issues; in such situations, most multiple testing corrections methods, if used with conventional thresholds, will fail to detect any true positives even when many exist. In this low power, medium scale situation, other methods such as effect size considerations or peptide-level calculations may be a more effective option, even if they do not offer the same theoretical guarantee of a low FDR. Thus, we aim to highlight in this article that proteomics presents some specific challenges to the standard multiple testing corrections methods, which should be employed as a useful tool but not be regarded as a required rubber stamp. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Perez-Riverol, Yasset; Xu, Qing-Wei; Wang, Rui; Uszkoreit, Julian; Griss, Johannes; Sanchez, Aniel; Reisinger, Florian; Csordas, Attila; Ternent, Tobias; Del-Toro, Noemi; Dianes, Jose A; Eisenacher, Martin; Hermjakob, Henning; Vizcaíno, Juan Antonio
The original PRIDE Inspector tool was developed as an open source standalone tool to enable the visualization and validation of mass-spectrometry (MS)-based proteomics data before data submission or already publicly available in the Proteomics Identifications (PRIDE) database. The initial implementation of the tool focused on visualizing PRIDE data by supporting the PRIDE XML format and a direct access to private (password protected) and public experiments in PRIDE.The ProteomeXchange (PX) Consortium has been set up to enable a better integration of existing public proteomics repositories, maximizing its benefit to the scientific community through the implementation of standard submission and dissemination pipelines. Within the Consortium, PRIDE is focused on supporting submissions of tandem MS data. The increasing use and popularity of the new Proteomics Standards Initiative (PSI) data standards such as mzIdentML and mzTab, and the diversity of workflows supported by the PX resources, prompted us to design and implement a new suite of algorithms and libraries that would build upon the success of the original PRIDE Inspector and would enable users to visualize and validate PX "complete" submissions. The PRIDE Inspector Toolsuite supports the handling and visualization of different experimental output files, ranging from spectra (mzML, mzXML, and the most popular peak lists formats) and peptide and protein identification results (mzIdentML, PRIDE XML, mzTab) to quantification data (mzTab, PRIDE XML), using a modular and extensible set of open-source, cross-platform libraries. We believe that the PRIDE Inspector Toolsuite represents a milestone in the visualization and quality assessment of proteomics data. It is freely available at http://github.com/PRIDE-Toolsuite/. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
Bereman, Michael S
With advances in liquid chromatography coupled to tandem mass spectrometry technologies combined with the continued goals of biomarker discovery, clinical applications of established biomarkers, and integrating large multiomic datasets (i.e. "big data"), there remains an urgent need for robust tools to assess instrument performance (i.e. system suitability) in proteomic workflows. To this end, several freely available tools have been introduced that monitor a number of peptide identification (ID) and/or peptide ID free metrics. Peptide ID metrics include numbers of proteins, peptides, or peptide spectral matches identified from a complex mixture. Peptide ID free metrics include retention time reproducibility, full width half maximum, ion injection times, and integrated peptide intensities. The main driving force in the development of these tools is to monitor both intra- and interexperiment performance variability and to identify sources of variation. The purpose of this review is to summarize and evaluate these tools based on versatility, automation, vendor neutrality, metrics monitored, and visualization capabilities. In addition, the implementation of a robust system suitability workflow is discussed in terms of metrics, type of standard, and frequency of evaluation along with the obstacles to overcome prior to incorporating a more proactive approach to overall quality control in liquid chromatography coupled to tandem mass spectrometry based proteomic workflows. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Vizcaíno, Juan Antonio; Reisinger, Florian; Côté, Richard; Martens, Lennart
The Proteomics Identifications Database (PRIDE, http://www.ebi.ac.uk/pride ) provides users with the ability to explore and compare mass spectrometry-based proteomics experiments that reveal details of the protein expression found in a broad range of taxonomic groups, tissues, and disease states. A PRIDE experiment typically includes identifications of proteins, peptides, and protein modifications. Additionally, many of the submitted experiments also include the mass spectra that provide the evidence for these identifications. Finally, one of the strongest advantages of PRIDE in comparison with other proteomics repositories is the amount of metadata it contains, a key point to put the above-mentioned data in biological and/or technical context. Several informatics tools have been developed in support of the PRIDE database. The most recent one is called "Database on Demand" (DoD), which allows custom sequence databases to be built in order to optimize the results from search engines. We describe the use of DoD in this chapter. Additionally, in order to show the potential of PRIDE as a source for data mining, we also explore complex queries using federated BioMart queries to integrate PRIDE data with other resources, such as Ensembl, Reactome, or UniProt.
Torres-Arroyo, Angélica; Ruiz-Lara, Arturo; Castillo-Villanueva, Adriana; Méndez-Cruz, Sara Teresa; Espinosa-Padilla, Sara Elvia; Espinosa-Rosales, Francisco Javier; Zarate-Mondragón, Flora; Cervantes-Bustamante, Roberto; Bosch-Canto, Vanessa; Vizzuett-López, Iris; Ordaz-Fávila, Juan Carlos; Oria-Hernández, Jesús; Reyes-Vivas, Horacio
Proteomics is the study of the expression of changes and post-translational modifications (PTM) of proteins along a metabolic condition either normal or pathological. In the field of health, proteomics allows obtaining valuable data for treatment, diagnosis or pathophysiological mechanisms of different illnesses. To illustrate the aforementioned, we describe two projects currently being performed at the Instituto Nacional de Pediatría: The immuno-proteomic study of cow milk allergy and the Proteomic study of childhood cataract. Cow's milk proteins (CMP) are the first antigens to which infants are exposed and generate allergy in some of them. In Mexico, the incidence of CMP allergy has been estimated at 5-7%. Clinical manifestations include both gastrointestinal and extra-gastrointestinal symptoms, making its diagnosis extremely difficult. An inappropriate diagnosis affects the development and growth of children. The goals of the study are to identify the main immune-reactive CMP in Mexican pediatric population and to design more accurate diagnostic tools for this disease. Childhood cataract is a major ocular disease representing one of the main causes of blindness in infants; in developing countries, this disease promotes up to 27% of cases related to visual loss. From this group, it has been estimated that close to 60% of children do not survive beyond two years after vision lost. PTM have been pointed out as the main cause of protein precipitation at the crystalline and, consequently, clouding of this tissue. The study of childhood cataract represents an outstanding opportunity to identify the PTM associated to the cataract-genesis process. Copyright © 2017 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.
Tølbøll, Trine Højgaard; Danscher, Anne Mette; Andersen, Pia Haubro
to current research strategies there is a need to develop novel approaches and methods that expand understanding of the disease mechanisms involved in CHD. The objectives of the present study were to explore the potential of liquid chromatography tandem mass spectrometry (LC–MS/MS) in mapping protein...... expression in three different bovine claw tissues, and to provide a relevant functional annotation of the proteins characterized in these tissues. LC–MS/MS was used to characterize protein expression in coronary band skin (C), claw dermal (D) and lamellar (L) tissues from two heifers. A total of 388...... different proteins were identified, with 146 proteins available for identification in C, 279 proteins in D and 269 proteins in L. A functional annotation of the identified proteins was obtained using the on-line Blast2GO tool. Three hundred and sixteen of the identified proteins could be subsequently...
van den Brink, Floris Teunis Gerardus; Gool, Elmar; Frimat, Jean-Philippe; Bomer, Johan G.; van den Berg, Albert; le Gac, Severine
We report a PDMS microfluidic platform for parallel single-cell analysis (PaSCAl) as a powerful tool to decipher the heterogeneity found in cell populations. Cells are trapped individually in dedicated pockets, and thereafter, a number of invasive or non-invasive analysis schemes are performed.
Full Text Available Experiments involving mass spectrometry (MS-based proteomics are widely used for analyses of connective tissues. Common examples include the use of relative quantification to identify differentially expressed peptides and proteins in cartilage and tendon. We are working on characterising so-called ‘neopeptides’, i.e. peptides formed due to native cleavage of proteins, for example under pathological conditions. Unlike peptides typically quantified in MS workflows due to the in vitro use of an enzyme such as trypsin, a neopeptide has at least one terminus that was not due to the use of trypsin in the workflow. The identification of neopeptides within these datasets is important in understanding disease pathology, and the development of antibodies that could be utilised as diagnostic biomarkers for diseases, such as osteoarthritis, and targets for novel treatments. Our previously described neopeptide data analysis workflow was laborious and was not amenable to robust statistical analysis, which reduced confidence in the neopeptides identified. To overcome this, we developed ‘Neopeptide Analyser’, a user friendly neopeptide analysis tool used in conjunction with label-free MS quantification tool Progenesis QIP for proteomics. Neopeptide Analyser filters data sourced from Progenesis QIP output to identify neopeptide sequences, as well as give the residues that are adjacent to the peptide in its corresponding protein sequence. It also produces normalised values for the neopeptide quantification values and uses these to perform statistical tests, which are also included in the output. Neopeptide Analyser is available as a Java application for Mac, Windows and Linux. The analysis features and ease of use encourages data exploration, which could aid the discovery of novel pathways in extracellular matrix degradation, the identification of potential biomarkers and as a tool to investigate matrix turnover. Neopeptide Analyser is available from
Full Text Available The identification of drugs capable of reactivating γ-globin to ameliorate β-thalassemia and Sickle Cell anemia is still a challenge, as available γ-globin inducers still have limited clinical indications. High-throughput screenings (HTS aimed to identify new potentially therapeutic drugs require suitable first-step-screening methods combining the possibility to detect variation in the γ/β globin ratio with the robustness of a cell line. We took advantage of a K562 cell line variant expressing β-globin (β-K562 to set up a new multiplexed high-content immunofluorescence assay for the quantification of γ- and β-globin content at single-cell level. The assay was validated by using the known globin inducers hemin, hydroxyurea and butyric acid and further tested in a pilot screening that confirmed HDACs as targets for γ-globin induction (as proved by siRNA-mediated HDAC3 knockdown and by treatment with HDACs inhibitors entinostat and dacinostat and identified Heme-oxygenases as novel candidate targets for γ-globin induction. Indeed, Heme-oxygenase2 siRNA knockdown as well as its inhibition by Tin protoporphyrin-IX (TinPPIX greatly increased γ-globin expression. This result is particularly interesting as several metalloporphyrins have already been developed for clinical uses and could be tested (alone or in combination with other drugs to improve pharmacological γ-globin reactivation for the treatment of β-hemoglobinopathies.
Gross, Andre; Schoendube, Jonas; Zimmermann, Stefan; Steeb, Maximilian; Zengerle, Roland; Koltay, Peter
The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting) respectively Flow cytometry (33% usage), laser microdissection (17%), manual cell picking (17%), random seeding/dilution (15%), and microfluidics/lab-on-a-chip devices (12%) are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field.
Gross, Andre; Schoendube, Jonas; Zimmermann, Stefan; Steeb, Maximilian; Zengerle, Roland; Koltay, Peter
The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting) respectively Flow cytometry (33% usage), laser microdissection (17%), manual cell picking (17%), random seeding/dilution (15%), and microfluidics/lab-on-a-chip devices (12%) are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field. PMID:26213926
Full Text Available The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting respectively Flow cytometry (33% usage, laser microdissection (17%, manual cell picking (17%, random seeding/dilution (15%, and microfluidics/lab-on-a-chip devices (12% are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field.
Full Text Available The search for clinically useful protein biomarkers using advanced mass spectrometry approaches represents a major focus in cancer research. However, the direct analysis of human samples may be challenging due to limited availability, the absence of appropriate control samples, or the large background variability observed in patient material. As an alternative approach, human tumors orthotopically implanted into a different species (xenografts are clinically relevant models that have proven their utility in pre-clinical research. Patient derived xenografts for glioblastoma have been extensively characterized in our laboratory and have been shown to retain the characteristics of the parental tumor at the phenotypic and genetic level. Such models were also found to adequately mimic the behavior and treatment response of human tumors. The reproducibility of such xenograft models, the possibility to identify their host background and perform tumor-host interaction studies, are major advantages over the direct analysis of human samples.At the proteome level, the analysis of xenograft samples is challenged by the presence of proteins from two different species which, depending on tumor size, type or location, often appear at variable ratios. Any proteomics approach aimed at quantifying proteins within such samples must consider the identification of species specific peptides in order to avoid biases introduced by the host proteome. Here, we present an in-house methodology and tool developed to select peptides used as surrogates for protein candidates from a defined proteome (e.g., human in a host proteome background (e.g., mouse, rat suited for a mass spectrometry analysis. The tools presented here are applicable to any species specific proteome, provided a protein database is available. By linking the information from both proteomes, PeptideManager significantly facilitates and expedites the selection of peptides used as surrogates to analyze
Colangelo, Christopher M; Chung, Lisa; Bruce, Can; Cheung, Kei-Hoi
Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
Povinelli, Benjamin J; Rodriguez-Meira, Alba; Mead, Adam J
The hematopoietic system is well established as a paradigm for the study of cellular hierarchies, their disruption in disease and therapeutic use in regenerative medicine. Traditional approaches to study hematopoiesis involve purification of cell populations based on a small number of surface markers. However, such population-based analysis obscures underlying heterogeneity contained within any phenotypically defined cell population. This heterogeneity can only be resolved through single cell analysis. Recent advances in single cell techniques allow analysis of the genome, transcriptome, epigenome and proteome in single cells at an unprecedented scale. The application of these new single cell methods to investigate the hematopoietic system has led to paradigm shifts in our understanding of cellular heterogeneity in hematopoiesis and how this is disrupted in disease. In this review, we summarize how single cell techniques have been applied to the analysis of hematopoietic stem/progenitor cells in normal and malignant hematopoiesis, with a particular focus on recent advances in single-cell genomics, including how these might be utilized for clinical application. Copyright © 2017. Published by Elsevier Ltd.
Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping
Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. email@example.com and firstname.lastname@example.org. Supplementary data are available at Bioinformatics online.
Jensen, Marie Pødenphant
Isolation and manipulation of single cells have gained an increasing interest from researchers because of the heterogeneity of cells from the same cell culture. Single cell analysis can ensure a better understanding of differences between individual cells and potentially solve a variety of clinical...... problems. In this thesis lab on a chip systems for rare single cell analysis are investigated. The focus was to develop a commercial, disposable device for circulating tumour cell (CTC) analysis. Such a device must be able to separate rare cells from blood samples and subsequently capture the specific...... cells, and simultaneously be fabricated and operated at low costs and be user-friendly. These challenges were addressed through development of two microfluidic devices, one for rare cell isolation based on pinched flow fractionation (PFF) and one for single cell capture based on hydrodynamic trapping...
Aiyetan, Paul; Zhang, Bai; Chen, Lily; Zhang, Zhen; Zhang, Hui
Proteome Discoverer is one of many tools used for protein database search and peptide to spectrum assignment in mass spectrometry-based proteomics. However, the inadequacy of conversion tools makes it challenging to compare and integrate its results to those of other analytical tools. Here we present M2Lite, an open-source, light-weight, easily pluggable and fast conversion tool. M2Lite converts proteome discoverer derived MSF files to the proteomics community defined standard - the mzIdentML file format. M2Lite's source code is available as open-source at https://bitbucket.org/paiyetan/m2lite/src and its compiled binaries and documentation can be freely downloaded at https://bitbucket.org/paiyetan/m2lite/downloads.
Palmblad, Magnus; van der Burgt, Yuri E M; Dalebout, Hans; Derks, Rico J E; Schoenmaker, Bart; Deelder, André M
Accurate mass determination enhances peptide identification in mass spectrometry based proteomics. We here describe the combination of two previously published open source software tools to improve mass measurement accuracy in Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS). The first program, msalign, aligns one MS/MS dataset with one FTICRMS dataset. The second software, recal2, uses peptides identified from the MS/MS data for automated internal calibration of the FTICR spectra, resulting in sub-ppm mass measurement errors.
Stanfill, Bryan A; Nakayasu, Ernesto S; Bramer, Lisa M; Thompson, Allison M; Ansong, Charles K; Clauss, Therese; Gritsenko, Marina A; Monroe, Matthew E; Moore, Ronald J; Orton, Daniel J; Piehowski, Paul D; Schepmoes, Athena A; Smith, Richard D; Webb-Robertson, Bobbie-Jo; Metz, Thomas O; TEDDY Study Group, The Environmental Determinants Of Diabetes In The Young
Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.
Marco-Ramell, Anna; Bassols, Anna; Bislev, Stine Lønnerup
. Selected reaction monitoring (SRM), a targeted quantitative proteomic technique, may be used as an alternative to commercial kits for the measurement and validation of target proteins. Acute phase proteins (APPs) are widely recognized inflammation and infection biomarkers (Eckersall, 2010...
Neu, Karlynn E; Tang, Qingming; Wilson, Patrick C; Khan, Aly A
Single cell genomics offers powerful tools for studying lymphocytes, which make it possible to observe rare and intermediate cell states that cannot be resolved at the population-level. Advances in computer science and single cell sequencing technology have created a data-driven revolution in immunology. The challenge for immunologists is to harness computing and turn an avalanche of quantitative data into meaningful discovery of immunological principles, predictive models, and strategies for therapeutics. Here, we review the current literature on computational analysis of single cell RNA-seq data and discuss underlying assumptions, methods, and applications in immunology, and highlight important directions for future research. PMID:28094102
Høgdall, Claus; Fung, Eric T; Christensen, Ib J
Previous reports have shown that the proteomic markers apolipoprotein A1, hepcidin, transferrin, inter-alpha trypsin IV internal fragment, transthyretin, connective-tissue activating protein 3 and beta-2 microglobulin may discriminate between a benign pelvic mass and ovarian cancer (OC). The aim...... was to determine if these serum proteomic biomarkers alone as well as in combination with age and serum CA125, could be helpful in triage of women with a pelvic mass....
Full Text Available Increasing evidence shows that the heterogeneity of individual cells within a genetically identical population can be critical to their peculiar function and fate. Conventional cell based assays mainly analysis the average responses from a population cells, while the difference within individual cells may often be masked. The cell size, RNA transcripts and protein expression level are quite different within individual cells and these variations are key point to answer the problems in cancer, neurobiology, stem cell biology, immunology and developmental biology. To better understand the cell-to-cell variations, the single cell analysis can provide much more detailed information which may be helpful for therapeutic decisions in an increasingly personalized medicine. In this review, we will focus on the recent development in single cell analysis, including methods used in single cell isolation, analysis and some application examples. The review provides the historical background to single cell analysis, discusses limitations, and current and future possibilities in this exciting field of research.
Naylor, Bradley C; Porter, Michael T; Wilson, Elise; Herring, Adam; Lofthouse, Spencer; Hannemann, Austin; Piccolo, Stephen R; Rockwood, Alan L; Price, John C
Using mass spectrometry to measure the concentration and turnover of the individual proteins in a proteome, enables the calculation of individual synthesis and degradation rates for each protein. Software to analyze concentration is readily available, but software to analyze turnover is lacking. Data analysis workflows typically don't access the full breadth of information about instrument precision and accuracy that is present in each peptide isotopic envelope measurement. This method utilizes both isotope distribution and changes in neutromer spacing, which benefits the analysis of both concentration and turnover. We have developed a data analysis tool, DeuteRater, to measure protein turnover from metabolic D 2 O labeling. DeuteRater uses theoretical predictions for label-dependent change in isotope abundance and inter-peak (neutromer) spacing within the isotope envelope to calculate protein turnover rate. We have also used these metrics to evaluate the accuracy and precision of peptide measurements and thereby determined the optimal data acquisition parameters of different instruments, as well as the effect of data processing steps. We show that these combined measurements can be used to remove noise and increase confidence in the protein turnover measurement for each protein. Source code and ReadMe for Python 2 and 3 versions of DeuteRater are available at https://github.com/JC-Price/DeuteRater . Data is at https://chorusproject.org/pages/index.html project number 1147. Critical Intermediate calculation files provided as Tables S3 and S4. Software has only been tested on Windows machines. email@example.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org
Roncada, Paola; Stipetic, Laurence H; Bonizzi, Luigi; Burchmore, Richard J S; Kennedy, Malcolm W
Proteins in milk have wide range of functions, they are carriers of minerals or chemically vulnerable and insoluble vitamins and other compounds, stabilisers of large aggregates or micelles of lipids, and components of both innate and acquired immune defence systems. Together with other components of milk, proteins may also contribute to the selection and establishment of appropriate microbiome in the gut of the infant. The proteome of mammalian milk is now known to be dynamic and changes radically with time after birth from colostrum to mature lactation. Significantly, immune and innate defence proteins appear in milk during infection of the mammary gland and possibly also during systemic infections. The understanding of the human milk proteome and how it changes with time during lactation and in disease is developing rapidly, and is to a large extent informed by proteomics of the milks of non-human mammals, domestic animals in particular. We review general methods now being applied for proteomic analysis of human milk. Moreover we place emphasis on how the milk proteome may change in different ways in response to disease, mastitis in particular, how such changes may be specific to pathogen types, and we give some insights about evolution. Copyright © 2013 Elsevier B.V. All rights reserved.
Full Text Available The central dogma of molecular biology explains how genetic information is converted into its end product, proteins, which are responsible for the phenotypic state of the cell. Along with the protein type, the phenotypic state depends on the protein copy number. Therefore, quantification of the protein expression in a single cell is critical for quantitative characterization of the phenotypic states. Protein expression is typically a dynamic and stochastic phenomenon that cannot be well described by standard experimental methods. As an alternative, fluorescence imaging is being explored for the study of protein expression, because of its high sensitivity and high throughput. Here we review key recent progresses in fluorescence imaging-based methods and discuss their application to proteome analysis at the single cell level.
Urfer, Wolfgang; Grzegorczyk, Marco; Jung, Klaus
Most proteomics experiments make use of 'high throughput' technologies such a's 2-DE, MS or protein arrays to measure simultaneously the expression levels of thousands of proteins. Such experiments yield, large, high-dimensional data sets which usually reflect not only the biological but also
Wöhlbrand, Lars; Trautwein, Kathleen; Rabus, Ralf
The steadily increasing amount of (meta-)genomic sequence information of diverse organisms and habitats has a strong impact on research in microbial physiology and ecology. In-depth functional understanding of metabolic processes and overall physiological adaptation to environmental changes, however, requires application of proteomics, as the context specific proteome constitutes the true functional output of a cell. Considering the enormous structural and functional diversity of proteins, only rational combinations of various analytical approaches allow a holistic view on the overall state of the cell. Within the past decade, proteomic methods became increasingly accessible to microbiologists mainly due to the robustness of analytical methods (e.g. 2DE), and affordability of mass spectrometers and their relative ease of use. This review provides an overview on the complex portfolio of state-of-the-art proteomics and highlights the basic principles of key methods, ranging from sample preparation of laboratory or environmental samples, via protein/peptide separation (gel-based or gel-free) and different types of mass spectrometric protein/peptide analyses, to protein identification and abundance determination. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
This presentation specifically addresses the advantages and limitations of state of the art gel, protein arrays and peptide-based labeling proteomic approaches to assess the effects of a suite of model T4 inhibitors on the thyroid axis of Xenopus laevis.
Høgdall, Claus; Fung, Eric T; Christensen, Ib J
Previous reports have shown that the proteomic markers apolipoprotein A1, hepcidin, transferrin, inter-alpha trypsin IV internal fragment, transthyretin, connective-tissue activating protein 3 and beta-2 microglobulin may discriminate between a benign pelvic mass and ovarian cancer (OC). The aim...
Lion, N; Prudent, M; Crettaz, D; Tissot, J-D
The term "proteomics" covers tools and techniques that are used to analyze and characterize complex mixtures of proteins from various biological samples. In this short review, a typical proteomic approach, related to the study of particular and illustrative situation related to transfusion medicine is reported. This "case report" will allow the reader to be familiar with a practical proteomic approach of a real situation, and will permit to describe the tools that are usually used in proteomic labs, and, in a second part, to present various proteomic applications in transfusion medicine. Copyright © 2011 Elsevier Masson SAS. All rights reserved.
Pang, Chi Nam Ignatius; Tay, Aidan P; Aya, Carlos; Twine, Natalie A; Harkness, Linda; Hart-Smith, Gene; Chia, Samantha Z; Chen, Zhiliang; Deshpande, Nandan P; Kaakoush, Nadeem O; Mitchell, Hazel M; Kassem, Moustapha; Wilkins, Marc R
Direct links between proteomic and genomic/transcriptomic data are not frequently made, partly because of lack of appropriate bioinformatics tools. To help address this, we have developed the PG Nexus pipeline. The PG Nexus allows users to covisualize peptides in the context of genomes or genomic contigs, along with RNA-seq reads. This is done in the Integrated Genome Viewer (IGV). A Results Analyzer reports the precise base position where LC-MS/MS-derived peptides cover genes or gene isoforms, on the chromosomes or contigs where this occurs. In prokaryotes, the PG Nexus pipeline facilitates the validation of genes, where annotation or gene prediction is available, or the discovery of genes using a "virtual protein"-based unbiased approach. We illustrate this with a comprehensive proteogenomics analysis of two strains of Campylobacter concisus . For higher eukaryotes, the PG Nexus facilitates gene validation and supports the identification of mRNA splice junction boundaries and splice variants that are protein-coding. This is illustrated with an analysis of splice junctions covered by human phosphopeptides, and other examples of relevance to the Chromosome-Centric Human Proteome Project. The PG Nexus is open-source and available from https://github.com/IntersectAustralia/ap11_Samifier. It has been integrated into Galaxy and made available in the Galaxy tool shed.
Grover, William H; Bryan, Andrea K; Diez-Silva, Monica; Suresh, Subra; Higgins, John M; Manalis, Scott R
We have used a microfluidic mass sensor to measure the density of single living cells. By weighing each cell in two fluids of different densities, our technique measures the single-cell mass, volume, and density of approximately 500 cells per hour with a density precision of 0.001 g mL(-1). We observe that the intrinsic cell-to-cell variation in density is nearly 100-fold smaller than the mass or volume variation. As a result, we can measure changes in cell density indicative of cellular processes that would be otherwise undetectable by mass or volume measurements. Here, we demonstrate this with four examples: identifying Plasmodium falciparum malaria-infected erythrocytes in a culture, distinguishing transfused blood cells from a patient's own blood, identifying irreversibly sickled cells in a sickle cell patient, and identifying leukemia cells in the early stages of responding to a drug treatment. These demonstrations suggest that the ability to measure single-cell density will provide valuable insights into cell state for a wide range of biological processes.
Francisco José Pérez -Llarena
Full Text Available Proteomic studies have improved our understanding of the microbial world. The most recent advances in this field have helped us to explore aspects beyond genomics. For example, by studying proteins and their regulation, researchers now understand how some pathogenic bacteria have adapted to the lethal actions of antibiotics. Proteomics has also advanced our knowledge of mechanisms of bacterial virulence and some important aspects of how bacteria interact with human cells and, thus, of the pathogenesis of infectious diseases. This review article addresses these issues in some of the most important human pathogens. It also reports some applications of MALDI-TOF mass spectrometry that may be important for the diagnosis of bacterial resistance in clinical laboratories in the future. The reported advances will enable new diagnostic and therapeutic strategies to be developed in the fight against some of the most lethal bacteria affecting humans.
Federal Laboratory Consortium — Proteomics Core is the central resource for mass spectrometry based proteomics within the NHLBI. The Core staff help collaborators design proteomics experiments in a...
This book provides an overview of single-cell isolation, separation, injection, lysis and dynamics analysis as well as a study of their heterogeneity using different miniaturized devices. As an important part of single-cell analysis, different techniques including electroporation, microinjection, optical trapping, optoporation, rapid electrokinetic patterning and optoelectronic tweezers are described in detail. It presents different fluidic systems (e.g. continuous micro/nano-fluidic devices, microfluidic cytometry) and their integration with sensor technology, optical and hydrodynamic stretchers etc., and demonstrates the applications of single-cell analysis in systems biology, proteomics, genomics, epigenomics, cancer transcriptomics, metabolomics, biomedicine and drug delivery systems. It also discusses the future challenges for single-cell analysis, including the advantages and limitations. This book is enjoyable reading material while at the same time providing essential information to scientists in acad...
Wang, Daojing; Bodovitz, Steven
Cellular heterogeneity arising from stochastic expression of genes, proteins, and metabolites is a fundamental principle of cell biology, but single cell analysis has been beyond the capabilities of 'Omics' technologies. This is rapidly changing with the recent examples of single cell genomics, transcriptomics, proteomics, and metabolomics. The rate of change is expected to accelerate owing to emerging technologies that range from micro/nanofluidics to microfabricated interfaces for mass spectrometry to third- and fourth-generation automated DNA sequencers. As described in this review, single cell analysis is the new frontier in Omics, and single cell Omics has the potential to transform systems biology through new discoveries derived from cellular heterogeneity.
Neu, Karlynn E; Tang, Qingming; Wilson, Patrick C; Khan, Aly A
Single-cell genomics offers powerful tools for studying immune cells, which make it possible to observe rare and intermediate cell states that cannot be resolved at the population level. Advances in computer science and single-cell sequencing technology have created a data-driven revolution in immunology. The challenge for immunologists is to harness computing and turn an avalanche of quantitative data into meaningful discovery of immunological principles, predictive models, and strategies for therapeutics. Here, we review the current literature on computational analysis of single-cell RNA-sequencing data and discuss underlying assumptions, methods, and applications in immunology, and highlight important directions for future research. Copyright © 2016 Elsevier Ltd. All rights reserved.
Wen, Lu; Tang, Fuchou
Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of stem cell populations, but these differences are masked when bulk cells are used for omic analysis. Single-cell sequencing technologies serve as powerful tools to dissect cellular heterogeneity comprehensively and to identify distinct phenotypic cell types, even within a 'homogeneous' stem cell population. These technologies, including single-cell genome, epigenome, and transcriptome sequencing technologies, have been developing rapidly in recent years. The application of these methods to different types of stem cells, including pluripotent stem cells and tissue-specific stem cells, has led to exciting new findings in the stem cell field. In this review, we discuss the recent progress as well as future perspectives in the methodologies and applications of single-cell omic sequencing technologies.
Ji, Zhicheng; Zhou, Weiqiang; Ji, Hongkai
Emerging single-cell technologies (e.g. single-cell ATAC-seq, DNase-seq or ChIP-seq) have made it possible to assay regulome of individual cells. Single-cell regulome data are highly sparse and discrete. Analyzing such data is challenging. User-friendly software tools are still lacking. We present SCRAT, a Single-Cell Regulome Analysis Toolbox with a graphical user interface, for studying cell heterogeneity using single-cell regulome data. SCRAT can be used to conveniently summarize regulatory activities according to different features (e.g. gene sets, transcription factor binding motif sites, etc.). Using these features, users can identify cell subpopulations in a heterogeneous biological sample, infer cell identities of each subpopulation, and discover distinguishing features such as gene sets and transcription factors that show different activities among subpopulations. SCRAT is freely available at https://zhiji.shinyapps.io/scrat as an online web service and at https://github.com/zji90/SCRAT as an R package. email@example.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Full Text Available Single-cell analysis has become an established method to study cell heterogeneity and for rare cell characterization. Despite the high cost and technical constraints, applications are increasing every year in all fields of biology. Following the trend, there is a tremendous development of tools for single-cell analysis, especially in the RNA sequencing field. Every improvement increases sensitivity and throughput. Collecting a large amount of data also stimulates the development of new approaches for bioinformatic analysis and interpretation. However, the essential requirement for any analysis is the collection of single cells of high quality. The single-cell isolation must be fast, effective, and gentle to maintain the native expression profiles. Classical methods for single-cell isolation are micromanipulation, microdissection, and fluorescence-activated cell sorting (FACS. In the last decade several new and highly efficient approaches have been developed, which not just supplement but may fully replace the traditional ones. These new techniques are based on microfluidic chips, droplets, micro-well plates, and automatic collection of cells using capillaries, magnets, an electric field, or a punching probe. In this review we summarize the current methods and developments in this field. We discuss the advantages of the different commercially available platforms and their applicability, and also provide remarks on future developments.
Valihrach, Lukas; Androvic, Peter; Kubista, Mikael
Single-cell analysis has become an established method to study cell heterogeneity and for rare cell characterization. Despite the high cost and technical constraints, applications are increasing every year in all fields of biology. Following the trend, there is a tremendous development of tools for single-cell analysis, especially in the RNA sequencing field. Every improvement increases sensitivity and throughput. Collecting a large amount of data also stimulates the development of new approaches for bioinformatic analysis and interpretation. However, the essential requirement for any analysis is the collection of single cells of high quality. The single-cell isolation must be fast, effective, and gentle to maintain the native expression profiles. Classical methods for single-cell isolation are micromanipulation, microdissection, and fluorescence-activated cell sorting (FACS). In the last decade several new and highly efficient approaches have been developed, which not just supplement but may fully replace the traditional ones. These new techniques are based on microfluidic chips, droplets, micro-well plates, and automatic collection of cells using capillaries, magnets, an electric field, or a punching probe. In this review we summarize the current methods and developments in this field. We discuss the advantages of the different commercially available platforms and their applicability, and also provide remarks on future developments.
Jensen, Sissel Juul; Harmsen, Charlotte; Nielsen, Mette Juul
Conventional diagnosis based on ensemble measurements often overlooks the variation among cells. Here, we present a droplet-microfluidics based platform to investigate single cell activities. Adopting a previously developed isothermal rolling circle amplification-based assay, we demonstrate...... detection of enzymatic activities down to the single cell level with small quantities of biological samples, which outcompetes existing techniques. Such a system, capable of resolving single cell activities, will ultimately have clinical applications in diagnosis, prediction of drug response and treatment...
Silva, Tomé S.; Matos, Elisabete; Cordeire, Odete
proteins, and consequent muscle softening. The purpose of this study was to modulate the energy status of the muscle at the time of death through the use of dietary muscle buffering compounds, namely glycerol and maslinic acid. Four fish groups of gilthead seabream (in duplicate) were fed for three months...... and isolipidic. Fish were slaughtered by immersion in ice-salt water slurry and muscle samples were immediately obtained from three fish of each tank, for a total of six muscle samples per treatment. Sarcoplasmic proteins were extracted from each muscle sample, separated/quantified by 2D-DIGE and identified...... by peptide fragment fingerprinting using MALDI-TOF MS. Preliminary analysis of the results shows an effect of the diets on muscle parameters such as measured pH and onset of rigor mortis. At the proteome level, the addition of glycerol and maslinic acid to the diets seemed to have affected the abundance...
Lv, Jian; Qian, Ruo-Can; Hu, Yong-Xu; Liu, Shao-Chuang; Cao, Yue; Zheng, Yong-Jie; Long, Yi-Tao
The precise transportation of fluorescent probes to the designated location in living cells is still a challenge. Here, we present a new addition to nanopipettes as a powerful tool to deliver fluorescent molecules to a given place in a single cell by electroosmotic flow, indicating favorable potential for further application in single-cell imaging.
Skvortsov, V S; Alekseychuk, N N; Khudyakov, D V; Mikurova, A V; Rybina, A V; Novikova, S E; Tikhonova, O V
ProteoCat is a computer program has been designed to help researchers in the planning of large-scale proteomic experiments. The central part of this program is the subprogram of hydrolysis simulation that supports 4 proteases (trypsin, lysine C, endoproteinases AspN and GluC). For the peptides obtained after virtual hydrolysis or loaded from data file a number of properties important in mass-spectrometric experiments can be calculated or predicted. The data can be analyzed or filtered to reduce a set of peptides. The program is using new and improved modification of our methods developed to predict pI and probability of peptide detection; pI can also be predicted for a number of popular pKa's scales, proposed by other investigators. The algorithm for prediction of peptide retention time was realized similar to the algorithm used in the program SSRCalc. ProteoCat can estimate the coverage of amino acid sequences of proteins under defined limitation on peptides detection, as well as the possibility of assembly of peptide fragments with user-defined size of "sticky" ends. The program has a graphical user interface, written on JAVA and available at http://www.ibmc.msk.ru/LPCIT/ProteoCat.
Zhang, Wei; Zhang, Jiyang; Xu, Changming; Li, Ning; Liu, Hui; Ma, Jie; Zhu, Yunping; Xie, Hongwei
Database searching based methods for label-free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross-assignment among different runs. Here, we present a new label-free fast quantitative analysis tool, LFQuant, for high-resolution LC-MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL-Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Minde, David-Paul; Dunker, A Keith; Lilley, Kathryn S
Proteins are highly dynamic entities. Their myriad functions require specific structures, but proteins' dynamic nature ranges all the way from the local mobility of their amino acid constituents to mobility within and well beyond single cells. A truly comprehensive view of the dynamic structural proteome includes: (i) alternative sequences, (ii) alternative conformations, (iii) alternative interactions with a range of biomolecules, (iv) cellular localizations, (v) alternative behaviors in different cell types. While these aspects have traditionally been explored one protein at a time, we highlight recently emerging global approaches that accelerate comprehensive insights into these facets of the dynamic nature of protein structure. Computational tools that integrate and expand on multiple orthogonal data types promise to enable the transition from a disjointed list of static snapshots to a structurally explicit understanding of the dynamics of cellular mechanisms. © 2017 The Authors. Proteomics Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Kodzius, Rimantas; Gojobori, Takashi
Environmental studies are primarily done by culturing isolated microorganisms or by amplifying and sequencing conserved genes. Difficulties understanding the complexity of large numbers of various microorganisms in an environment led to the development of techniques to enrich specific microorganisms for upstream analysis, ultimately leading to single-cell isolation and analyses. We discuss the significance of single-cell technologies in omics studies with focus on metagenomics and metatranscriptomics. We propose that by reducing sample heterogeneity using single-cell genomics, metaomic studies can be simplified.
Environmental studies are primarily done by culturing isolated microorganisms or by amplifying and sequencing conserved genes. Difficulties understanding the complexity of large numbers of various microorganisms in an environment led to the development of techniques to enrich specific microorganisms for upstream analysis, ultimately leading to single-cell isolation and analyses. We discuss the significance of single-cell technologies in omics studies with focus on metagenomics and metatranscriptomics. We propose that by reducing sample heterogeneity using single-cell genomics, metaomic studies can be simplified.
Bheda, Poonam; Schneider, Robert
Mechanistically, how epigenetic states are inherited through cellular divisions remains an important open question in the chromatin field and beyond. Defining the heritability of epigenetic states and the underlying chromatin-based mechanisms within a population of cells is complicated due to cell heterogeneity combined with varying levels of stability of these states; thus, efforts must be focused toward single-cell analyses. The approaches presented here constitute the forefront of epigenetics research at the single-cell level using classic and innovative methods to dissect epigenetics mechanisms from the limited material available in a single cell. This review further outlines exciting future avenues of research to address the significance of epigenetic heterogeneity and the contributions of microfluidics technologies to single-cell isolation and analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.
Knudsen, Anders Dahl; Bennike, Tue; Kjeldal, Henrik; Birkelund, Svend; Otzen, Daniel Erik; Stensballe, Allan
We describe Condenser, a freely available, comprehensive open-source tool for merging multidimensional quantitative proteomics data from the Matrix Science Mascot Distiller Quantitation Toolbox into a common format ready for subsequent bioinformatic analysis. A number of different relative quantitation technologies, such as metabolic (15)N and amino acid stable isotope incorporation, label-free and chemical-label quantitation are supported. The program features multiple options for curative filtering of the quantified peptides, allowing the user to choose data quality thresholds appropriate for the current dataset, and ensure the quality of the calculated relative protein abundances. Condenser also features optional global normalization, peptide outlier removal, multiple testing and calculation of t-test statistics for highlighting and evaluating proteins with significantly altered relative protein abundances. Condenser provides an attractive addition to the gold-standard quantitative workflow of Mascot Distiller, allowing easy handling of larger multi-dimensional experiments. Source code, binaries, test data set and documentation are available at http://condenser.googlecode.com/. Copyright © 2014 Elsevier B.V. All rights reserved.
Veit, Johannes; Sachsenberg, Timo; Chernev, Aleksandar; Aicheler, Fabian; Urlaub, Henning; Kohlbacher, Oliver
Modern mass spectrometry setups used in today's proteomics studies generate vast amounts of raw data, calling for highly efficient data processing and analysis tools. Software for analyzing these data is either monolithic (easy to use, but sometimes too rigid) or workflow-driven (easy to customize, but sometimes complex). Thermo Proteome Discoverer (PD) is a powerful software for workflow-driven data analysis in proteomics which, in our eyes, achieves a good trade-off between flexibility and usability. Here, we present two open-source plugins for PD providing additional functionality: LFQProfiler for label-free quantification of peptides and proteins, and RNP(xl) for UV-induced peptide-RNA cross-linking data analysis. LFQProfiler interacts with existing PD nodes for peptide identification and validation and takes care of the entire quantitative part of the workflow. We show that it performs at least on par with other state-of-the-art software solutions for label-free quantification in a recently published benchmark ( Ramus, C.; J. Proteomics 2016 , 132 , 51 - 62 ). The second workflow, RNP(xl), represents the first software solution to date for identification of peptide-RNA cross-links including automatic localization of the cross-links at amino acid resolution and localization scoring. It comes with a customized integrated cross-link fragment spectrum viewer for convenient manual inspection and validation of the results.
Barkla, Bronwyn J.; Vera-Estrella, Rosario
One of the remarkable adaptive features of the halophyte and facultative CAM plant Mesembryathemum crystallinum are the specialized modified trichomes called epidermal bladder cells (EBC) which cover the leaves, stems, and peduncle of the plant. They are present from an early developmental stage but upon salt stress rapidly expand due to the accumulation of water and sodium. This particular plant feature makes it an attractive system for single cell type studies, with recent proteomics and tr...
Thurber, Greg M; Yang, Katy S; Reiner, Thomas; Kohler, Rainer H; Sorger, Peter; Mitchison, Tim; Weissleder, Ralph
Pharmacokinetic analysis at the organ level provides insight into how drugs distribute throughout the body, but cannot explain how drugs work at the cellular level. Here we demonstrate in vivo single-cell pharmacokinetic imaging of PARP-1 inhibitors and model drug behaviour under varying conditions. We visualize intracellular kinetics of the PARP-1 inhibitor distribution in real time, showing that PARP-1 inhibitors reach their cellular target compartment, the nucleus, within minutes in vivo both in cancer and normal cells in various cancer models. We also use these data to validate predictive finite element modelling. Our theoretical and experimental data indicate that tumour cells are exposed to sufficiently high PARP-1 inhibitor concentrations in vivo and suggest that drug inefficiency is likely related to proteomic heterogeneity or insensitivity of cancer cells to DNA-repair inhibition. This suggests that single-cell pharmacokinetic imaging and derived modelling improve our understanding of drug action at single-cell resolution in vivo.
Schaeffer, Mathieu; Gateau, Alain; Teixeira, Daniel; Michel, Pierre-André; Zahn-Zabal, Monique; Lane, Lydie
The neXtProt peptide uniqueness checker allows scientists to define which peptides can be used to validate the existence of human proteins, i.e. map uniquely versus multiply to human protein sequences taking into account isobaric substitutions, alternative splicing and single amino acid variants. The pepx program is available at https://github.com/calipho-sib/pepx and can be launched from the command line or through a cgi web interface. Indexing requires a sequence file in FASTA format. The peptide uniqueness checker tool is freely available on the web at https://www.nextprot.org/tools/peptide-uniqueness-checker and from the neXtProt API at https://api.nextprot.org/. firstname.lastname@example.org. © The Author(s) 2017. Published by Oxford University Press.
Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader
Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular pH of individual cells within a cell population is challenging with existing technologies, and there is a need to engineer new methodologies. In this paper, we discuss the use of nanopipette technology to overcome the limitations of intracellular pH measurements at the single-cell level. We have developed a nano-pH probe through physisorption of chitosan onto hydroxylated quartz nanopipettes with extremely small pore sizes (~100 nm). The dynamic pH range of the nano-pH probe was from 2.6 to 10.7 with a sensitivity of 0.09 units. We have performed single-cell intracellular pH measurements using non-cancerous and cancerous cell lines, including human fibroblasts, HeLa, MDA-MB-231 and MCF-7, with the pH nanoprobe. We have further demonstrated the real-time continuous single-cell pH measurement capability of the sensor, showing the cellular pH response to pharmaceutical manipulations. These findings suggest that the chitosan-functionalized nanopore is a powerful nano-tool for pH sensing at the single-cell level with high temporal and spatial resolution. PMID:27708772
Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader
Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular pH of individual cells within a cell population is challenging with existing technologies, and there is a need to engineer new methodologies. In this paper, we discuss the use of nanopipette technology to overcome the limitations of intracellular pH measurements at the single-cell level. We have developed a nano-pH probe through physisorption of chitosan onto hydroxylated quartz nanopipettes with extremely small pore sizes (~100 nm). The dynamic pH range of the nano-pH probe was from 2.6 to 10.7 with a sensitivity of 0.09 units. We have performed single-cell intracellular pH measurements using non-cancerous and cancerous cell lines, including human fibroblasts, HeLa, MDA-MB-231 and MCF-7, with the pH nanoprobe. We have further demonstrated the real-time continuous single-cell pH measurement capability of the sensor, showing the cellular pH response to pharmaceutical manipulations. These findings suggest that the chitosan-functionalized nanopore is a powerful nano-tool for pH sensing at the single-cell level with high temporal and spatial resolution.
The full proteomics analysis of a small tumor sample (similar in mass to a few grains of rice) produces well over 500 megabytes of unprocessed "raw" data when analyzed on a mass spectrometer (MS). Thus, for every proteomics experiment there is a vast amount of raw data that must be analyzed and interrogated in order to extract biological information. Moreover, the raw data output from different MS vendors are generally in different formats inhibiting the ability of labs to productively work together.
Zeng, Guanghong; Ogaki, Ryosuke; Regina, Viduthalai R.
be considered. We have therefore developed a simple and versatile method to make single-cell bacterial probes for measuring single cell adhesion with atomic force microscopy (AFM). A single-cell probe was readily made by picking up a bacterial cell from a glass surface using a tipless AFM cantilever coated...... random immobilization is obtained by submerging the cantilever in a bacterial suspension. The reported method provides a general platform for investigating single cell interactions of bacteria with different surfaces and other cells by AFM force spectroscopy, thus improving our understanding....... The strain-dependent susceptibility to bacterial colonization on conventional PLL-g-PEG illustrates how bacterial diversity challenges development of “universal” antifouling coatings, and AFM single-cell force spectroscopy was proven to be a powerful tool to provide insights into the molecular mechanisms...
Ramirez-Garcia, Andoni; Pellon, Aize; Buldain, Idoia; Antoran, Aitziber; Arbizu-Delgado, Aitana; Guruceaga, Xabier; Rementeria, Aitor; Hernando, Fernando L
Cystic fibrosis (CF) is a genetic disorder that increases the risk of suffering microbial, including fungal, infections. In this paper, proteomics-based information was collated relating to secreted and cell wall proteins with potential medical applications from the most common filamentous fungi in CF, i.e., Aspergillus and Scedosporium/Lomentospora species. Among the Aspergillus fumigatus secreted allergens, β-1,3-endoglucanase, the alkaline protease 1 (Alp1/oryzin), Asp f 2, Asp f 13/15, chitinase, chitosanase, dipeptidyl-peptidase V (DppV), the metalloprotease Asp f 5, mitogillin/Asp f 1, and thioredoxin reductase receive a special mention. In addition, the antigens β-glucosidase 1, catalase, glucan endo-1,3-β-glucosidase EglC, β-1,3-glucanosyltransferases Gel1 and Gel2, and glutaminase A were also identified in secretomes of other Aspergillus species associated with CF: Aspergillus flavus, Aspergillus niger, Aspergillus nidulans, and Aspergillus terreus. Regarding cell wall proteins, cytochrome P450 and eEF-3 were proposed as diagnostic targets, and alkaline protease 2 (Alp2), Asp f 3 (putative peroxiredoxin pmp20), probable glycosidases Asp f 9/Crf1 and Crf2, GPI-anchored protein Ecm33, β-1,3-glucanosyltransferase Gel4, conidial hydrophobin Hyp1/RodA, and secreted aspartyl protease Pep2 as protective vaccines in A. fumigatus. On the other hand, for Scedosporium/Lomentospora species, the heat shock protein Hsp70 stands out as a relevant secreted and cell wall antigen. Additionally, the secreted aspartyl proteinase and an ortholog of Asp f 13, as well as the cell wall endo-1,3-β-D-glucosidase and 1,3-β-glucanosyl transferase, were also found to be significant proteins. In conclusion, proteins mentioned in this review may be promising candidates for developing innovative diagnostic and therapeutic tools for fungal infections in CF patients.
Single-cell RNA-sequence (RNA-seq) is a widely used tool to study biological questions in single cells. The discussed study identified 92 genes being predominantly expressed in podocytes based on a 5-fold higher expression compared with endothelial and mesangial cells. In addition to technical pitfalls, the question that is discussed in this commentary is whether results of a single-cell RNAseq study are able to deliver expression data that truly characterize a podocyte. Copyright © 2017 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.
Clingenpeel, Scott [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Schwientek, Patrick [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Hugenholtz, Philip [Univ. of Queensland, Brisbane (Australia); Woyke, Tanja [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
It is known that single-cell genomics is a powerful tool for accessing genetic information from uncultivated microorganisms. Methods of handling samples before single-cell genomic amplification may affect the quality of the genomes obtained. Using three bacterial strains we demonstrate that, compared to cryopreservation, lower-quality single-cell genomes are recovered when the sample is preserved in ethanol or if the sample undergoes fluorescence in situ hybridization, while sample preservation in paraformaldehyde renders it completely unsuitable for sequencing.
Carberry, Steven; Zweyer, Margit; Swandulla, Dieter; Ohlendieck, Kay
In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic investigations. Although two-dimensional gels usually underestimate the cellular presence of very high molecular mass proteins, integral membrane proteins and low copy number proteins, this method is extremely powerful in the comprehensive analysis of contractile proteins, metabolic enzymes, structural proteins and molecular chaperones. This gives rise to two-dimensional gel electrophoretic separation as the method of choice for studying contractile tissues in health and disease. For comparative studies, fluorescence difference in-gel electrophoresis has been shown to provide an excellent biomarker discovery tool. Since aged diaphragm fibres from the mdx mouse model of Duchenne muscular dystrophy closely resemble the human pathology, we have carried out a mass spectrometry-based comparison of the naturally aged diaphragm versus the senescent dystrophic diaphragm. The proteomic comparison of wild type versus mdx diaphragm resulted in the identification of 84 altered protein species. Novel molecular insights into dystrophic changes suggest increased cellular stress, impaired calcium buffering, cytostructural alterations and disturbances of mitochondrial metabolism in dystrophin-deficient muscle tissue. PMID:24833232
Lapainis, Theodore E.
Understanding the functioning of the brain is hindered by a lack of knowledge of the full complement of neurotransmitters and neuromodulatory compounds. Single cell measurements aid in the discovery of neurotransmitters used by small subsets of neurons that would be diluted below detection limits or masked by ubiquitous compounds when working with…
Templer, Richard H.; Ces, Oscar
For this special issue of J. R. Soc. Interface we present an overview of the driving forces behind technological advances in the field of single-cell analysis. These range from increasing our understanding of cellular heterogeneity through to the study of rare cells, areas of research that cannot be tackled effectively using current high-throughput population-based averaging techniques.
Hochholdinger, Frank; Marcon, Caroline; Baldauf, Jutta A; Yu, Peng; Frey, Felix P
Maize forms a complex root system with structurally and functionally diverse root types that are formed at different developmental stages to extract water and mineral nutrients from soil. In recent years proteomics has been intensively applied to identify proteins involved in shaping the three-dimensional architecture and regulating the function of the maize root system. With the help of developmental mutants, proteomic changes during the initiation and emergence of shoot-borne, lateral and seminal roots have been examined. Furthermore, root hairs were surveyed to understand the proteomic changes during the elongation of these single cell type structures. In addition, primary roots have been used to study developmental changes of the proteome but also to investigate the proteomes of distinct tissues such as the meristematic zone, the elongation zone as well as stele and cortex of the differentiation zone. Moreover, subcellular fractions of the primary root including cell walls, plasma membranes and secreted mucilage have been analyzed. Finally, the superior vigor of hybrid seedling roots compared to their parental inbred lines was studied on the proteome level. In summary, these studies provide novel insights into the complex proteomic interactions of the elaborate maize root system during development.
Full Text Available Maize forms a complex root system with structurally and functionally diverse root types that are formed at different developmental stages to extract water and mineral nutrients from soil. In recent years proteomics has been intensively applied to identify proteins involved in shaping the three-dimensional architecture and regulating the function of the maize root system. With the help of developmental mutants, proteomic changes during the initiation and emergence of shoot-borne, lateral and seminal roots have been examined. Furthermore, root hairs were surveyed to understand the proteomic changes during the elongation of these single cell type structures. In addition, primary roots have been used to study developmental changes of the proteome but also to investigate the proteomes of distinct tissues such as the meristematic zone, the elongation zone as well as stele and cortex of the differentiation zone. Moreover, subcellular fractions of the primary root including cell walls, plasma membranes and secreted mucilage have been analyzed. Finally, the superior vigor of hybrid seedling roots compared to their parental inbred lines was studied on the proteome level. In summary, these studies provide novel insights into the complex proteomic interactions of the elaborate maize root system during development.
Donolato, Marco; Torti, A.; Kostesha, Natalie
The ability to trap, manipulate and release single cells on a surface is important both for fundamental studies of cellular processes and for the development of novel lab-on-chip miniaturized tools for biological and medical applications. In this paper we demonstrate how magnetic domain walls...... walls over 16 hours. Moreover, we demonstrate the controlled transport and release of individual yeast cells via displacement and annihilation of individual domain walls in micro- and nano-sized magnetic structures. These results pave the way to the implementation of magnetic devices based on domain...... walls technology in lab-on-chip systems devoted to accurate individual cell trapping and manipulation....
Ren, M.Q.; Thong, P.S.P.; Kara, U.; Watt, F.
The use of Particle Induced X-ray Emission (PIXE), Rutherford Backscattering Spectrometry (RBS) and Scanning Transmission Ion Microscopy (STIM) to provide quantitative elemental analysis of single cells is an area which has high potential, particularly when the trace elements such as Ca, Fe, Zn and Cu can be monitored. We describe the methodology of sample preparation for two cell types, the procedures of cell imaging using STIM, and the quantitative elemental analysis of single cells using RBS and PIXE. Recent work on single cells at the Nuclear Microscopy Research Centre,National University of Singapore has centred around two research areas: (a) Apoptosis (programmed cell death), which has been recently implicated in a wide range of pathological conditions such as cancer, Parkinson's disease etc, and (b) Malaria (infection of red blood cells by the malaria parasite). Firstly we present results on the elemental analysis of human Chang liver cells (ATTCC CCL 13) where vanadium ions were used to trigger apoptosis, and demonstrate that nuclear microscopy has the capability of monitoring vanadium loading within individual cells. Secondly we present the results of elemental changes taking place in individual mouse red blood cells which have been infected with the malaria parasite and treated with the anti-malaria drug Qinghaosu (QHS)
Schmidt, Tobias; Samaras, Patroklos; Frejno, Martin; Gessulat, Siegfried; Barnert, Maximilian; Kienegger, Harald; Krcmar, Helmut; Schlegl, Judith; Ehrlich, Hans-Christian; Aiche, Stephan; Kuster, Bernhard; Wilhelm, Mathias
ProteomicsDB (https://www.ProteomicsDB.org) is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. ProteomicsDB was first released in 2014 to enable the interactive exploration of the first draft of the human proteome. To date, it contains quantitative data from 78 projects totalling over 19k LC-MS/MS experiments. A standardized analysis pipeline enables comparisons between multiple datasets to facilitate the exploration of protein expression across hundreds of tissues, body fluids and cell lines. We recently extended the data model to enable the storage and integrated visualization of other quantitative omics data. This includes transcriptomics data from e.g. NCBI GEO, protein-protein interaction information from STRING, functional annotations from KEGG, drug-sensitivity/selectivity data from several public sources and reference mass spectra from the ProteomeTools project. The extended functionality transforms ProteomicsDB into a multi-purpose resource connecting quantification and meta-data for each protein. The rich user interface helps researchers to navigate all data sources in either a protein-centric or multi-protein-centric manner. Several options are available to download data manually, while our application programming interface enables accessing quantitative data systematically. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Kobayashi, Kyogo; Nakano, Shunji; Amano, Mutsuki; Tsuboi, Daisuke; Nishioka, Tomoki; Ikeda, Shingo; Yokoyama, Genta; Kaibuchi, Kozo; Mori, Ikue
Unveiling the molecular and cellular mechanisms underlying memory has been a challenge for the past few decades. Although synaptic plasticity is proven to be essential for memory formation, the significance of "single-cell memory" still remains elusive. Here, we exploited a primary culture system for the analysis of C. elegans neurons and show that a single thermosensory neuron has an ability to form, retain, and reset a temperature memory. Genetic and proteomic analyses found that the expression of the single-cell memory exhibits inter-individual variability, which is controlled by the evolutionarily conserved CaMKI/IV and Raf pathway. The variable responses of a sensory neuron influenced the neural activity of downstream interneurons, suggesting that modulation of the sensory neurons ultimately determines the behavioral output in C. elegans. Our results provide proof of single-cell memory and suggest that the individual differences in neural responses at the single-cell level can confer individuality. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Wu, Jincheng; Tzanakakis, Emmanuel S.
Isogenic stem cell populations display cell-to-cell variations in a multitude of attributes including gene or protein expression, epigenetic state, morphology, proliferation and proclivity for differentiation. The origins of the observed heterogeneity and its roles in the maintenance of pluripotency and the lineage specification of stem cells remain unclear. Addressing pertinent questions will require the employment of single-cell analysis methods as traditional cell biochemical and biomolecular assays yield mostly population-average data. In addition to time-lapse microscopy and flow cytometry, recent advances in single-cell genomic, transcriptomic and proteomic profiling are reviewed. The application of multiple displacement amplification, next generation sequencing, mass cytometry and spectrometry to stem cell systems is expected to provide a wealth of information affording unprecedented levels of multiparametric characterization of cell ensembles under defined conditions promoting pluripotency or commitment. Establishing connections between single-cell analysis information and the observed phenotypes will also require suitable mathematical models. Stem cell self-renewal and differentiation are orchestrated by the coordinated regulation of subcellular, intercellular and niche-wide processes spanning multiple time scales. Here, we discuss different modeling approaches and challenges arising from their application to stem cell populations. Integrating single-cell analysis with computational methods will fill gaps in our knowledge about the functions of heterogeneity in stem cell physiology. This combination will also aid the rational design of efficient differentiation and reprogramming strategies as well as bioprocesses for the production of clinically valuable stem cell derivatives. PMID:24035899
Aubusson-Fleury, Anne; Cohen, Jean; Lemullois, Michel
Paramecium is a single cell able to divide in its morphologically differentiated stage that has many cilia anchored at its cell surface. Many thousands of cilia are thus assembled in a short period of time during division to duplicate the cell pattern while the cell continues swimming. Most, but not all, of these sensory cilia are motile and involved in two main functions: prey capture and cell locomotion. These cilia display heterogeneity, both in their length and their biochemical properties. Thanks to these properties, as well as to the availability of many postgenomic tools and the possibility to follow the regrowth of cilia after deciliation, Paramecium offers a nice opportunity to study the assembly of the cilia, as well as the genesis of their diversity within a single cell. In this paper, after a brief survey of Paramecium morphology and cilia properties, we describe the tools and the protocols currently used for immunofluorescence, transmission electron microscopy, and ultrastructural immunocytochemistry to analyze cilia, with special recommendations to overcome the problem raised by cilium diversity. Copyright © 2015. Published by Elsevier Inc.
Toprak, Umut H; Gillet, Ludovic C; Maiolica, Alessio; Navarro, Pedro; Leitner, Alexander; Aebersold, Ruedi
Quantifying the similarity of spectra is an important task in various areas of spectroscopy, for example, to identify a compound by comparing sample spectra to those of reference standards. In mass spectrometry based discovery proteomics, spectral comparisons are used to infer the amino acid sequence of peptides. In targeted proteomics by selected reaction monitoring (SRM) or SWATH MS, predetermined sets of fragment ion signals integrated over chromatographic time are used to identify target peptides in complex samples. In both cases, confidence in peptide identification is directly related to the quality of spectral matches. In this study, we used sets of simulated spectra of well-controlled dissimilarity to benchmark different spectral comparison measures and to develop a robust scoring scheme that quantifies the similarity of fragment ion spectra. We applied the normalized spectral contrast angle score to quantify the similarity of spectra to objectively assess fragment ion variability of tandem mass spectrometric datasets, to evaluate portability of peptide fragment ion spectra for targeted mass spectrometry across different types of mass spectrometers and to discriminate target assays from decoys in targeted proteomics. Altogether, this study validates the use of the normalized spectral contrast angle as a sensitive spectral similarity measure for targeted proteomics, and more generally provides a methodology to assess the performance of spectral comparisons and to support the rational selection of the most appropriate similarity measure. The algorithms used in this study are made publicly available as an open source toolset with a graphical user interface. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.
Xue, Qiong; Bettini, Emily; Paczkowski, Patrick; Ng, Colin; Kaiser, Alaina; McConnell, Timothy; Kodrasi, Olja; Quigley, Máire F; Heath, James; Fan, Rong; Mackay, Sean; Dudley, Mark E; Kassim, Sadik H; Zhou, Jing
It remains challenging to characterize the functional attributes of chimeric antigen receptor (CAR)-engineered T cell product targeting CD19 related to potency and immunotoxicity ex vivo, despite promising in vivo efficacy in patients with B cell malignancies. We employed a single-cell, 16-plex cytokine microfluidics device and new analysis techniques to evaluate the functional profile of CD19 CAR-T cells upon antigen-specific stimulation. CAR-T cells were manufactured from human PBMCs transfected with the lentivirus encoding the CD19-BB-z transgene and expanded with anti-CD3/anti-CD28 coated beads. The enriched CAR-T cells were stimulated with anti-CAR or control IgG beads, stained with anti-CD4 RPE and anti-CD8 Alexa Fluor 647 antibodies, and incubated for 16 h in a single-cell barcode chip (SCBC). Each SCBC contains ~12,000 microchambers, covered with a glass slide that was pre-patterned with a complete copy of a 16-plex antibody array. Protein secretions from single CAR-T cells were captured and subsequently analyzed using proprietary software and new visualization methods. We demonstrate a new method for single-cell profiling of CD19 CAR-T pre-infusion products prepared from 4 healthy donors. CAR-T single cells exhibited a marked heterogeneity of cytokine secretions and polyfunctional (2+ cytokine) subsets specific to anti-CAR bead stimulation. The breadth of responses includes anti-tumor effector (Granzyme B, IFN-γ, MIP-1α, TNF-α), stimulatory (GM-CSF, IL-2, IL-8), regulatory (IL-4, IL-13, IL-22), and inflammatory (IL-6, IL-17A) functions. Furthermore, we developed two new bioinformatics tools for more effective polyfunctional subset visualization and comparison between donors. Single-cell, multiplexed, proteomic profiling of CD19 CAR-T product reveals a diverse landscape of immune effector response of CD19 CAR-T cells to antigen-specific challenge, providing a new platform for capturing CAR-T product data for correlative analysis. Additionally, such high
Danna, Erika A; Nolan, Garry P
The application of proteomics to disease research promises to enhance the understanding and treatment of many human maladies through the identification of molecular profiles associated with each disease. However, although much is made of the utility of molecular signatures as markers of disease state, insufficient emphasis is often placed on the simultaneous need for biological mechanism inquiry. Focused and detailed analyses of disease-associated signaling networks have the potential to be more mechanistically informative than large-scale proteomic profiling approaches, providing insight into the cellular processes involved in pathogenesis, disease progression and therapeutic resistance; while still providing diagnostic or clinical management direction. Phospho-specific flow cytometry provides a method for the analysis of pathological signaling networks, enabling the investigation of disease mechanisms at the single-cell level.
Blattmann, Peter; Heusel, Moritz; Aebersold, Ruedi
SWATH-MS is an acquisition and analysis technique of targeted proteomics that enables measuring several thousand proteins with high reproducibility and accuracy across many samples. OpenSWATH is popular open-source software for peptide identification and quantification from SWATH-MS data. For downstream statistical and quantitative analysis there exist different tools such as MSstats, mapDIA and aLFQ. However, the transfer of data from OpenSWATH to the downstream statistical tools is currently technically challenging. Here we introduce the R/Bioconductor package SWATH2stats, which allows convenient processing of the data into a format directly readable by the downstream analysis tools. In addition, SWATH2stats allows annotation, analyzing the variation and the reproducibility of the measurements, FDR estimation, and advanced filtering before submitting the processed data to downstream tools. These functionalities are important to quickly analyze the quality of the SWATH-MS data. Hence, SWATH2stats is a new open-source tool that summarizes several practical functionalities for analyzing, processing, and converting SWATH-MS data and thus facilitates the efficient analysis of large-scale SWATH/DIA datasets.
Khurshid, Zohaib; Zohaib, Sana; Najeeb, Shariq; Zafar, Muhammad Sohail; Rehman, Rabia; Rehman, Ihtesham Ur
Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed.
Full Text Available Abstract Background Viruses and small-genome bacteria (~2 megabases and smaller comprise a considerable population in the biosphere and are of interest to many researchers. These genomes are now sequenced at an unprecedented rate and require complementary computational tools to analyze. "CoreGenesUniqueGenes" (CGUG is an in silico genome data mining tool that determines a "core" set of genes from two to five organisms with genomes in this size range. Core and unique genes may reflect similar niches and needs, and may be used in classifying organisms. Findings CGUG is available at http://binf.gmu.edu/geneorder.html as a web-based on-the-fly tool that performs iterative BLASTP analyses using a reference genome and up to four query genomes to provide a table of genes common to these genomes. The result is an in silico display of genomes and their proteomes, allowing for further analysis. CGUG can be used for "genome annotation by homology", as demonstrated with Chlamydophila and Francisella genomes. Conclusion CGUG is used to reanalyze the ICTV-based classifications of bacteriophages, to reconfirm long-standing relationships and to explore new classifications. These genomes have been problematic in the past, due largely to horizontal gene transfers. CGUG is validated as a tool for reannotating small genome bacteria using more up-to-date annotations by similarity or homology. These serve as an entry point for wet-bench experiments to confirm the functions of these "hypothetical" and "unknown" proteins.
Albrethsen, Jakob; Frederiksen, Hanne; Johannsen, Trine Holm
Clinical proteomics aims to deliver cost-effective multiplexing of potentially hundreds of diagnostic proteins, including distinct protein isoforms. The analytical strategy known as targeted proteomics is particularly promising because it is compatible with robust mass spectrometry (MS)-platforms...... standards and calibrants. The present challenge is to examine if targeted proteomics of IGF-I can truly measure up to the routine performance that must be expected from a clinical testing platform.......Clinical proteomics aims to deliver cost-effective multiplexing of potentially hundreds of diagnostic proteins, including distinct protein isoforms. The analytical strategy known as targeted proteomics is particularly promising because it is compatible with robust mass spectrometry (MS......)-platforms already implemented in many clinical laboratories for routine quantitation of small molecules (i.e. uHPLC coupled to triple-quadrupole MS). Progress in targeted proteomics of circulating insulin-like growth factor 1 (IGF-I) have provided valuable insights about tryptic peptides, transitions, internal...
Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell
The datasets presented in this article are related to the research articles entitled “Neutrophil Extracellular Traps in Ulcerative Colitis: A Proteome Analysis of Intestinal Biopsies” (Bennike et al., 2015 ), and “Proteome Analysis of Rheumatoid Arthritis Gut Mucosa” (Bennike et al., 2017 )...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....
Hasan, I.A.; Mohamed, N.E.; El-Sayed, E.A.; Younis, N.A.
In this study, the nutritional value of single cell protein (SCP) was evaluated as a non conventional protein source produced by fermenting fungal local strains of Trichoderma longibrachiatum, Aspergillus niger, Aspergillus terreus and Penicillium funiculosum with alkali treated sugar cane bagasse. Amino acid analysis revealed that the produced SCP contains essential and non essential amino acids. Male mice were fed on normal (basal) diet which contains 18% conventional protein and served as control group. In the second (T1) and the third (T2) group, the animals were fed on a diet in which 15% and 30% of conventional protein source were replaced by SCP, respectively. At intervals of 15, 30, 45 and 60 days, mice were sacrificed and the blood samples were collected for the biochemical evaluation. The daily averages of body weight were significantly higher with group T2 than group T1. Where as, the kidney weights in groups (T1) and (T2) were significantly increased as compared with control. A non significant difference between the tested groups in the enzyme activities of AST, ALT and GSH content of liver tissue were recorded. While, cholesterol and triglycerides contents showed a significant decrease in both (T1) and (T2) groups as compared with control. The recorded values of the serum hormone (T4), ALP activities, albumin and A/G ratio did not changed by the previous treatments. Serum levels of total protein, urea, creatinine and uric acid were higher for groups (T1) and (T2) than the control group. In conclusion, partial substitution of soy bean protein in mice diet with single cell protein (15%) improved the mice growth without any adverse effects on some of the physiological functions tested
Full Text Available The emerging single-cell RNA-Seq (scRNA-Seq technology holds the promise to revolutionize our understanding of diseases and associated biological processes at an unprecedented resolution. It opens the door to reveal the intercellular heterogeneity and has been employed to a variety of applications, ranging from characterizing cancer cells subpopulations to elucidating tumor resistance mechanisms. Parallel to improving experimental protocols to deal with technological issues, deriving new analytical methods to reveal the complexity in scRNA-Seq data is just as challenging. Here we review the current state-of-the-art bioinformatics tools and methods for scRNA-Seq analysis, as well as addressing some critical analytical challenges that the field faces.
Single cell genomics is increasingly utilized as a powerful tool to decipher the metabolic potential, evolutionary histories and in situ interactions of environmental microorganisms. This transformative technology recovers extensive information from cultivation-unbiased samples of individual, unicellular organisms. Thus, it does not require data binning into arbitrary phylogenetic or functional groups and therefore is highly compatible with agent-based modeling approaches. I will present several technological advances in this field, which significantly improve genomic data recovery from individual cells and provide direct linkages between cell's genomic and phenotypic properties. I will also demonstrate how these new technical capabilities help understanding the metabolic potential and viral infections of the "microbial dark matter" inhabiting aquatic and subsurface environments.
Schwämmle, Veit; León, Ileana R.; Jensen, Ole Nørregaard
Large-scale quantitative analyses of biological systems are often performed with few replicate experiments, leading to multiple nonidentical data sets due to missing values. For example, mass spectrometry driven proteomics experiments are frequently performed with few biological or technical...... replicates due to sample-scarcity or due to duty-cycle or sensitivity constraints, or limited capacity of the available instrumentation, leading to incomplete results where detection of significant feature changes becomes a challenge. This problem is further exacerbated for the detection of significant...... as a novel and optimal way to detect significantly changing features in these data sets. This approach is suitable for large quantitative data sets from stable isotope labeling and mass spectrometry experiments and should be applicable to large data sets of any type. An R script that implements the improved...
Braun, M.; Limbach, C.
Single-celled systems are favourable cell types for studying several aspects of gravisensing and gravitropic responses. Whether and how actin is involved in both processes in higher plant statocytes is still a matter of intensive debate. In single-celled and tip-growing characean rhizoids and protonemata, however, there is clear evidence that actin is a central keyplayer controlling polarized growth and the mechanisms of gravity sensing and growth reorientation. Both cell types exhibit a unique actin polymerization in the extending tip, strictly colocalized with the prominent ER-aggregate in the center of the Spitzenkoerper. The local accumulation of ADF and profilin in this central array suggest that actin polymerization is controlled by these actin-binding proteins, which can be regulated by calcium, pH and a variety of other parameters. Distinct actin filaments extend even into the outermost tip and form a dense meshwork in the apical and subapical region, before they become bundled by villin to form two populations of thick actin cables that generate rotational cytoplasmic streaming in the basal region. Actomyosin not only mediates the delivery of secretory vesicles to the growing tip and controls the incorporation pattern of cell wall material, but also coordinates the tip-focused distribution pattern of calcium channels in the apical membrane. They establish the tip-high calcium gradient, a prerequisite for exocytosis. Microgravity experiments have added much to our understanding that both cell types use an efficient actomyosin-based system to control and correct the position of their statoliths and to direct sedimenting statoliths to confined graviperception sites at the plasma membrane. Actin's involvement in the graviresponses is more indirect. The upward growth of negatively gravitropic protonemata was shown to be preceded by a statolith-induced relocalization the Ca2+-calcium gradient to the upper flank that does not occur in positively gravitropic
Bendixen, Emøke; Danielsen, Marianne; Hollung, Kristin
In agricultural sciences as in all other areas of life science, the implementation of proteomics and other post-genomic tools is an important step towards more detailed understanding of the complex biological systems that control physiology and pathology of living beings. Farm animals are raised...... and cattle are relevant not only for farm animal sciences, but also for adding to our understanding of complex biological mechanisms of health and disease in humans. The aim of this review is to present an overview of the specific topics of interest within farm animal proteomics, and to highlight some...... of the areas where synergy between classic model organism proteomics and farm animal proteomics is rapidly emerging. Focus will be on introducing the special biological traits that play an important role in food production, and on how proteomics may help optimize farm animal production...
The knowledge of the intracellular distribution of biological relevant metals is important to understand their mechanisms of action in cells, either for physiological, toxicological or pathological processes. However, the direct detection of trace metals in single cells is a challenging task that requires sophisticated analytical developments. The combination of micro-PIXE with RBS and STIM (Scanning Transmission Ion Microscopy) allows the quantitative determination of trace metal content within sub-cellular compartments. The application of STIM analysis provides high spatial resolution imaging (< 200 nm) and excellent mass sensitivity (< 0.1 ng). Application of the STIM-PIXE-RBS methodology is absolutely needed when organic mass loss appears during PIXE-RBS irradiation. This combination of STIM-PIXE-RBS provides fully quantitative determination of trace element content, expressed in μg/g, which is a quite unique capability for micro-PIXE compared to other micro-analytical methods such as the electron and synchrotron x-ray fluorescence. Examples of micro-PIXE studies for sub-cellular imaging of trace elements in various fields of interest will be presented: in patho-physiology of trace elements involved in neurodegenerative diseases such as Parkinson's disease, and in toxicology of metals such as cobalt. (author)
Mishio, M.; Magai, J.
As the hydrolysis of mandarin orange peel with macerating enzyme (40 degrees C, 24 h) produced 0.59 g g-1 reducing sugar per dry peel compared to 0.36 by acid-hydrolysis (15 min at 120 degrees C with 0.8 N H2S04), the production of single cell protein (SCP) from orange peel was studied mostly using enzymatically hydrolyzed orange peel. When the enzymatically hydrolyzed peel media were used, the utilization efficiency of reducing sugars (%) and the growth yield from reducing sugars (g g-1) were: 63 and 0.51 for Saccharomyces cerevisiae; 56 and 0.48 for Candida utilis; 74 and 0.69 for Debaryomyces hansenii and 64 and 0.70 for Rhodotorula glutinis. SCP production from orange peel by D. hansenii and R. glutinis were further studied. Batch cultures for 24 h at 30 degrees C using 100g dried orange peel produced 45 g of dried cultivated peel (protein content, 33%) with D. hansenii and 34 g (protein content, 50%) with R. glutinis, and 38 g (protein content, 44%) with a mixture of both yeasts. (Refs. 12).
Full Text Available Crocins, the glucosides of crocetin, are present at high concentrations in saffron stigmas and accumulate in the vacuole. However, the biogenesis of the saffron chromoplast, the changes during the development of the stigma and the transport of crocins to the vacuole, are processes that remain poorly understood. We studied the process of chromoplast differentiation in saffron throughout stigma development by means of transmission electron microscopy. Our results provided an overview of a massive transport of crocins to the vacuole in the later developmental stages, when electron dense drops of a much greater size than plastoglobules (here defined “crocinoplast” were observed in the chromoplast, connected to the vacuole with a subsequent transfer of these large globules inside the vacuole. A proteome analysis of chromoplasts from saffron stigma allowed the identification of several well-known plastid proteins and new candidates involved in crocetin metabolism. Furthermore, expressions throughout five developmental stages of candidate genes responsible for carotenoid and apocarotenoid biogenesis, crocins transport to the vacuole and starch metabolism were analyzed. Correlation matrices and networks were exploited to identify a series of transcripts highly associated to crocetin (such as 1-Deoxy-d-xylulose 5-phosphate synthase (DXS, 1-Deoxy-d-xylulose 5-phosphate reductoisomerase (DXR, carotenoid isomerase (CRTISO, Crocetin glucosyltransferase 2 (UGT2, etc. and crocin (e.g., ζ-carotene desaturase (ZDS and plastid-lipid-associated proteins (PLAP2 accumulation; in addition, candidate aldehyde dehydrogenase (ADH genes were highlighted.
Gómez-Gómez, Lourdes; Parra-Vega, Verónica; Rivas-Sendra, Alba; Seguí-Simarro, Jose M.; Molina, Rosa Victoria; Pallotti, Claudia; Rubio-Moraga, Ángela; Diretto, Gianfranco; Prieto, Alicia; Ahrazem, Oussama
Crocins, the glucosides of crocetin, are present at high concentrations in saffron stigmas and accumulate in the vacuole. However, the biogenesis of the saffron chromoplast, the changes during the development of the stigma and the transport of crocins to the vacuole, are processes that remain poorly understood. We studied the process of chromoplast differentiation in saffron throughout stigma development by means of transmission electron microscopy. Our results provided an overview of a massive transport of crocins to the vacuole in the later developmental stages, when electron dense drops of a much greater size than plastoglobules (here defined “crocinoplast”) were observed in the chromoplast, connected to the vacuole with a subsequent transfer of these large globules inside the vacuole. A proteome analysis of chromoplasts from saffron stigma allowed the identification of several well-known plastid proteins and new candidates involved in crocetin metabolism. Furthermore, expressions throughout five developmental stages of candidate genes responsible for carotenoid and apocarotenoid biogenesis, crocins transport to the vacuole and starch metabolism were analyzed. Correlation matrices and networks were exploited to identify a series of transcripts highly associated to crocetin (such as 1-Deoxy-d-xylulose 5-phosphate synthase (DXS), 1-Deoxy-d-xylulose 5-phosphate reductoisomerase (DXR), carotenoid isomerase (CRTISO), Crocetin glucosyltransferase 2 (UGT2), etc.) and crocin (e.g., ζ-carotene desaturase (ZDS) and plastid-lipid-associated proteins (PLAP2)) accumulation; in addition, candidate aldehyde dehydrogenase (ADH) genes were highlighted. PMID:28045431
Bogdanov, Evgeny; Dominova, Irina; Shusharina, Natalia; Botman, Stepan; Kasymov, Vitaliy; Patrushev, Maksim
A limited amount of DNA extracted from single cells, and the development of single cell diagnostics make it necessary to create a new highly effective method for the single cells nucleic acids isolation. In this paper, we propose the DNA isolation method from biomaterials with limited DNA quantity in sample, and from samples with degradable DNA based on the use of solid-phase adsorbent silicon dioxide nanofilm deposited on the inner surface of PCR tube. PMID:23874571
How to use and integrate bioinformatics tools to compare proteomic data from distinct conditions? A tutorial using the pathological similarities between Aortic Valve Stenosis and Coronary Artery Disease as a case-study.
Trindade, Fábio; Ferreira, Rita; Magalhães, Beatriz; Leite-Moreira, Adelino; Falcão-Pires, Inês; Vitorino, Rui
Nowadays we are surrounded by a plethora of bioinformatics tools, powerful enough to deal with the large amounts of data arising from proteomic studies, but whose application is sometimes hard to find. Therefore, we used a specific clinical problem - to discriminate pathophysiology and potential biomarkers between two similar cardiovascular diseases, aortic valve stenosis (AVS) and coronary artery disease (CAD) - to make a step-by-step guide through four bioinformatics tools: STRING, DisGeNET, Cytoscape and ClueGO. Proteome data was collected from articles available on PubMed centered on proteomic studies enrolling subjects with AVS or CAD. Through the analysis of gene ontology provided by STRING and ClueGO we could find specific biological phenomena associated with AVS, such as down-regulation of elastic fiber assembly, and with CAD, such as up-regulation of plasminogen activation. Moreover, through Cytoscape and DisGeNET we could pinpoint surrogate markers either for AVS (e.g. popeye domain containing protein 2 and 28S ribosomal protein S36, mitochondrial) or for CAD (e.g. ankyrin repeat and SOCS box protein 7) which deserve future validation. Data recycling and integration as well as research orientation are among the main advantages of resorting to bioinformatics analysis, hence these tutorials can be of great convenience for proteomics investigators. As we saw for aortic valve stenosis and coronary artery disease, it can be of great relevance to perform preliminary bioinformatics analysis with already published proteomics data. It not only saves us time in the lab (avoiding work duplication) as it points out new hypothesis to explain the phenotypical presentation of the diseases as well as new surrogate markers with clinical relevance, deserving future scrutiny. These essential steps can be easily overcome if one follows the steps proposed in our tutorial for STRING, DisGeNET, Cytoscape and ClueGO utilization. Copyright © 2017 Elsevier B.V. All rights
Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell
patients (Morgan et al., 2012; Abraham and Medzhitov, 2011; Bennike, 2014) [8–10. Therefore, we characterized the proteome of colon mucosa biopsies from 10 inflammatory bowel disease ulcerative colitis (UC) patients, 11 gastrointestinal healthy rheumatoid arthritis (RA) patients, and 10 controls. We...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....
Malorni, A.; Facchiano, A.
We have developed new bioinformatic tools and strategies, aimed to the identification and characterization of proteins as markers of pathological states, for the analysis of data derived from protein expression profiles obtained by mass spectrometry techniques, for the study of structural and functional properties of the proteins, and for the analysis of data from omics approaches
Zrazhevskiy, Pavel S.
preparation and specimen labeling, requiring no advanced technical skills and being directly applicable for a wide range of molecular profiling studies. Utilization of quantum dot platform for single-cell molecular profiling promises to greatly benefit both biomedical research and clinical diagnostics by providing a tool for addressing phenotypic heterogeneity within large cell populations, opening access to studying low-abundance events often masked or completely erased by batch processing, and elucidating biomarker signatures of diseases critical for accurate diagnostics and targeted therapy.
Charles F A de Bourcy
Full Text Available Single-cell sequencing is emerging as an important tool for studies of genomic heterogeneity. Whole genome amplification (WGA is a key step in single-cell sequencing workflows and a multitude of methods have been introduced. Here, we compare three state-of-the-art methods on both bulk and single-cell samples of E. coli DNA: Multiple Displacement Amplification (MDA, Multiple Annealing and Looping Based Amplification Cycles (MALBAC, and the PicoPLEX single-cell WGA kit (NEB-WGA. We considered the effects of reaction gain on coverage uniformity, error rates and the level of background contamination. We compared the suitability of the different WGA methods for the detection of copy-number variations, for the detection of single-nucleotide polymorphisms and for de-novo genome assembly. No single method performed best across all criteria and significant differences in characteristics were observed; the choice of which amplifier to use will depend strongly on the details of the type of question being asked in any given experiment.
Gomis-Rüth, Susana; Stiess, Michael; Wierenga, Corette J; Meyn, Liane; Bradke, Frank
An understanding of the molecular mechanisms of axon regeneration after injury is key for the development of potential therapies. Single-cell axotomy of dissociated neurons enables the study of the intrinsic regenerative capacities of injured axons. This protocol describes how to perform single-cell axotomy on dissociated hippocampal neurons containing synapses. Furthermore, to axotomize hippocampal neurons integrated in neuronal circuits, we describe how to set up coculture with a few fluorescently labeled neurons. This approach allows axotomy of single cells in a complex neuronal network and the observation of morphological and molecular changes during axon regeneration. Thus, single-cell axotomy of mature neurons is a valuable tool for gaining insights into cell intrinsic axon regeneration and the plasticity of neuronal polarity of mature neurons. Dissociation of the hippocampus and plating of hippocampal neurons takes ∼2 h. Neurons are then left to grow for 2 weeks, during which time they integrate into neuronal circuits. Subsequent axotomy takes 10 min per neuron and further imaging takes 10 min per neuron.
Full Text Available Recent years have seen significant progress in understanding basic bacterial cell cycle properties such as cell growth and cell division. While characterization and regulation of bacterial cell cycle is quite well documented in the case of fast growing aerobic model organisms, no data has been so far reported for anaerobic bacteria. This lack of information in anaerobic microorganisms can mainly be explained by the absence of molecular and cellular tools such as single cell microscopy and fluorescent probes usable for anaerobes and essential to study cellular events and/or subcellular localization of the actors involved in cell cycle.In this study, single-cell microscopy has been adapted to study for the first time, in real time, the cell cycle of a bacterial anaerobe, Desulfovibrio vulgaris Hildenborough (DvH. This single-cell analysis provides mechanistic insights into the cell division cycle of DvH, which seems to be governed by the recently discussed so-called incremental model that generates remarkably homogeneous cell sizes. Furthermore, cell division was reversibly blocked during oxygen exposure. This may constitute a strategy for anaerobic cells to cope with transient exposure to oxygen that they may encounter in their natural environment, thereby contributing to their aerotolerance. This study lays the foundation for the first molecular, single-cell assay that will address factors that cannot otherwise be resolved in bulk assays and that will allow visualization of a wide range of molecular mechanisms within living anaerobic cells.
Weis-Garcia, Frances; Bandura, Dmitry; Baranov, Vladimir; Ornatsky, Olga; Tanner, Scott
Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is a distinct flavor of mass spectrometry that has had little association with cell biology: it remains the state of the art for the determination of the atomic composition of materials. Unrelatedly, flow cytometry is the superior method for distinguishing the heterogeneity of cells through the determination of antigen signatures using tagged antibodies. Simply replacing fluorophore tags with stable isotopes of the heavy metals, and measuring these cell-by-cell with ICP-MS, dramatically increases the number of probes that can be simultaneously measured in cytometry and enables a transformative increase in the resolution of rare cell populations in complex biological samples. While this can be thought of as a novel incarnation of single-cell targeted proteomics, the metal-labeling reagents, ICP-MS of single cells, and accompanying informatics comprise a new field of technology termed Mass Cytometry. While the conception of mass cytometry is simple the embodiment to address the issues of multi-parameter flow cytometry has been far more challenging. There are many elements, and many more stable isotopes of those elements, that might be used as distinct reporter tags. Still, there are many approaches to conjugating metals to antibodies (or other affinity reagents) and work in this area along with developing new applications is ongoing. The mass resolution and linear (quantitative) dynamic range of ICP-MS allows those many stable isotopes to be measured simultaneously and without the spectral overlap issues that limit fluorescence assay. However, the adaptation of ICP-MS to allow high-speed simultaneous measurement with single cell distinction at high throughput required innovation of the cell introduction system, ion optics (sampling, transmission and beam-shaping), mass analysis, and signal handling and processing. An overview of “the nuts and bolts” of Mass Cytometry is presented.
Matthiesen, Rune; Jensen, Ole N
The systematic study of proteins and protein networks, that is, proteomics, calls for qualitative and quantitative analysis of proteins and peptides. Mass spectrometry (MS) is a key analytical technology in current proteomics and modern mass spectrometers generate large amounts of high-quality data...... that in turn allow protein identification, annotation of secondary modifications, and determination of the absolute or relative abundance of individual proteins. Advances in mass spectrometry-driven proteomics rely on robust bioinformatics tools that enable large-scale data analysis. This chapter describes...... some of the basic concepts and current approaches to the analysis of MS and MS/MS data in proteomics....
Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John
Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.
Liang, Shao-Bo; Fu, Li-Wu
In this review, we have outlined the application of single-cell technology in cancer research. Single-cell technology has made encouraging progress in recent years and now provides the means to detect rare cancer cells such as circulating tumor cells and cancer stem cells. We reveal how this technology has advanced the analysis of intratumor heterogeneity and tumor epigenetics, and guided individualized treatment strategies. The future prospects now are to bring single-cell technology into the clinical arena. We believe that the clinical application of single-cell technology will be beneficial in cancer diagnostics and treatment, and ultimately improve survival in cancer patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Marine Sponges (Porifera) are known to harbor enormous amounts of microorganisms with members belonging to at least 30 different bacterial phyla including several candidate phyla and both archaeal lineages. Here, we applied single cell genomics to the mic
Zeng, Guanghong; Müller, Torsten; Meyer, Rikke Louise
be considered. We have developed a simple and versatile method to make single-cell bacterial probes for measuring single cell adhesion by force spectroscopy using atomic force microscopy (AFM). A single-cell probe was readily made by picking up a bacterial cell from a glass surface by approaching a tipless AFM...... cantilever coated with the commercial cell adhesive CellTakTM. We applied the method to study adhesion of living cells to abiotic surfaces at the single-cell level. Immobilisation of single bacterial cells to the cantilever was stable for several hours, and viability was confirmed by Live/Dead staining...... on the adhesion force, we explored the bond formation and adhesive strength of four different bacterial strains towards three abiotic substrates with variable hydrophobicity and surface roughness. The adhesion force and final rupture length were dependent on bacterial strains, surfaces properties, and time...
Caprio, Di; Stokes, Chris; Higgins, John M.; Schonbrun, Ethan
Oxygen is transported throughout the body by hemoglobin in red blood cells. While the oxygen affinity of blood is well understood and is routinely assessed in patients by pulse oximetry, variability at the single-cell level has not been previously measured. In contrast, single-cell measurements of red blood cell volume and hemoglobin concentration are taken millions of times per day by clinical hematology analyzers and are important factors in determining the health of the hematologic system....
Satwik Rajaram; Louise E. Heinrich; John D. Gordan; Jayant Avva; Kathy M. Bonness; Agnieszka K. Witkiewicz; James S. Malter; Chloe E. Atreya; Robert S. Warren; Lani F. Wu; Steven J. Altschuler
Advances in single-cell technologies have highlighted the prevalence and biological significance of cellular heterogeneity. A critical question is how to design experiments that faithfully capture the true range of heterogeneity from samples of cellular populations. Here, we develop a data-driven approach, illustrated in the context of image data, that estimates the sampling depth required for prospective investigations of single-cell heterogeneity from an existing collection of samples. ...
Ghodasara, P; Sadowski, P; Satake, N; Kopp, S; Mills, P C
Over the last two decades, technological advancements in the field of proteomics have advanced our understanding of the complex biological systems of living organisms. Techniques based on mass spectrometry (MS) have emerged as powerful tools to contextualise existing genomic information and to create quantitative protein profiles from plasma, tissues or cell lines of various species. Proteomic approaches have been used increasingly in veterinary science to investigate biological processes responsible for growth, reproduction and pathological events. However, the adoption of proteomic approaches by veterinary investigators lags behind that of researchers in the human medical field. Furthermore, in contrast to human proteomics studies, interpretation of veterinary proteomic data is difficult due to the limited protein databases available for many animal species. This review article examines the current use of advanced proteomics techniques for evaluation of animal health and welfare and covers the current status of clinical veterinary proteomics research, including successful protein identification and data interpretation studies. It includes a description of an emerging tool, sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS), available on selected mass spectrometry instruments. This newly developed data acquisition technique combines advantages of discovery and targeted proteomics approaches, and thus has the potential to advance the veterinary proteomics field by enhancing identification and reproducibility of proteomics data. Copyright © 2017 Elsevier Ltd. All rights reserved.
Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H
Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European
Sun, Zhe; Wang, Ting; Deng, Ke; Wang, Xiao-Feng; Lafyatis, Robert; Ding, Ying; Hu, Ming; Chen, Wei
Single cell transcriptome sequencing (scRNA-Seq) has become a revolutionary tool to study cellular and molecular processes at single cell resolution. Among existing technologies, the recently developed droplet-based platform enables efficient parallel processing of thousands of single cells with direct counting of transcript copies using Unique Molecular Identifier (UMI). Despite the technology advances, statistical methods and computational tools are still lacking for analyzing droplet-based scRNA-Seq data. Particularly, model-based approaches for clustering large-scale single cell transcriptomic data are still under-explored. We developed DIMM-SC, a Dirichlet Mixture Model for clustering droplet-based Single Cell transcriptomic data. This approach explicitly models UMI count data from scRNA-Seq experiments and characterizes variations across different cell clusters via a Dirichlet mixture prior. We performed comprehensive simulations to evaluate DIMM-SC and compared it with existing clustering methods such as K-means, CellTree and Seurat. In addition, we analyzed public scRNA-Seq datasets with known cluster labels and in-house scRNA-Seq datasets from a study of systemic sclerosis with prior biological knowledge to benchmark and validate DIMM-SC. Both simulation studies and real data applications demonstrated that overall, DIMM-SC achieves substantially improved clustering accuracy and much lower clustering variability compared to other existing clustering methods. More importantly, as a model-based approach, DIMM-SC is able to quantify the clustering uncertainty for each single cell, facilitating rigorous statistical inference and biological interpretations, which are typically unavailable from existing clustering methods. DIMM-SC has been implemented in a user-friendly R package with a detailed tutorial available on www.pitt.edu/∼wec47/singlecell.html. email@example.com or firstname.lastname@example.org. Supplementary data are available at Bioinformatics online. © The Author
Wu, Kui; Jia, Feifei; Zheng, Wei; Luo, Qun; Zhao, Yao; Wang, Fuyi
Secondary ion mass spectrometry, including nanoscale secondary ion mass spectrometry (NanoSIMS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), has emerged as a powerful tool for biological imaging, especially for single cell imaging. SIMS imaging can provide information on subcellular distribution of endogenous and exogenous chemicals, including metallodrugs, from membrane through to cytoplasm and nucleus without labeling, and with high spatial resolution and chemical specificity. In this mini-review, we summarize recent progress in the field of SIMS imaging, particularly in the characterization of the subcellular distribution of metallodrugs. We anticipate that the SIMS imaging method will be widely applied to visualize subcellular distributions of drugs and drug candidates in single cells, exerting significant influence on early drug evaluation and metabolism in medicinal and pharmaceutical chemistry. Recent progress of SIMS applications in characterizing the subcellular distributions of metallodrugs was summarized.
Di Caprio, Giuseppe; Stokes, Chris; Higgins, John M; Schonbrun, Ethan
Oxygen is transported throughout the body by hemoglobin (Hb) in red blood cells (RBCs). Although the oxygen affinity of blood is well-understood and routinely assessed in patients by pulse oximetry, variability at the single-cell level has not been previously measured. In contrast, single-cell measurements of RBC volume and Hb concentration are taken millions of times per day by clinical hematology analyzers, and they are important factors in determining the health of the hematologic system. To better understand the variability and determinants of oxygen affinity on a cellular level, we have developed a system that quantifies the oxygen saturation, cell volume, and Hb concentration for individual RBCs in high throughput. We find that the variability in single-cell saturation peaks at an oxygen partial pressure of 2.9%, which corresponds to the maximum slope of the oxygen-Hb dissociation curve. In addition, single-cell oxygen affinity is positively correlated with Hb concentration but independent of osmolarity, which suggests variation in the Hb to 2,3-diphosphoglycerate (2-3 DPG) ratio on a cellular level. By quantifying the functional behavior of a cellular population, our system adds a dimension to blood cell analysis and other measurements of single-cell variability.
The Cancer Research Technology Program (CRTP) develops and implements emerging technology, cancer biology expertise and research capabilities to accomplish NCI research objectives. The CRTP is an outward-facing, multi-disciplinary hub purposed to enable the external cancer research community and provides dedicated support to NCI’s intramural Center for Cancer Research (CCR). The dedicated units provide electron microscopy, protein characterization, protein expression, optical microscopy and nextGen sequencing. These research efforts are an integral part of CCR at the Frederick National Laboratory for Cancer Research (FNLCR). CRTP scientists also work collaboratively with intramural NCI investigators to provide research technologies and expertise. KEY ROLES AND RESPONSIBILITIES We are seeking a highly motivated Scientist II to join the newly established Single Cell Analysis Facility (SCAF) of the Center for Cancer Research (CCR) at NCI. The SCAF will house state of the art single cell sequencing technologies including 10xGenomics Chromium, BD Genomics Rhapsody, DEPPArray, and other emerging single cell technologies. The Scientist: Will interact with close to 200 laboratories within the CCR to design and carry out single cell experiments for cancer research Will work on single cell isolation/preparation from various tissues and cells and related NexGen sequencing library preparation Is expected to author publications in peer reviewed scientific journals
Full Text Available Significant advances have been made in methods to analyze genomes and transcriptomes of single cells, but to fully define cell states, proteins must also be accessed as central actors defining a cell’s phenotype. Methods currently used to analyze endogenous protein expression in single cells are limited in specificity, throughput, or multiplex capability. Here, we present an approach to simultaneously and specifically interrogate large sets of protein and RNA targets in lysates from individual cells, enabling investigations of cell functions and responses. We applied our method to investigate the effects of BMP4, an experimental therapeutic agent, on early-passage glioblastoma cell cultures. We uncovered significant heterogeneity in responses to treatment at levels of RNA and protein, with a subset of cells reacting in a distinct manner to BMP4. Moreover, we found overall poor correlation between protein and RNA at the level of single cells, with proteins more accurately defining responses to treatment.
Proserpio, Valentina; Mahata, Bidesh
The immune system is composed of a variety of cells that act in a coordinated fashion to protect the organism against a multitude of different pathogens. The great variability of existing pathogens corresponds to a similar high heterogeneity of the immune cells. The study of individual immune cells, the fundamental unit of immunity, has recently transformed from a qualitative microscopic imaging to a nearly complete quantitative transcriptomic analysis. This shift has been driven by the rapid development of multiple single-cell technologies. These new advances are expected to boost the detection of less frequent cell types and transient or intermediate cell states. They will highlight the individuality of each single cell and greatly expand the resolution of current available classifications and differentiation trajectories. In this review we discuss the recent advancement and application of single-cell technologies, their limitations and future applications to study the immune system. © 2015 The Authors. Immunology Published by John Wiley & Sons Ltd.
Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv
Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.
Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv
Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923
Mitra, A K; Mukherjee, U K; Harding, T; Jang, J S; Stessman, H; Li, Y; Abyzov, A; Jen, J; Kumar, S; Rajkumar, V; Van Ness, B
Multiple myeloma (MM) is characterized by significant genetic diversity at subclonal levels that have a defining role in the heterogeneity of tumor progression, clinical aggressiveness and drug sensitivity. Although genome profiling studies have demonstrated heterogeneity in subclonal architecture that may ultimately lead to relapse, a gene expression-based prediction program that can identify, distinguish and quantify drug response in sub-populations within a bulk population of myeloma cells is lacking. In this study, we performed targeted transcriptome analysis on 528 pre-treatment single cells from 11 myeloma cell lines and 418 single cells from 8 drug-naïve MM patients, followed by intensive bioinformatics and statistical analysis for prediction of proteasome inhibitor sensitivity in individual cells. Using our previously reported drug response gene expression profile signature at the single-cell level, we developed an R Statistical analysis package available at https://github.com/bvnlabSCATTome, SCATTome (single-cell analysis of targeted transcriptome), that restructures the data obtained from Fluidigm single-cell quantitative real-time-PCR analysis run, filters missing data, performs scaling of filtered data, builds classification models and predicts drug response of individual cells based on targeted transcriptome using an assortment of machine learning methods. Application of SCATT should contribute to clinically relevant analysis of intratumor heterogeneity, and better inform drug choices based on subclonal cellular responses.
Diaz-de-Quijano, Daniel; Palacios, Pilar; Hornák, Karel; Felip, Marisol
The ELF or fluorescence-labeled enzyme activity (FLEA) technique is a culture-independent single-cell tool for assessing plankton enzyme activity in close-to-in situ conditions. We demonstrate that single-cell FLEA quantifications based on two-dimensional (2D) image analysis were biased by up to one order of magnitude relative to deconvolved 3D. This was basically attributed to out-of-focus light, and partially to object size. Nevertheless, if sufficient cells were measured (25-40 cells), bia...
Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee
de Bruin, Jeroen S.; Deelder, André M.; Palmblad, Magnus
Data processing in proteomics can be a challenging endeavor, requiring extensive knowledge of many different software packages, all with different algorithms, data format requirements, and user interfaces. In this article we describe the integration of a number of existing programs and tools in Taverna Workbench, a scientific workflow manager currently being developed in the bioinformatics community. We demonstrate how a workflow manager provides a single, visually clear and intuitive interface to complex data analysis tasks in proteomics, from raw mass spectrometry data to protein identifications and beyond. PMID:22411703
Bagre, M.; Jain, V.; Yedle, A.; Maurya, T.; Yadav, A.; Puntambekar, A.; Goswami, S.G.; Choudhary, R.S.; Sandha, S.; Dwivedi, J.; Kane, G.V.; Mahawar, A.; Mohania, P.; Shrivastava, P.; Sharma, S.; Gupta, R.; Sharma, S.D.; Joshi, S.C.; Mistri, K.K.; Prakash, P.N.
Raja Ramanna Centre for Advanced Technology has initiated the work on development of Superconducting Radio Frequency (SCRF) cavities and associated technologies as part of R and D activities for upcoming Spallation Neutron Source (SNS) project involving superconducting Linear Accelerator (LINAC). It is planned to use 650 MHz SCRF cavities for the medium and high energy section of the proposed LINAC. Under Indian Institution Fermilab Collaboration (IIFC), Raja Ramanna Centre for Advanced Technology is also working on development of 650 MHz (β=0.9) SCRF cavities proposed to be used in the high energy section of Project-X at FNAL. The work has been initiated with design and development of 650 MHz single cell SCRF cavity. FE analysis was done to estimate change in frequency with temperature as well as to estimate the frequency of the cavity at different cavity manufacturing stages. The development cycle comprises of design and manufacturing of forming tooling, machining, welding and RF measurement fixtures as well as design for manufacturing. The half-cell and beam tubes forming and machining of all parts were done using in-house facilities. The Electron beam welding was carried out at Inter-University Accelerator Centre (IUAC), New Delhi under a MoU. One 650 MHz single cell SCRF cavity has been recently manufactured. In this paper we present the development efforts on manufacturing and pre-qualification of 650 MHz (β=0.9) single cell SCRF cavity. (author)
Fox, Zachary [School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States); Neuert, Gregor [Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee 37232 (United States); Department of Pharmacology, School of Medicine, Vanderbilt University, Nashville, Tennessee 37232 (United States); Department of Biomedical Engineering, Vanderbilt University School of Engineering, Nashville, Tennessee 37232 (United States); Munsky, Brian [School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States); Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States)
Emerging techniques now allow for precise quantification of distributions of biological molecules in single cells. These rapidly advancing experimental methods have created a need for more rigorous and efficient modeling tools. Here, we derive new bounds on the likelihood that observations of single-cell, single-molecule responses come from a discrete stochastic model, posed in the form of the chemical master equation. These strict upper and lower bounds are based on a finite state projection approach, and they converge monotonically to the exact likelihood value. These bounds allow one to discriminate rigorously between models and with a minimum level of computational effort. In practice, these bounds can be incorporated into stochastic model identification and parameter inference routines, which improve the accuracy and efficiency of endeavors to analyze and predict single-cell behavior. We demonstrate the applicability of our approach using simulated data for three example models as well as for experimental measurements of a time-varying stochastic transcriptional response in yeast.
Full Text Available Cellular heterogeneity plays a pivotal role in a variety of functional processes in vivo including carcinogenesis. However, our knowledge about cell-to-cell diversity and how differences in individual cells manifest in alterations at the population level remains very limited mainly due to the lack of appropriate tools enabling studies at the single-cell level. We present a study on changes in cellular heterogeneity in the context of pre-malignant progression in response to hypoxic stress. Utilizing pre-malignant progression of Barrett's esophagus (BE as a disease model system we studied molecular mechanisms underlying the progression from metaplastic to dysplastic (pre-cancerous stage. We used newly developed methods enabling measurements of cell-to-cell differences in copy numbers of mitochondrial DNA, expression levels of a set of mitochondrial and nuclear genes involved in hypoxia response pathways, and mitochondrial membrane potential. In contrast to bulk cell studies reported earlier, our study shows significant differences between metaplastic and dysplastic BE cells in both average values and single-cell parameter distributions of mtDNA copy numbers, mitochondrial function, and mRNA expression levels of studied genes. Based on single-cell data analysis, we propose that mitochondria may be one of the key factors in pre-malignant progression in BE.
Gong, Haibiao; Do, Devin; Ramakrishnan, Ramesh
Single-cell mRNA-seq is a valuable tool to dissect expression profiles and to understand the regulatory network of genes. Microfluidics is well suited for single-cell analysis owing both to the small volume of the reaction chambers and easiness of automation. Here we describe the workflow of single-cell mRNA-seq using C1 IFC, which can isolate and process up to 96 cells. Both on-chip procedure (lysis, reverse transcription, and preamplification PCR) and off-chip sequencing library preparation protocols are described. The workflow generates full-length mRNA information, which is more valuable compared to 3' end counting method for many applications.
The utilization of food waste into products like single cell protein is an alternative solution to global protein shortage and to alleviate pollution problems. This investigation was carried out with food wastes such as orange, pineapple, banana, watermelon and cucumber waste as growth media for A. niger using standard ...
customary food and feed sources of protein (agriculnrre and fishery) to ocher sources like single cell protein (SCP); whose production from hydrocarbons is one ... origin is unicellular or simple multicellular organism such as bacteria, yeasts, fungi, algae. protozoa, mid even bacterinphagcs generally cultivated on substrates ...
Miao, Jun; Li, Xiaolian; Cui, Liwang
Malaria parasite cloning is traditionally carried out mainly by using the limiting dilution method, which is laborious, imprecise, and unable to distinguish multiply-infected RBCs. In this study, we used a parasite engineered to express green fluorescent protein (GFP) to evaluate a single-cell sorting method for rapidly cloning Plasmodium falciparum. By dividing a two-dimensional scattergram from a cell sorter into 17 gates, we determined the parameters for isolating singly-infected erythrocytes and sorted them into individual cultures. Pre-gating of the engineered parasites for GFP allowed the isolation of almost 100% GFP-positive clones. Compared with the limiting dilution method, the number of parasite clones obtained by single-cell sorting was much higher. Molecular analyses showed that parasite isolates obtained by single-cell sorting were highly homogenous. This highly efficient single-cell sorting method should prove very useful for cloning both P. falciparum laboratory populations from genetic manipulation experiments and clinical samples. Copyright 2010 Elsevier Inc. All rights reserved.
Porubský, David; Sanders, Ashley D; van Wietmarschen, Niek; Falconer, Ester; Hills, Mark; Spierings, Diana C J; Bevova, Marianna R; Guryev, Victor; Lansdorp, Peter Michael
Haplotypes are fundamental to fully characterize the diploid genome of an individual, yet methods to directly chart the unique genetic makeup of each parental chromosome are lacking. Here we introduce single-cell DNA template strand sequencing (Strand-seq) as a novel approach to phasing diploid
origin is unicellular or simple multicellular organism such as bacteria, yeasts, fungi, ... Pilot plant produe1io11 of single cell proteins now take place in several centre.ii in ... animal feed but little or no information has been documented as per its ...
Thomas, P.; Straube, A.V.; Timmer, J.; Fleck, C.; Grima, R.
A class of theoretical models seeks to explain rhythmic single cell data by postulating that they are generated by intrinsic noise in biochemical systems whose deterministic models exhibit only damped oscillations. The main features of such noise-induced oscillations are quantified by the power
A single-cell cavity, made of copper, with tapered connectors for impedance measurements. It was used as a model of LEP-type superconducting cavities, to investigate impedance and higher-order modes and operated at around 600 MHz (the LEP acceleration frequency was 352.2 MHz). See 8202500.
Ghita, Mihaela; Fernandez-Palomo, Cristian; Fukunaga, Hisanori
Purpose: This review follows the development of microbeam technology from the early days of single cell irradiations, to investigations of specific cellular mechanisms and to the development of new treatment modalities in vivo. A number of microbeam applications are discussed with a focus on prec...... to deliver radiotherapy using plane parallel microbeams, in Microbeam Radiotherapy (MRT)....
Robert, Lydia; Ollion, Jean; Robert, Jerome; Song, Xiaohu; Matic, Ivan; Elez, Marina
Mutations have been investigated for more than a century but remain difficult to observe directly in single cells, which limits the characterization of their dynamics and fitness effects. By combining microfluidics, time-lapse imaging, and a fluorescent tag of the mismatch repair system in Escherichia coli , we visualized the emergence of mutations in single cells, revealing Poissonian dynamics. Concomitantly, we tracked the growth and life span of single cells, accumulating ~20,000 mutations genome-wide over hundreds of generations. This analysis revealed that 1% of mutations were lethal; nonlethal mutations displayed a heavy-tailed distribution of fitness effects and were dominated by quasi-neutral mutations with an average cost of 0.3%. Our approach has enabled the investigation of single-cell individuality in mutation rate, mutation fitness costs, and mutation interactions. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Full Text Available Microfluidic cell-based arraying technology is widely used in the field of single-cell analysis. However, among developed devices, there is a compromise between cellular loading efficiencies and trapped cell densities, which deserves further analysis and optimization. To address this issue, the cell trapping efficiency of a microfluidic device with two parallel micro channels interconnected with cellular trapping sites was studied in this paper. By regulating channel inlet and outlet status, the microfluidic trapping structure can mimic key functioning units of previously reported devices. Numerical simulations were used to model this cellular trapping structure, quantifying the effects of channel on/off status and trapping structure geometries on the cellular trapping efficiency. Furthermore, the microfluidic device was fabricated based on conventional microfabrication and the cellular trapping efficiency was quantified in experiments. Experimental results showed that, besides geometry parameters, cellular travelling velocities and sizes also affected the single-cell trapping efficiency. By fine tuning parameters, more than 95% of trapping sites were taken by individual cells. This study may lay foundation in further studies of single-cell positioning in microfluidics and push forward the study of single-cell analysis.
Miao, Jun; Li, Xiaolian; Cui, Liwang
Malaria parasite cloning is traditionally carried out mainly by using the limiting dilution method, which is laborious, imprecise, and unable to distinguish multiply-infected RBCs. In this study, we used a parasite engineered to express green fluorescent protein (GFP) to evaluate a single-cell sorting method for rapidly cloning Plasmodium falciparum. By dividing a two dimensional scattergram from a cell sorter into 17 gates, we determined the parameters for isolating singly-infected erythrocytes and sorted them into individual cultures. Pre-gating of the engineered parasites for GFP allowed the isolation of almost 100% GFP-positive clones. Compared with the limiting dilution method, the number of parasite clones obtained by single-cell sorting was much higher. Molecular analyses showed that parasite isolates obtained by single-cell sorting were highly homogenous. This highly efficient single-cell sorting method should prove very useful for cloning both P. falciparum laboratory populations from genetic manipulation experiments and clinical samples. PMID:20435038
This thesis describes the development and use of a novel technology for single-cell fate mapping, called cellular barcoding. With this technology, unique and heritable genetic tags (barcodes) are introduced into naïve T cells. Using cellular barcoding, we investigated I) how different
An investigation was carried out on the possibility of replacing fishmeal with graded levels of yeast single cell protein (SCP; 10, 20, 30, 40 and 50%) in isonitrogenous feed formulations (30% protein) in the diet of Oreochromis niloticus fingerlings for a period of 12 weeks. The control diet had fishmeal as the primary protein ...
Bæk, Kristoffer Torbjørn; Svenningsen, Sine Lo; Eisen, Harvey
We have examined expression of the ¿cI operon in single cells via a rexgfp substitution. Although average fluorescence agreed with expectations for expression of ¿-repressor, fluorescence fluctuated greatly from cell-to-cell. Fluctuations in repressor concentration are not predicted by previous m...
When the frequency of appearance of apoptotic cells following was observed over a period of time, there was a significant increase in appearance of apoptosis when using single cell gel electrophoresis assay. The present report demonstrates that the characteristic pattern of apoptotic comets detected by the comet assay ...
van den Bos, Hilda; Bakker, Bjorn; Spierings, Diana C J; Lansdorp, Peter M; Foijer, Floris
The use of single-cell DNA sequencing (sc-seq) techniques for the diagnosis, prognosis and treatment of cancer is a rapidly developing field. Sc-seq research is gaining momentum by decreased sequencing costs and continuous improvements in techniques. In this review, we provide an overview of recent
Irish, Jonathan M; Doxie, Deon B
Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.
Mancuso, Francesco; Bunkenborg, Jakob; Wierer, Michael
In shot-gun proteomics raw tandem MS data are processed with extraction tools to produce condensed peak lists that can be uploaded to database search engines. Many extraction tools are available but to our knowledge, a systematic comparison of such tools has not yet been carried out. Using raw data...
Szoko, Nicholas; McShane, Adam J; Natowicz, Marvin R
Proteomics, the large-scale study of protein expression in cells and tissues, is a powerful tool to study the biology of clinical conditions and has provided significant insights in many experimental systems. Herein, we review the basics of proteomic methodology and discuss challenges in using proteomic approaches to study autism. Unlike other experimental approaches, such as genomic approaches, there have been few large-scale studies of proteins in tissues from persons with autism. Most of the proteomic studies on autism used blood or other peripheral tissues; few studies used brain tissue. Some studies found dysregulation of aspects of the immune system or of aspects of lipid metabolism, but no consistent findings were noted. Based on the challenges in using proteomics to study autism, we discuss considerations for future studies. Apart from the complex technical considerations implicit in any proteomic analysis, key nontechnical matters include attention to subject and specimen inclusion/exclusion criteria, having adequate sample size to ensure appropriate powering of the study, attention to the state of specimens prior to proteomic analysis, and the use of a replicate set of specimens, when possible. We conclude by discussing some potentially productive uses of proteomics, potentially coupled with other approaches, for future autism research including: (1) proteomic analysis of banked human brain specimens; (2) proteomic analysis of tissues from animal models of autism; and (3) proteomic analysis of induced pluripotent stem cells that are differentiated into various types of brain cells and neural organoids. Autism Res 2017, 10: 1460-1469. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.
Rødkær, Steven Vestergaard; Færgeman, Nils J.; Andersen, Jens S.
that are involved in this positive outcome. Based on that, processes like autophagy, lipid turnover and the generation/clearance of reactive oxygen species (ROS) have all been describe to affect life span, either alone, or in a not fully characterized interplay. The baker’s yeast Saccharomyces cerevisae is by now...... the organism with the best characterized proteome and is therefore the organism of choice in many proteomic studies. Additionally, this single-celled organism exhibits many conserved proteins and pathways of higher animals, thus observations in the yeast might reveal important information applying to other...
Vanhove, Anne-Catherine; Vermaelen, Wesley; Panis, Bart; Swennen, Rony; Carpentier, Sebastien C
There is a great need for research aimed at understanding drought tolerance, screening for drought tolerant varieties and breeding crops with an improved water use efficiency. Bananas and plantains are a major staple food and export product with a worldwide production of over 135 million tonnes per year. Water however is the most limiting abiotic factor in banana production. A screening of the Musa biodiversity has not yet been performed. We at KU Leuven host the Musa International Germplasm collection with over 1200 accessions. To screen the Musa biodiversity for drought tolerant varieties, we developed a screening test for in vitro plants. Five varieties representing different genomic constitutions in banana (AAAh, AAA, AAB, AABp, and ABB) were selected and subjected to a mild osmotic stress. The ABB variety showed the smallest stress induced growth reduction. To get an insight into the acclimation and the accomplishment of homeostasis, the leaf proteome of this variety was characterized via 2D DIGE. After extraction of the leaf proteome of six control and six stressed plants, 2600 spots could be distinguished. A PCA analysis indicates that control and stressed plants can blindly be classified based on their proteome. One hundred and twelve proteins were significantly more abundant in the stressed plants and 18 proteins were significantly more abundant in control plants (FDR α 0.05). Twenty four differential proteins could be identified. The proteome analysis clearly shows that there is a new balance in the stressed plants and that the respiration, metabolism of ROS and several dehydrogenases involved in NAD/NADH homeostasis play an important role.
Full Text Available Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.
Dolgashev, Valery A; Higo, Toshiyasu; Nantista, Christopher D; Tantawi, Sami G
Operating accelerating gradient in normal conducting accelerating structures is often limited by rf breakdown. The limit depends on multiple parameters, including input rf power, rf circuit, cavity shape and material. Experimental and theoretical study of the effects of these parameters on the breakdown limit in full scale structures is difficult and costly. We use 11.4 GHz single-cell traveling wave and standing wave accelerating structures for experiments and modeling of rf breakdown behavior. These test structures are designed so that the electromagnetic fields in one cell mimic the fields in prototype multicell structures for the X-band linear collider. Fields elsewhere in the test structures are significantly lower than that of the single cell. The setup uses matched mode converters that launch the circular TM01 mode into short test structures. The test structures are connected to the mode launchers with vacuum rf flanges. This setup allows economic testing of different cell geometries, cell materials an...
This book highlights the current state of the art in single cell analysis, an area that involves many fields of science – from clinical hematology, functional analysis and drug screening, to platelet and microparticle analysis, marine biology and fundamental cancer research. This book brings together an eclectic group of current applications, all of which have a significant impact on our current state of knowledge. The authors of these chapters are all pioneering researchers in the field of single cell analysis. The book will not only appeal to those readers more focused on clinical applications, but also those interested in highly technical aspects of the technologies. All of the technologies identified utilize unique applications of photon detection systems.
A simple technique of micro-agarose gel electrophoresis has been developed to quantify DNA damage in individual cells. Cells are embedded in agarose gel on microscope slides, lysed by detergents and then electrophoresed for a short time under neutral or alkaline condition. In irradiated cells, DNA migrates from the nucleus toward the anode, displaying commet-like pattern by staining with DNA-specific fluorescence dye. DNA damage is evaluated by measuring the distance of DNA migration. The technique was applied for measuring DNA damage in single cells exposed to 60 Co γ-rays, or to KUR radiation in the presence or absence of 10 B-enriched boric acid. The enhanced production of double-stranded DNA breaks by 10 B(n,α) 7 Li reaction was demonstrated here. The significant increase in the length of DNA migration was observed in single cells exposed to such a low dose as 20 cGy after alkaline micro electrophoresis. (author)
Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader
Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular p...
Moignard, Victoria Rachel; Göttgens, Berthold
Many assumptions about the way cells behave are based on analyses of populations. However, it is now widely recognized that even apparently pure populations can display a remarkable level of heterogeneity. This is particularly true in stem cell biology where it hinders our understanding of normal development and the development of strategies for regenerative medicine. Over the past decade technologies facilitating gene expression analysis at the single cell level have become widespread, provi...
Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R
Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.
Single cell profiling was performed to assess differences in RNA accumulation in neighboring hyphae of the fungus Aspergillus niger. A protocol was developed to isolate and amplify RNA from single hyphae or parts thereof. Microarray analysis resulted in a present call for 4 to 7% of the A. niger genes, of which 12% showed heterogeneous RNA levels. These genes belonged to a wide range of gene categories. PMID:21816052
Glenn, D R; Lee, K; Park, H; Weissleder, R; Yacoby, A; Lukin, M D; Lee, H; Walsworth, R L; Connolly, C B
We apply a quantum diamond microscope for detection and imaging of immunomagnetically labeled cells. This instrument uses nitrogen-vacancy (NV) centers in diamond for correlated magnetic and fluorescence imaging. Our device provides single-cell resolution and a field of view (∼1 mm(2)) two orders of magnitude larger than that of previous NV imaging technologies, enabling practical applications. To illustrate, we quantified cancer biomarkers expressed by rare tumor cells in a large population of healthy cells.
Darmanis, Spyros; Gallant, Caroline Julie; Marinescu, Voichita Dana; Niklasson, Mia; Segerman, Anna; Flamourakis, Georgios; Fredriksson, Simon; Assarsson, Erika; Lundberg, Martin; Nelander, Sven; Westermark, Bengt; Landegren, Ulf
Significant advances have been made in methods to analyze genomes and transcriptomes of single cells, but to fully define cell states, proteins must also be accessed as central actors defining a cell's phenotype. Methods currently used to analyze endogenous protein expression in single cells are limited in specificity, throughput, or multiplex capability. Here, we present an approach to simultaneously and specifically interrogate large sets of protein and RNA targets in lysates from individual cells, enabling investigations of cell functions and responses. We applied our method to investigate the effects of BMP4, an experimental therapeutic agent, on early-passage glioblastoma cell cultures. We uncovered significant heterogeneity in responses to treatment at levels of RNA and protein, with a subset of cells reacting in a distinct manner to BMP4. Moreover, we found overall poor correlation between protein and RNA at the level of single cells, with proteins more accurately defining responses to treatment. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Eustaquio, Trisha; Leary, James F
Properly evaluating the nanotoxicity of nanoparticles involves much more than bulk-cell assays of cell death by necrosis. Cells exposed to nanoparticles may undergo repairable oxidative stress and DNA damage or be induced into apoptosis. Exposure to nanoparticles may cause the cells to alter their proliferation or differentiation or their cell-cell signaling with neighboring cells in a tissue. Nanoparticles are usually more toxic to some cell subpopulations than others, and toxicity often varies with cell cycle. All of these facts dictate that any nanotoxicity assay must be at the single-cell level and must try whenever feasible and reasonable to include many of these other factors. Focusing on one type of quantitative measure of nanotoxicity, we describe flow and scanning image cytometry approaches to measuring nanotoxicity at the single-cell level by using a commonly used assay for distinguishing between necrotic and apoptotic causes of cell death by one type of nanoparticle. Flow cytometry is fast and quantitative, provided that the cells can be prepared into a single-cell suspension for analysis. But when cells cannot be put into suspension without altering nanotoxicity results, or if morphology, attachment, and stain location are important, a scanning image cytometry approach must be used. Both methods are described with application to a particular type of nanoparticle, a superparamagnetic iron oxide nanoparticle (SPION), as an example of how these assays may be applied to the more general problem of determining the effects of nanomaterial exposure to living cells.
Ciobanu, Doina; Clum, Alicia; Singh, Vasanth; Salamov, Asaf; Han, James; Copeland, Alex; Grigoriev, Igor; James, Timothy; Singer, Steven; Woyke, Tanja; Malmstrom, Rex; Cheng, Jan-Fang
Despite their small size, unicellular eukaryotes have complex genomes with a high degree of plasticity that allow them to adapt quickly to environmental changes. Unicellular eukaryotes live with prokaryotes and higher eukaryotes, frequently in symbiotic or parasitic niches. To this day their contribution to the dynamics of the environmental communities remains to be understood. Unfortunately, the vast majority of eukaryotic microorganisms are either uncultured or unculturable, making genome sequencing impossible using traditional approaches. We have developed an approach to isolate unicellular eukaryotes of interest from environmental samples, and to sequence and analyze their genomes and transcriptomes. We have tested our methods with six species: an uncharacterized protist from cellulose-enriched compost identified as Platyophrya, a close relative of P. vorax; the fungus Metschnikowia bicuspidate, a parasite of water flea Daphnia; the mycoparasitic fungi Piptocephalis cylindrospora, a parasite of Cokeromyces and Mucor; Caulochytrium protosteloides, a parasite of Sordaria; Rozella allomycis, a parasite of the water mold Allomyces; and the microalgae Chlamydomonas reinhardtii. Here, we present the four components of our approach: pre-sequencing methods, sequence analysis for single cell genome assembly, sequence analysis of single cell transcriptomes, and genome annotation. This technology has the potential to uncover the complexity of single cell eukaryotes and their role in the environmental samples.
Preimplantation genetic diagnosis (PGD) aims to help couples with heritable genetic disorders to avoid the birth of diseased offspring or the recurrence of loss of conception. Following in vitro fertilization, one or a few cells are biopsied from each human preimplantation embryo for genetic testing, allowing diagnosis and selection of healthy embryos for uterine transfer. Although classical methods, including single-cell PCR and fluorescent in situ hybridization, enable PGD for many genetic disorders, they have limitations. They often require family-specific designs and can be labor intensive, resulting in long waiting lists. Furthermore, certain types of genetic anomalies are not easy to diagnose using these classical approaches, and healthy offspring carrying the parental mutant allele(s) can result. Recently, state-of-the-art methods for single-cell genomics have flourished, which may overcome the limitations associated with classical PGD, and these underpin the development of generic assays for PGD that enable selection of embryos not only for the familial genetic disorder in question, but also for various other genetic aberrations and traits at once. Here, we discuss the latest single-cell genomics methodologies based on DNA microarrays, single-nucleotide polymorphism arrays or next-generation sequence analysis. We focus on their strengths, their validation status, their weaknesses and the challenges for implementing them in PGD. PMID:23998893
Pouyan, Maziyar Baran; Nourani, Mehrdad
Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.
Jafarpour, Farshid; Wright, Charles S.; Gudjonson, Herman; Riebling, Jedidiah; Dawson, Emma; Lo, Klevin; Fiebig, Aretha; Crosson, Sean; Dinner, Aaron R.; Iyer-Biswas, Srividya
How are granular details of stochastic growth and division of individual cells reflected in smooth deterministic growth of population numbers? We provide an integrated, multiscale perspective of microbial growth dynamics by formulating a data-validated theoretical framework that accounts for observables at both single-cell and population scales. We derive exact analytical complete time-dependent solutions to cell-age distributions and population growth rates as functionals of the underlying interdivision time distributions, for symmetric and asymmetric cell division. These results provide insights into the surprising implications of stochastic single-cell dynamics for population growth. Using our results for asymmetric division, we deduce the time to transition from the reproductively quiescent (swarmer) to the replication-competent (stalked) stage of the Caulobacter crescentus life cycle. Remarkably, population numbers can spontaneously oscillate with time. We elucidate the physics leading to these population oscillations. For C. crescentus cells, we show that a simple measurement of the population growth rate, for a given growth condition, is sufficient to characterize the condition-specific cellular unit of time and, thus, yields the mean (single-cell) growth and division timescales, fluctuations in cell division times, the cell-age distribution, and the quiescence timescale.
Background In recent years, high throughput and non-invasive Raman spectrometry technique has matured as an effective approach to identification of individual cells by species, even in complex, mixed populations. Raman profiling is an appealing optical microscopic method to achieve this. To fully utilize Raman proling for single-cell analysis, an extensive understanding of Raman spectra is necessary to answer questions such as which filtering methodologies are effective for pre-processing of Raman spectra, what strains can be distinguished by Raman spectra, and what features serve best as Raman-based biomarkers for single-cells, etc. Results In this work, we have proposed an approach called rDisc to discretize the original Raman spectrum into only a few (usually less than 20) representative peaks (Raman shifts). The approach has advantages in removing noises, and condensing the original spectrum. In particular, effective signal processing procedures were designed to eliminate noise, utilising wavelet transform denoising, baseline correction, and signal normalization. In the discretizing process, representative peaks were selected to signicantly decrease the Raman data size. More importantly, the selected peaks are chosen as suitable to serve as key biological markers to differentiate species and other cellular features. Additionally, the classication performance of discretized spectra was found to be comparable to full spectrum having more than 1000 Raman shifts. Overall, the discretized spectrum needs about 5storage space of a full spectrum and the processing speed is considerably faster. This makes rDisc clearly superior to other methods for single-cell classication.
It was the intention of this research to measure the affinity of antibody secreted by a single cell, and to describe the spectrum of affinities displayed in response to antigenic stimulation. The single cell secreting specific antibody was isolated by means of the hemolytic plaque assay. The amount of antibody secreted by the cell was to be measured through the use of a solid phase radioimmunoassay. The affinity of the antibody would be estimated by comparing the diameter of the plaque, and the amount of antibody secreted, with a mathematical theory of the formation of a plaque in agar. As a test system, a solid phase radioimmunoassay was developed for human serum albumin using antibody coupled to Sephadex. A sensitivity of 1 nanogram was attained with this assay. A solid phase radioimmunoassay for mouse immunoglobulin M was developed, using antibody coupled to Sepharose. The sensitivity attained with this assay was only on the order of 10 micrograms. The mouse immunoglobulin M radioimmunoassay was not sensitive enough to measure the amount of antibody secreted by a single cell. From a theoretical equation, the relationship between antibody affinity, plaque diameter and antibody secretion rate was calculated for the experimental conditions used in this research. By assuming a constant antibody secretion rate, an effective binding constant for the antibody was estimated from the average plaque diameters. This effective binding constant was observed to increase during the immune response
Full Text Available Abstract Background Lung cancer diagnosis in tissue material with commonly used histological techniques is sometimes inconvenient and in a number of cases leads to ambiguous conclusions. Frequently advanced immunostaining techniques have to be employed, yet they are both time consuming and limited. In this study a proteomic approach is presented which may help provide unambiguous pathologic diagnosis of tissue material. Methods Lung tissue material found to be pathologically changed was prepared to isolate proteome with fast and non selective procedure. Isolated peptides and proteins in ranging from 3.5 to 20 kDa were analysed directly using high resolution mass spectrometer (MALDI-TOF/TOF with sinapic acid as a matrix. Recorded complex spectra of a single run were then analyzed with multivariate statistical analysis algorithms (principle component analysis, classification methods. In the applied protocol we focused on obtaining the spectra richest in protein signals constituting a pattern of change within the sample containing detailed information about its protein composition. Advanced statistical methods were to indicate differences between examined groups. Results Obtained results indicate changes in proteome profiles of changed tissues in comparison to physiologically unchanged material (control group which were reflected in the result of principle component analysis (PCA. Points representing spectra of control group were located in different areas of multidimensional space and were less diffused in comparison to cancer tissues. Three different classification algorithms showed recognition capability of 100% regarding classification of examined material into an appropriate group. Conclusion The application of the presented protocol and method enabled finding pathological changes in tissue material regardless of localization and size of abnormalities in the sample volume. Proteomic profile as a complex, rich in signals spectrum of proteins
Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong
Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.
Maglica, Željka; Özdemir, Emre; McKinney, John D
ATP is a key molecule of cell physiology, but despite its importance, there are currently no methods for monitoring single-cell ATP fluctuations in live bacteria. This is a major obstacle in studies of bacterial energy metabolism, because there is a growing awareness that bacteria respond to stressors such as antibiotics in a highly individualistic manner. Here, we present a method for long-term single-cell tracking of ATP levels in Mycobacterium smegmatis based on a combination of microfluidics, time-lapse microscopy, and Förster resonance energy transfer (FRET)-based ATP biosensors. Upon treating cells with antibiotics, we observed that individual cells undergo an abrupt and irreversible switch from high to low intracellular ATP levels. The kinetics and extent of ATP switching clearly discriminate between an inhibitor of ATP synthesis and other classes of antibiotics. Cells that resume growth after 24 h of antibiotic treatment maintain high ATP levels throughout the exposure period. In contrast, antibiotic-treated cells that switch from ATP-high to ATP-low states never resume growth after antibiotic washout. Surprisingly, only a subset of these nongrowing ATP-low cells stains with propidium iodide (PI), a widely used live/dead cell marker. These experiments also reveal a cryptic subset of cells that do not resume growth after antibiotic washout despite remaining ATP high and PI negative. We conclude that ATP tracking is a more dynamic, sensitive, reliable, and discriminating marker of cell viability than staining with PI. This method could be used in studies to evaluate antimicrobial effectiveness and mechanism of action, as well as for high-throughput screening. New antimicrobials are urgently needed to stem the rising tide of antibiotic-resistant bacteria. All antibiotics are expected to affect bacterial energy metabolism, directly or indirectly, yet tools to assess the impact of antibiotics on the ATP content of individual bacterial cells are lacking. The
Albrethsen, Jakob; Goetze, Jens P; Johnsen, Anders H
Proteomics of secretory granules is an emerging strategy for identifying secreted proteins, including potentially novel candidate biomarkers and peptide hormones. In addition, proteomics can provide information about the abundance, localization and structure (post-translational modification) of g...
Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.
Full Text Available Whole genome amplification (WGA is essential for obtaining genome sequences from single bacterial cells because the quantity of template DNA contained in a single cell is very low. Multiple displacement amplification (MDA, using Phi29 DNA polymerase and random primers, is the most widely used method for single-cell WGA. However, single-cell MDA usually results in uneven genome coverage because of amplification bias, background amplification of contaminating DNA, and formation of chimeras by linking of non-contiguous chromosomal regions. Here, we present a novel MDA method, termed droplet MDA, that minimizes amplification bias and amplification of contaminants by using picoliter-sized droplets for compartmentalized WGA reactions. Extracted DNA fragments from a lysed cell in MDA mixture are divided into 105 droplets (67 pL within minutes via flow through simple microfluidic channels. Compartmentalized genome fragments can be individually amplified in these droplets without the risk of encounter with reagent-borne or environmental contaminants. Following quality assessment of WGA products from single Escherichia coli cells, we showed that droplet MDA minimized unexpected amplification and improved the percentage of genome recovery from 59% to 89%. Our results demonstrate that microfluidic-generated droplets show potential as an efficient tool for effective amplification of low-input DNA for single-cell genomics and greatly reduce the cost and labor investment required for determination of nearly complete genome sequences of uncultured bacteria from environmental samples.
Etzkorn, James R; Parviz, Babak A; Wu, Wen-Chung; Tian, Zhiyuan; Kim, Prince; Jang, Sei-Hum; Jen, Alex K-Y; Meldrum, Deirdre R
We present a method for self-assembling arrays of live single cells on a glass chip using a photopatternable polymer to form micro-traps. We have studied the single-cell self-assembly method and optimized the process to obtain a 52% yield of single-trapped cells. We also report a method to measure the oxygen consumption rate of a single cell using micro-patterned sensors. These molecular oxygen sensors were fabricated around each micro-trap allowing optical interrogation of oxygen concentration in the immediate environment of the trapped cell. Micromachined micro-wells were then used to seal the trap, sensor and cell in order to determine the oxygen consumption rate of single cells. These techniques reported here add to the collection of tools for performing 'singe-cell' biology. An oxygen consumption rate of 1.05 ± 0.28 fmol min −1 was found for a data set consisting of 25 single A549 cells.
Sprenger, Richard Remko; Roepstorff, Peter
Mass spectrometry has evolved into a crucial technology for the field of proteomics, enabling the comprehensive study of proteins in biological systems. Innovative developments have yielded flexible and versatile mass spectrometric tools, including quadrupole time-of-flight, linear ion trap......, Orbitrap and ion mobility instruments. Together they offer various and complementary capabilities in terms of ionization, sensitivity, speed, resolution, mass accuracy, dynamic range and methods of fragmentation. Mass spectrometers can acquire qualitative and quantitative information on a large scale...
Background Abundance and distribution of the plant hormone auxin play important roles in plant development. Besides other metabolic processes, various auxin carriers control the cellular level of active auxin and, hence, are major regulators of cellular auxin homeostasis. Despite the developmental importance of auxin transporters, a simple medium-to-high throughput approach to assess carrier activities is still missing. Here we show that carrier driven depletion of cellular auxin correlates with reduced nuclear auxin signaling in tobacco Bright Yellow-2 (BY-2) cell cultures. Results We developed an easy to use transient single-cell-based system to detect carrier activity. We use the relative changes in signaling output of the auxin responsive promoter element DR5 to indirectly visualize auxin carrier activity. The feasibility of the transient approach was demonstrated by pharmacological and genetic interference with auxin signaling and transport. As a proof of concept, we provide visual evidence that the prominent auxin transport proteins PIN-FORMED (PIN)2 and PIN5 regulate cellular auxin homeostasis at the plasma membrane and endoplasmic reticulum (ER), respectively. Our data suggest that PIN2 and PIN5 have different sensitivities to the auxin transport inhibitor 1-naphthylphthalamic acid (NPA). Also the putative PIN-LIKES (PILS) auxin carrier activity at the ER is insensitive to NPA in our system, indicating that NPA blocks intercellular, but not intracellular auxin transport. Conclusions This single-cell-based system is a useful tool by which the activity of putative auxin carriers, such as PINs, PILS and WALLS ARE THIN1 (WAT1), can be indirectly visualized in a medium-to-high throughput manner. Moreover, our single cell system might be useful to investigate also other hormonal signaling pathways, such as cytokinin. PMID:23379388
Gross, Benjamin J.; El-Naggar, Mohamed Y.
Metal-reducing bacteria gain energy by extracellular electron transfer to external solids, such as naturally abundant minerals, which substitute for oxygen or the other common soluble electron acceptors of respiration. This process is one of the earliest forms of respiration on earth and has significant environmental and technological implications. By performing electron transfer to electrodes instead of minerals, these microbes can be used as biocatalysts for conversion of diverse chemical fuels to electricity. Understanding such a complex biotic-abiotic interaction necessitates the development of tools capable of probing extracellular electron transfer down to the level of single cells. Here, we describe an experimental platform for single cell respiration measurements. The design integrates an infrared optical trap, perfusion chamber, and lithographically fabricated electrochemical chips containing potentiostatically controlled transparent indium tin oxide microelectrodes. Individual bacteria are manipulated using the optical trap and placed on the microelectrodes, which are biased at a suitable oxidizing potential in the absence of any chemical electron acceptor. The potentiostat is used to detect the respiration current correlated with cell-electrode contact. We demonstrate the system with single cell measurements of the dissimilatory-metal reducing bacterium Shewanella oneidensis MR-1, which resulted in respiration currents ranging from 15 fA to 100 fA per cell under our measurement conditions. Mutants lacking the outer-membrane cytochromes necessary for extracellular respiration did not result in any measurable current output upon contact. In addition to the application for extracellular electron transfer studies, the ability to electronically measure cell-specific respiration rates may provide answers for a variety of fundamental microbial physiology questions
Gross, Benjamin J; El-Naggar, Mohamed Y
Metal-reducing bacteria gain energy by extracellular electron transfer to external solids, such as naturally abundant minerals, which substitute for oxygen or the other common soluble electron acceptors of respiration. This process is one of the earliest forms of respiration on earth and has significant environmental and technological implications. By performing electron transfer to electrodes instead of minerals, these microbes can be used as biocatalysts for conversion of diverse chemical fuels to electricity. Understanding such a complex biotic-abiotic interaction necessitates the development of tools capable of probing extracellular electron transfer down to the level of single cells. Here, we describe an experimental platform for single cell respiration measurements. The design integrates an infrared optical trap, perfusion chamber, and lithographically fabricated electrochemical chips containing potentiostatically controlled transparent indium tin oxide microelectrodes. Individual bacteria are manipulated using the optical trap and placed on the microelectrodes, which are biased at a suitable oxidizing potential in the absence of any chemical electron acceptor. The potentiostat is used to detect the respiration current correlated with cell-electrode contact. We demonstrate the system with single cell measurements of the dissimilatory-metal reducing bacterium Shewanella oneidensis MR-1, which resulted in respiration currents ranging from 15 fA to 100 fA per cell under our measurement conditions. Mutants lacking the outer-membrane cytochromes necessary for extracellular respiration did not result in any measurable current output upon contact. In addition to the application for extracellular electron transfer studies, the ability to electronically measure cell-specific respiration rates may provide answers for a variety of fundamental microbial physiology questions.
Gross, Benjamin J. [Department of Physics and Astronomy, University of Southern California, 920 Bloom Walk, Los Angeles, California 90089-0484 (United States); El-Naggar, Mohamed Y., E-mail: email@example.com [Department of Physics and Astronomy, University of Southern California, 920 Bloom Walk, Los Angeles, California 90089-0484 (United States); Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, California 90089-0484 (United States); Department of Chemistry, University of Southern California, Los Angeles, California 90089-0484 (United States)
Metal-reducing bacteria gain energy by extracellular electron transfer to external solids, such as naturally abundant minerals, which substitute for oxygen or the other common soluble electron acceptors of respiration. This process is one of the earliest forms of respiration on earth and has significant environmental and technological implications. By performing electron transfer to electrodes instead of minerals, these microbes can be used as biocatalysts for conversion of diverse chemical fuels to electricity. Understanding such a complex biotic-abiotic interaction necessitates the development of tools capable of probing extracellular electron transfer down to the level of single cells. Here, we describe an experimental platform for single cell respiration measurements. The design integrates an infrared optical trap, perfusion chamber, and lithographically fabricated electrochemical chips containing potentiostatically controlled transparent indium tin oxide microelectrodes. Individual bacteria are manipulated using the optical trap and placed on the microelectrodes, which are biased at a suitable oxidizing potential in the absence of any chemical electron acceptor. The potentiostat is used to detect the respiration current correlated with cell-electrode contact. We demonstrate the system with single cell measurements of the dissimilatory-metal reducing bacterium Shewanella oneidensis MR-1, which resulted in respiration currents ranging from 15 fA to 100 fA per cell under our measurement conditions. Mutants lacking the outer-membrane cytochromes necessary for extracellular respiration did not result in any measurable current output upon contact. In addition to the application for extracellular electron transfer studies, the ability to electronically measure cell-specific respiration rates may provide answers for a variety of fundamental microbial physiology questions.
Perez-Riverol, Yasset; Alpi, Emanuele; Wang, Rui; Hermjakob, Henning; Vizcaíno, Juan Antonio
Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data. © 2014 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Thomas, Philipp; Straube, Arthur V; Timmer, Jens; Fleck, Christian; Grima, Ramon
A class of theoretical models seeks to explain rhythmic single cell data by postulating that they are generated by intrinsic noise in biochemical systems whose deterministic models exhibit only damped oscillations. The main features of such noise-induced oscillations are quantified by the power spectrum which measures the dependence of the oscillatory signal's power with frequency. In this paper we derive an approximate closed-form expression for the power spectrum of any monostable biochemical system close to a Hopf bifurcation, where noise-induced oscillations are most pronounced. Unlike the commonly used linear noise approximation which is valid in the macroscopic limit of large volumes, our theory is valid over a wide range of volumes and hence affords a more suitable description of single cell noise-induced oscillations. Our theory predicts that the spectra have three universal features: (i) a dominant peak at some frequency, (ii) a smaller peak at twice the frequency of the dominant peak and (iii) a peak at zero frequency. Of these, the linear noise approximation predicts only the first feature while the remaining two stem from the combination of intrinsic noise and nonlinearity in the law of mass action. The theoretical expressions are shown to accurately match the power spectra determined from stochastic simulations of mitotic and circadian oscillators. Furthermore it is shown how recently acquired single cell rhythmic fibroblast data displays all the features predicted by our theory and that the experimental spectrum is well described by our theory but not by the conventional linear noise approximation. © 2013 Elsevier Ltd. All rights reserved.
Full Text Available Cell adhesion is a fundamental phenomenon vital for all multicellular organisms. Recognition of and adhesion to specific macromolecules is a crucial task of leukocytes to initiate the immune response. To gain statistically reliable information of cell adhesion, large numbers of cells should be measured. However, direct measurement of the adhesion force of single cells is still challenging and today's techniques typically have an extremely low throughput (5-10 cells per day. Here, we introduce a computer controlled micropipette mounted onto a normal inverted microscope for probing single cell interactions with specific macromolecules. We calculated the estimated hydrodynamic lifting force acting on target cells by the numerical simulation of the flow at the micropipette tip. The adhesion force of surface attached cells could be accurately probed by repeating the pick-up process with increasing vacuum applied in the pipette positioned above the cell under investigation. Using the introduced methodology hundreds of cells adhered to specific macromolecules were measured one by one in a relatively short period of time (∼30 min. We blocked nonspecific cell adhesion by the protein non-adhesive PLL-g-PEG polymer. We found that human primary monocytes are less adherent to fibrinogen than their in vitro differentiated descendants: macrophages and dendritic cells, the latter producing the highest average adhesion force. Validation of the here introduced method was achieved by the hydrostatic step-pressure micropipette manipulation technique. Additionally the result was reinforced in standard microfluidic shear stress channels. Nevertheless, automated micropipette gave higher sensitivity and less side-effect than the shear stress channel. Using our technique, the probed single cells can be easily picked up and further investigated by other techniques; a definite advantage of the computer controlled micropipette. Our experiments revealed the existence of a
D'Arco, Annalisa; Ferrara, Maria Antonietta; Indolfi, Maurizio; Tufano, Vitaliano; Sirleto, Luigi
In this work, we present successfully realization of a nonlinear microscope, not purchasable in commerce, based on stimulated Raman scattering. It is obtained by the integration of a femtosecond SRS spectroscopic setup with an inverted research microscope equipped with a scanning unit. Taking account of strength of vibrational contrast of SRS, it provides label-free imaging of single cell analysis. Validation tests on images of polystyrene beads are reported to demonstrate the feasibility of the approach. In order to test the microscope on biological structures, we report and discuss the label-free images of lipid droplets inside fixed adipocyte cells.
Sakaki, Kelly; Foulds, Ian G.; Liu, William; Dechev, Nikolai; Burke, Robert Douglas; Park, Edward
Single cell research has the potential to revolutionize experimental methods in biomedical sciences and contribute to clinical practices. Recent studies suggest analysis of single cells reveals novel features of intracellular processes, cell-to-cell
Ok, Chi Young; Singh, Rajesh R; Salim, Alaa A
Tissues are heterogeneous in their components. If cells of interest are a minor population of collected tissue, it would be difficult to obtain genetic or genomic information of the interested cell population with conventional genomic DNA extraction from the collected tissue. Single-cell DNA analysis is important in the analysis of genetics of cell clonality, genetic anticipation, and single-cell DNA polymorphisms. Single-cell PCR using Single Cell Ampligrid/GeXP platform is described in this chapter.
Lando, David; Stevens, Tim J; Basu, Srinjan; Laue, Ernest D
Single-cell chromosome conformation capture approaches are revealing the extent of cell-to-cell variability in the organization and packaging of genomes. These single-cell methods, unlike their multi-cell counterparts, allow straightforward computation of realistic chromosome conformations that may be compared and combined with other, independent, techniques to study 3D structure. Here we discuss how single-cell Hi-C and subsequent 3D genome structure determination allows comparison with data from microscopy. We then carry out a systematic evaluation of recently published single-cell Hi-C datasets to establish a computational approach for the evaluation of single-cell Hi-C protocols. We show that the calculation of genome structures provides a useful tool for assessing the quality of single-cell Hi-C data because it requires a self-consistent network of interactions, relating to the underlying 3D conformation, with few errors, as well as sufficient longer-range cis- and trans-chromosomal contacts.
Ariza de Schellenberger A
Full Text Available Angela Ariza de Schellenberger,1 Harald Kratz,1 Tracy D Farr,2,3 Norbert Löwa,4 Ralf Hauptmann,1 Susanne Wagner,1 Matthias Taupitz,1 Jörg Schnorr,1 Eyk A Schellenberger1 1Department of Radiology, 2Department of Experimental Neurology, Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany; 3School of Life Sciences, University of Nottingham, Medical School, Nottingham, UK; 4Department of Biomagnetic Signals, Physikalisch-Technische Bundesanstalt Berlin, Berlin, Germany Abstract: Sensitive cell detection by magnetic resonance imaging (MRI is an important tool for the development of cell therapies. However, clinically approved contrast agents that allow single-cell detection are currently not available. Therefore, we compared very small iron oxide nanoparticles (VSOP and new multicore carboxymethyl dextran-coated iron oxide nanoparticles (multicore particles, MCP designed by our department for magnetic particle imaging (MPI with discontinued Resovist® regarding their suitability for detection of single mesenchymal stem cells (MSC by MRI. We achieved an average intracellular nanoparticle (NP load of >10 pg Fe per cell without the use of transfection agents. NP loading did not lead to significantly different results in proliferation, colony formation, and multilineage in vitro differentiation assays in comparison to controls. MRI allowed single-cell detection using VSOP, MCP, and Resovist® in conjunction with high-resolution T2*-weighted imaging at 7 T with postprocessing of phase images in agarose cell phantoms and in vivo after delivery of 2,000 NP-labeled MSC into mouse brains via the left carotid artery. With optimized labeling conditions, a detection rate of ~45% was achieved; however, the experiments were limited by nonhomogeneous NP loading of the MSC population. Attempts should be made to achieve better cell separation for homogeneous NP loading and to thus improve NP
Full Text Available With the completion of human genome project (HGP and the international HapMap project as well as rapid development of high-throughput biochip technology, whole genomic sequencing-targeted analysis of genomic structures has been primarily finished. Application of single cell for the analysis of the whole genomics is not only economical in material collection, but more importantly, the cell will be more purified, and the laboratory results will be more accurate and reliable. Therefore, exploration and analysis of hereditary information of single tumor cells has become the dream of all researchers in the field of basic research of tumors. At present, single-cell sequencing (SCS on malignancies has been widely used in the studies of pathogeneses of multiple malignancies, such as glioma, renal cancer and hematologic neoplasms, and in the studies of the metastatic mechanism of breast cancer by some researchers. This study mainly reviewed the SCS, the mechanisms and the methods of SCS in isolating tumor cells, and application of SCS technique in tumor-related basic research and clinical treatment.
Shah, Pratikkumar; Kaushik, Ajeet; Zhu, Xuena; Zhang, Chengxiao; Li, Chen-Zhong
Nanomaterials, because of their tunable properties and performances, have been utilized extensively in everyday life related consumable products and technology. On exposure, beyond the physiological range, nanomaterials cause health risks via affecting the function of organisms, genomic systems, and even the central nervous system. Thus, new analytical approaches for nanotoxicity assessment to verify the feasibility of nanomaterials for future use are in demand. The conventional analytical techniques, such as spectrophotometric assay-based techniques, usually require a lengthy and time-consuming process and often produce false positives, and often cannot be implemented at a single cell level measurement for studying cell behavior without interference from its surrounding environment. Hence, there is a demand for a precise, accurate, sensitive assessment for toxicity using single cells. Recently, due to the advantages of automation of fluids and minimization of human errors, the integration of a cell-on-a-chip (CoC) with a microfluidic system is in practice for nanotoxicity assessments. This review explains nanotoxicity and its assessment approaches with advantages/limitations and new approaches to overcome the confines of traditional techniques. Recent advances in nanotoxicity assessment using a CoC integrated with a microfluidic system are also discussed in this review, which may be of use for nanotoxicity assessment and diagnostics.
Goudeau, Danielle; Nath, Nandita; Ciobanu, Doina; Cheng, Jan-Fang; Malmstrom, Rex
Our approach to prokaryotic single-cell Whole Genome Amplification at the JGI continues to evolve. To increase both the quality and number of single-cell genomes produced, we explore all aspects of the process from cell sorting to sequencing. For example, we now utilize specialized reagents, acoustic liquid handling, and reduced reaction volumes eliminate non-target DNA contamination in WGA reactions. More specifically, we use a cleaner commercial WGA kit from Qiagen that employs a UV decontamination procedure initially developed at the JGI, and we use the Labcyte Echo for tip-less liquid transfer to set up 2uL reactions. Acoustic liquid handling also dramatically reduces reagent costs. In addition, we are exploring new cell lysis methods including treatment with Proteinase K, lysozyme, and other detergents, in order to complement standard alkaline lysis and allow for more efficient disruption of a wider range of cells. Incomplete lysis represents a major hurdle for WGA on some environmental samples, especially rhizosphere, peatland, and other soils. Finding effective lysis strategies that are also compatible with WGA is challenging, and we are currently assessing the impact of various strategies on genome recovery.
Stefan M Kallenberger
Full Text Available Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system.
Dolgashev, V.A.; Nantista, C.D.; Tantawi, S.G.; Higashi, Y.; Higo, T.
Operating accelerating gradient in normal conducting accelerating structures is often limited by rf breakdown. The limit depends on multiple parameters, including input rf power, rf circuit, cavity shape and material. Experimental and theoretical study of the effects of these parameters on the breakdown limit in full scale structures is difficult and costly. We use 11.4 GHz single-cell traveling wave and standing wave accelerating structures for experiments and modeling of rf breakdown behavior. These test structures are designed so that the electromagnetic fields in one cell mimic the fields in prototype multicell structures for the X-band linear collider. Fields elsewhere in the test structures are significantly lower than that of the single cell. The setup uses matched mode converters that launch the circular TM 01 mode into short test structures. The test structures are connected to the mode launchers with vacuum rf flanges. This setup allows economic testing of different cell geometries, cell materials and preparation techniques with short turn-around time. Simple 2D geometry of the test structures simplifies modeling of the breakdown currents and their thermal effects
Sullan, Ruby May A.; Beaussart, Audrey; Tripathi, Prachi; Derclaye, Sylvie; El-Kirat-Chatel, Sofiane; Li, James K.; Schneider, Yves-Jacques; Vanderleyden, Jos; Lebeer, Sarah; Dufrêne, Yves F.
Although bacterial pili are known to mediate cell adhesion to a variety of substrates, the molecular interactions behind this process are poorly understood. We report the direct measurement of the forces guiding pili-mediated adhesion, focusing on the medically important probiotic bacterium Lactobacillus rhamnosus GG (LGG). Using non-invasive single-cell force spectroscopy (SCFS), we quantify the adhesion forces between individual bacteria and biotic (mucin, intestinal cells) or abiotic (hydrophobic monolayers) surfaces. On hydrophobic surfaces, bacterial pili strengthen adhesion through remarkable nanospring properties, which - presumably - enable the bacteria to resist high shear forces under physiological conditions. On mucin, nanosprings are more frequent and adhesion forces larger, reflecting the influence of specific pili-mucin bonds. Interestingly, these mechanical responses are no longer observed on human intestinal Caco-2 cells. Rather, force curves exhibit constant force plateaus with extended ruptures reflecting the extraction of membrane nanotethers. These single-cell analyses provide novel insights into the molecular mechanisms by which piliated bacteria colonize surfaces (nanosprings, nanotethers), and offer exciting avenues in nanomedicine for understanding and controlling the adhesion of microbial cells (probiotics, pathogens).
Othon, Christina M; Ringeisen, Bradley R; Wu Xingjia; Anders, Juanita J
Biological laser printing (BioLP(TM)) is a unique tool capable of printing high resolution two- and three-dimensional patterns of living mammalian cells, with greater than 95% viability. These results have been extended to primary cultured olfactory ensheathing cells (OECs), harvested from adult Sprague-Dawley rats. OECs have been found to provide stimulating environments for neurite outgrowth in spinal cord injury models. BioLP is unique in that small load volumes (∼μLs) are required to achieve printing, enabling low numbers of OECs to be harvested, concentrated and printed. BioLP was used to form several 8 mm lines of OECs throughout a multilayer hydrogel scaffold. The line width was as low as 20 μm, with most lines comprising aligned single cells. Fluorescent confocal microscopy was used to determine the functionality of the printed OECs, to monitor interactions between printed OECs, and to determine the extent of cell migration throughout the 3D scaffold. High-resolution printing of low cell count, harvested OECs is an important advancement for in vitro study of cell interactions and functionality. In addition, these cell-printed scaffolds may provide an alternative for spinal cord repair studies, as the single-cell patterns formed here are on relevant size scales for neurite outgrowth
Full Text Available With the technological advances of mass spectrometry (MS-based platforms, clinical proteomics is one of the most rapidly growing areas in biomedical research. Urine proteomics has become a popular subdiscipline of clinical proteomics because it is an ideal source for the discovery of noninvasive disease biomarkers. The urine proteome offers a comprehensive view of the local and systemic physiology since the proteome is primarily composed of proteins/peptides from the kidneys and plasma. The emergence of MS-based proteomic platforms as prominent bioanalytical tools in clinical applications has enhanced the identification of protein-based urinary biomarkers. This review highlights the characteristics of urine that make it an attractive biofluid for biomarker discovery and the impact of MS-based technologies on the clinical assessment of urinary protein biomarkers.
Karr, T L
Proteomics is a relatively new scientific discipline that merges protein biochemistry, genome biology and bioinformatics to determine the spatial and temporal expression of proteins in cells, tissues and whole organisms. There has been very little application of proteomics to the fields of behavioral genetics, evolution, ecology and population dynamics, and has only recently been effectively applied to the closely allied fields of molecular evolution and genetics. However, there exists considerable potential for proteomics to impact in areas related to functional ecology; this review will introduce the general concepts and methodologies that define the field of proteomics and compare and contrast the advantages and disadvantages with other methods. Examples of how proteomics can aid, complement and indeed extend the study of functional ecology will be discussed including the main tool of ecological studies, population genetics with an emphasis on metapopulation structure analysis. Because proteomic analyses provide a direct measure of gene expression, it obviates some of the limitations associated with other genomic approaches, such as microarray and EST analyses. Likewise, in conjunction with associated bioinformatics and molecular evolutionary tools, proteomics can provide the foundation of a systems-level integration approach that can enhance ecological studies. It can be envisioned that proteomics will provide important new information on issues specific to metapopulation biology and adaptive processes in nature. A specific example of the application of proteomics to sperm ageing is provided to illustrate the potential utility of the approach.
Full Text Available Abstract Background Single-cell level studies are being used increasingly to measure cell properties not directly observable in a cell population. High-performance data acquisition systems for such studies have, by necessity, developed in synchrony. However, improvements in sample purification techniques are also required to reveal new phenomena. Here we assessed a cell sorter as a sample-pretreatment tool for a single-cell level assay. A cell sorter is routinely used for selecting one type of cells from a heterogeneous mixture of cells using specific fluorescence labels. In this case, we wanted to select cells of exactly the same size, shape, and cell-cycle stage from a population, without using a specific fluorescence label. Results We used four light scatter parameters: the peak height and area of the forward scatter (FSheight and FSarea and side scatter (SSheight and SSarea. The rat pheochromocytoma PC12 cell line, a neuronal cell line, was used for all experiments. The living cells concentrated in the high FSarea and middle SSheight/SSarea fractions. Single cells without cell clumps were concentrated in the low SS and middle FS fractions, and in the higher FSheight/FSarea and SSheight/SSarea fractions. The cell populations from these viable, single-cell-rich fractions were divided into twelve subfractions based on their FSarea-SSarea profiles, for more detailed analysis. We found that SSarea was proportional to the cell volume and the FSarea correlated with cell roundness and elongation, as well as with the level of DNA in the cell. To test the method and to characterize the basic properties of the isolated single cells, sorted cells were cultured in separate wells. The cells in all subfractions survived, proliferated and differentiated normally, suggesting that there was no serious damage. The smallest, roundest, and smoothest cells had the highest viability. There was no correlation between proliferation and differentiation. NGF increases
Full Text Available ABSTRACT The objective of the research was to evaluate nutritional values of microencapsulated diet made from single cell protein of microalgae. Complete randomized design was applied using three different types of microalgae for inclusion trials i.e. (A Nannochloropsis sp., (B Chlorella sp., and (C Spirulina sp. with five replications respectively. Microencapsulated diet was produced by a modification method based on thermal cross-linking with stable temperature. Phytoplankton was cultured in sea water for which fertilized by a modification of Walne and Guillard fertilizer. The results showed that the highest value of nutrition content was Spirulina sp. and the average composition of protein, crude lipid, carbohydrate, ash, nitrogen free extract, and water content was 34.80%, 0.30%, 18.53%, 20.09%, 26.29%, and 13.32%, respectively. Organoleptically, microcapsule showed that the color of capsule was dark green and smell fresh phytoplankton. Keywords: microcapsule, single-cell protein, thermal cross-linking, microalgae, phytoplankton ABSTRAK Tujuan penelitian adalah mengevaluasi kandungan nutrisi pakan mikrokapsul protein sel tunggal (single cell protein yang berasal dari berbagai jenis mikroalga (fitoplankton. Rancangan percobaan yang digunakan adalah rancangan acak lengkap, dengan perlakuan inklusi mikrokapsul dari jenis fitoplankton (A Nannochloropsis sp., (B Chlorella sp., dan (C Spirulina sp., masing-masing diulang lima kali. Pembuatan mikrokapsul dilakukan dengan menggunakan modifikasi metode dasar thermal cross-linking, serta menerapkan teknik pengeringan suhu konstan. Proses pembuatan mikrokapsul protein diawali dengan kultur fitoplankton jenis Nannochloropsis sp., Chlorella sp., dan Spirulina sp. Kultur dilakukan di dalam laboratorium menggunakan media air laut dan modifikasi pupuk Walne dan Guillard. Hasil penelitian menunjukkan bahwa kandungan nutrisi tertinggi terdapat pada jenis mikrokapsul protein sel tunggal yang berasal dari
Eric M. Strohm
Full Text Available High resolution ultrasound and photoacoustic images of stained neutrophils, lymphocytes and monocytes from a blood smear were acquired using a combined acoustic/photoacoustic microscope. Photoacoustic images were created using a pulsed 532 nm laser that was coupled to a single mode fiber to produce output wavelengths from 532 nm to 620 nm via stimulated Raman scattering. The excitation wavelength was selected using optical filters and focused onto the sample using a 20× objective. A 1000 MHz transducer was co-aligned with the laser spot and used for ultrasound and photoacoustic images, enabling micrometer resolution with both modalities. The different cell types could be easily identified due to variations in contrast within the acoustic and photoacoustic images. This technique provides a new way of probing leukocyte structure with potential applications towards detecting cellular abnormalities and diseased cells at the single cell level.
Full Text Available The increasing global population living below the poverty line is driving the scientific community to search for non-conventional protein sources that can replace conventional expensive ones. Microbial proteins, or single-cell protein (SCP, represent a potential future nutrient source for human food and animal feed. These microbial proteins can be grown rapidly on substrates with minimum dependence on soil, water and climate conditions. They can be produced from algae, fungi and bacteria the chief sources of SCP. It is convenient to use microorganisms for production of SCP as they grow rapidly and have high protein content. Industrially, they can be produced from algal biomass, yeast, fungi. There are several other ways of getting SCP as well. Despite numerous advantages of SCP, they have disadvantages and toxic effects too, especially related to mycotoxins and bacterial toxins.
Ren Minqin [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore); Department of Biochemistry, National University of Singapore (Singapore); Kan, J.A. van [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore); Bettiol, A.A. [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore); Daina, Lim [Department of Anatomy, National University of Singapore (Singapore); Gek, Chan Yee [Department of Anatomy, National University of Singapore (Singapore); Huat, Bay Boon [Department of Anatomy, National University of Singapore (Singapore); Whitlow, H.J. [Department of Physics, University of Jyvaskyla, P.O. Box 35 (YFL), FIN-40014 (Finland); Osipowicz, T. [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore); Watt, F. [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore)]. E-mail: firstname.lastname@example.org
Scanning transmission ion microscopy (STIM) is a technique which utilizes the energy loss of high energy (MeV) ions passing through a sample to provide structural images. In this paper, we have successfully demonstrated STIM imaging of single cells at the nano-level using the high resolution capability of the proton beam writing facility at the Centre for Ion Beam Applications, National University of Singapore. MCF-7 breast cancer cells (American Type Culture Collection [ATCC]) were seeded on to silicon nitride windows, backed by a Hamamatsu pin diode acting as a particle detector. A reasonable contrast was obtained using 1 MeV protons and excellent contrast obtained using 1 MeV alpha particles. In a further experiment, nano-STIM was also demonstrated using cells seeded on to the pin diode directly, and high quality nano-STIM images showing the nucleus and multiple nucleoli were extracted before the detector was significantly damaged.
Ahmed, Daniel; Ozcelik, Adem; Bojanala, Nagagireesh; Nama, Nitesh; Upadhyay, Awani; Chen, Yuchao; Hanna-Rose, Wendy; Huang, Tony Jun
The precise rotational manipulation of single cells or organisms is invaluable to many applications in biology, chemistry, physics and medicine. In this article, we describe an acoustic-based, on-chip manipulation method that can rotate single microparticles, cells and organisms. To achieve this, we trapped microbubbles within predefined sidewall microcavities inside a microchannel. In an acoustic field, trapped microbubbles were driven into oscillatory motion generating steady microvortices which were utilized to precisely rotate colloids, cells and entire organisms (that is, C. elegans). We have tested the capabilities of our method by analysing reproductive system pathologies and nervous system morphology in C. elegans. Using our device, we revealed the underlying abnormal cell fusion causing defective vulval morphology in mutant worms. Our acoustofluidic rotational manipulation (ARM) technique is an easy-to-use, compact, and biocompatible method, permitting rotation regardless of optical, magnetic or electrical properties of the sample under investigation.
Middle Eastern countries are experiencing a renaissance, with heavy investment in both in infrastructure and science. King Abdullah University of Science and Technology (KAUST) is a new and modern university in Saudi Arabia. At the Computational Bioscience Research Center (CBRC) we are working on exploring the Red Sea and beyond, collaborating with Japanese and other research centers. We are using the environment to collect and analyze the microorganisms present. The platform being established at CBRC allows to process samples in a pipeline. The pipeline components consist of sample collection, processing and sequencing, following the in silico analysis, determining the gene functions, identifying the organisms. The genomes of microorganisms of interest are targeted modified by genome editing technology such as CRISPR and desired properties are selected by single cell instrumentation. The final output is to identify valuable microorganisms with production of bio-energy, nutrients, the food and fine chemicals.
Sun, Shiwei; Wang, Xuetao; Gao, Xin; Ren, Lihui; Su, Xiaoquan; Bu, Dongbo; Ning, Kang
In this work, we have proposed an approach called rDisc to discretize the original Raman spectrum into only a few (usually less than 20) representative peaks (Raman shifts). The approach has advantages in removing noises, and condensing the original spectrum. In particular, effective signal processing procedures were designed to eliminate noise, utilising wavelet transform denoising, baseline correction, and signal normalization. In the discretizing process, representative peaks were selected to signicantly decrease the Raman data size. More importantly, the selected peaks are chosen as suitable to serve as key biological markers to differentiate species and other cellular features. Additionally, the classication performance of discretized spectra was found to be comparable to full spectrum having more than 1000 Raman shifts. Overall, the discretized spectrum needs about 5storage space of a full spectrum and the processing speed is considerably faster. This makes rDisc clearly superior to other methods for single-cell classication.
Sen, Rajeev; Dolgalev, Igor; Bayin, N Sumru; Heguy, Adriana; Tsirigos, Aris; Placantonakis, Dimitris G
Single-cell RNA sequencing (sc-RNASeq) is a recently developed technique used to evaluate the transcriptome of individual cells. As opposed to conventional RNASeq in which entire populations are sequenced in bulk, sc-RNASeq can be beneficial when trying to better understand gene expression patterns in markedly heterogeneous populations of cells or when trying to identify transcriptional signatures of rare cells that may be underrepresented when using conventional bulk RNASeq. In this method, we describe the generation and analysis of cDNA libraries from single patient-derived glioblastoma cells using the C1 Fluidigm system. The protocol details the use of the C1 integrated fluidics circuit (IFC) for capturing, imaging and lysing cells; performing reverse transcription; and generating cDNA libraries that are ready for sequencing and analysis.
Bronwyn Jane Barkla
Full Text Available One of the remarkable adaptive features of the halophyte and facultative CAM plant Mesembryathemum crystallinum are the specialized modified trichomes called epidermal bladder cells (EBC which cover the leaves, stems, and peduncle of the plant. They are present from an early developmental stage but upon salt stress rapidly expand due to the accumulation of water and sodium. This particular plant feature makes it an attractive system for single cell type studies, with recent proteomics and transcriptomics studies of the EBC establishing that these cells are metabolically active and have roles other than sodium sequestration. To continue our investigation into the function of these unusual cells we carried out a comprehensive global analysis of the metabolites present in the EBC extract by gas chromatography Time-of-Flight mass spectrometry (GC-TOF and identified 194 known and 722 total molecular features. Statistical analysis of the metabolic changes between control and salt-treated samples was used to identify 352 significantly differing metabolites (268 after correction for FDR. Principal components analysis provided an unbiased evaluation of the data variance structure. Biochemical pathway enrichment analysis suggested significant perturbations in 13 biochemical pathways as defined in KEGG. More than 50% of the metabolites that show significant changes in the EBC, can be classified as compatible solutes and include sugars, sugar alcohols, protein and non-protein amino acids, and organic acids, highlighting the need to maintain osmotic homeostasis to balance the accumulation of Na and Cl ions. Overall, the comparison of metabolic changes in salt treated relative to control samples suggest large alterations in Mesembryanthemum crystallinum epidermal bladder cells.
Barkla, Bronwyn J; Vera-Estrella, Rosario
One of the remarkable adaptive features of the halophyte Mesembryanthemum crystallinum are the specialized modified trichomes called epidermal bladder cells (EBC) which cover the leaves, stems, and peduncle of the plant. They are present from an early developmental stage but upon salt stress rapidly expand due to the accumulation of water and sodium. This particular plant feature makes it an attractive system for single cell type studies, with recent proteomics and transcriptomics studies of the EBC establishing that these cells are metabolically active and have roles other than sodium sequestration. To continue our investigation into the function of these unusual cells we carried out a comprehensive global analysis of the metabolites present in the EBC extract by gas chromatography Time-of-Flight mass spectrometry (GC-TOF) and identified 194 known and 722 total molecular features. Statistical analysis of the metabolic changes between control and salt-treated samples identified 352 significantly differing metabolites (268 after correction for FDR). Principal components analysis provided an unbiased evaluation of the data variance structure. Biochemical pathway enrichment analysis suggested significant perturbations in 13 biochemical pathways as defined in KEGG. More than 50% of the metabolites that show significant changes in the EBC, can be classified as compatible solutes and include sugars, sugar alcohols, protein and non-protein amino acids, and organic acids, highlighting the need to maintain osmotic homeostasis to balance the accumulation of Na(+) and Cl(-) ions. Overall, the comparison of metabolic changes in salt treated relative to control samples suggests large alterations in M. crystallinum epidermal bladder cells.
Barkla, Bronwyn J.; Vera-Estrella, Rosario
One of the remarkable adaptive features of the halophyte Mesembryanthemum crystallinum are the specialized modified trichomes called epidermal bladder cells (EBC) which cover the leaves, stems, and peduncle of the plant. They are present from an early developmental stage but upon salt stress rapidly expand due to the accumulation of water and sodium. This particular plant feature makes it an attractive system for single cell type studies, with recent proteomics and transcriptomics studies of the EBC establishing that these cells are metabolically active and have roles other than sodium sequestration. To continue our investigation into the function of these unusual cells we carried out a comprehensive global analysis of the metabolites present in the EBC extract by gas chromatography Time-of-Flight mass spectrometry (GC-TOF) and identified 194 known and 722 total molecular features. Statistical analysis of the metabolic changes between control and salt-treated samples identified 352 significantly differing metabolites (268 after correction for FDR). Principal components analysis provided an unbiased evaluation of the data variance structure. Biochemical pathway enrichment analysis suggested significant perturbations in 13 biochemical pathways as defined in KEGG. More than 50% of the metabolites that show significant changes in the EBC, can be classified as compatible solutes and include sugars, sugar alcohols, protein and non-protein amino acids, and organic acids, highlighting the need to maintain osmotic homeostasis to balance the accumulation of Na+ and Cl− ions. Overall, the comparison of metabolic changes in salt treated relative to control samples suggests large alterations in M. crystallinum epidermal bladder cells. PMID:26113856
Matsumura, Taku; Tatsumi, Kazuya; Noda, Yuichiro; Nakanishi, Naoyuki; Okonogi, Atsuhito; Hirano, Kunio; Li, Liu; Osumi, Takashi; Tada, Takashi; Kotera, Hidetoshi
The microenvironment of cells, which includes basement proteins, shear stress, and extracellular stimuli, should be taken into consideration when examining physiological cell behavior. Although microfluidic devices allow cellular responses to be analyzed with ease at the single-cell level, few have been designed to recover cells. We herein demonstrated that a newly developed microfluidic device helped to improve culture conditions and establish a clonality-validated human pluripotent stem cell line after tracing its growth at the single-cell level. The device will be a helpful tool for capturing various cell types in the human body that have not yet been established in vitro. Copyright © 2014 Elsevier Inc. All rights reserved.
Strohm, Eric M.; Berndl, Elizabeth S. L.; Kolios, Michael C.
We demonstrate a new technique to non-invasively determine the diameter and sound speed of single cells using a combined ultrasonic and photoacoustic technique. Two cell lines, B16-F1 melanoma cells and MCF7 breast cancer cells were examined using this technique. Using a 200 MHz transducer, the ultrasound backscatter from a single cell in suspension was recorded. Immediately following, the cell was irradiated with a 532 nm laser and the resulting photoacoustic wave recorded by the same transducer. The melanoma cells contain optically absorbing melanin particles, which facilitated photoacoustic wave generation. MCF7 cells have negligible optical absorption at 532 nm; the cells were permeabilized and stained with trypan blue prior to measurements. The measured ultrasound and photoacoustic power spectra were compared to theoretical equations with the cell diameter and sound speed as variables (Anderson scattering model for ultrasound, and a thermoelastic expansion model for photoacoustics). The diameter and sound speed were extracted from the models where the spectral shape matched the measured signals. However the photoacoustic spectrum for the melanoma cell did not match theory, which is likely because melanin particles are located around the cytoplasm, and not within the nucleus. Therefore a photoacoustic finite element model of a cell was developed where the central region was not used to generate a photoacoustic wave. The resulting power spectrum was in better agreement with the measured signal than the thermoelastic expansion model. The MCF7 cell diameter obtained using the spectral matching method was 17.5 μm, similar to the optical measurement of 16 μm, while the melanoma cell diameter obtained was 22 μm, similar to the optical measurement of 21 μm. The sound speed measured from the MCF7 and melanoma cell was 1573 and 1560 m/s, respectively, which is within acceptable values that have been published in literature.
Andrea, T.; Rothermel, M.; Werner, R.; Butz, T.; Reinert, T.
STIM (scanning transmission ion microscopy) tomography has been shown to be a valuable method for the three-dimensional characterization of microsamples. It has, however, rarely been employed for the study of single cells, since a free-standing sample is needed for an ordinary tomography experiment. This requirement places high demands on sample preparation techniques. In this study cells fixated on a substrate rather than free-standing were used for tomography. Since the substrate prevented a full rotation of the sample an algorithm for limited-angle tomography was devised. STIM projections covering only a limited angular range of ca. 120 o were supplemented with simulated projections generated from a back and forth iteration between real space and Radon space. The energy loss caused by the substrate was subtracted from each projection. The cells were reconstructed using filtered backprojection. The surface of the cells as well as some interior structures could be reconstructed. Following the STIM projections a lesser number of PIXE (particle induced X-ray emission) projections were taken in order to obtain information about the elemental distribution of the sample. From the PIXE projections the three-dimensional phosphorus distribution within the cell was reconstructed using limited-angle tomography. Superimposition of the STIM and PIXE tomograms revealed the location of intracellular structures. Whereas STIM tomography is sensitive to density contrast, which are greatest at the surface, PIXE tomography is sensitive to changes in elemental concentration. Hence, the combination of the two methods can be very fruitful, while the limited angle approach can compensate some of the difficulties associated with tomography of single cells, namely preparation difficulties and excessive sample damage.
Zbigniew T Czyż
Full Text Available BACKGROUND: Disseminated cancer cells (DCCs and circulating tumor cells (CTCs are extremely rare, but comprise the precursors cells of distant metastases or therapy resistant cells. The detailed molecular analysis of these cells may help to identify key events of cancer cell dissemination, metastatic colony formation and systemic therapy escape. METHODOLOGY/PRINCIPAL FINDINGS: Using the Ampli1™ whole genome amplification (WGA technology and high-resolution oligonucleotide aCGH microarrays we optimized conditions for the analysis of structural copy number changes. The protocol presented here enables reliable detection of numerical genomic alterations as small as 0.1 Mb in a single cell. Analysis of single cells from well-characterized cell lines and single normal cells confirmed the stringent quantitative nature of the amplification and hybridization protocol. Importantly, fixation and staining procedures used to detect DCCs showed no significant impact on the outcome of the analysis, proving the clinical usability of our method. In a proof-of-principle study we tracked the chromosomal changes of single DCCs over a full course of high-dose chemotherapy treatment by isolating and analyzing DCCs of an individual breast cancer patient at four different time points. CONCLUSIONS/SIGNIFICANCE: The protocol enables detailed genome analysis of DCCs and thereby assessment of the clonal evolution during the natural course of the disease and under selection pressures. The results from an exemplary patient provide evidence that DCCs surviving selective therapeutic conditions may be recruited from a pool of genomically less advanced cells, which display a stable subset of specific genomic alterations.
Tabas-Madrid, Daniel; Alves-Cruzeiro, Joao; Segura, Victor; Guruceaga, Elizabeth; Vialas, Vital; Prieto, Gorka; García, Carlos; Corrales, Fernando J; Albar, Juan Pablo; Pascual-Montano, Alberto
dasHPPboard is a novel proteomics-based dashboard that collects and reports the experiments produced by the Spanish Human Proteome Project consortium (SpHPP) and aims to help HPP to map the entire human proteome. We have followed the strategy of analog genomics projects like the Encyclopedia of DNA Elements (ENCODE), which provides a vast amount of data on human cell lines experiments. The dashboard includes results of shotgun and selected reaction monitoring proteomics experiments, post-translational modifications information, as well as proteogenomics studies. We have also processed the transcriptomics data from the ENCODE and Human Body Map (HBM) projects for the identification of specific gene expression patterns in different cell lines and tissues, taking special interest in those genes having little proteomic evidence available (missing proteins). Peptide databases have been built using single nucleotide variants and novel junctions derived from RNA-Seq data that can be used in search engines for sample-specific protein identifications on the same cell lines or tissues. The dasHPPboard has been designed as a tool that can be used to share and visualize a combination of proteomic and transcriptomic data, providing at the same time easy access to resources for proteogenomics analyses. The dasHPPboard can be freely accessed at: http://sphppdashboard.cnb.csic.es.
Cuesta Astroz, Yesid; Segura Latorre, Cesar
Malaria is a parasitic disease that has a high impact on public health in developing countries. The sequencing of the plasmodium falciparum genome and the development of proteomics have enabled a breakthrough in understanding the biology of the parasite. Proteomics have allowed to characterize qualitatively and quantitatively the parasite s expression of proteins and has provided information on protein expression under conditions of stress induced by antimalarial. Given the complexity of their life cycle, this takes place in the vertebrate host and mosquito vector. It has proven difficult to characterize the protein expression during each stage throughout the infection process in order to determine the proteome that mediates several metabolic, physiological and energetic processes. Two dimensional electrophoresis, liquid chromatography and mass spectrometry have been useful to assess the effects of antimalarial on parasite protein expression and to characterize the proteomic profile of different p. falciparum stages and organelles. The purpose of this review is to present state of the art tools and advances in proteomics applied to the study of malaria, and to present different experimental strategies used to study the parasite's proteome in order to show the advantages and disadvantages of each one.
Vercauteren, Freya G G; Bergeron, John J M; Vandesande, Frans; Arckens, Lut; Quirion, Rémi
Numerous applications of genomic technologies have enabled the assembly of unprecedented inventories of genes, expressed in cells under specific physiological and pathophysiological conditions. Complementing the valuable information generated through functional genomics with the integrative knowledge of protein expression and function should enable the development of more efficient diagnostic tools and therapeutic agents. Proteomic analyses are particularly suitable to elucidate posttranslational modifications, expression levels and protein-protein interactions of thousands of proteins at a time. In this review, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) investigations of brain tissues in neurodegenerative diseases such as Alzheimer's disease, Down syndrome and schizophrenia, and the construction of 2D-PAGE proteome maps of the brain are discussed. The role of the Human Proteome Organization (HUPO) as an international coordinating organization for proteomic efforts, as well as challenges for proteomic technologies and data analysis are also addressed. It is expected that the use of proteomic strategies will have significant impact in neuropharmacology over the coming decade.
Parkash, O; Singh, B P
Although Mycobacterium leprae was the first bacterial pathogen identified causing human disease, it remains one of the few that is non-cultivable. Understanding the biology of M. leprae is one of the primary challenges in current leprosy research. Genomics has been extremely valuable, nonetheless, functional proteins are ultimately responsible for controlling most aspects of cellular functions, which in turn could facilitate parasitizing the host. Furthermore, bacterial proteins provide targets for most of the vaccines and immunodiagnostic tools. Better understanding of the proteomics of M. leprae could also help in developing new drugs against M. leprae. During the past nearly 15 years, there have been several developments towards the identification of M. leprae proteins employing contemporary proteomics tools. In this review, we discuss the knowledge gained on the biology and pathogenesis of M. leprae from current proteomic studies. © 2012 The Authors. Scandinavian Journal of Immunology © 2012 Blackwell Publishing Ltd.
Bateman, Nicholas W; Conrads, Thomas P
Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with poor patient prognosis for many cancer types. Indeed, non-malignant cell populations, such as vascular endothelial and immune cells, are known to play key roles supporting and, in some cases, driving aggressive tumour biology, and represent targets of emerging therapeutics, such as antiangiogenesis and immune checkpoint inhibitors. The biochemical interplay between these cellular populations and how they contribute to molecular tumour heterogeneity remains enigmatic, particularly from the perspective of the tumour proteome. This review focuses on recent advances in proteomic methods, namely imaging mass spectrometry, single-cell proteomic techniques, and preanalytical sample processing, that are uniquely positioned to enable detailed analysis of discrete cellular populations within tumours to improve our understanding of tumour proteomic heterogeneity. This review further emphasizes the opportunity afforded by the application of these techniques to the analysis of tumour heterogeneity in formalin-fixed paraffin-embedded archival tumour tissues, as these represent an invaluable resource for retrospective analyses that is now routinely accessible, owing to recent technological and methodological advances in tumour tissue proteomics. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
The ability to manipulate light in subwavelength photonic and plasmonic structures has shown great potentials in revolutionizing how information is generated, transformed and processed. Chemically synthesized nanowires, in particular, offers a unique toolbox not only for highly compact and integrated photonic modules and devices, including coherent and incoherent light sources, waveguides, photodetectors and photovoltaics, but also for new types of nanoscopic bio-probes for spot cargo delivery and in-situ single cell endoscopy and sensing. Such nanowire probes would enable us to carry out intracellular imaging and probing with high spatial resolution, monitor in-vivo biological processes within single living cells and greatly improve our fundamental understanding of cell functions, intracellular physiological processes, and cellular signal pathways. My work is aimed at developing a material and instrumental platform for such single nanowire probe. Successful optical integration of Ag nanowire plasmonic waveguides, which offers deep subwavelength mode confinement, and conventional photonic waveguides was demonstrated on a single nanowire level. The highest plasmonic-photonic coupling efficiency coupling was found at small coupling angles and low input frequencies. The frequency dependent propagation loss was observed in Ag nanowire and was confirmed by quantitative measurement and in agreement with theoretical expectations. Rational integration of dielectric and Ag nanowire waveguide components into hybrid optical-plasmonic routing devices has been demonstrated. This capability is essential for incorporating sub-100nm Ag nanowire waveguides into optical fiber based nanoprobes for single cell endoscopy. The nanoprobe system based on single nanowire waveguides was demonstrated by optically coupling semiconductor or metal nanowire with an optical fiber with tapered tip. This nanoprobe design requires minimal instrumentation which makes it cost efficient and readily
Slattery, Marc; Ankisetty, Sridevi; Corrales, Jone; Marsh-Hunkin, K Erica; Gochfeld, Deborah J; Willett, Kristine L; Rimoldi, John M
The application of proteomics to marine sciences has increased in recent years because the proteome represents the interface between genotypic and phenotypic variability and, thus, corresponds to the broadest possible biomarker for eco-physiological responses and adaptations. Likewise, proteomics can provide important functional information regarding biosynthetic pathways, as well as insights into mechanism of action, of novel marine natural products. The goal of this review is to (1) explore the application of proteomics methodologies to marine systems, (2) assess the technical approaches that have been used, and (3) evaluate the pros and cons of this proteomic research, with the intent of providing a critical analysis of its future roles in marine sciences. To date, proteomics techniques have been utilized to investigate marine microbe, plant, invertebrate, and vertebrate physiology, developmental biology, seafood safety, susceptibility to disease, and responses to environmental change. However, marine proteomics studies often suffer from poor experimental design, sample processing/optimization difficulties, and data analysis/interpretation issues. Moreover, a major limitation is the lack of available annotated genomes and proteomes for most marine organisms, including several "model species". Even with these challenges in mind, there is no doubt that marine proteomics is a rapidly expanding and powerful integrative molecular research tool from which our knowledge of the marine environment, and the natural products from this resource, will be significantly expanded.
Kopylov, A T; Zgoda, V G
In modern science proteomic analysis is inseparable from other fields of systemic biology. Possessing huge resources quantitative proteomics operates colossal information on molecular mechanisms of life. Advances in proteomics help researchers to solve complex problems of cell signaling, posttranslational modification, structure and functional homology of proteins, molecular diagnostics etc. More than 40 various methods have been developed in proteomics for quantitative analysis of proteins. Although each method is unique and has certain advantages and disadvantages all these use various isotope labels (tags). In this review we will consider the most popular and effective methods employing both chemical modifications of proteins and also metabolic and enzymatic methods of isotope labeling.
Sakar, Mahmut Selman
One of the great challenges in nano and micro scale science and engineering is the independent manipulation of biological cells and small man-made objects with active sensing. For such biomedical applications as single cell manipulation, telemetry, and localized targeted delivery of chemicals, it is important to fabricate microstructures that can be powered and controlled without a tether in fluidic environments. These microstructures can be used to develop microrobots that have the potential to make existing therapeutic and diagnostic procedures less invasive. Actuation can be realized using various different organic and inorganic methods. Previous studies explored different forms of actuation and control with microorganisms. Bacteria, in particular, offer several advantages as controllable microactuators: they draw chemical energy directly from their environment, they are genetically modifiable, and they are scalable and configurable in the sense that any number of bacteria can be selectively patterned. Additionally, the study of bacteria inspires inorganic schemes of actuation and control. For these reasons, we chose to employ bacteria while controlling their motility using optical and electrical stimuli. In the first part of the thesis, we demonstrate a biointegrated approach by introducing MicroBioRobots (MBRs). MBRs are negative photosensitive epoxy (SU8) microfabricated structures with typical feature sizes ranging from 1-100 mum coated with a monolayer of the swarming Serratia marcescens . The adherent bacterial cells naturally coordinate to propel the microstructures in fluidic environments which we call Self-Actuation. First, we demonstrate the control of MBRs using self-actuation, DC electric fields and ultra-violet radiation and develop an experimentally-validated mathematical model for the MBRs. This model allows us to to steer the MBR to any position and orientation in a planar micro channel using visual feedback and an inverted microscope. Examples
Wills, Quin F; Mellado-Gomez, Esther; Nolan, Rory; Warner, Damien; Sharma, Eshita; Broxholme, John; Wright, Benjamin; Lockstone, Helen; James, William; Lynch, Mark; Gonzales, Michael; West, Jay; Leyrat, Anne; Padilla-Parra, Sergi; Filippi, Sarah; Holmes, Chris; Moore, Michael D; Bowden, Rory
Single-cell RNA-Seq can be a valuable and unbiased tool to dissect cellular heterogeneity, despite the transcriptome's limitations in describing higher functional phenotypes and protein events. Perhaps the most important shortfall with transcriptomic 'snapshots' of cell populations is that they risk being descriptive, only cataloging heterogeneity at one point in time, and without microenvironmental context. Studying the genetic ('nature') and environmental ('nurture') modifiers of heterogeneity, and how cell population dynamics unfold over time in response to these modifiers is key when studying highly plastic cells such as macrophages. We introduce the programmable Polaris™ microfluidic lab-on-chip for single-cell sequencing, which performs live-cell imaging while controlling for the culture microenvironment of each cell. Using gene-edited macrophages we demonstrate how previously unappreciated knockout effects of SAMHD1, such as an altered oxidative stress response, have a large paracrine signaling component. Furthermore, we demonstrate single-cell pathway enrichments for cell cycle arrest and APOBEC3G degradation, both associated with the oxidative stress response and altered proteostasis. Interestingly, SAMHD1 and APOBEC3G are both HIV-1 inhibitors ('restriction factors'), with no known co-regulation. As single-cell methods continue to mature, so will the ability to move beyond simple 'snapshots' of cell populations towards studying the determinants of population dynamics. By combining single-cell culture, live-cell imaging, and single-cell sequencing, we have demonstrated the ability to study cell phenotypes and microenvironmental influences. It's these microenvironmental components - ignored by standard single-cell workflows - that likely determine how macrophages, for example, react to inflammation and form treatment resistant HIV reservoirs.
Full Text Available Poly-beta-hydroxybutyrate (PHB can be formed in large amounts in Cupriavidus necator and is important for the industrial production of biodegradable plastics. In this investigation, laser tweezers Raman spectroscopy (LTRS was used to characterize dynamic changes in PHB content—as well as in the contents of other common biomolecule—in C. necator during batch growth at both the population and single-cell levels. PHB accumulation began in the early stages of bacterial growth, and the maximum PHB production rate occurred in the early and middle exponential phases. The active biosynthesis of DNA, RNA, and proteins occurred in the lag and early exponential phases, whereas the levels of these molecules decreased continuously during the remaining fermentation process until the minimum values were reached. The PHB content inside single cells was relatively homogenous in the middle stage of fermentation; during the late growth stage, the variation in PHB levels between cells increased. In addition, bacterial cells in various growth phases could be clearly discriminated when principle component analysis was performed on the spectral data. These results suggest that LTRS is a valuable single-cell analysis tool that can provide more comprehensive information about the physiological state of a growing microbial population.
Wang, Changling; Zhang, Yuxiang; Xia, Mingdian; Zhu, Xingxi; Qi, Shitao; Shen, Huaqiang; Liu, Tiebing; Tang, Liming
Biological processes in single cells, such as signal transduction, DNA duplication, and protein synthesis and trafficking, occur in subcellular compartments at nanoscale level. Achieving high spatial-temporal resolution, high sensitivity, and high specificity in single-cell detection poses a great challenge. Nanotechnology, which has been widely applied in the fields of medicine, electronics, biomaterials, and energy production, has the potential to provide solutions for single-cell detection. Here we present a review of the use of nanotechnology in single-cell detection over the past two decades. First, we review the main areas of scientific interest, including morphology, ion concentration, DNA, RNA, protein, intracellular temperature, elements, and mechanical properties. Second, four categories of application of nanotechnology to single-cell detection are described: nanomanipulation, nanodevices, nanomaterials as labels, and nano Secondary ion mass spectrometry. Finally, the prospects and future trends in single-cell detection and analysis are discussed.
Abi Ghanem, Maroun; Dehoux, Thomas; Liu, Liwang; Le Saux, Guillaume; Plawinski, Laurent; Durrieu, Marie-Christine; Audoin, Bertrand
Laser-generated GHz-ultrasonic-based technologies have shown the ability to image single cell adhesion and stiffness simultaneously. Using this new modality, we here demonstrate quantitative indicators to investigate contact mechanics and adhesion processes of the cell. We cultured human cells on a rigid substrate, and we used an inverted pulsed opto-acoustic microscope to generate acoustic pulses containing frequencies up to 100 GHz in the substrate. We map the reflection of the acoustic pulses at the cell-substrate interface to obtain images of the acoustic impedance of the cell, Zc, as well as of the stiffness of the interface, K, with 1 μm lateral resolution. Our results show that the standard deviation ΔZc reveals differences between different cell types arising from the multiplicity of local conformations within the nucleus. From the distribution of K-values within the nuclear region, we extract a mean interfacial stiffness, Km, that quantifies the average contact force in areas of the cell displaying weak bonding. By analogy with classical contact mechanics, we also define the ratio of the real to nominal contact areas, Sr/St. We show that Km can be interpreted as a quantitative indicator of passive contact at metal-cell interfaces, while Sr/St is sensitive to active adhesive processes in the nuclear region. The ability to separate the contributions of passive and active adhesion processes should allow gaining insight into cell-substrate interactions, with important applications in tissue engineering.
Lim, C.T.; Zhou, E.H.; Li, A.; Vedula, S.R.K.; Fu, H.X.
Stresses and strains that act on the human body can arise either from external physical forces or internal physiological environmental conditions. These biophysical interactions can occur not only at the musculoskeletal but also cellular and molecular levels and can determine the health and function of the human body. Here, we seek to investigate the structure-property-function relationship of cells and biomolecules so as to understand their important physiological functions as well as establish possible connections to human diseases. With the recent advancements in cell and molecular biology, biophysics and nanotechnology, several innovative and state-of-the-art experimental techniques and equipment have been developed to probe the structural and mechanical properties of biostructures from the micro- down to picoscale. Some of these experimental techniques include the optical or laser trap method, micropipette aspiration, step-pressure technique, atomic force microscopy and molecular force spectroscopy. In this article, we will review the basic principles and usage of these techniques to conduct single cell and single molecule biomechanics research
Li Zijie; Zhang Zhiyong; Chai Zhifang; Yu Ming; Zhou Yunlong
There are actually 20 chemical elements necessary or beneficial for plant growth. Carbon, hydrogen, and oxygen are supplied by air and water. The six macronutrients, nitrogen, phosphorus, potassium., calcium, magnesium, and sulfur are required by plants in large amounts. The rest of the elements are required in trace amounts (micronutrients). Essential trace elements include boron, chlorine, copper, iron, manganese, sodium, zinc, molybdenum, and nickel. Beneficial mineral elements include silicon and cobalt. The functions of the inorganic elements closely related to their destinations in plant cells. Plant cells have unique structures, including a central vacuole, plastids, and a thick cell wall that surrounds the cell membrane. Generally, it is very difficult to determine concentrations of inorganic elements in a single plant cell. Chara corallina is a freshwater plant that inhabits temperate zone ponds and lakes. It consists of alternating nodes and internodes. Each internodal segment is a single large cell, up to 10 cm in length, and 1 mm in diameter. With this species it was possible to isolate subcellular fractions with surgical methods with minimal risk of cross contamination. In this study, concentrations of magnesium, calcium, manganese, iron, copper, zinc, and molybdenum in the cell wall, cytoplasm, and vacuole of single cells of Chara corallina were determined by inductively coupled plasma mass spectrometry (ICP-MS). The distribution characteristics of these elements in the cell components were discussed.
Berman, E S; Fortson, S L; Kulp, K S; Checchi, K D; Wu, L; Felton, J S; Wu, K J
Characterizing chemical changes within single cells is important for determining fundamental mechanisms of biological processes that will lead to new biological insights and improved disease understanding. Imaging biological systems with mass spectrometry (MS) has gained popularity in recent years as a method for creating precise chemical maps of biological samples. In order to obtain high-quality mass spectral images that provide relevant molecular information about individual cells, samples must be prepared so that salts and other cell-culture components are removed from the cell surface and the cell contents are rendered accessible to the desorption beam. We have designed a cellular preparation protocol for imaging MS that preserves the cellular contents for investigation and removes the majority of the interfering species from the extracellular matrix. Using this method, we obtain excellent imaging results and reproducibility in three diverse cell types: MCF7 human breast cancer cells, Madin-Darby canine kidney (MDCK) cells, and NIH/3T3 mouse fibroblasts. This preparation technique allows routine imaging MS analysis of cultured cells, allowing for any number of experiments aimed at furthering scientific understanding of molecular processes within individual cells.
Nelson, J.M.; Braby, L.A.
The dose-limiting normal tissue of concern when irradiating head and neck lesions is often the vascular endothelium within the treatment field. Consequently, the response of capillary endothelial cells exposed to moderate doses of high LET particles is essential for establishing exposure limits for neutron-capture therapy. In an effort to characterize the high-LET radiation biology of cultured endothelial cells, the authors are attempting to measure cellular response to single particles. The single-particle irradiation apparatus, described below, allows them to expose individual cells to known numbers of high-LET particles and follow these cells for extended periods, in order to assess the impact of individual particles on cell growth kinetics. Preliminary cell irradiation experiments have revealed complications related to the smooth and efficient operation of the equipment; these are being resolved. Therefore, the following paragraphs deal primarily with the manner by which high LET particles deposit energy, the requirements for single-cell irradiation, construction and assembly of such apparatus, and testing of experimental procedures, rather than with the radiation biology of endothelial cells
Nishio, N.; Nagai, S.
As the hydrolysis of mandarin orange peel with macerating enzyme (40/sup 0/C,24 h)produced 0.59 g g/sup -1/ reducing sugar per dry peel compared to 0.36 by acid-hydrolysis (15 min at 120/sup 0/C with 0.8 N H/sub 2/SO/sub 4/), the production of single cell protein (SCP) from orange peel was studied mostly using enzymatically hydrolyzed orange peel. When the enzymatically hydrolyzed peel media were used, the utilization efficiency of reducing sugars (%) and the growth yield from reducing sugars (gg/sup -1/)were: 63 and 0.51 for Saccharomyces cerevisiae; 56 and 0.48 for Candida utilis; 74 and 0.69 for Debaryomyces hansenii and 64 and 0.70 for Rhodotorula glutinis. SCP production from orange peel by D. hansenii and R. glutinis were further studied. Batch cultures for 24 h at 30/sup 0/C using 100 g dried orange peel produced 45 g of dried cultivated peel (protein content, 33%) with D. hansenii and 34 g (protein content, 50%) with R. glutinis, and 38 g (protein content, 44%) with a mixture of both yeasts.
Wangler, N; Welsche, M; Blazek, M; Blessing, M; Vervliet-Scheebaum, M; Reski, R; Müller, C; Reinecke, H; Steigert, J; Roth, G; Zengerle, R; Paust, N
We present a new method for the distinct specific chemical stimulation of single cells and small cell clusters within their natural environment. By single-drop release of chemical agents with droplets in size of typical cell diameters (d agent release cartridge with integrated fluidic structures and integrated agent reservoirs are shown, tested, and compared in this publication. The single channel setup features a fluidic structure fabricated by anisotropic etching of silicon. To allow for simultaneous release of different agents even though maintaining the same device size, the second type comprises a double channel fluidic structure, fabricated by photolithographic patterning of TMMF. Dispensed droplet volumes are V = 15 pl and V = 10 pl for the silicon and the TMMF based setups, respectively. Utilizing the agent release cartridges, the application in biological assays was demonstrated by hormone-stimulated premature bud formation in Physcomitrella patens and the individual staining of one single L 929 cell within a confluent grown cell culture.
Huang, Hao-Ting; Ger, Tzong-Rong; Lin, Ya-Hui; Wei, Zung-Hang
A magnetic zigzag nanowire device was designed for single cell biosensing. Nanowires with widths of 150, 300, 500, and 800 nm were fabricated on silicon trenches by electron beam lithography, electron beam evaporation, and lift-off processes. Magnetoresistance measurements were performed before and after the attachment of a single magnetic cell to the nanowires to characterize the magnetic signal change due to the influence of the magnetic cell. Magnetoresistance responses were measured in different magnetic field directions, and the results showed that this nanowire device can be used for multi-directional detection. It was observed that the highest switching field variation occurred in a 150 nm wide nanowire when the field was perpendicular to the substrate plane. On the other hand, the highest magnetoresistance ratio variation occurred in a 800 nm wide nanowire also when the field was perpendicular to the substrate plane. Besides, the trench-structured substrate proposed in this study can fix the magnetic cell to the sensor in a fluid environment, and the stray field generated by the corners of the magnetic zigzag nanowires has the function of actively attracting the magnetic cells for detection.
AWARD NUMBER: W81XWH-15-1-0251 TITLE: “Evaluation of Human Adipose Tissue Stromal Heterogeneity in Metabolic Disease Using Single Cell RNA...Heterogeneity in Metabolic Disease Using Single- Cell RNA-Seq 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Linus Tzu-Yen...ABSTRACT We have developed a robust protocol to generate single cell transcriptional profiles from subcutaneous adipose tissue samples of both human
Patel, Tapan P; Man, Karen; Firestein, Bonnie L; Meaney, David F
Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s-1000+neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. Copyright © 2015. Published by Elsevier B.V.
Ståhlberg, Anders; Kubista, Mikael
Single cells are basic physiological and biological units that can function individually as well as in groups in tissues and organs. It is central to identify, characterize and profile single cells at molecular level to be able to distinguish different kinds, to understand their functions and determine how they interact with each other. During the last decade several technologies for single-cell profiling have been developed and used in various applications, revealing many novel findings. Quantitative PCR (qPCR) is one of the most developed methods for single-cell profiling that can be used to interrogate several analytes, including DNA, RNA and protein. Single-cell qPCR has the potential to become routine methodology but the technique is still challenging, as it involves several experimental steps and few molecules are handled. Here, we discuss technical aspects and provide recommendation for single-cell qPCR analysis. The workflow includes experimental design, sample preparation, single-cell collection, direct lysis, reverse transcription, preamplification, qPCR and data analysis. Detailed reporting and sharing of experimental details and data will promote further development and make validation studies possible. Efforts aiming to standardize single-cell qPCR open up means to move single-cell analysis from specialized research settings to standard research laboratories. Copyright © 2017 Elsevier Ltd. All rights reserved.
Chen, Jian; Xue, Chengcheng; Zhao, Yang; Chen, Deyong; Wu, Min-Hsien; Wang, Junbo
This article reviews recent developments in microfluidic impedance flow cytometry for high-throughput electrical property characterization of single cells. Four major perspectives of microfluidic impedance flow cytometry for single-cell characterization are included in this review: (1) early developments of microfluidic impedance flow cytometry for single-cell electrical property characterization; (2) microfluidic impedance flow cytometry with enhanced sensitivity; (3) microfluidic impedance and optical flow cytometry for single-cell analysis and (4) integrated point of care system based on microfluidic impedance flow cytometry. We examine the advantages and limitations of each technique and discuss future research opportunities from the perspectives of both technical innovation and clinical applications. PMID:25938973
Hosokawa, Masahito; Nishikawa, Yohei; Kogawa, Masato; Takeyama, Haruko
Massively parallel single-cell genome sequencing is required to further understand genetic diversities in complex biological systems. Whole genome amplification (WGA) is the first step for single-cell sequencing, but its throughput and accuracy are insufficient in conventional reaction platforms. Here, we introduce single droplet multiple displacement amplification (sd-MDA), a method that enables massively parallel amplification of single cell genomes while maintaining sequence accuracy and specificity. Tens of thousands of single cells are compartmentalized in millions of picoliter droplets and then subjected to lysis and WGA by passive droplet fusion in microfluidic channels. Because single cells are isolated in compartments, their genomes are amplified to saturation without contamination. This enables the high-throughput acquisition of contamination-free and cell specific sequence reads from single cells (21,000 single-cells/h), resulting in enhancement of the sequence data quality compared to conventional methods. This method allowed WGA of both single bacterial cells and human cancer cells. The obtained sequencing coverage rivals those of conventional techniques with superior sequence quality. In addition, we also demonstrate de novo assembly of uncultured soil bacteria and obtain draft genomes from single cell sequencing. This sd-MDA is promising for flexible and scalable use in single-cell sequencing.
Abi Ghanem, Maroun; Dehoux, Thomas; Liu, Liwang; Le Saux, Guillaume; Plawinski, Laurent; Durrieu, Marie-Christine; Audoin, Bertrand
Laser-generated GHz-ultrasonic-based technologies have shown the ability to image single cell adhesion and stiffness simultaneously. Using this new modality, we here demonstrate quantitative indicators to investigate contact mechanics and adhesion processes of the cell. We cultured human cells on a rigid substrate, and we used an inverted pulsed opto-acoustic microscope to generate acoustic pulses containing frequencies up to 100 GHz in the substrate. We map the reflection of the acoustic pulses at the cell-substrate interface to obtain images of the acoustic impedance of the cell, Z c , as well as of the stiffness of the interface, K, with 1 μm lateral resolution. Our results show that the standard deviation ΔZ c reveals differences between different cell types arising from the multiplicity of local conformations within the nucleus. From the distribution of K-values within the nuclear region, we extract a mean interfacial stiffness, K m , that quantifies the average contact force in areas of the cell displaying weak bonding. By analogy with classical contact mechanics, we also define the ratio of the real to nominal contact areas, S r /S t . We show that K m can be interpreted as a quantitative indicator of passive contact at metal-cell interfaces, while S r /S t is sensitive to active adhesive processes in the nuclear region. The ability to separate the contributions of passive and active adhesion processes should allow gaining insight into cell-substrate interactions, with important applications in tissue engineering.
Barraquio, V; Silverio, L G; Revilleza, R P; Fernadez, W L
The production of single-cell protein by yeast assimilation of lactose in soft cheese whey was studied using Candida pseudotropicalis as a test organism. Under shake-flask cultivation conditions with deproteinized whey as the medium, lactose (initially 4.20%) was completely assimilated in 48h; cell mass was 5.56 mg/mL after 72h; and average protein content of the dried mass was approximately 11.8%. Batch cultivation using undeproteinized whey resulted in a faster lactose utilization rate from an initial 3.93% to a residual 0.56% in 12 h; cell mass was 8.41 mg/mL in 10 h; and average protein was approximately 37.7%. In a semicontinuous culture with 10 to the power of 7 viable cells/mL as initial cell concentration, 15.69 mg/mL cell mass with a mean protein content of approximately 21.4% could be produced and lactose could be considerably consumed (from an initial 4.75% to a residual 0.42%) within 13-14 h. Supplementation with (NH/sub 4/)/sub 2/S0/sub 4/ and KH/sub 2/P0/sub 4/ did not increase cell mass (12.47 mg/mL in 12 h) and hasten lactose assimulation (from initial 4.49% to residual 0.3% in 12 h). Average protein content was approximately 31%. Cell mass yield was established as 0.29 mg yeast cell/mg lactose consumed. Factors that might have affected protein content are also discussed.
Rodrigues, Pedro M; Silva, Tomé S; Dias, Jorge; Jessen, Flemming
Over the last forty years global aquaculture presented a growth rate of 6.9% per annum with an amazing production of 52.5 million tonnes in 2008, and a contribution of 43% of aquatic animal food for human consumption. In order to meet the world's health requirements of fish protein, a continuous growth in production is still expected for decades to come. Aquaculture is, though, a very competitive market, and a global awareness regarding the use of scientific knowledge and emerging technologies to obtain a better farmed organism through a sustainable production has enhanced the importance of proteomics in seafood biology research. Proteomics, as a powerful comparative tool, has therefore been increasingly used over the last decade to address different questions in aquaculture, regarding welfare, nutrition, health, quality, and safety. In this paper we will give an overview of these biological questions and the role of proteomics in their investigation, outlining the advantages, disadvantages and future challenges. A brief description of the proteomics technical approaches will be presented. Special focus will be on the latest trends related to the aquaculture production of fish with defined nutritional, health or quality properties for functional foods and the integration of proteomics techniques in addressing this challenging issue. Copyright © 2012 Elsevier B.V. All rights reserved.
Christian Carsten Sachs
Full Text Available Microfluidic lab-on-chip technology combined with live-cell imaging has enabled the observation of single cells in their spatio-temporal context. The mother machine (MM cultivation system is particularly attractive for the long-term investigation of rod-shaped bacteria since it facilitates continuous cultivation and observation of individual cells over many generations in a highly parallelized manner. To date, the lack of fully automated image analysis software limits the practical applicability of the MM as a phenotypic screening tool.We present an image analysis pipeline for the automated processing of MM time lapse image stacks. The pipeline supports all analysis steps, i.e., image registration, orientation correction, channel/cell detection, cell tracking, and result visualization. Tailored algorithms account for the specialized MM layout to enable a robust automated analysis. Image data generated in a two-day growth study (≈ 90 GB is analyzed in ≈ 30 min with negligible differences in growth rate between automated and manual evaluation quality. The proposed methods are implemented in the software molyso (MOther machine AnaLYsis SOftware that provides a new profiling tool to analyze unbiasedly hitherto inaccessible large-scale MM image stacks.Presented is the software molyso, a ready-to-use open source software (BSD-licensed for the unsupervised analysis of MM time-lapse image stacks. molyso source code and user manual are available at https://github.com/modsim/molyso.
Li, Jiannong; Smalley, Inna; Schell, Michael J; Smalley, Keiran S M; Chen, Y Ann
Single-cell technologies allow characterization of transcriptomes and epigenomes for individual cells under different conditions and provide unprecedented resolution for researchers to investigate cellular heterogeneity in cancer. The SinCHet ( gle ell erogeneity) toolbox is developed in MATLAB and has a graphical user interface (GUI) for visualization and user interaction. It analyzes both continuous (e.g. mRNA expression) and binary omics data (e.g. discretized methylation data). The toolbox does not only quantify cellular heterogeneity using S hannon P rofile (SP) at different clonal resolutions but also detects heterogeneity differences using a D statistic between two populations. It is defined as the area under the P rofile of S hannon D ifference (PSD). This flexible tool provides a default clonal resolution using the change point of PSD detected by multivariate adaptive regression splines model; it also allows user-defined clonal resolutions for further investigation. This tool provides insights into emerging or disappearing clones between conditions, and enables the prioritization of biomarkers for follow-up experiments based on heterogeneity or marker differences between and/or within cell populations. The SinCHet software is freely available for non-profit academic use. The source code, example datasets, and the compiled package are available at http://labpages2.moffitt.org/chen/software/ . email@example.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
The techniques of proteomics (high resolution two-dimensional electrophoresis and protein characterisation) are widely used for microbiological research to analyse global protein synthesis as an indicator of gene expression. The rapid progress in microbial proteomics has been achieved through the wide availability of whole genome sequences for a number of bacterial groups. Beyond providing a basic understanding of microbial gene expression, proteomics has also played a role in medical areas of microbiology. Progress has been made in the use of the techniques for investigating the epidemiology and taxonomy of human microbial pathogens, the identification of novel pathogenic mechanisms and the analysis of drug resistance. In each of these areas, proteomics has provided new insights that complement genomic-based investigations. This review describes the current progress in these research fields and highlights some of the technical challenges existing for the application of proteomics in medical microbiology. The latter concern the analysis of genetically heterogeneous bacterial populations and the integration of the proteomic and genomic data for these bacteria. The characterisation of the proteomes of bacterial pathogens growing in their natural hosts remains a future challenge.
Amantonico, Andrea; Oh, Joo Yeon; Sobek, Jens; Heinemann, Matthias; Zenobi, Renato
Getting a look-in: An optimized MALDI-MS procedure has been developed to detect endogenous primary metabolites directly in the cell extract. A detection limit corresponding to metabolites from less than a single cell has been attained, opening the door to single-cell metabolomics by mass
Falconer, Ester; Hills, Mark; Naumann, Ulrike; Poon, Steven S. S.; Chavez, Elizabeth A.; Sanders, Ashley D.; Zhao, Yongjun; Hirst, Martin; Lansdorp, Peter M.
DNA rearrangements such as sister chromatid exchanges (SCEs) are sensitive indicators of genomic stress and instability, but they are typically masked by single-cell sequencing techniques. We developed Strand-seq to independently sequence parental DNA template strands from single cells, making it
Coller, Hilary A
Emerging technologies for the analysis of genome-wide information in single cells have the potential to transform many fields of biology, including our understanding of cell states, the response of cells to external stimuli, mosaicism, and intratumor heterogeneity. At Experimental Biology 2017 in Chicago, Physiological Genomics hosted a symposium in which five leaders in the field of single cell genomics presented their recent research. The speakers discussed emerging methodologies in single cell analysis and critical issues for the analysis of single cell data. Also discussed were applications of single cell genomics to understanding the different types of cells within an organism or tissue and the basis for cell-to-cell variability in response to stimuli. Copyright © 2017 the American Physiological Society.
Baslan, Timour; Hicks, James
The fundamental operative unit of a cancer is the genetically and epigenetically innovative single cell. Whether proliferating or quiescent, in the primary tumour mass or disseminated elsewhere, single cells govern the parameters that dictate all facets of the biology of cancer. Thus, single-cell analyses provide the ultimate level of resolution in our quest for a fundamental understanding of this disease. Historically, this quest has been hampered by technological shortcomings. In this Opinion article, we argue that the rapidly evolving field of single-cell sequencing has unshackled the cancer research community of these shortcomings. From furthering an elemental understanding of intra-tumoural genetic heterogeneity and cancer genome evolution to illuminating the governing principles of disease relapse and metastasis, we posit that single-cell sequencing promises to unravel the biology of all facets of this disease.
Gardeux, Vincent; David, Fabrice P A; Shajkofci, Adrian; Schwalie, Petra C; Deplancke, Bart
Single-cell RNA-sequencing (scRNA-seq) allows whole transcriptome profiling of thousands of individual cells, enabling the molecular exploration of tissues at the cellular level. Such analytical capacity is of great interest to many research groups in the world, yet these groups often lack the expertise to handle complex scRNA-seq datasets. We developed a fully integrated, web-based platform aimed at the complete analysis of scRNA-seq data post genome alignment: from the parsing, filtering and normalization of the input count data files, to the visual representation of the data, identification of cell clusters, differentially expressed genes (including cluster-specific marker genes), and functional gene set enrichment. This Automated Single-cell Analysis Pipeline (ASAP) combines a wide range of commonly used algorithms with sophisticated visualization tools. Compared with existing scRNA-seq analysis platforms, researchers (including those lacking computational expertise) are able to interact with the data in a straightforward fashion and in real time. Furthermore, given the overlap between scRNA-seq and bulk RNA-seq analysis workflows, ASAP should conceptually be broadly applicable to any RNA-seq dataset. As a validation, we demonstrate how we can use ASAP to simply reproduce the results from a single-cell study of 91 mouse cells involving five distinct cell types. The tool is freely available at asap.epfl.ch and R/Python scripts are available at github.com/DeplanckeLab/ASAP. firstname.lastname@example.org. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Buszczak, Michael; Paterno, Shelley; Lighthouse, Daniel; Bachman, Julia; Planck, Jamie; Owen, Stephenie; Skora, Andrew D; Nystul, Todd G; Ohlstein, Benjamin; Allen, Anna; Wilhelm, James E; Murphy, Terence D; Levis, Robert W; Matunis, Erika; Srivali, Nahathai; Hoskins, Roger A; Spradling, Allan C
Metazoan physiology depends on intricate patterns of gene expression that remain poorly known. Using transposon mutagenesis in Drosophila, we constructed a library of 7404 protein trap and enhancer trap lines, the Carnegie collection, to facilitate gene expression mapping at single-cell resolution. By sequencing the genomic insertion sites, determining splicing patterns downstream of the enhanced green fluorescent protein (EGFP) exon, and analyzing expression patterns in the ovary and salivary gland, we found that 600-900 different genes are trapped in our collection. A core set of 244 lines trapped different identifiable protein isoforms, while insertions likely to act as GFP-enhancer traps were found in 256 additional genes. At least 8 novel genes were also identified. Our results demonstrate that the Carnegie collection will be useful as a discovery tool in diverse areas of cell and developmental biology and suggest new strategies for greatly increasing the coverage of the Drosophila proteome with protein trap insertions.
Martin, Sarah F.; Falkenberg, Heiner; Dyrlund, Thomas Franck
, including arguments for community-wide open source software development and “big data” compatible solutions for the future. For the meantime, we have laid out ten top tips for data processing. With these at hand, a first large-scale proteomics analysis hopefully becomes less daunting to navigate.......However there is clearly a real need for robust tools, standard operating procedures and general acceptance of best practises. Thus we submit to the proteomics community a call for a community-wide open set of proteomics analysis challenges—PROTEINCHALLENGE—that directly target and compare data analysis workflows......In large-scale proteomics studies there is a temptation, after months of experimental work, to plug resulting data into a convenient—if poorly implemented—set of tools, which may neither do the data justice nor help answer the scientific question. In this paper we have captured key concerns...
Bhilwade, H.N.; Chaubey, R.C.; Rajagopalan, Rema
In this paper, observations made on the effect of gamma radiation on DNA strand breaks in human leucocytes using alkaline comet assay are communicated. Human peripheral blood was collected from healthy volunteers and exposed in vitro to different doses of gamma radiation in the medium 0.125, 0.25, 0.50 and 1.0 Gy and high doses range of 2.04.0 and 8 Gy, using a 6 0C o Teletherapy machine at a dose rate of 0.668 Gy/min at 0 deg C in air. Migration of DNA fragments (TL) and tail moment (TM) was taken as the criteria of genetic damage and measured using the application software, SCGE-Pro, developed in our laboratory. Data were analyzed using one-way ANOVA for statistical significance. A dose dependent increase in the TL (p<0.001 ) and TM (p<0.001 ) was observed for DNA single strand breaks in the medium dose range, from 0.125 to 1.00 Gy dose. Similarly, data on DNA strand breaks from the high dose (e.g. 2 to 8 Gy) experiments also showed a significant increase in TL (p<0.001) and TM (p<0.001) at all the doses tested. The major finding of these experiments was the detection of DNA single strand breaks in human leucocytes, even at the lowest dose of 0.125 Gy. (author)
Nagano, Takashi; Lubling, Yaniv; Yaffe, Eitan; Wingett, Steven W; Dean, Wendy; Tanay, Amos; Fraser, Peter
Hi-C is a powerful method that provides pairwise information on genomic regions in spatial proximity in the nucleus. Hi-C requires millions of cells as input and, as genome organization varies from cell to cell, a limitation of Hi-C is that it only provides a population average of genome conformations. We developed single-cell Hi-C to create snapshots of thousands of chromatin interactions that occur simultaneously in a single cell. To adapt Hi-C to single-cell analysis, we modified the protocol to include in-nucleus ligation. This enables the isolation of single nuclei carrying Hi-C-ligated DNA into separate tubes, followed by reversal of cross-links, capture of biotinylated ligation junctions on streptavidin-coated magnetic beads and PCR amplification of single-cell Hi-C libraries. The entire laboratory protocol can be carried out in 1 week, and although we have demonstrated its use in mouse T helper (TH1) cells, it should be applicable to any cell type or species for which standard Hi-C has been successful. We also developed an analysis pipeline to filter noise and assess the quality of data sets in a few hours. Although the interactome maps produced by single-cell Hi-C are sparse, the data provide useful information to understand cellular variability in nuclear genome organization and chromosome structure. Standard wet and dry laboratory skills in molecular biology and computational analysis are required.
Schneider, Michel; Tognolli, Michael; Bairoch, Amos
The Swiss-Prot protein knowledgebase provides manually annotated entries for all species, but concentrates on the annotation of entries from model organisms to ensure the presence of high quality annotation of representative members of all protein families. A specific Plant Protein Annotation Program (PPAP) was started to cope with the increasing amount of data produced by the complete sequencing of plant genomes. Its main goal is the annotation of proteins from the model plant organism Arabidopsis thaliana. In addition to bibliographic references, experimental results, computed features and sometimes even contradictory conclusions, direct links to specialized databases connect amino acid sequences with the current knowledge in plant sciences. As protein families and groups of plant-specific proteins are regularly reviewed to keep up with current scientific findings, we hope that the wealth of information of Arabidopsis origin accumulated in our knowledgebase, and the numerous software tools provided on the Expert Protein Analysis System (ExPASy) web site might help to identify and reveal the function of proteins originating from other plants. Recently, a single, centralized, authoritative resource for protein sequences and functional information, UniProt, was created by joining the information contained in Swiss-Prot, Translation of the EMBL nucleotide sequence (TrEMBL), and the Protein Information Resource-Protein Sequence Database (PIR-PSD). A rising problem is that an increasing number of nucleotide sequences are not being submitted to the public databases, and thus the proteins inferred from such sequences will have difficulties finding their way to the Swiss-Prot or TrEMBL databases.
Vizcaíno, Juan Antonio; Walzer, Mathias; Jiménez, Rafael C.
in computational proteomics that would complement existing activities and close gaps in the portfolio of tools and services offered by ELIXIR so far. We provide some suggestions on how these activities could be integrated into ELIXIR's existing platforms, and how it could lead to a new ELIXIR use case...... involved, and in particular with other representatives of the proteomics community, to further refine this paper....
Poetsch, Ansgar; Wolters, Dirk
About one quarter to one third of all bacterial genes encode proteins of the inner or outer bacterial membrane. These proteins perform essential physiological functions, such as the import or export of metabolites, the homeostasis of metal ions, the extrusion of toxic substances or antibiotics, and the generation or conversion of energy. The last years have witnessed completion of a plethora of whole-genome sequences of bacteria important for biotechnology or medicine, which is the foundation for proteome and other functional genome analyses. In this review, we discuss the challenges in membrane proteome analysis, starting from sample preparation and leading to MS-data analysis and quantification. The current state of available proteomics technologies as well as their advantages and disadvantages will be described with a focus on shotgun proteomics. Then, we will briefly introduce the most abundant proteins and protein families present in bacterial membranes before bacterial membrane proteomics studies of the last years will be presented. It will be shown how these works enlarged our knowledge about the physiological adaptations that take place in bacteria during fine chemical production, bioremediation, protein overexpression, and during infections. Furthermore, several examples from literature demonstrate the suitability of membrane proteomics for the identification of antigens and different pathogenic strains, as well as the elucidation of membrane protein structure and function.
Veiseh, Mandana; Veiseh, Omid; Martin, Michael C.; Asphahani,Fareid; Zhang, Miqin
Single cell patterning holds important implications forbiology, biochemistry, biotechnology, medicine, and bioinformatics. Thechallenge for single cell patterning is to produce small islands hostingonly single cells and retaining their viability for a prolonged period oftime. This study demonstrated a surface engineering approach that uses acovalently bound short peptide as a mediator to pattern cells withimproved single cell adhesion and prolonged cellular viabilityon goldpatterned SiO2 substrates. The underlying hypothesis is that celladhesion is regulated bythe type, availability, and stability ofeffective cell adhesion peptides, and thus covalently bound shortpeptides would promote cell spreading and, thus, single cell adhesion andviability. The effectiveness of this approach and the underlyingmechanism for the increased probability of single cell adhesion andprolonged cell viability by short peptides were studied by comparingcellular behavior of human umbilical cord vein endothelial cells on threemodelsurfaces whose gold electrodes were immobilized with fibronectin,physically adsorbed Arg-Glu-Asp-Val-Tyr, and covalently boundLys-Arg-Glu-Asp-Val-Tyr, respectively. The surface chemistry and bindingproperties were characterized by reflectance Fourier transform infraredspectroscopy. Both short peptides were superior to fibronectin inproducing adhesion of only single cells, whereas the covalently boundpeptide also reduced apoptosis and necrosisof adhered cells. Controllingcell spreading by peptide binding domains to regulate apoptosis andviability represents a fundamental mechanism in cell-materialsinteraction and provides an effective strategy in engineering arrays ofsingle cells.
Full Text Available Single-cell phenotyping is critical to the success of biological reductionism. Raman-activated cell sorting (RACS has shown promise in resolving the dynamics of living cells at the individual level and to uncover population heterogeneities in comparison to established approaches such as fluorescence-activated cell sorting (FACS. Given that the number of single-cells would be massive in any experiment, the power of Raman profiling technique for single-cell analysis would be fully utilized only when coupled with a high-throughput and intelligent process control and data analysis system. In this work, we established QSpec, an automatic system that supports high-throughput Raman-based single-cell phenotyping. Additionally, a single-cell Raman profile database has been established upon which data-mining could be applied to discover the heterogeneity among single-cells under different conditions. To test the effectiveness of this control and data analysis system, a sub-system was also developed to simulate the phenotypes of single-cells as well as the device features.
Amelia Ahmad Khalili
Full Text Available Single-cell analysis has become the interest of a wide range of biological and biomedical engineering research. It could provide precise information on individual cells, leading to important knowledge regarding human diseases. To perform single-cell analysis, it is crucial to isolate the individual cells before further manipulation is carried out. Recently, microfluidic biochips have been widely used for cell trapping and single cell analysis, such as mechanical and electrical detection. This work focuses on developing a finite element simulation model of single-cell trapping system for any types of cells or particles based on the hydrodynamic flow resistance (Rh manipulations in the main channel and trap channel to achieve successful trapping. Analysis is carried out using finite element ABAQUS-FEA™ software. A guideline to design and optimize single-cell trapping model is proposed and the example of a thorough optimization analysis is carried out using a yeast cell model. The results show the finite element model is able to trap a single cell inside the fluidic environment. Fluid’s velocity profile and streamline plots for successful and unsuccessful single yeast cell trapping are presented according to the hydrodynamic concept. The single-cell trapping model can be a significant important guideline in designing a new chip for biomedical applications.
Full Text Available The study of single cells has evolved over the past several years to include expression and genomic analysis of an increasing number of single cells. Several studies have demonstrated wide-spread variation and heterogeneity within cell populations of similar phenotype. While the characterization of these populations will likely set the foundation for our understanding of genomic- and expression-based diversity, it will not be able to link the functional differences of a single cell to its underlying genomic structure and activity. Currently, it is difficult to perturb single cells in a controlled environment, monitor and measure the response due to perturbation, and link these response measurements to downstream genomic and transcriptomic analysis. In order to address this challenge, we developed a platform to integrate and miniaturize many of the experimental steps required to study single-cell function. The heart of this platform is an elastomer-based Integrated Fluidic Circuit (IFC that uses fluidic logic to select and sequester specific single cells based on a phenotypic trait for downstream experimentation. Experiments with sequestered cells that have been performed include on-chip culture, exposure to a variety of stimulants, and post-exposure image-based response analysis, followed by preparation of the mRNA transcriptome for massively parallel sequencing analysis. The flexible system embodies experimental design and execution that enable routine functional studies of single cells.
Rezende, Taia M B; Lima, Stella M F; Petriz, Bernardo A; Silva, Osmar N; Freire, Mirna S; Franco, Octávio L
Despite all the dental information acquired over centuries and the importance of proteome research, the cross-link between these two areas only emerged around mid-nineties. Proteomic tools can help dentistry in the identification of risk factors, early diagnosis, prevention, and systematic control that will promote the evolution of treatment in all dentistry specialties. This review mainly focuses on the evolution of dentistry in different specialties based on proteomic research and how these tools can improve knowledge in dentistry. The subjects covered are an overview of proteomics in dentistry, specific information on different fields in dentistry (dental structure, restorative dentistry, endodontics, periodontics, oral pathology, oral surgery, and orthodontics) and future directions. There are many new proteomic technologies that have never been used in dentistry studies and some dentistry areas that have never been explored by proteomic tools. It is expected that a greater integration of these areas will help to understand what is still unknown in oral health and disease. Copyright © 2013 Wiley Periodicals, Inc.
Seon B. Kim
Full Text Available The goal of the present study is to integrate different datasets in cell biology to derive additional quantitative information about a gene or protein of interest within a single cell using computational simulations. We propose a novel prototype cell simulator as a quantitative tool to integrate datasets including dynamic information about transcript and protein levels and the spatial information on protein trafficking in a complex cellular geometry. In order to represent the stochastic nature of transcription and gene expression, our cell simulator uses event-based stochastic simulations to capture transcription, translation, and dynamic trafficking events. In a reconstructed cellular geometry, a realistic microtubule structure is generated with a novel growth algorithm for simulating vesicular transport and trafficking events. In a case study, we investigate the change in quantitative expression levels of a water channel-aquaporin 4-in a single astrocyte cell, upon pharmacological treatment. Gillespie based discrete time approximation method results in stochastic fluctuation of mRNA and protein levels. In addition, we compute the dynamic trafficking of aquaporin-4 on microtubules in this reconstructed astrocyte. Computational predictions are validated with experimental data. The demonstrated cell simulator facilitates the analysis and prediction of protein expression dynamics.
Taghavi, Zeinab; Movahedi, Narjes S; Draghici, Sorin; Chitsaz, Hamidreza
Identification of every single genome present in a microbial sample is an important and challenging task with crucial applications. It is challenging because there are typically millions of cells in a microbial sample, the vast majority of which elude cultivation. The most accurate method to date is exhaustive single-cell sequencing using multiple displacement amplification, which is simply intractable for a large number of cells. However, there is hope for breaking this barrier, as the number of different cell types with distinct genome sequences is usually much smaller than the number of cells. Here, we present a novel divide and conquer method to sequence and de novo assemble all distinct genomes present in a microbial sample with a sequencing cost and computational complexity proportional to the number of genome types, rather than the number of cells. The method is implemented in a tool called Squeezambler. We evaluated Squeezambler on simulated data. The proposed divide and conquer method successfully reduces the cost of sequencing in comparison with the naïve exhaustive approach. Squeezambler and datasets are available at http://compbio.cs.wayne.edu/software/squeezambler/.
Kriszt, Rókus; Arai, Satoshi; Itoh, Hideki; Lee, Michelle H; Goralczyk, Anna G; Ang, Xiu Min; Cypess, Aaron M; White, Andrew P; Shamsi, Farnaz; Xue, Ruidan; Lee, Jung Yeol; Lee, Sung-Chan; Hou, Yanyan; Kitaguchi, Tetsuya; Sudhaharan, Thankiah; Ishiwata, Shin'ichi; Lane, E Birgitte; Chang, Young-Tae; Tseng, Yu-Hua; Suzuki, Madoka; Raghunath, Michael
The identification of brown adipose deposits in adults has led to significant interest in targeting this metabolically active tissue for treatment of obesity and diabetes. Improved methods for the direct measurement of heat production as the signature function of brown adipocytes (BAs), particularly at the single cell level, would be of substantial benefit to these ongoing efforts. Here, we report the first application of a small molecule-type thermosensitive fluorescent dye, ERthermAC, to monitor thermogenesis in BAs derived from murine brown fat precursors and in human brown fat cells differentiated from human neck brown preadipocytes. ERthermAC accumulated in the endoplasmic reticulum of BAs and displayed a marked change in fluorescence intensity in response to adrenergic stimulation of cells, which corresponded to temperature change. ERthermAC fluorescence intensity profiles were congruent with mitochondrial depolarisation events visualised by the JC-1 probe. Moreover, the averaged fluorescence intensity changes across a population of cells correlated well with dynamic changes such as thermal power, oxygen consumption, and extracellular acidification rates. These findings suggest ERthermAC as a promising new tool for studying thermogenic function in brown adipocytes of both murine and human origins.
The study of the role of trace elements at cellular level requires the use of state-of-the-art analytical tools that could achieve enough sensitivity and spatial resolution. We developed a new methodology for the accurate quantification of chemical element distribution in single cells based on a combination of ion beam analysis techniques STIM, PIXE and RBS. The quantification procedure relies on the development of a STIM data analysis software (Paparamborde). Validity of this methodology and limits are discussed here. The method allows the quantification of trace elements (μg/g) with a 19.8 % uncertainty in cellular compartments with mass below 0.1 ng. The main limit of the method lies in the poor number of samples that can be analyzed, due to long irradiation times required and limited access to ion beam analysis facilities. This is the reason why we developed a database for cellular chemical composition capitalization (BDC4). BDC4 has been designed in order to use cellular chemical composition as a tracer for biological activities and is expected to provide in the future reference chemical compositions for any cellular type or compartment. Application of the STIM-PIXE-RBS methodology to the study of nuclear toxicology of cobalt compounds is presented here showing that STIM analysis is absolutely needed when organic mass loss appears during PIXE-RBS irradiation. (author)
Full Text Available Microbial hydrolysis of polysaccharides is critical to ecosystem functioning and is of great interest in diverse biotechnological applications, such as biofuel production and bioremediation. Here we demonstrate the use of a new, efficient approach to recover genomes of active polysaccharide degraders from natural, complex microbial assemblages, using a combination of fluorescently labeled substrates, fluorescence-activated cell sorting, and single cell genomics. We employed this approach to analyze freshwater and coastal bacterioplankton for degraders of laminarin and xylan, two of the most abundant storage and structural polysaccharides in nature. Our results suggest that a few phylotypes of Verrucomicrobia make a considerable contribution to polysaccharide degradation, although they constituted only a minor fraction of the total microbial community. Genomic sequencing of five cells, representing the most predominant, polysaccharide-active Verrucomicrobia phylotype, revealed significant enrichment in genes encoding a wide spectrum of glycoside hydrolases, sulfatases, peptidases, carbohydrate lyases and esterases, confirming that these organisms were well equipped for the hydrolysis of diverse polysaccharides. Remarkably, this enrichment was on average higher than in the sequenced representatives of Bacteroidetes, which are frequently regarded as highly efficient biopolymer degraders. These findings shed light on the ecological roles of uncultured Verrucomicrobia and suggest specific taxa as promising bioprospecting targets. The employed method offers a powerful tool to rapidly identify and recover discrete genomes of active players in polysaccharide degradation, without the need for cultivation.
Chan, James W.; Liu, Rui; Matthews, Dennis L.
Laser tweezers Raman spectroscopy (LTRS) combines optical trapping with micro-Raman spectroscopy to enable label-free biochemical analysis of individual cells and small biological particles in suspension. The integration of the two technologies greatly simplifies the sample preparation and handling of suspension cells for spectroscopic analysis in physiologically meaningful conditions. In our group, LTRS has been used to study the effects of external perturbations, both chemical and mechanical, on the biochemistry of the cell. Single cell dynamics can be studied by performing longitudinal studies to continuously monitor the response of the cell as it interacts with its environment. The ability to carry out these measurements in-vitro makes LTRS an attractive tool for many biomedical applications. Here, we discuss the use of LTRS to study the response of cancer cells to chemotherapeutics and bacteria cells to antibiotics and show that the life cycle and apoptosis of the cells can be detected. These results show the promise of LTRS for drug discovery/screening, antibiotic susceptibility testing, and chemotherapy response monitoring applications. In separate experiments, we study the response of red blood cells to the mechanical forces imposed on the cell by the optical tweezers. A laser power dependent deoxygenation of the red blood cell in the single beam trap is reported. Normal, sickle cell, and fetal red blood cells have a different behavior that enables the discrimination of the cell types based on this mechanochemical response. These results show the potential utility of LTRS for diagnosing and studying red blood cell diseases.
This paper considers the uplink of a single-cell large-scale multiple-input multiple output (MIMO) system in which m mono-antenna users communicate with a base station (BS) outfitted by n antennas. We assume that the number of antennas at the BS and that of users take large values, as envisioned by large-scale MIMO systems. This allows for high spectral efficiency gains but obviously comes at the cost of higher complexity, a fact that becomes all the more critical as the number of antennas grows large. To solve this issue is to choose a subset of the available n antennas. The subset must be carefully chosen to achieve the best performance. However, finding the optimal subset of antennas is usually a difficult task, requiring one to solve a high dimensional combinatorial optimization problem. In this paper, we approach this problem in two ways. The first one consists in solving a convex relaxation of the problem using standard convex optimization tools. The second technique solves the problem using a greedy approach. The main advantages of the greedy approach lies in its wider scope, in that, unlike the first approach, it can be applied irrespective of the considered performance criterion. As an outcome of this feature, we show that the greedy approach can be applied even when only the channel statistics are available at the BS, which provides blind way to perform antenna selection.
Yang, Fen; Jacobsen, Susanne; Jørgensen, Hans J L
of humans and animals. In recent years, high-throughput proteomics, aiming at identifying a broad spectrum of proteins with a potential role in the pathogenicity and host resistance, has become a very useful tool in plant-fungus interaction research. In this review, we describe the progress in proteomics...... applications toward a better understanding of pathogenesis, virulence, and host defense mechanisms. The contribution of proteomics to the development of crop protection strategies against this pathogen is also discussed briefly....
Hjortland, Geir Olav; Fodstad, Oystein; Smeland, Sigbjorn; Hovig, Eivind; Meza-Zepeda, Leonardo A; Beiske, Klaus; Ree, Anne H; Tveito, Siri; Hoifodt, Hanne; Bohler, Per J; Hole, Knut H; Myklebost, Ola
Metastatic progression due to development or enrichment of therapy-resistant tumor cells is eventually lethal. Molecular characterization of such chemotherapy resistant tumor cell clones may identify markers responsible for malignant progression and potential targets for new treatment. Here, in a case of stage IV adenocarcinoma of the gastroesophageal junction, we report the successful genome wide analysis using array comparative genomic hybridization (CGH) of DNA from only fourteen tumor cells using a bead-based single cell selection method from a bone metastasis progressing during chemotherapy. In a case of metastatic adenocarcinoma of the gastroesophageal junction, the progression of bone metastasis was observed during a chemotherapy regimen of epirubicin, oxaliplatin and capecitabine, whereas lung-, liver and lymph node metastases as well as the primary tumor were regressing. A bone marrow aspirate sampled at the site of progressing metastasis in the right iliac bone was performed, and single cell molecular analysis using array-CGH of Epithelial Specific Antigen (ESA)-positive metastatic cells, and revealed two distinct regions of amplification, 12p12.1 and 17q12-q21.2 amplicons, containing the KRAS (12p) and ERBB2 (HER2/NEU) (17q) oncogenes. Further intrapatient tumor heterogeneity of these highlighted gene copy number changes was analyzed by fluorescence in situ hybridization (FISH) in all available primary and metastatic tumor biopsies, and ErbB2 protein expression was investigated by immunohistochemistry. ERBB2 was heterogeneously amplified by FISH analysis in the primary tumor, as well as liver and bone metastasis, but homogenously amplified in biopsy specimens from a progressing bone metastasis after three initial cycles of chemotherapy, indicating a possible enrichment of erbB2 positive tumor cells in the progressing bone marrow metastasis during chemotherapy. A similar amplification profile was detected for wild-type KRAS, although more heterogeneously
Screening of Chlamydomonas reinhardtii Populations with Single-Cell Resolution by Using a High-Throughput Microscale Sample Preparation for Matrix-Assisted Laser Desorption Ionization Mass Spectrometry.
Krismer, Jasmin; Sobek, Jens; Steinhoff, Robert F; Fagerer, Stephan R; Pabst, Martin; Zenobi, Renato
The consequences of cellular heterogeneity, such as biocide persistence, can only be tackled by studying each individual in a cell population. Fluorescent tags provide tools for the high-throughput analysis of genomes, RNA transcripts, or proteins on the single-cell level. However, the analysis of lower-molecular-weight compounds that elude tagging is still a great challenge. Here, we describe a novel high-throughput microscale sample preparation technique for single cells that allows a mass spectrum to be obtained for each individual cell within a microbial population. The approach presented includes spotting Chlamydomonas reinhardtii cells, using a noncontact microarrayer, onto a specialized slide and controlled lysis of cells separated on the slide. Throughout the sample preparation, analytes were traced and individual steps optimized using autofluorescence detection of chlorophyll. The lysates of isolated cells are subjected to a direct, label-free analysis using matrix-assisted laser desorption ionization mass spectrometry. Thus, we were able to differentiate individual cells of two Chlamydomonas reinhardtii strains based on single-cell mass spectra. Furthermore, we showed that only population profiles with real single-cell resolution render a nondistorted picture of the phenotypes contained in a population. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
Boehmer, Jamie L
The pursuit of biomarkers for use as clinical screening tools, measures for early detection, disease monitoring, and as a means for assessing therapeutic responses has steadily evolved in human and veterinary medicine over the past two decades. Concurrently, advances in mass spectrometry have markedly expanded proteomic capabilities for biomarker discovery. While initial mass spectrometric biomarker discovery endeavors focused primarily on the detection of modulated proteins in human tissues and fluids, recent efforts have shifted to include proteomic analyses of biological samples from food animal species. Mastitis continues to garner attention in veterinary research due mainly to affiliated financial losses and food safety concerns over antimicrobial use, but also because there are only a limited number of efficacious mastitis treatment options. Accordingly, comparative proteomic analyses of bovine milk have emerged in recent years. Efforts to prevent agricultural-related food-borne illness have likewise fueled an interest in the proteomic evaluation of several prominent strains of bacteria, including common mastitis pathogens. The interest in establishing biomarkers of the host and pathogen responses during bovine mastitis stems largely from the need to better characterize mechanisms of the disease, to identify reliable biomarkers for use as measures of early detection and drug efficacy, and to uncover potentially novel targets for the development of alternative therapeutics. The following review focuses primarily on comparative proteomic analyses conducted on healthy versus mastitic bovine milk. However, a comparison of the host defense proteome of human and bovine milk and the proteomic analysis of common veterinary pathogens are likewise introduced.
Vizcaíno, Juan Antonio; Walzer, Mathias; Jiménez, Rafael C; Bittremieux, Wout; Bouyssié, David; Carapito, Christine; Corrales, Fernando; Ferro, Myriam; Heck, Albert J R; Horvatovich, Peter; Hubalek, Martin; Lane, Lydie; Laukens, Kris; Levander, Fredrik; Lisacek, Frederique; Novak, Petr; Palmblad, Magnus; Piovesan, Damiano; Pühler, Alfred; Schwämmle, Veit; Valkenborg, Dirk; van Rijswijk, Merlijn; Vondrasek, Jiri; Eisenacher, Martin; Martens, Lennart; Kohlbacher, Oliver
Computational approaches have been major drivers behind the progress of proteomics in recent years. The aim of this white paper is to provide a framework for integrating computational proteomics into ELIXIR in the near future, and thus to broaden the portfolio of omics technologies supported by this European distributed infrastructure. This white paper is the direct result of a strategy meeting on 'The Future of Proteomics in ELIXIR' that took place in March 2017 in Tübingen (Germany), and involved representatives of eleven ELIXIR nodes. These discussions led to a list of priority areas in computational proteomics that would complement existing activities and close gaps in the portfolio of tools and services offered by ELIXIR so far. We provide some suggestions on how these activities could be integrated into ELIXIR's existing platforms, and how it could lead to a new ELIXIR use case in proteomics. We also highlight connections to the related field of metabolomics, where similar activities are ongoing. This white paper could thus serve as a starting point for the integration of computational proteomics into ELIXIR. Over the next few months we will be working closely with all stakeholders involved, and in particular with other representatives of the proteomics community, to further refine this paper.
Full Text Available The inner ear, one of the most complex organs, contains within its bony shell three sensory systems, the evolutionary oldest gravity receptor system, the three semicircular canals for the detection of angular acceleration, and the auditory system - unrivaled in sensitivity and frequency discrimination. All three systems are susceptible to a host of afflictions affecting the quality of life for all of us. In the first part of this review we present an introduction to the milestones of inner ear research to pave the way for understanding the complexities of a proteomics approach to the ear. Minute sensory structures, surrounded by large fluid spaces and a hard bony shell, pose extreme challenges to the ear researcher. In spite of these obstacles, a powerful preparatory technique was developed, whereby precisely defined microscopic tissue elements can be isolated and analyzed, while maintaining the biochemical state representative of the in vivo conditions. The second part consists of a discussion of proteomics as a tool in the elucidation of basic and pathologic mechanisms, diagnosis of disease, as well as treatment. Examples are the organ of Corti proteins OCP1 and OCP2, oncomodulin, a highly specific calcium-binding protein, and several disease entities, Meniere's disease, benign paroxysmal positional vertigo, and perilymphatic fistula.
Full Text Available The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation.
Snyder, John; Skovsen, Esben; Lambert, John D. C.
The lowest excited electronic state of molecular oxygen, singlet molecular oxygen, O2(a 1g), is a reactive species involved in many chemical and biological processes. To better understand the roles played by singlet oxygen in biological systems, particularly at the sub-cellular level, optical tools...... including across the cell membrane into the extracellular environment. On one hand, these results demonstrate that the behavior of singlet oxygen in an intact cell can be significantly different from that inferred from model bulk studies. More generally, these results provide a new perspective...
Zhang, Boyang; Huang, Kunlun; Zhu, Liye; Luo, Yunbo; Xu, Wentao
In this review, we introduce a new concept, precision toxicology: the mode of action of chemical- or drug-induced toxicity can be sensitively and specifically investigated by isolating a small group of cells or even a single cell with typical phenotype of interest followed by a single cell sequencing-based analysis. Precision toxicology can contribute to the better detection of subtle intracellular changes in response to exogenous substrates, and thus help researchers find solutions to control or relieve the toxicological effects that are serious threats to human health. We give examples for single cell isolation and recommend laser capture microdissection for in vivo studies and flow cytometric sorting for in vitro studies. In addition, we introduce the procedures for single cell sequencing and describe the expected application of these techniques to toxicological evaluations and mechanism exploration, which we believe will become a trend in toxicology.
Sanders, Ashley D; Falconer, Ester; Hills, Mark; Spierings, Diana C J; Lansdorp, Peter M.
The ability to distinguish between genome sequences of homologous chromosomes in single cells is important for studies of copy-neutral genomic rearrangements (such as inversions and translocations), building chromosome-length haplotypes, refining genome assemblies, mapping sister chromatid exchange
Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.
Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.
Xiao-hong Li; Fang-yin Meng
@@ PCR based single-cell DNA analysis has been widely used in forensic science, preimplantation genetic diagnosis and so on. However, the original sample cannot be efficiently retrieved following single cell PCR, consequently the amount of information gained is limited. HLA system is too sophisticated that it is very hard to complete HLA typing by single cell. A Taq polymerase-based method using random primers to amplify whole genome termed as whole genome amplification (WGA) has demonstrated to be a useful method in increasing the copies of minimum sample. We establish a technique in this study to amplify HLA-A and HLA-B loci at same time in a single cell using WGA.
Zhou, Ting; Matsunami, Hiroaki
The advent of single-cell RNA-sequencing (RNA-Seq) technology has enabled transcriptome profiling of individual cells. Comprehensive gene expression analysis at the single-cell level has proven to be effective in characterizing the most fundamental aspects of cellular function and identity. This unbiased approach is revolutionary for small and/or heterogeneous tissues like oxygen-sensing cells in identifying key molecules. Here, we review the major methods of current single-cell RNA-Seq technology. We discuss how this technology has advanced the understanding of oxygen-sensing glomus cells in the carotid body and helped uncover novel oxygen-sensing cells and mechanisms in the mice olfactory system. We conclude by providing our perspective on future single-cell RNA-Seq research directed at oxygen-sensing cells.
van Manen, H.J.; Otto, Cornelis
We have overcome the traditional incompatibility of Raman microscopy with fluorescence microscopy by exploiting the optical properties of semiconductor fluorescent quantum dots (QDs). Here we present a hybrid Raman fluorescence spectral imaging approach for single-cell microscopy applications. We
Zimny, Philip; Juncker, David; Reisner, Walter
Current single cell DNA analysis methods suffer from (i) bias introduced by the need for molecular amplification and (ii) limited ability to sequence repetitive elements, resulting in (iii) an inability to obtain information regarding long range genomic features. Recent efforts to circumvent these limitations rely on techniques for sensing single molecules of DNA extracted from single-cells. Here we demonstrate a droplet microfluidic approach for encapsulation and biochemical processing of single-cells inside alginate microparticles. In our approach, single-cells are first packaged inside the alginate microparticles followed by cell lysis, DNA purification, and labeling steps performed off-chip inside this microparticle system. The alginate microparticles are then introduced inside a micro/nanofluidic system where the alginate is broken down via a chelating buffer, releasing long DNA molecules which are then extended inside nanofluidic channels for analysis via standard mapping protocols.
Yang, Tie; Bragheri, Francesca; Nava, Giovanni
We realized an integrated microfluidic chip that allows measuring both optical deformability and acoustic compressibility on single cells, by optical stretching and acoustophoresis experiments respectively. Additionally, we propose a measurement protocol that allows evaluating the experimental ap...
Full text: Recent developments in the sequencing of the human genome have indicated that the number of coding gene sequences may be as few as 30,000. It is clear, however, that the complexity of the human species is dependent on the much greater diversity of the corresponding protein complement. Estimates of the diversity (discrete protein species) of the human proteome range from 200,000 to 300,000 at the lower end to 2,000,000 to 3,000,000 at the high end. In addition, proteomics (the study of the protein complement to the genome) has been subdivided into two main approaches. Global proteomics refers to a high throughput examination of the full protein set present in a cell under a given environmental condition. Focused proteomics refers to a more detailed study of a restricted set of proteins that are related to a specified biochemical pathway or subcellular structure. While many of the advances in proteomics will be based on the sequencing of the human genome, de novo characterization of protein microheterogeneity (glycosylation, phosphorylation and sulfation as well as the incorporation of lipid components) will be required in disease studies. To characterize these modifications it is necessary to digest the protein mixture with an enzyme to produce the corresponding mixture of peptides. In a process analogous to sequencing of the genome, shot-gun sequencing of the proteome is based on the characterization of the key fragments produced by such a digest. Thus, a glycopeptide and hence a specific glycosylation motif will be identified by a unique mass and then a diagnostic MS/MS spectrum. Mass spectrometry will be the preferred detector in these applications because of the unparalleled information content provided by one or more dimensions of mass measurement. In addition, highly efficient separation processes are an absolute requirement for advanced proteomic studies. For example, a combination of the orthogonal approaches, HPLC and HPCE, can be very powerful
Seger, R. Adam; Actis, Paolo; Penfold, Catherine; Maalouf, Michelle; Vilozny, Boaz; Pourmand, Nader
Manipulation and analysis of single cells is the next frontier in understanding processes that control the function and fate of cells. Herein we describe a single-cell injection platform based on nanopipettes. The system uses scanning microscopy techniques to detect cell surfaces, and voltage pulses to deliver molecules into individual cells. As a proof of concept, we injected adherent mammalian cells with fluorescent dyes. PMID:22899383
Stahlberg, A.; Rusňáková, Vendula; Forootan, A.; Anděrová, Miroslava; Kubista, Mikael
Roč. 59, č. 1 (2013), s. 80-88 ISSN 1046-2023 R&D Projects: GA MŠk(CZ) ME10052; GA ČR GAP303/10/1338 Institutional research plan: CEZ:AV0Z50520701 Institutional support: RVO:68378041 Keywords : RT-qPCR * Single-cell biology * Single-cell data analysis Subject RIV: EB - Genetics ; Molecular Biology; FH - Neurology (UEM-P) Impact factor: 3.221, year: 2013
Finak, Greg; McDavid, Andrew; Chattopadhyay, Pratip; Dominguez, Maria; De Rosa, Steve; Roederer, Mario; Gottardo, Raphael
Blood and tissue are composed of many functionally distinct cell subsets. In immunological studies, these can be measured accurately only using single-cell assays. The characterization of these small cell subsets is crucial to decipher system-level biological changes. For this reason, an increasing number of studies rely on assays that provide single-cell measurements of multiple genes and proteins from bulk cell samples. A common problem in the analysis of such data is to identify biomarkers...
Ezer, Daphne; Moignard, Victoria; G?ttgens, Berthold; Adryan, Boris
Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete ...
Single cell research has the potential to revolutionize experimental methods in biomedical sciences and contribute to clinical practices. Recent studies suggest analysis of single cells reveals novel features of intracellular processes, cell-to-cell interactions and cell structure. The methods of single cell analysis require mechanical resolution and accuracy that is not possible using conventional techniques. Robotic instruments and novel microdevices can achieve higher throughput and repeatability; however, the development of such instrumentation is a formidable task. A void exists in the state-of-the-art for automated analysis of single cells. With the increase in interest in single cell analyses in stem cell and cancer research the ability to facilitate higher throughput and repeatable procedures is necessary. In this paper, a high-throughput, single cell microarray-based robotic instrument, called the RoboSCell, is described. The proposed instrument employs a partially transparent single cell microarray (SCM) integrated with a robotic biomanipulator for in vitro analyses of live single cells trapped at the array sites. Cells, labeled with immunomagnetic particles, are captured at the array sites by channeling magnetic fields through encapsulated permalloy channels in the SCM. The RoboSCell is capable of systematically scanning the captured cells temporarily immobilized at the array sites and using optical methods to repeatedly measure extracellular and intracellular characteristics over time. The instrument\\'s capabilities are demonstrated by arraying human T lymphocytes and measuring the uptake dynamics of calcein acetoxymethylester-all in a fully automated fashion. © 2009 Springer Science+Business Media, LLC.
Guo, Guoji; Luc, Sidinh; Marco, Eugenio; Lin, Ta-Wei; Peng, Cong; Kerenyi, Marc A.; Beyaz, Semir; Kim, Woojin; Xu, Jian; Das, Partha Pratim; Neff, Tobias; Zou, Keyong; Yuan, Guo-Cheng; Orkin, Stuart H.
Stem cell differentiation pathways are most often studied at the population level, whereas critical decisions are executed at the level of single cells. We have established a highly multiplexed, quantitative PCR assay to profile in an unbiased manner a panel of all commonly used cell surface markers (280 genes) from individual cells. With this method we analyzed over 1500 single cells throughout the mouse hematopoietic system, and illustrate its utility for revealing important biological insi...
Falconer, Ester; Hills, Mark; Naumann, Ulrike; Poon, Steven S. S.; Chavez, Elizabeth A.; Sanders, Ashley D.; Zhao, Yongjun; Hirst, Martin; Lansdorp, Peter M.
DNA rearrangements such as sister chromatid exchanges (SCEs) are sensitive indicators of genomic stress and instability, but they are typically masked by single-cell sequencing techniques. We developed Strand-seq to independently sequence parental DNA template strands from single cells, making it possible to map SCEs at orders-of-magnitude greater resolution than was previously possible. On average, murine embryonic stem (mES) cells exhibit eight SCEs, which are detected at a resolution of up...
Full Text Available Objective. In the search of new human genotoxic biomarkers, the single cell gel electrophoresis assay has been proposed as a sensible alternative. Material and methods. This technique detects principally single strand breaks as well as alkali-labile and repair-retarded sites. Results. Herein we present our experience using the single cell gel electrophoresis assay in human population studies, both occupationally and environmentally exposed. Conclusions. We discuss the assay feasibility as a genotoxic biomarker.
Cudjoe, Emmanuel K; Saleh, Tareq; Hawkridge, Adam M; Gewirtz, David A
Autophagy, a conserved cellular process by which cells recycle their contents either to maintain basal homeostasis or in response to external stimuli, has for the past two decades become one of the most studied physiological processes in cell biology. The 2016 Nobel Prize in Medicine and Biology awarded to Dr. Ohsumi Yoshinori, one of the first scientists to characterize this cellular mechanism, attests to its importance. The induction and consequent completion of the process of autophagy results in wide ranging changes to the cellular proteome as well as the secretome. MS-based proteomics affords the ability to measure, in an unbiased manner, the ubiquitous changes that occur when autophagy is initiated and progresses in the cell. The continuous improvements and advances in mass spectrometers, especially relating to ionization sources and detectors, coupled with advances in proteomics experimental design, has made it possible to study autophagy, among other process, in great detail. Innovative labeling strategies and protein separation techniques as well as complementary methods including immuno-capture/blotting/staining have been used in proteomics studies to provide more specific protein identification. In this review, we will discuss recent advances in proteomics studies focused on autophagy. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Barsnes, Harald; Vaudel, Marc; Colaert, Niklaas; Helsens, Kenny; Sickmann, Albert; Berven, Frode S; Martens, Lennart
The growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with) spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool. In order to simplify the development of proteomics tools, we have implemented an open-source support library for computational proteomics, called compomics-utilities. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development. As a user-friendly, well-documented and open-source library, compomics-utilities greatly simplifies the implementation of the basic features needed in most proteomics tools. Implemented in 100% Java, compomics-utilities is fully portable across platforms and architectures. Our library thus allows the developers to focus on the novel aspects of their tools, rather than on the basic functions, which can contribute substantially to faster development, and better tools for proteomics.
Full Text Available Abstract Background The growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool. Results In order to simplify the development of proteomics tools, we have implemented an open-source support library for computational proteomics, called compomics-utilities. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development. Conclusions As a user-friendly, well-documented and open-source library, compomics-utilities greatly simplifies the implementation of the basic features needed in most proteomics tools. Implemented in 100% Java, compomics-utilities is fully portable across platforms and architectures. Our library thus allows the developers to focus on the novel aspects of their tools, rather than on the basic functions, which can contribute substantially to faster development, and better tools for proteomics.
Babin, Brett M.; Atangcho, Lydia; van Eldijk, Mark B.
involved in central carbon metabolism. We differentiated the immediate proteomic response, characterized by an increase in flagellar motility, from the long-term adaptive strategy, which included the upregulation of purine synthesis. This targeted, selective analysis of a bacterial subpopulation...... amino acid tagging (BONCAT) method to enable selective proteomic analysis of a Pseudomonas aeruginosa biofilm subpopulation. Through controlled expression of a mutant methionyl-tRNA synthetase, we targeted BONCAT labeling to cells in the regions of biofilm microcolonies that showed increased tolerance...... demonstrates how the study of proteome dynamics can enhance our understanding of biofilm heterogeneity and antibiotic tolerance. IMPORTANCE Bacterial growth is frequently characterized by behavioral heterogeneity at the single-cell level. Heterogeneity is especially evident in the physiology of biofilms...
Zhu, Ying; Piehowski, Paul D; Zhao, Rui; Chen, Jing; Shen, Yufeng; Moore, Ronald J; Shukla, Anil K; Petyuk, Vladislav A; Campbell-Thompson, Martha; Mathews, Clayton E; Smith, Richard D; Qian, Wei-Jun; Kelly, Ryan T
Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to 3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.
Agrawal, G.K.; Pedreschi, R.; Barkla, B.J.; Bindschedler, L.V.; Cramer, R.; Sarkar, A.; Renaut, J.; Job, D.; Rakwal, R.
Translational proteomics is an emerging sub-discipline of the proteomics field in the biological sciences. Translational plant proteomics aims to integrate knowledge from basic sciences to translate it into field applications to solve issues related but not limited to the recreational and economic
Wong, Ieong; Atsumi, Shota; Huang, Wei-Chih; Wu, Tung-Yun; Hanai, Taizo; Lam, Miu-Ling; Tang, Ping; Yang, Jian; Liao, James C; Ho, Chih-Ming
Significance of single cell measurements stems from the substantial temporal fluctuations and cell-cell variability possessed by individual cells. A major difficulty in monitoring surface non-adherent cells such as bacteria and yeast is that these cells tend to aggregate into clumps during growth, obstructing the tracking or identification of single-cells over long time periods. Here, we developed a microfluidic platform for long term single-cell tracking and cultivation with continuous media refreshing and dynamic chemical perturbation capability. The design highlights a simple device-assembly process between PDMS microchannel and agar membrane through conformal contact, and can be easily adapted by microbiologists for their routine laboratory use. The device confines cell growth in monolayer between an agar membrane and a glass surface. Efficient nutrient diffusion through the membrane and reliable temperature maintenance provide optimal growth condition for the cells, which exhibited fast exponential growth and constant distribution of cell sizes. More than 24 h of single-cell tracking was demonstrated on a transcription-metabolism integrated synthetic biological model, the gene-metabolic oscillator. Single cell morphology study under alcohol toxicity allowed us to discover and characterize cell filamentation exhibited by different E. coli isobutanol tolerant strains. We believe this novel device will bring new capabilities to quantitative microbiology, providing a versatile platform for single cell dynamic studies.
Liu, Mingshan; Liu, Yang; Di, Jiabo; Su, Zhe; Yang, Hong; Jiang, Beihai; Wang, Zaozao; Zhuang, Meng; Bai, Fan; Su, Xiangqian
Colorectal cancer is a heterogeneous group of malignancies with complex molecular subtypes. While colon cancer has been widely investigated, studies on rectal cancer are very limited. Here, we performed multi-region whole-exome sequencing and single-cell whole-genome sequencing to examine the genomic intratumor heterogeneity (ITH) of rectal tumors. We sequenced nine tumor regions and 88 single cells from two rectal cancer patients with tumors of the same molecular classification and characterized their mutation profiles and somatic copy number alterations (SCNAs) at the multi-region and the single-cell levels. A variable extent of genomic heterogeneity was observed between the two patients, and the degree of ITH increased when analyzed on the single-cell level. We found that major SCNAs were early events in cancer development and inherited steadily. Single-cell sequencing revealed mutations and SCNAs which were hidden in bulk sequencing. In summary, we studied the ITH of rectal cancer at regional and single-cell resolution and demonstrated that variable heterogeneity existed in two patients. The mutational scenarios and SCNA profiles of two patients with treatment naïve from the same molecular subtype are quite different. Our results suggest each tumor possesses its own architecture, which may result in different diagnosis, prognosis, and drug responses. Remarkable ITH exists in the two patients we have studied, providing a preliminary impression of ITH in rectal cancer.
Full Text Available Microfluidics-based single-cell study is an emerging approach in personalized treatment or precision medicine studies. Single-cell gene expression holds a potential to provide treatment selections with maximized efficacy to help cancer patients based on a genetic understanding of their disease. This work presents a multi-layer microchip for single-cell multiplexed gene expression profiling and genotoxicity detection. Treated by three drug reagents (i.e., methyl methanesulfonate, docetaxel and colchicine with varied concentrations and time lengths, individual human cancer cells (MDA-MB-231 are lysed on-chip, and the released mRNA templates are captured and reversely transcribed into single strand DNA. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH, cyclin-dependent kinase inhibitor 1A (CDKN1A, and aurora kinase A (AURKA genes from single cells are amplified and real-time quantified through multiplex polymerase chain reaction. The microchip is capable of integrating all steps of single-cell multiplexed gene expression profiling, and providing precision detection of drug induced genotoxic stress. Throughput has been set to be 18, and can be further increased following the same approach. Numerical simulation of on-chip single cell trapping and heat transfer has been employed to evaluate the chip design and operation.
Eldakak, Moustafa; Milad, Sanaa I. M.; Nawar, Ali I.; Rohila, Jai S.
A sharp decline in the availability of arable land and sufficient supply of irrigation water along with a continuous steep increase in food demands have exerted a pressure on farmers to produce more with fewer resources. A viable solution to release this pressure is to speed up the plant breeding process by employing biotechnology in breeding programs. The majority of biotechnological applications rely on information generated from various -omic technologies. The latest outstanding improve...
in plants under low N and iv) proteomes of uninfected plants were similar under two N levels. Correlation of level of proteolysis induced by the fungus with measurement of Fusarium-damaged kernels, fungal biomass and mycotoxin levels indicated that FHB was more severe in barley with low N. In Chapter 3......, the molecular mechanisms of barley defense to Fusarium graminearum at the early infection stage were studied. Antibodies against barley β-amylases were shown to be the markers for infection at proteome level and for selection of the time for proteome analysis before extensive degradation caused by the fungus...... the disease. Due to the advantages of gel-based proteomics that differentially expressed proteins involved in the interaction can be directly detected by comparing protein profiles displayed on 2-D gels, it is used as a tool for studying the barley- Fusarium graminearum interaction form three different...
Zhang, Zheng; Milias-Argeitis, Andreas; Heinemann, Matthias
Recent work has shown that metabolism between individual bacterial cells in an otherwise isogenetic population can be different. To investigate such heterogeneity, experimental methods to zoom into the metabolism of individual cells are required. To this end, the autofluoresence of the redox cofactors NADH and NADPH offers great potential for single-cell dynamic NAD(P)H measurements. However, NAD(P)H excitation requires UV light, which can cause cell damage. In this work, we developed a method for time-lapse NAD(P)H imaging in single E. coli cells. Our method combines a setup with reduced background emission, UV-enhanced microscopy equipment and optimized exposure settings, overall generating acceptable NAD(P)H signals from single cells, with minimal negative effect on cell growth. Through different experiments, in which we perturb E. coli's redox metabolism, we demonstrated that the acquired fluorescence signal indeed corresponds to NAD(P)H. Using this new method, for the first time, we report that intracellular NAD(P)H levels oscillate along the bacterial cell division cycle. The developed method for dynamic measurement of NAD(P)H in single bacterial cells will be an important tool to zoom into metabolism of individual cells.
Uveal melanoma is the most common primary intraocular malignancy in adults, with an incidence of 5-7 per million per year. It is associated with the development of metastasis in about 50% of cases, and 40% of patients with uveal melanoma die of metastatic disease despite successful treatment of the primary tumour. The survival rates at 5, 10 and 15 years are 65%, 50% and 45% respectively. Unlike progress made in many other areas of cancer, uveal melanoma is still poorly understood and survival rates have remained similar over the past 25 years. Recently, advances made in molecular genetics have improved our understanding of this disease and stratification of patients into low risk and high risk for developing metastasis. However, only a limited number of studies have been performed using proteomic methods. This review will give an overview of various proteomic technologies currently employed in life sciences research, and discuss proteomic studies of uveal melanoma.
Lovegrove, Alison; Salt, Louise; Shewry, Peter R.
Wheat is a major crop in world agriculture and is consumed after processing into a range of food products. It is therefore of great importance to determine the consequences (intended and unintended) of transgenesis in wheat and whether genetically modified lines are substantially equivalent to those produced by conventional plant breeding. Proteomic analysis is one of several approaches which can be used to address these questions. Two-dimensional PAGE (2D PAGE) remains the most widely available method for proteomic analysis, but is notoriously difficult to reproduce between laboratories. We therefore describe methods which have been developed as standard operating procedures in our laboratory to ensure the reproducibility of proteomic analyses of wheat using 2D PAGE analysis of grain proteins.
Silva, Tomé Santos; Richard, Nadege; Dias, Jorge P.
-based proteomics, summarizing the current state of research within this field. Particular focus is given on discussing the usefulness of available multivariate analysis tools both for data visualization and feature selection purposes. Visual examples are given using a real gel-based proteomic dataset as basis....
Dietrich, H.R.C.; Young, I.T.; Garini, Y.
The intense research in proteomics is demanding for fast, reliable and easy-to-use methods in order to study the proteome. In this proceeding we report the development of such a novel research tool based on spectral imaging and Resonance Light Scattering gold particles. This method will allow the
Go, Young-Mi; Jones, Dean P.
The redox proteome consists of reversible and irreversible covalent modifications that link redox metabolism to biologic structure and function. These modifications, especially of Cys, function at the molecular level in protein folding and maturation, catalytic activity, signaling, and macromolecular interactions and at the macroscopic level in control of secretion and cell shape. Interaction of the redox proteome with redox-active chemicals is central to macromolecular structure, regulation, and signaling during the life cycle and has a central role in the tolerance and adaptability to diet and environmental challenges. PMID:23861437
Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wisniewski, Jacek R; Jun, Wang; Mann, Matthias
Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.
Maurer, Martin H
Whereas genomics describes the study of genome, mainly represented by its gene expression on the DNA or RNA level, the term proteomics denotes the study of the proteome, which is the protein complement encoded by the genome. In recent years, the number of proteomic experiments increased tremendously. While all fields of proteomics have made major technological advances, the biggest step was seen in bioinformatics. Biological information management relies on sequence and structure databases and powerful software tools to translate experimental results into meaningful biological hypotheses and answers. In this resource article, I provide a collection of databases and software available on the Internet that are useful to interpret genomic and proteomic data. The article is a toolbox for researchers who have genomic or proteomic datasets and need to put their findings into a biological context.
Agrawal, Ganesh Kumar; Pedreschi, Romina; Barkla, Bronwyn J; Bindschedler, Laurence Veronique; Cramer, Rainer; Sarkar, Abhijit; Renaut, Jenny; Job, Dominique; Rakwal, Randeep
Translational proteomics is an emerging sub-discipline of the proteomics field in the biological sciences. Translational plant proteomics aims to integrate knowledge from basic sciences to translate it into field applications to solve issues related but not limited to the recreational and economic values of plants, food security and safety, and energy sustainability. In this review, we highlight the substantial progress reached in plant proteomics during the past decade which has paved the way for translational plant proteomics. Increasing proteomics knowledge in plants is not limited to model and non-model plants, proteogenomics, crop improvement, and food analysis, safety, and nutrition but to many more potential applications. Given the wealth of information generated and to some extent applied, there is the need for more efficient and broader channels to freely disseminate the information to the scientific community. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.
Bonomini, Mario; Pieroni, Luisa; Di Liberato, Lorenzo; Sirolli, Vittorio; Urbani, Andrea
The success and the quality of hemodialysis therapy are mainly related to both clearance and biocompatibility properties of the artificial membrane packed in the hemodialyzer. Performance of a membrane is strongly influenced by its interaction with the plasma protein repertoire during the extracorporeal procedure. Recognition that a number of medium-high molecular weight solutes, including proteins and protein-bound molecules, are potentially toxic has prompted the development of more permeable membranes. Such membrane engineering, however, may cause loss of vital proteins, with membrane removal being nonspecific. In addition, plasma proteins can be adsorbed onto the membrane surface upon blood contact during dialysis. Adsorption can contribute to the removal of toxic compounds and governs the biocompatibility of a membrane, since surface-adsorbed proteins may trigger a variety of biologic blood pathways with pathophysiologic consequences. Over the last years, use of proteomic approaches has allowed polypeptide spectrum involved in the process of hemodialysis, a key issue previously hampered by lack of suitable technology, to be assessed in an unbiased manner and in its full complexity. Proteomics has been successfully applied to identify and quantify proteins in complex mixtures such as dialysis outflow fluid and fluid desorbed from dialysis membrane containing adsorbed proteins. The identified proteins can also be characterized by their involvement in metabolic and signaling pathways, molecular networks, and biologic processes through application of bioinformatics tools. Proteomics may thus provide an actual functional definition as to the effect of a membrane material on plasma proteins during hemodialysis. Here, we review the results of proteomic studies on the performance of hemodialysis membranes, as evaluated in terms of solute removal efficiency and blood-membrane interactions. The evidence collected indicates that the information provided by proteomic
Full Text Available Single cell manipulation technology has been widely applied in biological fields, such as cell injection/enucleation, cell physiological measurement, and cell imaging. Recently, a biochip platform with a novel configuration of electrodes for cell 3D rotation has been successfully developed by generating rotating electric fields. However, the rotation platform still has two major shortcomings that need to be improved. The primary problem is that there is no on-chip module to facilitate the placement of a single cell into the rotation chamber, which causes very low efficiency in experiment to manually pipette single 10-micron-scale cells into rotation position. Secondly, the cell in the chamber may suffer from unstable rotation, which includes gravity-induced sinking down to the chamber bottom or electric-force-induced on-plane movement. To solve the two problems, in this paper we propose a new microfluidic chip with manipulation capabilities of single cell trap and single cell 3D stable rotation, both on one chip. The new microfluidic chip consists of two parts. The top capture part is based on the least flow resistance principle and is used to capture a single cell and to transport it to the rotation chamber. The bottom rotation part is based on dielectrophoresis (DEP and is used to 3D rotate the single cell in the rotation chamber with enhanced stability. The two parts are aligned and bonded together to form closed channels for microfluidic handling. Using COMSOL simulation and preliminary experiments, we have verified, in principle, the concept of on-chip single cell traps and 3D stable rotation, and identified key parameters for chip structures, microfluidic handling, and electrode configurations. The work has laid a solid foundation for on-going chip fabrication and experiment validation.
Full Text Available Combining single-cell methods and next-generation sequencing should provide a powerful means to understand single-cell biology and obviate the effects of sample heterogeneity. Here we report a single-cell identification method and seamless cancer gene profiling using semiconductor-based massively parallel sequencing. A549 cells (adenocarcinomic human alveolar basal epithelial cell line were used as a model. Single-cell capture was performed using laser capture microdissection (LCM with an Arcturus® XT system, and a captured single cell and a bulk population of A549 cells (≈106 cells were subjected to whole genome amplification (WGA. For cell identification, a multiplex PCR method (AmpliSeq™ SNP HID panel was used to enrich 136 highly discriminatory SNPs with a genotype concordance probability of 1031–35. For cancer gene profiling, we used mutation profiling that was performed in parallel using a hotspot panel for 50 cancer-related genes. Sequencing was performed using a semiconductor-based bench top sequencer. The distribution of sequence reads for both HID and Cancer panel amplicons was consistent across these samples. For the bulk population of cells, the percentages of sequence covered at coverage of more than 100× were 99.04% for the HID panel and 98.83% for the Cancer panel, while for the single cell percentages of sequence covered at coverage of more than 100× were 55.93% for the HID panel and 65.96% for the Cancer panel. Partial amplification failure or randomly distributed non-amplified regions across samples from single cells during the WGA procedures or random allele drop out probably caused these differences. However, comparative analyses showed that this method successfully discriminated a single A549 cancer cell from a bulk population of A549 cells. Thus, our approach provides a powerful means to overcome tumor sample heterogeneity when searching for somatic mutations.
Perdian, D C; Cha, Sangwon; Oh, Jisun; Sakaguchi, Donald S; Yeung, Edward S; Lee, Young Jin
Mass spectrometric imaging has been utilized to localize individual astrocytes and to obtain cholesterol populations at the single-cell level in laser desorption ionization (LDI) with colloidal silver. The silver ion adduct of membrane-bound cholesterol was monitored to detect individual cells. Good correlation between mass spectrometric and optical images at different cell densities indicates the ability to perform single-cell studies of cholesterol abundance. The feasibility of quantification is confirmed by the agreement between the LDI-MS ion signals and the results from a traditional enzymatic fluorometric assay. We propose that this approach could be an effective tool to study chemical populations at the cellular level. Published in 2010 by John Wiley & Sons, Ltd.
Matysiak, Magdalena; Kapka-Skrzypczak, Lucyna; Brzóska, Kamil; Gutleb, Arno C; Kruszewski, Marcin
In recent years a large number of engineered nanomaterials (NMs) have been developed with promising technical benefits for consumers and medical appliances. In addition to already known potentially advantageous biological properties (antibiotic, antifungal and antiviral activity) of NMs, many new medical applications of NMs are foreseen, such as drug carriers, contrast agents, radiopharmaceuticals and many others. However, there is increasing concern about potential environmental and health effects due to NMs exposure. An increasing body of evidence suggests that NMs may trigger undesirable hazardous interactions with biological systems with potential to generate harmful effects. In this review we summarized a current state of knowledge on the proteomics approaches to nanotoxicity, including protein corona formation, in vitro and in vivo effects of exposure to NMs on proteome of different classes of organisms, from bacteria and plants to mammals. The effects of NMs on the proteome of environmentally relevant organisms are also described. Despite the benefit that development of nanotechnology may bring to the society, there are still major gaps of knowledge on the influence of nanomaterials on human health and the environment. Thus, it seems necessary to conduct further interdisciplinary research to fill the knowledge gaps in NM toxicity, using more holistic approaches than offered by conventional biological techniques. “OMICS” techniques will certainly help researchers in this field. In this paper we summarized the current stage of knowledge of the effects of nanoparticles on the proteome of different organisms, including those commonly used as an environmentally relevant indicator organisms.
John D. Bussell
Full Text Available The analytical depth of investigation of the peroxisomal proteome of the model plant Arabidopsis thaliana has not yet reached that of other major cellular organelles such as chloroplasts or mitochondria. This is primarily due to the difficulties associated with isolating and obtaining purified samples of peroxisomes from Arabidopsis. So far only a handful of research groups have been successful in obtaining such fractions. To make things worse, enriched peroxisome fractions frequently suffer from significant organellar contamination, lowering confidence in localization assignment of the identified proteins. As with other cellular compartments, identification of peroxisomal proteins forms the basis for investigations of the dynamics of the peroxisomal proteome. It is therefore not surprising that, in terms of functional analyses by proteomic means, there remains a considerable gap between peroxisomes and chloroplasts or mitochondria. Alternative strategies are needed to overcome the obstacle of hard-to-obtain organellar fractions. This will help to close the knowledge gap between peroxisomes and other organelles and provide a full picture of the physiological pathways shared between organelles. In this review we briefly summarize the status quo and discuss some of the methodological alternatives to classic organelle proteomic approaches.
de Bernonville, Thomas Dugé; Albenne, Cécile; Arlat, Matthieu; Hoffmann, Laurent; Lauber, Emmanuelle; Jamet, Elisabeth
Proteomic analysis of xylem sap has recently become a major field of interest to understand several biological questions related to plant development and responses to environmental clues. The xylem sap appears as a dynamic fluid undergoing changes in its proteome upon abiotic and biotic stresses. Unlike cell compartments which are amenable to purification in sufficient amount prior to proteomic analysis, the xylem sap has to be collected in particular conditions to avoid contamination by intracellular proteins and to obtain enough material. A model plant like Arabidopsis thaliana is not suitable for such an analysis because efficient harvesting of xylem sap is difficult. The analysis of the xylem sap proteome also requires specific procedures to concentrate proteins and to focus on proteins predicted to be secreted. Indeed, xylem sap proteins appear to be synthesized and secreted in the root stele or to originate from dying differentiated xylem cells. This chapter describes protocols to collect xylem sap from Brassica species and to prepare total and N-glycoprotein extracts for identification of proteins by mass spectrometry analyses and bioinformatics.
Bunkenborg, Jakob; Espadas, Guadalupe; Molina, Henrik
Tryptic digestion is an important component of most proteomics experiments, and trypsin is available from many sources with a cost that varies by more than 1000-fold. This high-mass-accuracy LC-MS study benchmarks six commercially available trypsins with respect to autolytic species and sequence ...
Rella, Lorenzo; Fernandes Póvoa, Euclides E; Korswagen, Hendrik C
During development, cell migration plays a central role in the formation of tissues and organs. Understanding the molecular mechanisms that drive and control these migrations is a key challenge in developmental biology that will provide important insights into disease processes, including cancer cell metastasis. In this article, we discuss the Caenorhabditis elegans Q neuroblasts and their descendants as a tool to study cell migration at single-cell resolution in vivo. The highly stereotypical migration of these cells provides a powerful system to study the dynamic cytoskeletal processes that drive migration as well as the evolutionarily conserved signaling pathways (including different Wnt signaling cascades) that guide the cells along their specific trajectories. Here, we provide an overview of what is currently known about Q neuroblast migration and highlight the live-cell imaging, genome editing, and quantitative gene expression techniques that have been developed to study this process. © 2016 Wiley Periodicals, Inc.
Catanzaro, Daniele; Shackney, Stanley E; Schaffer, Alejandro A; Schwartz, Russell
Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints.
Panisko, Ellen A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Grigoriev, Igor [USDOE Joint Genome Inst., Walnut Creek, CA (United States); Daly, Don S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Webb-Robertson, Bobbie-Jo [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Baker, Scott E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Biologists are awash with genomic sequence data. In large part, this is due to the rapid acceleration in the generation of DNA sequence that occurred as public and private research institutes raced to sequence the human genome. In parallel with the large human genome effort, mostly smaller genomes of other important model organisms were sequenced. Projects following on these initial efforts have made use of technological advances and the DNA sequencing infrastructure that was built for the human and other organism genome projects. As a result, the genome sequences of many organisms are available in high quality draft form. While in many ways this is good news, there are limitations to the biological insights that can be gleaned from DNA sequences alone; genome sequences offer only a bird's eye view of the biological processes endemic to an organism or community. Fortunately, the genome sequences now being produced at such a high rate can serve as the foundation for other global experimental platforms such as proteomics. Proteomic methods offer a snapshot of the proteins present at a point in time for a given biological sample. Current global proteomics methods combine enzymatic digestion, separations, mass spectrometry and database searching for peptide identification. One key aspect of proteomics is the prediction of peptide sequences from mass spectrometry data. Global proteomic analysis uses computational matching of experimental mass spectra with predicted spectra based on databases of gene models that are often generated computationally. Thus, the quality of gene models predicted from a genome sequence is crucial in the generation of high quality peptide identifications. Once peptides are identified they can be assigned to their parent protein. Proteins identified as expressed in a given experiment are most useful when compared to other expressed proteins in a larger biological context or biochemical pathway. In this chapter we will discuss the automatic
Teschendorff, Andrew E.; Enver, Tariq
The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes. PMID:28569836
Zhu, Jiang; Wooh, Jong Wei; Hou, Jeff Jia Cheng; Hughes, Benjamin S; Gray, Peter P; Munro, Trent P
Biologic drugs, such as monoclonal antibodies, are commonly made using mammalian cells in culture. The cell lines used for manufacturing should ideally be clonal, meaning derived from a single cell, which represents a technically challenging process. Fetal bovine serum is often used to support low cell density cultures, however, from a regulatory perspective, it is preferable to avoid animal-derived components to increase process consistency and reduce the risk of contamination from adventitious agents. Chinese hamster ovary (CHO) cells are the most widely used cell line in industry and a large number of serum-free, protein-free, and fully chemically defined growth media are commercially available, although these media alone do not readily support efficient single cell cloning. In this work, we have developed a simple, fully defined, single-cell cloning media, specifically for CHO cells, using commercially available reagents. Our results show that a 1:1 mixture of CD-CHO™ and DMEM/F12 supplemented with 1.5 g/L of recombinant albumin (Albucult®) supports single cell cloning. This formulation can support recovery of single cells in 43% of cultures compared to 62% in the presence of serum. Copyright © 2012 American Institute of Chemical Engineers (AIChE).
Tang, Lijun; Zhou, Nan
Single-cell RNA sequencing (RNA-seq) allows the analysis of gene expression with high resolution. The intrinsic defects of this promising technology imports technical noise into the single-cell RNA-seq data, increasing the difficulty of accurate downstream inference. Normalization is a crucial step in single-cell RNA-seq data pre-processing. SCnorm is an accurate and efficient method that can be used for this purpose. An R implementation of this method is currently available. On one hand, the R package possesses many excellent features from R. On the other hand, R programming ability is required, which prevents the biologists who lack the skills from learning to use it quickly. To make this method more user-friendly, we developed a graphical user interface, visnormsc, for normalization of single-cell RNA-seq data. It is implemented in Python and is freely available at https://github.com/solo7773/visnormsc . Although visnormsc is based on the existing method, it contributes to this field by offering a user-friendly alternative. The out-of-the-box and cross-platform features make visnormsc easy to learn and to use. It is expected to serve biologists by simplifying single-cell RNA-seq normalization.
Nagano, Takashi; Wingett, Steven W; Fraser, Peter
Hi-C is a powerful method to investigate genome-wide, higher-order chromatin and chromosome conformations averaged from a population of cells. To expand the potential of Hi-C for single-cell analysis, we developed single-cell Hi-C. Similar to the existing "ensemble" Hi-C method, single-cell Hi-C detects proximity-dependent ligation events between cross-linked and restriction-digested chromatin fragments in cells. A major difference between the single-cell Hi-C and ensemble Hi-C protocol is that the proximity-dependent ligation is carried out in the nucleus. This allows the isolation of individual cells in which nearly the entire Hi-C procedure has been carried out, enabling the production of a Hi-C library and data from individual cells. With this new method, we studied genome conformations and found evidence for conserved topological domain organization from cell to cell, but highly variable interdomain contacts and chromosome folding genome wide. In addition, we found that the single-cell Hi-C protocol provided cleaner results with less technical noise suggesting it could be used to improve the ensemble Hi-C technique.
Giustacchini, Alice; Thongjuea, Supat; Barkas, Nikolaos; Woll, Petter S; Povinelli, Benjamin J; Booth, Christopher A G; Sopp, Paul; Norfo, Ruggiero; Rodriguez-Meira, Alba; Ashley, Neil; Jamieson, Lauren; Vyas, Paresh; Anderson, Kristina; Segerstolpe, Åsa; Qian, Hong; Olsson-Strömberg, Ulla; Mustjoki, Satu; Sandberg, Rickard; Jacobsen, Sten Eirik W; Mead, Adam J
Recent advances in single-cell transcriptomics are ideally placed to unravel intratumoral heterogeneity and selective resistance of cancer stem cell (SC) subpopulations to molecularly targeted cancer therapies. However, current single-cell RNA-sequencing approaches lack the sensitivity required to reliably detect somatic mutations. We developed a method that combines high-sensitivity mutation detection with whole-transcriptome analysis of the same single cell. We applied this technique to analyze more than 2,000 SCs from patients with chronic myeloid leukemia (CML) throughout the disease course, revealing heterogeneity of CML-SCs, including the identification of a subgroup of CML-SCs with a distinct molecular signature that selectively persisted during prolonged therapy. Analysis of nonleukemic SCs from patients with CML also provided new insights into cell-extrinsic disruption of hematopoiesis in CML associated with clinical outcome. Furthermore, we used this single-cell approach to identify a blast-crisis-specific SC population, which was also present in a subclone of CML-SCs during the chronic phase in a patient who subsequently developed blast crisis. This approach, which might be broadly applied to any malignancy, illustrates how single-cell analysis can identify subpopulations of therapy-resistant SCs that are not apparent through cell-population analysis.
Full Text Available Chronic obstructive pulmonary disease (COPD is a complex disorder involving both airways and lung parenchyma, usually associated with progressive and poorly reversible airflow limitation. In order to better characterize the phenotypic heterogeneity and the prognosis of patients with COPD, there is currently an urgent need for discovery and validation of reliable disease biomarkers. Within this context, proteomic and peptidomic techniques are emerging as very valuable tools that can be applied to both systemic and pulmonary samples, including peripheral blood, induced sputum, exhaled breath condensate, bronchoalveolar lavage fluid, and lung tissues. Identification of COPD biomarkers by means of proteomic and peptidomic approaches can thus also lead to discovery of new molecular targets potentially useful to improve and personalize the therapeutic management of this widespread respiratory disease.
Kranenburg, Onno; Emmink, Benjamin L; Knol, Jaco; van Houdt, Winan J; Rinkes, Inne H M Borel; Jimenez, Connie R
Normal multipotent tissue stem cells (SCs) are the driving force behind tissue turnover and repair. The cancer stem cell theory holds that tumors also contain stem-like cells that drive tumor growth and metastasis formation. However, very little is known about the regulation of SC maintenance pathways in cancer and how these are affected by cancer-specific genetic alterations and by treatment. Proteomics is emerging as a powerful tool to identify the signaling complexes and pathways that control multi- and pluri-potency and SC differentiation. Here, the authors review the novel insights that these studies have provided and present a comprehensive strategy for the use of proteomics in studying cancer SC biology.
Deutsch, Eric W; Orchard, Sandra; Binz, Pierre-Alain; Bittremieux, Wout; Eisenacher, Martin; Hermjakob, Henning; Kawano, Shin; Lam, Henry; Mayer, Gerhard; Menschaert, Gerben; Perez-Riverol, Yasset; Salek, Reza M; Tabb, David L; Tenzer, Stefan; Vizcaíno, Juan Antonio; Walzer, Mathias; Jones, Andrew R
The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI.
Rieger, Michael A; Schroeder, Timm
Cytokines are important regulators of cell fates with high clinical and commercial relevance. However, despite decades of intense academic and industrial research, it proved surprisingly difficult to describe the biological functions of cytokines in a precise and comprehensive manner. The exact analysis of cytokine biology is complicated by the fact that individual cytokines control many different cell fates and activate a multitude of intracellular signaling pathways. Moreover, although activating different molecular programs, different cytokines can be redundant in their biological effects. In addition, cytokines with different biological effects can activate overlapping signaling pathways. This prospect article will outline the necessity of continuous single cell biochemistry to unravel the biological functions of molecular cytokine signaling. It focuses on potentials and limitations of recent technical developments in fluorescent time-lapse imaging and single cell tracking allowing constant long-term observation of molecules and behavior of single cells. (c) 2009 Wiley-Liss, Inc.
Huang, Lei; Ma, Fei; Chapman, Alec; Lu, Sijia; Xie, Xiaoliang Sunney
We present a survey of single-cell whole-genome amplification (WGA) methods, including degenerate oligonucleotide-primed polymerase chain reaction (DOP-PCR), multiple displacement amplification (MDA), and multiple annealing and looping-based amplification cycles (MALBAC). The key parameters to characterize the performance of these methods are defined, including genome coverage, uniformity, reproducibility, unmappable rates, chimera rates, allele dropout rates, false positive rates for calling single-nucleotide variations, and ability to call copy-number variations. Using these parameters, we compare five commercial WGA kits by performing deep sequencing of multiple single cells. We also discuss several major applications of single-cell genomics, including studies of whole-genome de novo mutation rates, the early evolution of cancer genomes, circulating tumor cells (CTCs), meiotic recombination of germ cells, preimplantation genetic diagnosis (PGD), and preimplantation genomic screening (PGS) for in vitro-fertilized embryos.
Borgström, Erik; Paterlini, Marta; Mold, Jeff E; Frisen, Jonas; Lundeberg, Joakim
Whole genome amplification (WGA) is currently a prerequisite for single cell whole genome or exome sequencing. Depending on the method used the rate of artifact formation, allelic dropout and sequence coverage over the genome may differ significantly. The largest difference between the evaluated protocols was observed when analyzing the target coverage and read depth distribution. These differences also had impact on the downstream variant calling. Conclusively, the products from the AMPLI1 and MALBAC kits were shown to be most similar to the bulk samples and are therefore recommended for WGA of single cells. In this study four commercial kits for WGA (AMPLI1, MALBAC, Repli-G and PicoPlex) were used to amplify human single cells. The WGA products were exome sequenced together with non-amplified bulk samples from the same source. The resulting data was evaluated in terms of genomic coverage, allelic dropout and SNP calling.
Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Rantalainen, Mattias; Pawitan, Yudi
Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: email@example.com or firstname.lastname@example.org Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com.
Dineshram, R.; Wong, Kelvin K.W.; Xiao, Shu; Yu, Ziniu; Qian, Pei Yuan; Thiyagarajan, Vengatesen
Most calcifying organisms show depressed metabolic, growth and calcification rates as symptoms to high-CO2 due to ocean acidification (OA) process. Analysis of the global expression pattern of proteins (proteome analysis) represents a powerful tool
Full Text Available Single cell sorting based either on fluorescence or on mechanical properties has been exploited in the last years in microfluidic devices. Hydrodynamic focusing allows increasing the efficiency of theses devices by improving the matching between the region of optical analysis and that of cell flow. Here we present a very simple solution fabricated by femtosecond laser micromachining that exploits flow laminarity in microfluidic channels to easily lift the sample flowing position to the channel portion illuminated by the optical waveguides used for single cell trapping and analysis.
Ullal, Adeeti V; Weissleder, Ralph
We describe a DNA-barcoded antibody sensing technique for single cell protein analysis in which the barcodes are photocleaved and digitally detected without amplification steps (Ullal et al., Sci Transl Med 6:219, 2014). After photocleaving the unique ~70 mer DNA barcodes we use a fluorescent hybridization technology for detection, similar to what is commonly done for nucleic acid readouts. This protocol offers a simple method for multiplexed protein detection using 100+ antibodies and can be performed on clinical samples as well as single cells.
Perozziello, Gerardo; Candeloro, Patrizio; De Grazia, Antonio
In this work a Raman flow cytometer is presented. It consists of a microfluidic device that takes advantages of the basic principles of Raman spectroscopy and flow cytometry. The microfluidic device integrates calibrated microfluidic channels-where the cells can flow one-by-one -, allowing single...... cell Raman analysis. The microfluidic channel integrates plasmonic nanodimers in a fluidic trapping region. In this way it is possible to perform Enhanced Raman Spectroscopy on single cell. These allow a label-free analysis, providing information about the biochemical content of membrane and cytoplasm...
Salvato, Fernanda; Havelund, Jesper Foged; Chen, Mingjie
Mitochondria are called the powerhouses of the cell. To better understand the role of mitochondria in maintaining and regulating metabolism in storage tissues, highly purified mitochondria were isolated from dormant potato tubers (Solanum tuberosum 'Folva') and their proteome investigated. Proteins...... manner using normalized spectral counts including as many as 5-fold more "extreme" proteins (low mass, high isoelectric point, hydrophobic) than previous mitochondrial proteome studies. We estimate that this compendium of proteins represents a high coverage of the potato tuber mitochondrial proteome...
Romagnolo, Donato F.; Milner, John A.
Knowledge gaps persist about the efficacy of cancer prevention strategies based on dietary food components. Adaptations to nutrient supply are executed through tuning of multiple protein networks that include transcription factors, histones, modifying enzymes, translation factors, membrane and nuclear receptors, and secreted proteins. However, the simultaneous quantitative and qualitative measurement of all proteins that regulate cancer processes is not practical using traditional protein methodologies. Proteomics offers an attractive opportunity to fill this knowledge gap and unravel the effects of dietary components on protein networks that impinge on cancer. The articles presented in this supplement are from talks proffered in the “Nutrition Proteomics and Cancer Prevention” session at the American Institute for Cancer Research Annual Research Conference on Food, Nutrition, Physical Activity and Cancer held in Washington, DC on October 21 and 22, 2010. Recent advances in MS technologies suggest that studies in nutrition and cancer prevention may benefit from the adoption of proteomic tools to elucidate the impact on biological processes that govern the transition from normal to malignant phenotype; to identify protein changes that determine both positive and negative responses to food components; to assess how protein networks mediate dose-, time-, and tissue-dependent responses to food components; and, finally, for predicting responders and nonresponders. However, both the limited accessibility to proteomic technologies and research funding appear to be hampering the routine adoption of proteomic tools in nutrition and cancer prevention research. PMID:22649262
Navrot, Nicolas; Finnie, Christine; Svensson, Birte
PTMs in regulating enzymatic activities and controlling biological processes in plants. Notably, proteins controlling the cellular redox state, e.g. thioredoxin and glutaredoxin, appear to play dual roles to maintain oxidative stress resistance and regulate signal transduction pathways via redox PTMs......In common with other aerobic organisms, plants are exposed to reactive oxygen species resulting in formation of post-translational modifications related to protein oxidoreduction (redox PTMs) that may inflict oxidative protein damage. Accumulating evidence also underscores the importance of redox....... To get a comprehensive overview of these types of redox-regulated pathways there is therefore an emerging interest to monitor changes in redox PTMs on a proteome scale. Compared to some other PTMs, e.g. protein phosphorylation, redox PTMs have received less attention in plant proteome analysis, possibly...
Rodrigues, Pedro M.; Silva, Tomé S.; Dias, Jorge
Over the last forty years global aquaculture presented a growth rate of 6.9% per annum with an amazing production of 52.5million tonnes in 2008, and a contribution of 43% of aquatic animal food for human consumption. In order to meet the world's health requirements of fish protein, a continuous...... growth in production is still expected for decades to come. Aquaculture is, though, a very competitive market, and a global awareness regarding the use of scientific knowledge and emerging technologies to obtain a better farmed organism through a sustainable production has enhanced the importance...... questions and the role of proteomics in their investigation, outlining the advantages, disadvantages and future challenges. A brief description of the proteomics technical approaches will be presented. Special focus will be on the latest trends related to the aquaculture production of fish with defined...
Millar, A.H.; Heazlewood, J.L.; Kristensen, B.K.
The plant mitochondrial proteome might contain as many as 2000-3000 different gene products, each of which might undergo post-translational modification. Recent studies using analytical methods, such as one-, two- and three-dimensional gel electrophoresis and one- and two-dimensional liquid...... context to be defined for them. There are indications that some of these proteins add novel activities to mitochondrial protein complexes in plants....
simultaneously analyzed in an array format, the likelihood of each interaction occurring in any given physiological settings can be evaluated. WISE can be easily extended to a variety of protein interaction domains, including those binding to modified peptides, thereby offering a powerful proteomic tool to help completing a full description of the cell interactome.
Full Text Available Mario Bonomini,1 Luisa Pieroni,2 Lorenzo Di Liberato,1 Vittorio Sirolli,1 Andrea Urbani2,3 1Department of Medicine, G. d’Annunzio University, Chieti, 2Proteomic and Metabonomic Units, IRCCS S. Lucia Foundation, Rome, 3Faculty of Medicine, Biochemistry and Clinical Biochemistry Institute, Catholic University of the “Sacred Heart”, Rome, Italy Abstract: The success and the quality of hemodialysis therapy are mainly related to both clearance and biocompatibility properties of the artificial membrane packed in the hemodialyzer. Performance of a membrane is strongly influenced by its interaction with the plasma protein repertoire during the extracorporeal procedure. Recognition that a number of medium–high molecular weight solutes, including proteins and protein-bound molecules, are potentially toxic has prompted the development of more permeable membranes. Such membrane engineering, however, may cause loss of vital proteins, with membrane removal being nonspecific. In addition, plasma proteins can be adsorbed onto the membrane surface upon blood contact during dialysis. Adsorption can contribute to the removal of toxic compounds and governs the biocompatibility of a membrane, since surface-adsorbed proteins may trigger a variety of biologic blood pathways with pathophysiologic consequences. Over the last years, use of proteomic approaches has allowed polypeptide spectrum involved in the process of hemodialysis, a key issue previously hampered by lack of suitable technology, to be assessed in an unbiased manner and in its full complexity. Proteomics has been successfully applied to identify and quantify proteins in complex mixtures such as dialysis outflow fluid and fluid desorbed from dialysis membrane containing adsorbed proteins. The identified proteins can also be characterized by their involvement in metabolic and signaling pathways, molecular networks, and biologic processes through application of bioinformatics tools. Proteomics may
Walther, Tobias C; Olsen, Jesper Velgaard; Mann, Matthias
-translational controls contribute majorly to regulation of protein abundance, for example in heat shock stress response. The development of new sample preparation methods, high-resolution mass spectrometry and novel bioinfomatic tools close this gap and allow the global quantitation of the yeast proteome under different...
The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the NVIDIA Foundation are pleased to announce funding opportunities in the fight against cancer. Each organization has launched a request for proposals (RFP) that will collectively fund up to $2 million to help to develop a new generation of data-intensive scientific tools to find new ways to treat cancer.
Less than a decade ago, protein sequencing was the bane of paleobiology. Since that time researchers have completely sequenced proteins in >50 Ka fossils, been dazzled by reports of collagen peptides in dinosaur bones, and witnessed the development of phylogenetic trees from ancient protein sequences. Enlisting proteomics as biosignature is now in our grasp. In this talk the pitfalls and challenges of mass spectrometric approaches to protein sequencing will be illustrated and phylogenetic applications will be discussed. Work on extinct organisms at Michigan State University, University of Michigan and York University will provide a vantage point to assess methodologies, explore diagenetic alterations, evaluate mass spectra and illustrate issues associated with data base searching. Challenges encountered in the study of paleoproteomics, such as the absence of sequences for extinct organisms in commercially available databases, protein diagenesis and low concentrations of target are parallel to those that will be encountered when protein sequencing is extended to extreme and extraterrestrial environments. Thus, lessons learned from interrogating the ancient proteome are important and necessary step in developing proteomics as a biosignature tools.
R Alan Wilson
Full Text Available An effective vaccine against schistosomiasis mansoni would be a valuable control tool and the high levels of protection elicited in rodents and primates by radiation-attenuated cercariae provide proof of principle. A major obstacle to vaccine development is the difficulty of identifying the antigens that mediate protection, not least because of the size of the genome at 280Mb DNA encoding 14,000 to 20,000 genes. The technologies collectively called proteomics, including 2D electrophoresis, liquid chromatography and mass spectrometry, now permit any protein to be identified provided there is extensive DNA data, and preferably a genome sequence. Applied to soluble (cytosolic proteins from schistosomes, proteomics reveals the great similarity in composition between life cycle stages, with several WHO vaccine candidates amongst the most abundant constituents. The proteomic approach has been successfully applied to identify the secretions used by cercaria to penetrate host skin, the gut secretions of adult worms and the proteins exposed on the tegument surface. Soluble proteins can also be separated by 2D electrophoresis before western blotting to identify the full range of antigenic targets present in a parasite preparation. The next step is to discover which target proteins represent the weak points in the worm's defences.
Semrau, Stefan; Goldmann, Johanna E; Soumillon, Magali; Mikkelsen, Tarjei S; Jaenisch, Rudolf; van Oudenaarden, Alexander
Gene expression heterogeneity in the pluripotent state of mouse embryonic stem cells (mESCs) has been increasingly well-characterized. In contrast, exit from pluripotency and lineage commitment have not been studied systematically at the single-cell level. Here we measure the gene expression
Hammar, Petter; Angermayr, S. Andreas; Sjostrom, Staffan L.
Background: Photosynthetic cyanobacteria are attractive for a range of biotechnological applications including biofuel production. However, due to slow growth, screening of mutant libraries using microtiter plates is not feasible.Results: We present a method for high-throughput, single-cell analy...
Tanzi, S.; Larsen, S.T.; Matteucci, M.
This work demonstrates a novel all-in-polymer device for single cell capture applicable for biological recordings. The chip is injection molded and comprises a "cornered" (non planar) aperture. It has been demonstrated how cornered apertures are straightforward to mold in PDMS [1,2]. In this stud...
Rasouli, Zahra; Valverde Pérez, Borja; D'Este, Martina
microalgae – as a means to recover nutrients from industrial wastewater and upcycle them to feed grade single cell protein. Results demonstrated that both algae and bacteria could remove or assimilate most of the organic carbon present in the wastewater. However, their growth stopped before nutrients...
Han, Sung-Woong; Nakamura, Chikashi; Miyake, Jun; Chang, Sang-Mok; Adachi, Taiji
The recent single-cell manipulation technology using atomic force microscopy (AFM) not only allows high-resolution visualization and probing of biomolecules and cells but also provides spatial and temporal access to the interior of living cells via the nanoneedle technology. Here we review the development and application of single-cell manipulations and the DNA delivery technology using a nanoneedle. We briefly describe various DNA delivery methods and discuss their advantages and disadvantages. Fabrication of the nanoneedle, visualization of nanoneedle insertion into living cells, DNA modification on the nanoneedle surface, and the invasiveness of nanoneedle insertion into living cells are described. Different methods of DNA delivery into a living cell, such as lipofection, microinjection, and nanoneedles, are then compared. Finally, single-cell diagnostics using the nanoneedle and the perspectives of the nanoneedle technology are outlined. The nanoneedle-based DNA delivery technology provides new opportunities for efficient and specific introduction of DNA and other biomolecules into precious living cells with a high spatial resolution within a desired time frame. This technology has the potential to be applied for many basic cellular studies and for clinical studies such as single-cell diagnostics.
Hammar, P.; Angermayr, S.A.; Sjostrom, S.L.; van der Meer, J.; Hellingwerf, K.J.; Hudson, E.P.; Joensson, H.N.
BACKGROUND: Photosynthetic cyanobacteria are attractive for a range of biotechnological applications including biofuel production. However, due to slow growth, screening of mutant libraries using microtiter plates is not feasible. RESULTS: We present a method for high-throughput, single-cell
Breuer, Rebecca J; Bandyopadhyay, Arpan; O'Brien, Sofie A; Barnes, Aaron M T; Hunter, Ryan C; Hu, Wei-Shou; Dunny, Gary M
In Enterococcus faecalis, sex pheromone-mediated transfer of antibiotic resistance plasmids can occur under unfavorable conditions, for example, when inducing pheromone concentrations are low and inhibiting pheromone concentrations are high. To better understand this paradox, we adapted fluorescence in situ hybridization chain reaction (HCR) methodology for simultaneous quantification of multiple E. faecalis transcripts at the single cell level. We present direct evidence for variability in the minimum period, maximum response level, and duration of response of individual cells to a specific inducing condition. Tracking of induction patterns of single cells temporally using a fluorescent reporter supported HCR findings. It also revealed subpopulations of rapid responders, even under low inducing pheromone concentrations where the overall response of the entire population was slow. The strong, rapid induction of small numbers of cells in cultures exposed to low pheromone concentrations is in agreement with predictions of a stochastic model of the enterococcal pheromone response. The previously documented complex regulatory circuitry controlling the pheromone response likely contributes to stochastic variation in this system. In addition to increasing our basic understanding of the biology of a horizontal gene transfer system regulated by cell-cell signaling, demonstration of the stochastic nature of the pheromone response also impacts any future efforts to develop therapeutic agents targeting the system. Quantitative single cell analysis using HCR also has great potential to elucidate important bacterial regulatory mechanisms not previously amenable to study at the single cell level, and to accelerate the pace of functional genomic studies.
Wu, Meiye; Singh, Anup K.
The present invention relates to a microfluidic device and platform configured to conduct multiplexed analysis within the device. In particular, the device allows multiple targets to be detected on a single-cell level. Also provided are methods of performing multiplexed analyses to detect one or more target nucleic acids, proteins, and post-translational modifications.
and to discuss library preparations protocols and data analysis techniques. The goal is to develop a single cell sequencing analysis toolkit . In...Research Support LUNGevity Career Development Award What other organizations were involved as partners? Organization Name: Broad Institute 19
Kouno, Tsukasa; de Hoon, Michiel; Mar, Jessica C; Tomaru, Yasuhiro; Kawano, Mitsuoki; Carninci, Piero; Suzuki, Harukazu; Hayashizaki, Yoshihide; Shin, Jay W
Changes in environmental conditions lead to expression variation that manifest at the level of gene regulatory networks. Despite a strong understanding of the role noise plays in synthetic biological systems, it remains unclear how propagation of expression heterogeneity in an endogenous regulatory network is distributed and utilized by cells transitioning through a key developmental event. Here we investigate the temporal dynamics of a single-cell transcriptional network of 45 transcription factors in THP-1 human myeloid monocytic leukemia cells undergoing differentiation to macrophages. We systematically measure temporal regulation of expression and variation by profiling 120 single cells at eight distinct time points, and infer highly controlled regulatory modules through which signaling operates with stochastic effects. This reveals dynamic and specific rewiring as a cellular strategy for differentiation. The integration of both positive and negative co-expression networks further identifies the proto-oncogene MYB as a network hinge to modulate both the pro- and anti-differentiation pathways. Compared to averaged cell populations, temporal single-cell expression profiling provides a much more powerful technique to probe for mechanistic insights underlying cellular differentiation. We believe that our approach will form the basis of novel strategies to study the regulation of transcription at a single-cell level.
Suffiotti, Madeleine; Carmona, Santiago J; Jandus, Camilla; Gfeller, David
Innate lymphoid cells (ILCs) consist of natural killer (NK) cells and non-cytotoxic ILCs that are broadly classified into ILC1, ILC2, and ILC3 subtypes. These cells recently emerged as important early effectors of innate immunity for their roles in tissue homeostasis and inflammation. Over the last few years, ILCs have been extensively studied in mouse and human at the functional and molecular level, including gene expression profiling. However, sorting ILCs with flow cytometry for gene expression analysis is a delicate and time-consuming process. Here we propose and validate a novel framework for studying ILCs at the transcriptomic level using single-cell RNA-Seq data. Our approach combines unsupervised clustering and a new cell type classifier trained on mouse ILC gene expression data. We show that this approach can accurately identify different ILCs, especially ILC2 cells, in human lymphocyte single-cell RNA-Seq data. Our new model relies only on genes conserved across vertebrates, thereby making it in principle applicable in any vertebrate species. Considering the rapid increase in throughput of single-cell RNA-Seq technology, our work provides a computational framework for studying ILC2 cells in single-cell transcriptomic data and may help exploring their conservation in distant vertebrate species.
In our study of germ cell differentiation, we applied two recently developed technologies on the germline of various model organisms: single-cell mRNA sequencing and RNA-tomography. For the first time we could look at gene expression with such a high resolution, and this led us to discover the
徐晨明; 金帆; 黄荷凤; 陶冶; 叶英辉
Objective To develop a reliable and sensitive method for detection of sex and multiloci of Duchenne muscular dystrophy (DMD) gene in single cell Materials & methods Whole genome of single cell were amplified by using 15-base random primers (primer extension preamplification, PEP), then a small aliquot of PEP product were analyzed by using locus-specific nest PCR amplification. The procedure was evaluated by detection dystrophin exons 8, 17, 19, 44, 45, 48 and human testis-determining gene (SRY)in single lymphocytes from known sources and single blastomeres from the couples with no family history of DMD.Results The amplification efficiency rate of six dystrophin exons from single lymphocytes and single blastomeres were 97. 2% (175/180) and 100% (60/60) respectively.Results of SRY showed that 100% (15/15) amplification in single male-derived lymphocytes and 0% (0/15) amplification in single female-derived lymphocytes. Conclusion The technique of single cell PEP-nest PCR for dystrophin exons 8, 17,19, 44, 45, 48 and SRY is highly specifc. PEP-nest PCR is suitable for Preimplantation genetic diagnosis (PGD) of DMD at single cell level.
Full Text Available Since only a small fraction of environmental bacteria are amenable to laboratory culture, there is great interest in genomic sequencing directly from single cells. Sufficient DNA for sequencing can be obtained from one cell by the Multiple Displacement Amplification (MDA method, thereby eliminating the need to develop culture methods. Here we used a microfluidic device to isolate individual Escherichia coli and amplify genomic DNA by MDA in 60-nl reactions. Our results confirm a report that reduced MDA reaction volume lowers nonspecific synthesis that can result from contaminant DNA templates and unfavourable interaction between primers. The quality of the genome amplification was assessed by qPCR and compared favourably to single-cell amplifications performed in standard 50-microl volumes. Amplification bias was greatly reduced in nanoliter volumes, thereby providing a more even representation of all sequences. Single-cell amplicons from both microliter and nanoliter volumes provided high-quality sequence data by high-throughput pyrosequencing, thereby demonstrating a straightforward route to sequencing genomes from single cells.
Klepárník, Karel; Foret, František
Roč. 800, OCT (2013), s. 12-21 ISSN 0003-2670 R&D Projects: GA MŠk(CZ) EE2.3.20.0182; GA ČR GAP206/11/2377 Institutional support: RVO:68081715 Keywords : single cell analysis * capillary electrophoresis * electrochemistry * microfluidic devices Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 4.517, year: 2013
Kaiser, Matthias; Jug, Florian; Julou, Thomas; Deshpande, S.R.; Pfohl, Thomas; Silander, Olin K.; Myers, Gene; Van Nimwegen, Erik
Much is still not understood about how gene regulatory interactions control cell fate decisions in single cells, in part due to the difficulty of directly observing gene regulatory processes in vivo. We introduce here a novel integrated setup consisting of a microfluidic chip and accompanying
Drejer, André; Ritschel, Tobias Kasper Skovborg; Jørgensen, Sten Bay
The production of single-cell protein (SCP) in a U-loop reactor by a methanotroph is a cost efficient sustainable alternative to protein from fish meal obtained by over-fishing the oceans. SCP serves as animal feed. In this paper, we present a mathematical model that describes the dynamics of SCP...
Musat, Niculina; Halm, Hannah; Winterholler, Bärbel
Quantitative information on the ecophysiology of individual microorganisms is generally limited because it is difficult to assign specific metabolic activities to identified single cells. Here, we develop and apply a method, Halogen In Situ Hybridization-Secondary Ion Mass Spectroscopy (HISH...
Adalsteinsson, Viktor A; Tahirova, Narmin; Tallapragada, Naren; Yao, Xiaosai; Campion, Liam; Angelini, Alessandro; Douce, Thomas B; Huang, Cindy; Bowman, Brittany; Williamson, Christina A; Kwon, Douglas S; Wittrup, K Dane; Love, J Christopher
Cancer is an inflammatory disease of tissue that is largely influenced by the interactions between multiple cell types, secreted factors, and signal transduction pathways. While single-cell sequencing continues to refine our understanding of the clonotypic heterogeneity within tumors, the complex interplay between genetic variations and non-genetic factors ultimately affects therapeutic outcome. Much has been learned through bulk studies of secreted factors in the tumor microenvironment, but the secretory behavior of single cells has been largely uncharacterized. Here we directly profiled the secretions of ELR+ CXC chemokines from thousands of single colorectal tumor and stromal cells, using an array of subnanoliter wells and a technique called microengraving to characterize both the rates of secretion of several factors at once and the numbers of cells secreting each chemokine. The ELR+ CXC chemokines are highly redundant, pro-angiogenic cytokines that signal via the CXCR1 and CXCR2 receptors, influencing tumor growth and progression. We find that human primary colorectal tumor and stromal cells exhibit polyfunctional heterogeneity in the combinations and magnitudes of secretions for these chemokines. In cell lines, we observe similar variance: phenotypes observed in bulk can be largely absent among the majority of single cells, and discordances exist between secretory states measured and gene expression for these chemokines among single cells. Together, these measures suggest secretory states among tumor cells are complex and can evolve dynamically. Most importantly, this study reveals new insight into the intratumoral phenotypic heterogeneity of human primary tumors.
Full Text Available Abstract Background The essential Escherichia coli gene ygjD belongs to a universally conserved group of genes whose function has been the focus of a number of recent studies. Here, we put ygjD under control of an inducible promoter, and used time-lapse microscopy and single cell analysis to investigate the phenotypic consequences of the depletion of YgjD protein from growing cells. Results We show that loss of YgjD leads to a marked decrease in cell size and termination of cell division. The transition towards smaller size occurs in a controlled manner: cell elongation and cell division remain coupled, but cell size at division decreases. We also find evidence that depletion of YgjD leads to the synthesis of the intracellular signaling molecule (pppGpp, inducing a cellular reaction resembling the stringent response. Concomitant deletion of the relA and spoT genes - leading to a strain that is uncapable of synthesizing (pppGpp - abrogates the decrease in cell size, but does not prevent termination of cell division upon YgjD depletion. Conclusions Depletion of YgjD protein from growing cells leads to a decrease in cell size that is contingent on (pppGpp, and to a termination of cell division. The combination of single-cell timelapse microscopy and statistical analysis can give detailed insights into the phenotypic consequences of the loss of essential genes, and can thus serve as a new tool to study the function of essential genes.
Full Text Available Keying Che,1,* Yang Zhao,2,3,* Xiao Qu,1 Zhaofei Pang,1 Yang Ni,4 Tiehong Zhang,4 Jiajun Du,1,5 Hongchang Shen4 1Institute of Oncology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, 2Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Collaborative Innovation Center of Cancer Medicine, Fudan University Shanghai Cancer Center, 3Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 4Department of Oncology, Shandong Provincial Hospital Affiliated to Shandong University, 5Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, People’s Republic of China *These authors contributed equally to this work Purpose: Gastric carcinoma (GC is a highly aggressive cancer and one of the leading causes of cancer-related deaths worldwide. Histopathological evaluation pertaining to invasiveness is likely to provide additional information in relation to patient outcome. In this study, we aimed to evaluate the prognostic significance of tumor budding and single cell invasion in gastric adenocarcinoma.Materials and methods: Hematoxylin and eosin-stained slides generated from 296 gastric adenocarcinoma patients with full clinical and pathological and follow-up information were systematically reviewed. The patients were grouped on the basis of tumor budding, single cell invasion, large cell invasion, mitotic count, and fibrosis. The association between histopathological parameters, different classification systems, and overall survival (OS was statistically analyzed.Results: Among the 296 cases that were analyzed, high-grade tumor budding was observed in 49.0% (145 of them. Single cell invasion and large cell invasion were observed in 62.8% (186 and 16.9% (50 of the cases, respectively. Following univariate analysis, patients with high-grade tumor budding had shorter OS than those with low-grade tumor budding (hazard ratio [HR]: 2.260, P<0
Full Text Available Comprehensive genome wide analyses of single cells became increasingly important in cancer research, but remain to be a technically challenging task. Here, we provide a protocol for array comparative genomic hybridization (aCGH of single cells. The protocol is based on an established adapter-linker PCR (WGAM and allowed us to detect copy number alterations as small as 56 kb in single cells. In addition we report on factors influencing the success of single cell aCGH downstream of the amplification method, including the characteristics of the reference DNA, the labeling technique, the amount of input DNA, reamplification, the aCGH resolution, and data analysis. In comparison with two other commercially available non-linear single cell amplification methods, WGAM showed a very good performance in aCGH experiments. Finally, we demonstrate that cancer cells that were processed and identified by the CellSearch® System and that were subsequently isolated from the CellSearch® cartridge as single cells by fluorescence activated cell sorting (FACS could be successfully analyzed using our WGAM-aCGH protocol. We believe that even in the era of next-generation sequencing, our single cell aCGH protocol will be a useful and (cost- effective approach to study copy number alterations in single cells at resolution comparable to those reported currently for single cell digital karyotyping based on next generation sequencing data.
Witschi, M.; Xia, D.; Sanderson, S.; Baumgartner, M.; Wastling, J.M.; Dobbelaere, D.A.E.
The apicomplexan parasite, Theileria annulata, is the causative agent of tropical theileriosis, a devastating lymphoproliferative disease of cattle. The schizont stage transforms bovine leukocytes and provides an intriguing model to study host/pathogen interactions. The genome of T. annulata has been sequenced and transcriptomic data are rapidly accumulating. In contrast, little is known about the proteome of the schizont, the pathogenic, transforming life cycle stage of the parasite. Using one-dimensional (1-D) gel LC-MS/MS, a proteomic analysis of purified T. annulata schizonts was carried out. In whole parasite lysates, 645 proteins were identified. Proteins with transmembrane domains (TMDs) were under-represented and no proteins with more than four TMDs could be detected. To tackle this problem, Triton X-114 treatment was applied, which facilitates the extraction of membrane proteins, followed by 1-D gel LC-MS/MS. This resulted in the identification of an additional 153 proteins. Half of those had one or more TMD and 30 proteins with more than four TMDs were identified. This demonstrates that Triton X-114 treatment can provide a valuable additional tool for the identification of new membrane proteins in proteomic studies. With two exceptions, all proteins involved in glycolysis and the citric acid cycle were identified. For at least 29% of identified proteins, the corresponding transcripts were not present in the existing expressed sequence tag databases. The proteomics data were integrated into the publicly accessible database resource at EuPathDB (www.eupathdb.org) so that mass spectrometry-based protein expression evidence for T. annulata can be queried alongside transcriptional and other genomics data available for these parasites. PMID:23178997
Wahl, Karen L.; Wunschel, David S.; Clowers, Brian H.
Proteomics is a relatively new scientific discipline dedicated to the comprehensive study of the protein composition of biological systems. While genomic sequencing is an invaluable tool for bioforensic sample identification, proteomics complements genomics in that the genes present in an organism code for the proteins that can be present in a microorganism. Many proteins are conserved for general identification while other protein expression varies with environment/growth state/growth conditions (i.e. not all proteins are expressed at any given time or condition) providing additional information beyond genomic analysis. This expression specificity and the relative stability of proteins with respect to genetic material make them attractive targets for microorganism identification and forensic applications to complement genomic approaches. Proteomic analysis depends upon the availability of genome sequences of the relevant organisms or their near relatives. The known amino acid sequences for potential proteins within the database can be compared to amino acid sequences of actual proteins present in a sample as determined with high mass accuracy by mass spectrometry for identification of the proteins in the sample. With the development of technology for rapid genome sequencing of organisms, the known protein database is growing, supporting improved identification of the proteins present in a sample. Recent developments in mass spectrometry instrumentation and microbial sequencing are leading to an increased growth in application of proteomics to microbiology, pathogen detection, disease diagnosis and microbial forensics as well as other biological disciplines. Mass spectrometry analysis does not require a priori knowledge of the sample or expected targets to gain meaningful.
Mendenhall, Alexander; Driscoll, Monica; Brent, Roger
Genetically identical organisms in homogeneous environments have different lifespans and healthspans. These differences are often attributed to stochastic events, such as mutations and 'epimutations', changes in DNA methylation and chromatin that change gene function and expression. But work in the last 10 years has revealed differences in lifespan- and health-related phenotypes that are not caused by lasting changes in DNA or identified by modifications to DNA or chromatin. This work has demonstrated persistent differences in single-cell and whole-organism physiological states operationally defined by values of reporter gene signals in living cells. While some single-cell states, for example, responses to oxygen deprivation, were defined previously, others, such as a generally heightened ability to make proteins, were, revealed by direct experiment only recently, and are not well understood. Here, we review technical progress that promises to greatly increase the number of these measurable single-cell physiological variables and measureable states. We discuss concepts that facilitate use of single-cell measurements to provide insight into physiological states and state transitions. We assert that researchers will use this information to relate cell level physiological readouts to whole-organism outcomes, to stratify aging populations into groups based on different physiologies, to define biomarkers predictive of outcomes, and to shed light on the molecular processes that bring about different individual physiologies. For these reasons, quantitative study of single-cell physiological variables and state transitions should provide a valuable complement to genetic and molecular explanations of how organisms age. © 2015 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.
Nestorowa, Sonia; Hamey, Fiona K; Pijuan Sala, Blanca; Diamanti, Evangelia; Shepherd, Mairi; Laurenti, Elisa; Wilson, Nicola K; Kent, David G; Göttgens, Berthold
Maintenance of the blood system requires balanced cell fate decisions by hematopoietic stem and progenitor cells (HSPCs). Because cell fate choices are executed at the individual cell level, new single-cell profiling technologies offer exciting possibilities for mapping the dynamic molecular changes underlying HSPC differentiation. Here, we have used single-cell RNA sequencing to profile more than 1600 single HSPCs, and deep sequencing has enabled detection of an average of 6558 protein-coding genes per cell. Index sorting, in combination with broad sorting gates, allowed us to retrospectively assign cells to 12 commonly sorted HSPC phenotypes while also capturing intermediate cells typically excluded by conventional gating. We further show that independently generated single-cell data sets can be projected onto the single-cell resolution expression map to directly compare data from multiple groups and to build and refine new hypotheses. Reconstruction of differentiation trajectories reveals dynamic expression changes associated with early lymphoid, erythroid, and granulocyte-macrophage differentiation. The latter two trajectories were characterized by common upregulation of cell cycle and oxidative phosphorylation transcriptional programs. By using external spike-in controls, we estimate absolute messenger RNA (mRNA) levels per cell, showing for the first time that despite a general reduction in total mRNA, a subset of genes shows higher expression levels in immature stem cells consistent with active maintenance of the stem-cell state. Finally, we report the development of an intuitive Web interface as a new community resource to permit visualization of gene expression in HSPCs at single-cell resolution for any gene of choice. © 2016 by The American Society of Hematology.
Clark, David J; Fondrie, William E; Liao, Zhongping; Hanson, Phyllis I; Fulton, Amy; Mao, Li; Yang, Austin J
Exosomes are microvesicles of endocytic origin constitutively released by multiple cell types into the extracellular environment. With evidence that exosomes can be detected in the blood of patients with various malignancies, the development of a platform that uses exosomes as a diagnostic tool has been proposed. However, it has been difficult to truly define the exosome proteome due to the challenge of discerning contaminant proteins that may be identified via mass spectrometry using various exosome enrichment strategies. To better define the exosome proteome in breast cancer, we incorporated a combination of Tandem-Mass-Tag (TMT) quantitative proteomics approach and Support Vector Machine (SVM) cluster analysis of three conditioned media derived fractions corresponding to a 10 000g cellular debris pellet, a 100 000g crude exosome pellet, and an Optiprep enriched exosome pellet. The quantitative analysis identified 2 179 proteins in all three fractions, with known exosomal cargo proteins displaying at least a 2-fold enrichment in the exosome fraction based on the TMT protein ratios. Employing SVM cluster analysis allowed for the classification 251 proteins as "true" exosomal cargo proteins. This study provides a robust and vigorous framework for the future development of using exosomes as a potential multiprotein marker phenotyping tool that could be useful in breast cancer diagnosis and monitoring disease progression.
Reddy, Panga Jaipal; Atak, Apurva; Ghantasala, Saicharan; Kumar, Saurabh; Gupta, Shabarni; Prasad, T S Keshava; Zingde, Surekha M; Srivastava, Sanjeeva
After a successful completion of the Human Genome Project, deciphering the mystery surrounding the human proteome posed a major challenge. Despite not being largely involved in the Human Genome Project, the Indian scientific community contributed towards proteomic research along with the global community. Currently, more than 76 research/academic institutes and nearly 145 research labs are involved in core proteomic research across India. The Indian researchers have been major contributors in drafting the "human proteome map" along with international efforts. In addition to this, virtual proteomics labs, proteomics courses and remote triggered proteomics labs have helped to overcome the limitations of proteomics education posed due to expensive lab infrastructure. The establishment of Proteomics Society, India (PSI) has created a platform for the Indian proteomic researchers to share ideas, research collaborations and conduct annual conferences and workshops. Indian proteomic research is really moving forward with the global proteomics community in a quest to solve the mysteries of proteomics. A draft map of the human proteome enhances the enthusiasm among intellectuals to promote proteomic research in India to the world.This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.
Arthur, J.W.; Harrison, M.; Manoharan, A.; Traini, M.; Shaw, E.; Wilkins, M.
Proteomics (Wilkins et al. 1997) involves the large-scale analysis of expressed proteins. At each stage of the discovery process the researcher accumulates large volumes of data. These include: clinical or biological data about the sample being studied; details of sample purification and separation; images of 2D gels and associated information; MALDI mass spectra; MS/MS and PSD spectra; as well as meta-data relating to the projects undertaken and experiments performed. All this must be combined with existing databases of protein and EST sequences, post-translational modifications, and protein glycosylation, then processed with sophisticated bioinformatics tools in order to extract meaningful answers to questions of biological, clinical, and agricultural significance. BioinformatlQ TM is a web-based application for the storage, management, and automated bioinformatic analysis of proteomic information. This poster will demonstrate the integration of these disparate data sources in proteomics
Righetti, Pier Giorgio; Boschetti, Egisto
The performance of a hexapeptide ligand library in capturing the 'hidden proteome' is illustrated and evaluated. This library, insolubilized on an organic polymer and available under the trade name 'Equalizer Bead Technology', acts by capturing all components of a given proteome, by concentrating rare and very rare proteins, and simultaneously diluting the abundant ones. This results in a proteome of 'normalized' relative abundances, amenable to analysis by MS and any other analytical tool. Examples are given of analysis of human urine and serum, as well as cell and tissue lysates, such as Escherichia coli and Saccharomyces cerevisiae extracts. Another important application is impurity tracking and polishing of recombinant DNA products, especially biopharmaceuticals meant for human consumption.
Rossing, Kasper; Mischak, Harald; Rossing, Peter
Diabetes represents one of the main chronic diseases worldwide. Diabetes and its associated complications may be detectable even at early stages in the urinary proteome. In this article we review the current literature on urinary proteomics applied to the study of diabetes and diabetic...... complications. Further, we present recent data that strongly indicate urinary proteome analysis may be a valuable tool in detecting diabetes-associated pathophysiological changes at an early stage, and also may enable assessment of disease progression and efficacy of therapy. Current data indicate that collagen......-derived peptides represent one of the main peptidic components in urine, which are consistently found at reduced levels in diabetes. It is tempting to speculate that this decrease in urinary collagen-derived peptides is related to an increase in extracellular matrix deposition which is a major complication...
Han, Yumiao; Garcia, Benjamin A
Epigenetics is the study of changes in gene expression or cellular phenotype that do not change the DNA sequence. In this review, current methods, both genomic and proteomic, associated with epigenetics research are discussed. Among them, chromatin immunoprecipitation (ChIP) followed by sequencing and other ChIP-based techniques are powerful techniques for genome-wide profiling of DNA-binding proteins, histone post-translational modifications or nucleosome positions. However, mass spectrometry-based proteomics is increasingly being used in functional biological studies and has proved to be an indispensable tool to characterize histone modifications, as well as DNA–protein and protein–protein interactions. With the development of genomic and proteomic approaches, combination of ChIP and mass spectrometry has the potential to expand our knowledge of epigenetics research to a higher level. PMID:23895656
Martin, Sarah F.; Falkenberg, Heiner; Dyrlund, Thomas Franck
, including arguments for community-wide open source software development and “big data” compatible solutions for the future. For the meantime, we have laid out ten top tips for data processing. With these at hand, a first large-scale proteomics analysis hopefully becomes less daunting to navigate......, with the aim of setting a community-driven gold standard for data handling, reporting and sharing. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012].......In large-scale proteomics studies there is a temptation, after months of experimental work, to plug resulting data into a convenient—if poorly implemented—set of tools, which may neither do the data justice nor help answer the scientific question. In this paper we have captured key concerns...
Fredens, Julius; Engholm-Keller, Kasper; Giessing, Anders
We demonstrate labeling of Caenorhabditis elegans with heavy isotope-labeled lysine by feeding them with heavy isotope-labeled Escherichia coli. Using heavy isotope-labeled worms and quantitative proteomics methods, we identified several proteins that are regulated in response to loss or RNAi-med......-mediated knockdown of the nuclear hormone receptor 49 in C. elegans. The combined use of quantitative proteomics and selective gene knockdown is a powerful tool for C. elegans biology.......We demonstrate labeling of Caenorhabditis elegans with heavy isotope-labeled lysine by feeding them with heavy isotope-labeled Escherichia coli. Using heavy isotope-labeled worms and quantitative proteomics methods, we identified several proteins that are regulated in response to loss or RNAi...
Thomas, Samuel; Hao, Ling; Ricke, William A; Li, Lingjun
Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Schoeman, R.M.; Kemna, Evelien; Wolbers, F.; van den Berg, Albert
In this article, we present a microfluidic device capable of successive high-yield single-cell encapsulation in droplets, with additional droplet pairing, fusion, and shrinkage. Deterministic single-cell encapsulation is realized using Dean-coupled inertial ordering of cells in a Yin-Yang-shaped
Martínez-Bartolomé, Salvador; Deutsch, Eric W; Binz, Pierre-Alain; Jones, Andrew R; Eisenacher, Martin; Mayer, Gerhard; Campos, Alex; Canals, Francesc; Bech-Serra, Joan-Josep; Carrascal, Montserrat; Gay, Marina; Paradela, Alberto; Navajas, Rosana; Marcilla, Miguel; Hernáez, María Luisa; Gutiérrez-Blázquez, María Dolores; Velarde, Luis Felipe Clemente; Aloria, Kerman; Beaskoetxea, Jabier; Medina-Aunon, J Alberto; Albar, Juan P
Mass spectrometry is already a well-established protein identification tool and recent methodological and technological developments have also made possible the extraction of quantitative data of protein abundance in large-scale studies. Several strategies for absolute and relative quantitative proteomics and the statistical assessment of quantifications are possible, each having specific measurements and therefore, different data analysis workflows. The guidelines for Mass Spectrometry Quantification allow the description of a wide range of quantitative approaches, including labeled and label-free techniques and also targeted approaches such as Selected Reaction Monitoring (SRM). The HUPO Proteomics Standards Initiative (HUPO-PSI) has invested considerable efforts to improve the standardization of proteomics data handling, representation and sharing through the development of data standards, reporting guidelines, controlled vocabularies and tooling. In this manuscript, we describe a key output from the HUPO-PSI-namely the MIAPE Quant guidelines, which have developed in parallel with the corresponding data exchange format mzQuantML . The MIAPE Quant guidelines describe the HUPO-PSI proposal concerning the minimum information to be reported when a quantitative data set, derived from mass spectrometry (MS), is submitted to a database or as supplementary information to a journal. The guidelines have been developed with input from a broad spectrum of stakeholders in the proteomics field to represent a true consensus view of the most important data types and metadata, required for a quantitative experiment to be analyzed critically or a data analysis pipeline to be reproduced. It is anticipated that they will influence or be directly adopted as part of journal guidelines for publication and by public proteomics databases and thus may have an impact on proteomics laboratories across the world. This article is part of a Special Issue entitled: Standardization and
Chen, Qi; Yan, Guoquan; Gao, Mingxia; Zhang, Xiangmin
To analyze the proteome of an extremely low number of cells or even a single cell, we established a new method of digesting whole cells into mass-spectrometry-identifiable peptides in a single step within 2 h. Our sampling method greatly simplified the processes of cell lysis, protein extraction, protein purification, and overnight digestion, without compromising efficiency. We used our method to digest hundred-scale cells. As far as we know, there is no report of proteome analysis starting directly with as few as 100 cells. We identified an average of 109 proteins from 100 cells, and with three replicates, the number of proteins rose to 204. Good reproducibility was achieved, showing stability and reliability of the method. Gene Ontology analysis revealed that proteins in different cellular compartments were well represented.
Schoenfelder, Stefan; Yaffe, Eitan; Dean, Wendy; Laue, Ernest D.; Tanay, Amos; Fraser, Peter
Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. PMID:24067610
Full Text Available Differentiation of human pluripotent stem cells towards definitive endoderm (DE is the critical first step for generating cells comprising organs such as the gut, liver, pancreas and lung. This in-vitro differentiation process generates a heterogeneous population with a proportion of cells failing to differentiate properly and maintaining expression of pluripotency factors such as Oct4. RNA sequencing of single cells collected at four time points during a 4-day DE differentiation identified high expression of metallothionein genes in the residual Oct4-positive cells that failed to differentiate to DE. Using X-ray fluorescence microscopy and multi-isotope mass spectrometry, we discovered that high intracellular zinc level corresponds with persistent Oct4 expression and failure to differentiate. This study improves our understanding of the cellular heterogeneity during in-vitro directed differentiation and provides a valuable resource to improve DE differentiation efficiency. Keywords: hPSC, Differentiation, Definitive endoderm, Heterogeneity, Single cell, RNA sequencing
Full Text Available Having determined the mass of a single cell of brewer yeast Saccharomyces cerevisiae by means of a microcantilever-based biosensor Cantisens CSR-801 (Concentris, Basel, Switzerland, it was found that its dry mass is 47,65 ± 1,05 pg. Found to be crucial in this mass determination was the cell position along the length of the cantilever. Moreover, calculations including cells positions on the cantilever provide a threefold better degree of accuracy than those which assume uniform mass distribution. We have also examined the influence of storage time on the single cell mass. Our results show that after 6 months there is an increase in the average mass of a single yeast cell.
Łabędź, Bogdan; Wańczyk, Aleksandra; Rajfur, Zenon
Having determined the mass of a single cell of brewer yeast Saccharomyces cerevisiae by means of a microcantilever-based biosensor Cantisens CSR-801 (Concentris, Basel, Switzerland), it was found that its dry mass is 47,65 ± 1,05 pg. Found to be crucial in this mass determination was the cell position along the length of the cantilever. Moreover, calculations including cells positions on the cantilever provide a threefold better degree of accuracy than those which assume uniform mass distribution. We have also examined the influence of storage time on the single cell mass. Our results show that after 6 months there is an increase in the average mass of a single yeast cell.
Radecki, Guillaume; Nargeot, Romuald; Jelescu, Ileana Ozana; Le Bihan, Denis; Ciobanu, Luisa
In this work, we show the feasibility of performing functional MRI studies with single-cell resolution. At ultrahigh magnetic field, manganese-enhanced magnetic resonance microscopy allows the identification of most motor neurons in the buccal network of Aplysia at low, nontoxic Mn2+ concentrations. We establish that Mn2+ accumulates intracellularly on injection into the living Aplysia and that its concentration increases when the animals are presented with a sensory stimulus. We also show that we can distinguish between neuronal activities elicited by different types of stimuli. This method opens up a new avenue into probing the functional organization and plasticity of neuronal networks involved in goal-directed behaviors with single-cell resolution. PMID:24872449
In this work a Raman flow cytometer is presented. It consists of a microfluidic device that takes advantages of the basic principles of Raman spectroscopy and flow cytometry. The microfluidic device integrates calibrated microfluidic channels- where the cells can flow one-by-one -, allowing single cell Raman analysis. The microfluidic channel integrates plasmonic nanodimers in a fluidic trapping region. In this way it is possible to perform Enhanced Raman Spectroscopy on single cell. These allow a label-free analysis, providing information about the biochemical content of membrane and cytoplasm of the each cell. Experiments are performed on red blood cells (RBCs), peripheral blood lymphocytes (PBLs) and myelogenous leukemia tumor cells (K562). © 2015 Optical Society of America.
Marcia Luciana Cazetta
Full Text Available Different molasses/ vinasse ratio were used as substrate to investigate single cell protein and total lipids production by five microorganisms: four yeasts strains: Candida lipolytica, Rhodotorula mucilaginosa, Saccharomyces cerevisiae, a yeast isolated from vinasse lake (denominated LLV98 and a bacterium strain, Corynebacterium glutamicum. The media utilized were: a 50% molasses and 50% vinasse; b 25% molasses and 75% vinasse and c 75% molasses and 25% vinasse. The objective of this work was to study the growth of microorganisms and also evaluate protein and lipids content in the biomass obtained from these by-products. The highest single cell protein production was obtained by S. cerevisiae, 50.35%, followed by R. mucilaginosa, 41.96%. The lowest productions were obtained by C. glutamicum. The higher total lipids productions, more than 26%, were founded in molasses plus vinasse at 50%/50% by S. cerevisiae and C. glutamicum.
Faigle, Christoph; Lautenschläger, Franziska; Whyte, Graeme; Homewood, Philip; Martín-Badosa, Estela; Guck, Jochen
The mechanical properties of biological cells have long been considered as inherent markers of biological function and disease. However, the screening and active sorting of heterogeneous populations based on serial single-cell mechanical measurements has not been demonstrated. Here we present a novel monolithic glass chip for combined fluorescence detection and mechanical phenotyping using an optical stretcher. A new design and manufacturing process, involving the bonding of two asymmetrically etched glass plates, combines exact optical fiber alignment, low laser damage threshold and high imaging quality with the possibility of several microfluidic inlet and outlet channels. We show the utility of such a custom-built optical stretcher glass chip by measuring and sorting single cells in a heterogeneous population based on their different mechanical properties and verify sorting accuracy by simultaneous fluorescence detection. This offers new possibilities of exact characterization and sorting of small populations based on rheological properties for biological and biomedical applications.
Wang, Xiaochen; Gong, Yuemin; Ema, Hideo
Adult hematopoietic stem cells (HSCs), the ideal system for regenerative research, were isolated at single cell levels decades ago, whereas studies on embryonic HSCs are much more difficult. Zhou et al identified a new pre-HSC cell surface marker, CD201, by which they isolated pre-HSCs at single cell levels for further analyses. The novel expression pattern of HSC development is revealed, including the fundamental role of mammalian targets of rapamycin (mTOR) signaling pathway in HSCs emergence, and the repopulation potential of S/G2/M phase pre-HSCs. Deeper understandings of the cellular origin and developmental regulatory network of HSCs are essential to develop new strategies of generating HSCs in vitro for clinical application.
Hamey, Fiona; Nestorowa, Sonia; Wilson, Nicola Kaye; Göttgens, Berthold
Haematopoietic stem and progenitor cells (HSPCs) sit at the top of the haematopoietic hierarchy, and their fate choices need to be carefully controlled to ensure balanced production of all mature blood cell types. As cell fate decisions are made at the level of the individual cells, recent technological advances in measuring gene and protein expression in increasingly large numbers of single cells have been rapidly adopted to study both normal and pathological HSPC function. In this review we...
Goeij, J.J.M. de; Zegers, C.
The amount of selenium in single cell protein (SCP), a product of BP Research Centre at Sunbury-at-Thames, England, was determined by neutron activation analysis. The SCP-samples were irradiated in the reactor of the Interuniversity Reactor Institute at Delft, in a neutron flux of 1.0 x 10 13 n/cm 2 s for 24 hours. After chemical destruction of the samples the amount of selenium was determined by measuring the γ-peaks of selenium-75
Rodriguez-Emmenegger, Cesar; Janel, S.; de los Santos Pereira, Andres; Bruns, M.; Lafont, F.
Roč. 6, č. 31 (2015), s. 5740-5751 ISSN 1759-9954 R&D Projects: GA ČR(CZ) GJ15-09368Y; GA MŠk(CZ) ED1.1.00/02.0109 Grant - others:OPPK(XE) CZ.2.16/3.1.00/21545 Program:OPPK Institutional support: RVO:61389013 Keywords : antifouling polymer brushes * single-cell force spectroscopy * bacterial adhesion Subject RIV: BO - Biophysics Impact factor: 5.687, year: 2015
Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan
In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...
Hou, Yong; Wu, Kui; Shi, Xulian
methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly...... performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level....
Stahlberg, A.; Kubista, Mikael; Aman, P.
Roč. 11, č. 7 (2011), s. 735-740 ISSN 1473-7159 R&D Projects: GA ČR(CZ) GAP303/10/1338; GA ČR(CZ) GA301/09/1752 Institutional research plan: CEZ:AV0Z50520701 Keywords : gene-expression profiling * RT-qPCR * single-cell gene-expression profiling Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.859, year: 2011
Fan, Beiyuan; Li, Xiufeng; Chen, Deyong; Peng, Hongshang; Wang, Junbo; Chen, Jian
This article reviews recent developments in microfluidic systems enabling high-throughput characterization of single-cell proteins. Four key perspectives of microfluidic platforms are included in this review: (1) microfluidic fluorescent flow cytometry; (2) droplet based microfluidic flow cytometry; (3) large-array micro wells (microengraving); and (4) large-array micro chambers (barcode microchips). We examine the advantages and limitations of each technique and discuss future research oppor...
Santos, Carla Santana; Kowaltowski, Alicia J.; Bertotti, Mauro
We developed a highly sensitive oxygen consumption scanning microscopy system using platinized platinum disc microelectrodes. The system is capable of reliably detecting single-cell respiration, responding to classical regulators of mitochondrial oxygen consumption activity as expected. Comparisons with commercial multi-cell oxygen detection systems show that the system has comparable errors (if not smaller), with the advantage of being able to monitor inter and intra-cell heterogeneity in ox...
AWARD NUMBER: W81XWH-16-1-0253 TITLE: Lung Injury; Relates to Real- Time Endoscopic Monitoring of Single Cells Respiratory Health in Lung...2017 TYPE OF REPORT: Annual PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 DISTRIBUTION ...STATEMENT: Approved for Public Release; Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author(s
Stahlberg, A.; Kubista, Mikael
Roč. 14, č. 3 (2014), s. 323-331 ISSN 1473-7159 R&D Projects: GA ČR GA13-02154S; GA MŠk(CZ) ED1.1.00/02.0109 Institutional support: RVO:86652036 Keywords : single-cell workflow * gene expression profiling * RT-qPCR Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.516, year: 2014
Rusňáková, Vendula; Honsa, Pavel; Džamba, Dávid; Stahlberg, A.; Kubista, Mikael; Anděrová, Miroslava
Roč. 8, č. 8 (2013), e69734 E-ISSN 1932-6203 R&D Projects: GA ČR GA13-02154S Institutional research plan: CEZ:AV0Z50520701; CEZ:AV0Z50390703 Keywords : Single cell expression profiling * astrocytes * GenEx Subject RIV: EB - Genetics ; Molecular Biology; FH - Neurology (UEM-P) Impact factor: 3.534, year: 2013
Lagus, Todd P.; Edd, Jon F.
Microfluidic encapsulation methods have been previously utilized to capture cells in picoliter-scale aqueous, monodisperse drops, providing confinement from a bulk fluid environment with applications in high throughput screening, cytometry, and mass spectrometry. We describe a method to not only encapsulate single cells, but to repeatedly capture a set number of cells (here we demonstrate one- and two-cell encapsulation) to study both isolation and the interactions between cells in groups of ...
Full Text Available Based on the histological features and outcome, the current WHO classification separates thymomas into A, AB, B1, B2 and B3 subtypes. It is hypothesized that the type A thymomas are derived from the thymic medulla while the type B thymomas are derived from the cortex. Due to occasional histological overlap between the tumor subtypes creating difficulties in their separation, the aim of this study was to provide their proteomic characterization and identify potential immunohistochemical markers aiding in tissue diagnosis. Pair-wise comparison of neoplastic and normal thymus by liquid chromatography tandem mass spectrometry (LC-MS/MS of formalin fixed paraffin embedded tissue revealed 61 proteins differentially expressed in thymomas compared to normal tissue. Hierarchical clustering showed distinct segregation of subtypes AB, B1 and B2 from that of A and B3. Most notably, desmoyokin, a protein that is encoded by the AHNAK gene, was associated with type A thymomas and medulla of normal thymus, by LC-MS/MS and immunohistochemistry. In this global proteomic characterization of the thymoma, several proteins unique to different thymic compartments and thymoma subtypes were identified. Among differentially expressed proteins, desmoyokin is a marker specific for thymic medulla and is potentially promising immunohistochemical marker in separation of type A and B3 thymomas.
Zhu, Haixin; Holl, Mark; Ray, Tathagata; Bhushan, Shivani; Meldrum, Deirdre R
The development of a high-throughput single-cell metabolic rate monitoring system relies on the use of transparent substrate material for a single cell-trapping platform. The high optical transparency, high chemical resistance, improved surface quality and compatibility with the silicon micromachining process of fused silica make it very attractive and desirable for this application. In this paper, we report the results from the development and characterization of a hydrofluoric acid (HF) based deep wet-etch process on fused silica. The pin holes and notching defects of various single-coated masking layers during the etching are characterized and the most suitable masking materials are identified for different etch depths. The dependence of the average etch rate and surface roughness on the etch depth, impurity concentration and HF composition are also examined. The resulting undercut from the deep HF etch using various masking materials is also investigated. The developed and characterized process techniques have been successfully implemented in the fabrication of micro-well arrays for single cell trapping and sensor deposition. Up to 60 µm deep micro-wells have been etched in a fused silica substrate with over 90% process yield and repeatability. To our knowledge, such etch depth has never been achieved in a fused silica substrate by using a non-diluted HF etchant and a single-coated masking layer at room temperature
Zaki, M.; Said, S. D.
The dependency on fish meal as a major protein source for animal feed can lead toit priceinstability in line with the increasing in meat production and consumption in Indonesia. In order todeal with this problem, an effort to produce an alternative protein sources production is needed. This scenario is possible due to the abundantavailability of agricultural residues such as rice straw whichcould be utilized as substrate for production of single cell proteins as an alternative proteinsource. This work investigated the potential utilization of rice straw pulp and urea mixture as substrate for the production of local Trichoderma reesei single cell protein in solid state fermentation system. Some parameters have been analyzed to evaluate the effect of ratio of rice straw pulp to urea on mixed single cell protein biomass (mixed SCP biomass) composition, such as total crude protein (analyzed by kjedhal method) and lignin content (TAPPI method).The results showed that crude protein content in mixed SCP biomassincreases with the increasing in fermentation time, otherwise it decreases with the increasing insubstrate carbon to nitrogen (C/N) ratio. Residual lignin content in mixed SCP biomass decreases from 7% to 0.63% during fermentationproceeded of 21 days. The highest crude protein content in mixed SCP biomasswas obtained at substrate C/N ratio 20:1 of 25%.
Jaitin, Diego Adhemar; Keren-Shaul, Hadas; Elefant, Naama; Amit, Ido
Hematopoiesis and immunity are mediated through complex interactions between multiple cell types and states. This complexity is currently addressed following a reductionist approach of characterizing cell types by a small number of cell surface molecular features and gross functions. While the introduction of global transcriptional profiling technologies enabled a more comprehensive view, heterogeneity within sampled populations remained unaddressed, obscuring the true picture of hematopoiesis and immune system function. A critical mass of technological advances in molecular biology and genomics has enabled genome-wide measurements of single cells - the fundamental unit of immunity. These new advances are expected to boost detection of less frequent cell types and fuzzy intermediate cell states, greatly expanding the resolution of current available classifications. This new era of single-cell genomics in immunology research holds great promise for further understanding of the mechanisms and circuits regulating hematopoiesis and immunity in both health and disease. In the near future, the accuracy of single-cell genomics will ultimately enable precise diagnostics and treatment of multiple hematopoietic and immune related diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.
Fu, Audrey Qiuyan; Pachter, Lior
Gene expression is stochastic and displays variation (“noise”) both within and between cells. Intracellular (intrinsic) variance can be distinguished from extracellular (extrinsic) variance by applying the law of total variance to data from two-reporter assays that probe expression of identically regulated gene pairs in single cells. We examine established formulas [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.] for the estimation of intrinsic and extrinsic noise and provide interpretations of them in terms of a hierarchical model. This allows us to derive alternative estimators that minimize bias or mean squared error. We provide a geometric interpretation of these results that clarifies the interpretation in [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.]. We also demonstrate through simulation and re-analysis of published data that the distribution assumptions underlying the hierarchical model have to be satisfied for the estimators to produce sensible results, which highlights the importance of normalization. PMID:27875323
Jae Hoon Jeong
Full Text Available The cholinoceptive system in the hypothalamus, in particular in the arcuate nucleus (ARC, plays a role in regulating food intake. Neurons in the ARC contain multiple neuropeptides, amines, and neurotransmitters. To study molecular and neurochemical heterogeneity of ARC neurons, we combine single-cell qRT-PCR and single-cell whole transcriptome amplification methods to analyze expression patterns of our hand-picked 60 genes in individual neurons in the ARC. Immunohistochemical and single-cell qRT-PCR analyses show choline acetyltransferase (ChAT-expressing neurons in the ARC. Gene expression patterns are remarkably distinct in each individual cholinergic neuron. Two-thirds of cholinergic neurons express tyrosine hydroxylase (Th mRNA. A large subset of these Th-positive cholinergic neurons is GABAergic as they express the GABA synthesizing enzyme glutamate decarboxylase and vesicular GABA transporter transcripts. Some cholinergic neurons also express the vesicular glutamate transporter transcript gene. POMC and POMC-processing enzyme transcripts are found in a subpopulation of cholinergic neurons. Despite this heterogeneity, gene expression patterns in individual cholinergic cells appear to be highly regulated in a cell-specific manner. In fact, membrane receptor transcripts are clustered with their respective intracellular signaling and downstream targets. This novel population of cholinergic neurons may be part of the neural circuitries that detect homeostatic need for food and control the drive to eat.
Full Text Available Abstract Background Vibrio harveyi and closely related species are important pathogens in aquaculture. A complex quorum sensing cascade involving three autoinducers controls bioluminescence and several genes encoding virulence factors. Single cell analysis of a V. harveyi population has already indicated intercellular heterogeneity in the production of bioluminescence. This study was undertaken to analyze the expression of various autoinducer-dependent genes in individual cells. Results Here we used reporter strains bearing promoter::gfp fusions to monitor the induction/repression of three autoinducer-regulated genes in wild type conjugates at the single cell level. Two genes involved in pathogenesis - vhp and vscP, which code for an exoprotease and a component of the type III secretion system, respectively, and luxC (the first gene in the lux operon were chosen for analysis. The lux operon and the exoprotease gene are induced, while vscP is repressed at high cell density. As controls luxS and recA, whose expression is not dependent on autoinducers, were examined. The responses of the promoter::gfp fusions in individual cells from the same culture ranged from no to high induction. Importantly, simultaneous analysis of two autoinducer induced phenotypes, bioluminescence (light detection and exoproteolytic activity (fluorescence of a promoter::gfp fusion, in single cells provided evidence for functional heterogeneity within a V. harveyi population. Conclusions Autoinducers are not only an indicator for cell density, but play a pivotal role in the coordination of physiological activities within the population.
Labib, Mahmoud; Mohamadi, Reza M.; Poudineh, Mahla; Ahmed, Sharif U.; Ivanov, Ivaylo; Huang, Ching-Lung; Moosavi, Maral; Sargent, Edward H.; Kelley, Shana O.
Cell-to-cell variation in gene expression creates a need for techniques that can characterize expression at the level of individual cells. This is particularly true for rare circulating tumour cells, in which subtyping and drug resistance are of intense interest. Here we describe a method for cell analysis—single-cell mRNA cytometry—that enables the isolation of rare cells from whole blood as a function of target mRNA sequences. This approach uses two classes of magnetic particles that are labelled to selectively hybridize with different regions of the target mRNA. Hybridization leads to the formation of large magnetic clusters that remain localized within the cells of interest, thereby enabling the cells to be magnetically separated. Targeting specific intracellular mRNAs enablescirculating tumour cells to be distinguished from normal haematopoietic cells. No polymerase chain reaction amplification is required to determine RNA expression levels and genotype at the single-cell level, and minimal cell manipulation is required. To demonstrate this approach we use single-cell mRNA cytometry to detect clinically important sequences in prostate cancer specimens.
Luxardi, Guillaume; Reid, Brian; Maillard, Pauline; Zhao, Min
Breaching of the cell membrane is one of the earliest and most common causes of cell injury, tissue damage, and disease. If the compromise in cell membrane is not repaired quickly, irreversible cell damage, cell death and defective organ functions will result. It is therefore fundamentally important to efficiently repair damage to the cell membrane. While the molecular aspects of single cell wound healing are starting to be deciphered, its bio-physical counterpart has been poorly investigated. Using Xenopus laevis oocytes as a model for single cell wound healing, we describe the temporal and spatial dynamics of the wound electric current circuitry and the temporal dynamics of cell membrane potential variation. In addition, we show the role of calcium influx in controlling electric current circuitry and cell membrane potential variations. (i) Upon wounding a single cell: an inward electric current appears at the wound center while an outward electric current is observed at its sides, illustrating the wound electric current circuitry; the cell membrane is depolarized; calcium flows into the cell. (ii) During cell membrane re-sealing: the wound center current density is maintained for a few minutes before decreasing; the cell membrane gradually re-polarizes; calcium flow into the cell drops. (iii) In conclusion, calcium influx is required for the formation and maintenance of the wound electric current circuitry, for cell membrane re-polarization and for wound healing.
Abraham, Parvin; Maliekal, Tessy Thomas
Research of the past two decades has proved the relevance of single cell biology in basic research and translational medicine. Successful detection and isolation of specific subsets is the key to understand their functional heterogeneity. Antibodies are conventionally used for this purpose, but their relevance in certain contexts is limited. In this review, we discuss some of these contexts, posing bottle neck for different fields of biology including biomedical research. With the advancement of chemistry, several methods have been introduced to overcome these problems. Even though microfluidics and microraft array are newer techniques exploited for single cell biology, fluorescence-activated cell sorting (FACS) remains the gold standard technique for isolation of cells for many biomedical applications, like stem cell therapy. Here, we present a comprehensive and comparative account of some of the probes that are useful in FACS. Further, we illustrate how these techniques could be applied in biomedical research. It is postulated that intracellular molecular markers like nucleostemin (GNL3), alkaline phosphatase (ALPL) and HIRA can be used for improving the outcome of cardiac as well as bone regeneration. Another field that could utilize intracellular markers is diagnostics, and we propose the use of specific peptide nucleic acid probes (PNPs) against certain miRNAs for cancer surgical margin prediction. The newer techniques for single cell biology, based on intracellular molecules, will immensely enhance the repertoire of possible markers for the isolation of cell types useful in biomedical research.
Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike
An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.
Guo, Guoji; Luc, Sidinh; Marco, Eugenio; Lin, Ta-Wei; Peng, Cong; Kerenyi, Marc A; Beyaz, Semir; Kim, Woojin; Xu, Jian; Das, Partha Pratim; Neff, Tobias; Zou, Keyong; Yuan, Guo-Cheng; Orkin, Stuart H
Stem cell differentiation pathways are most often studied at the population level, whereas critical decisions are executed at the level of single cells. We have established a highly multiplexed, quantitative PCR assay to profile in an unbiased manner a panel of all commonly used cell surface markers (280 genes) from individual cells. With this method, we analyzed over 1,500 single cells throughout the mouse hematopoietic system and illustrate its utility for revealing important biological insights. The comprehensive single cell data set permits mapping of the mouse hematopoietic stem cell differentiation hierarchy by computational lineage progression analysis. Further profiling of 180 intracellular regulators enabled construction of a genetic network to assign the earliest differentiation event during hematopoietic lineage specification. Analysis of acute myeloid leukemia elicited by MLL-AF9 uncovered a distinct cellular hierarchy containing two independent self-renewing lineages with different clonal activities. The strategy has broad applicability in other cellular systems. Copyright © 2013 Elsevier Inc. All rights reserved.
Rullan, Marc; Benzinger, Dirk; Schmidt, Gregor W; Milias-Argeitis, Andreas; Khammash, Mustafa
Transcription is a highly regulated and inherently stochastic process. The complexity of signal transduction and gene regulation makes it challenging to analyze how the dynamic activity of transcriptional regulators affects stochastic transcription. By combining a fast-acting, photo-regulatable transcription factor with nascent RNA quantification in live cells and an experimental setup for precise spatiotemporal delivery of light inputs, we constructed a platform for the real-time, single-cell interrogation of transcription in Saccharomyces cerevisiae. We show that transcriptional activation and deactivation are fast and memoryless. By analyzing the temporal activity of individual cells, we found that transcription occurs in bursts, whose duration and timing are modulated by transcription factor activity. Using our platform, we regulated transcription via light-driven feedback loops at the single-cell level. Feedback markedly reduced cell-to-cell variability and led to qualitative differences in cellular transcriptional dynamics. Our platform establishes a flexible method for studying transcriptional dynamics in single cells. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Nedosekin, Dmitry A.; Nolan, Jacqueline; Biris, Alexandru S.; Zharov, Vladimir P.
Arkansas Nanomedicine Center at the University of Arkansas for Medical Sciences in collaboration with other Arkansas Universities and the FDA-based National Center of Toxicological Research in Jefferson, AR is developing novel techniques for rapid quantification of graphene-based nanomaterials (GBNs) in various biological samples. All-carbon GBNs have wide range of potential applications in industry, agriculture, food processing and medicine; however, quantification of GBNs is difficult in carbon reach biological tissues. The accurate quantification of GBNs is essential for research on material toxicity and the development of GBNs-based drug delivery platforms. We have developed microscopy and cytometry platforms for detection and quantification of GBNs in single cells, tissue and blood samples using photoacoustic contrast of GBNs. We demonstrated PA quantification of individual graphene uptake by single cells. High-resolution PA microscopy provided mapping of GBN distribution within live cells to establish correlation with intracellular toxic phenomena using apoptotic and necrotic assays. This new methodology and corresponding technical platform provide the insight on possible toxicological risks of GBNs at singe cells levels. In addition, in vivo PA image flow cytometry demonstrated the capability to monitor of GBNs pharmacokinetics in mouse model and to map the resulting biodistribution of GBNs in mouse tissues. The integrated PA platform provided an unprecedented sensitivity toward GBNs and allowed to enhance conventional toxicology research by providing a direct correlation between uptake of GBNs at a single cell level and cell viability status.
Full Text Available A major fraction of Earth's prokaryotic biomass dwells in the deep subsurface, where cellular abundances per volume of sample are lower, metabolism is slower, and generation times are longer than those in surface terrestrial and marine environments. How these conditions impact biotic interactions and evolutionary processes is largely unknown. Here we employed single cell genomics to analyze cell-to-cell genome content variability and signatures of horizontal gene transfer (HGT and viral infections in five cells of Candidatus Desulforudis audaxviator, which were collected from a three km-deep fracture water in the 2.9 Ga-old Witwatersrand Basin of South Africa. Between 0 and 32 % of genes recovered from single cells were not present in the original, metagenomic assembly of Desulforudis, which was obtained from a neighboring subsurface fracture. We found a transposable prophage, a retron, multiple clustered regularly interspaced short palindromic repeats (CRISPRs and restriction-modification systems, and an unusually high frequency of transposases in the analyzed single cell genomes. This indicates that recombination, HGT and viral infections are prevalent evolutionary events in the studied population of microorganisms inhabiting a highly stable deep subsurface environment.
Yann S Dufour
Full Text Available Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with in situ hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in Escherichia coli motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB at different levels, we quantitatively mapped motile phenotype (tumble bias to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage.
Jia, Cheng; Hu, Yu; Kelly, Derek; Kim, Junhyong; Li, Mingyao; Zhang, Nancy R
Recent technological breakthroughs have made it possible to measure RNA expression at the single-cell level, thus paving the way for exploring expression heterogeneity among individual cells. Current single-cell RNA sequencing (scRNA-seq) protocols are complex and introduce technical biases that vary across cells, which can bias downstream analysis without proper adjustment. To account for cell-to-cell technical differences, we propose a statistical framework, TASC (Toolkit for Analysis of Single Cell RNA-seq), an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins. TASC incorporates the technical parameters, which reflect cell-to-cell batch effects, into a hierarchical mixture model to estimate the biological variance of a gene and detect differentially expressed genes. More importantly, TASC is able to adjust for covariates to further eliminate confounding that may originate from cell size and cell cycle differences. In simulation and real scRNA-seq data, TASC achieves accurate Type I error control and displays competitive sensitivity and improved robustness to batch effects in differential expression analysis, compared to existing methods. TASC is programmed to be computationally efficient, taking advantage of multi-threaded parallelization. We believe that TASC will provide a robust platform for researchers to leverage the power of scRNA-seq. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Anetzberger, Claudia; Schell, Ursula; Jung, Kirsten
Vibrio harveyi and closely related species are important pathogens in aquaculture. A complex quorum sensing cascade involving three autoinducers controls bioluminescence and several genes encoding virulence factors. Single cell analysis of a V. harveyi population has already indicated intercellular heterogeneity in the production of bioluminescence. This study was undertaken to analyze the expression of various autoinducer-dependent genes in individual cells. Here we used reporter strains bearing promoter::gfp fusions to monitor the induction/repression of three autoinducer-regulated genes in wild type conjugates at the single cell level. Two genes involved in pathogenesis - vhp and vscP, which code for an exoprotease and a component of the type III secretion system, respectively, and luxC (the first gene in the lux operon) were chosen for analysis. The lux operon and the exoprotease gene are induced, while vscP is repressed at high cell density. As controls luxS and recA, whose expression is not dependent on autoinducers, were examined. The responses of the promoter::gfp fusions in individual cells from the same culture ranged from no to high induction. Importantly, simultaneous analysis of two autoinducer induced phenotypes, bioluminescence (light detection) and exoproteolytic activity (fluorescence of a promoter::gfp fusion), in single cells provided evidence for functional heterogeneity within a V. harveyi population. Autoinducers are not only an indicator for cell density, but play a pivotal role in the coordination of physiological activities within the population.
Haug Trude M
Full Text Available Abstract Background The incidence of false positives is a potential problem in single-cell PCR experiments. This paper describes an optimized protocol for single-cell qPCR measurements in primary pituitary cell cultures following patch-clamp recordings. Two different cell harvesting methods were assessed using both the GH4 prolactin producing cell line from rat, and primary cell culture from fish pituitaries. Results Harvesting whole cells followed by cell lysis and qPCR performed satisfactory on the GH4 cell line. However, harvesting of whole cells from primary pituitary cultures regularly produced false positives, probably due to RNA leakage from cells ruptured during the dispersion of the pituitary cells. To reduce RNA contamination affecting the results, we optimized the conditions by harvesting only the cytosol through a patch pipette, subsequent to electrophysiological experiments. Two important factors proved crucial for reliable harvesting. First, silanizing the patch pipette glass prevented foreign extracellular RNA from attaching to charged residues on the glass surface. Second, substituting the commonly used perforating antibiotic amphotericin B with β-escin allowed efficient cytosol harvest without loosing the giga seal. Importantly, the two harvesting protocols revealed no difference in RNA isolation efficiency. Conclusion Depending on the cell type and preparation, validation of the harvesting technique is extremely important as contaminations may give false positives. Here we present an optimized protocol allowing secure harvesting of RNA from single cells in primary pituitary cell culture following perforated whole cell patch clamp experiments.
Brück, Simon; Evers, Heidrun; Heidorn, Frank; Müller, Ute; Kilper, Roland; Verhoff, Marcel A
The purpose of this project was to develop a method that, while providing morphological quality control, allows single cells to be obtained from the surfaces of various evidence materials and be made available for DNA analysis in cases where only small amounts of cell material are present or where only mixed traces are found. With the SteREO Lumar.V12 stereomicroscope and UV unit from Zeiss, it was possible to detect and assess single epithelial cells on the surfaces of various objects (e.g., glass, plastic, metal). A digitally operated micromanipulator developed by aura optik was used to lift a single cell from the surface of evidence material and to transfer it to a conventional PCR tube or to an AmpliGrid(®) from Advalytix. The actual lifting of the cells was performed with microglobes that acted as carriers. The microglobes were held with microtweezers and were transferred to the DNA analysis receptacles along with the adhering cells. In a next step, the PCR can be carried out in this receptacle without removing the microglobe. Our method allows a single cell to be isolated directly from evidence material and be made available for forensic DNA analysis. © 2010 American Academy of Forensic Sciences.
Barkla, Bronwyn J; Garibay-Hernández, Adriana; Melzer, Michael; Rupasinghe, Thusitha W T; Roessner, Ute
Salt stress causes dramatic changes in the organization and dynamic properties of membranes, however, little is known about the underlying mechanisms involved. Modified trichomes, known as epidermal bladder cells (EBC), on the leaves and stems of the halophyte Mesembryanthemum crystallinum can be successfully exploited as a single-cell-type system to investigate salt-induced changes to cellular lipid composition. In this study alterations in key molecular species from different lipid classes highlighted an increase in phospholipid species, particularly those from phosphatidylcholine (PC) and phosphatidic acid (PA), where the latter is central to the synthesis of membrane lipids. Triacylglycerol (TG) species decreased during salinity, while there was little change in plastidic galactolipids. EBC transcriptomic and proteomic data mining revealed changes in genes and proteins involved in lipid metabolism and the upregulation of transcripts for PIPKIB, PI5PII, PIPKIII, and PLDδ, suggested the induction of signalling processes mediated by phosphoinositides and PA. TEM and flow cytometry showed the dynamic nature of lipid droplets in these cells under salt stress. Altogether, this work indicates the metabolism of TG might play an important role in EBC response to salinity as either an energy reserve for sodium accumulation and/or driving membrane biosynthesis for EBC expansion. This article is protected by copyright. All rights reserved.
Tue Bjerg Bennike
In addition, we analyzed the proteome of human plasma, and compared the proteomes to the obtained porcine synovial fluid proteome. The proteome of the two body fluids were found highly similar, underlining the detected plasma derived nature of many synovial fluid components. The healthy porcine synovial fluid proteomics data, human rheumatoid arthritis synovial fluid proteomics data used in the method optimization, human plasma proteomics data, and search results, have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD000935.
Steyer, Grant J.; Roy, Debashish; Salvado, Olivier; Stone, Meredith E.; Wilson, David L.
We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryoimaging system consists of a fluorescence microscope, robotic imaging positioner, customized cryostat, PC-based control system, and visualization/analysis software. The system alternates between sectioning (10-40 μm) and imaging, collecting color brightfield and fluorescent blockface image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells, GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation parameters were found [uT : heart (267 +/- 47.6 μm), liver (218 +/- 27.1 μm), brain (161 +/- 27.4 μm)] to be within the range of estimates in the literature. "Next image" processing removed subsurface fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and analysis of 200 microsphere images in the brain gave 97+/-2% reduction of subsurface fluorescence. Fluorescent signals were determined to arise from single cells based upon geometric and integrated intensity measurements. Next image processing greatly improved axial resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells with connected component analysis by up to 24%. Analysis of image volumes identified metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere distribution correlated with blood flow patterns. We developed and evaluated cryo-imaging to provide single-cell detection of fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB), micron
Tang, Shaojun; Hemberg, Martin; Cansizoglu, Ertugrul; Belin, Stephane; Kosik, Kenneth; Kreiman, Gabriel; Steen, Hanno; Steen, Judith
The ability to integrate 'omics' (i.e., transcriptomics and proteomics) is becoming increasingly important to the understanding of regulatory mechanisms. There are currently no tools available to identify differentially expressed genes (DEGs)across different 'omics'data types or multi-dimensional data including time courses. We present a model capable of simultaneously identifying DEGs from continuous and discrete transcriptomic, proteomic and integrated proteogenomic data. We show that...
, of altered protein expressions profiles and/or their posttranslational modifications (PTMs). Mass spectrometry (MS)-based proteomics offer enormous promise for investigating the molecular mechanisms underlying skeletal muscle insulin resistance and exercise-induced adaptation; however, skeletal muscle......Skeletal muscle is the largest tissue in the human body and plays an important role in locomotion and whole body metabolism. It accounts for ~80% of insulin stimulated glucose disposal. Skeletal muscle insulin resistance, a primary feature of Type 2 diabetes, is caused by a decreased ability...... of muscle to respond to circulating insulin. Physical exercise improves insulin sensitivity and whole body metabolism and remains one of the most promising interventions for the prevention of Type 2 diabetes. Insulin resistance and exercise adaptations in skeletal muscle might be a cause, or consequence...
Barroso Peña, Alvaro; Grüner, Malte; Forbes, Taylor; Denz, Cornelia; Strassert, Cristian A.
Antimicrobial Photodynamic Inactivation (PDI) represents an attractive alternative in the treatment of infections by antibiotic-resistant pathogenic bacteria. In PDI a photosensitizer (PS) is administered to the site of the biological target in order to generate cytotoxic singlet oxygen which reacts with the biological membrane upon application of harmless visible light. Established methods for testing the photoinduced cytotoxicity of PSs rely on the observation of the whole bacterial ensemble providing only a population-averaged information about the overall produced toxicity. However, for a deeper understanding of the processes that take place in PDI, new methods are required that provide simultaneous regulation of the ROS production, monitoring the subsequent damage induced in the bacteria cells, and full control of the distance between the bacteria and the center of the singlet oxygen production. Herein we present a novel method that enables the quantitative spatio-time-resolved analysis at the single cell level of the photoinduced damage produced by transparent microspheres functionalized with PSs. For this purpose, a methodology was introduced to monitor phototriggered changes with spatiotemporal resolution employing holographic optical tweezers and functional fluorescence microscopy. The defined distance between the photoactive particles and individual bacteria can be fixed under the microscope before the photosensitization process, and the photoinduced damage is monitored by tracing the fluorescence turn-on of a suitable marker. Our methodology constitutes a new tool for the in vitro design and analysis of photosensitizers, as it enables a quantitative response evaluation of living systems towards oxidative stress.
Merkley, Eric D.; Metz, Thomas O.; Smith, Richard D.; Baynes, John; Frizell, Norma
Succination is a chemical modification of cysteine in protein by the Krebs cycle intermediate, fumarate, yielding S-(2-succino)cysteine (2SC). Intracellular fumarate concentration and succination of proteins are increased by hyperpolarization of the inner mitochondrial membrane, in concert with mitochondrial, endoplasmic reticulum (ER) and oxidative stress in adipocytes grown in high glucose medium and in adipose tissue in obesity and diabetes. Increased succination of proteins is also detected in the kidney of a fumarase conditional knock-out mouse which develops renal tumors. Keap1, the gatekeeper of the antioxidant response, was identified as a major succinated protein in renal cancer cells, suggesting that succination may play a role in activation of the antioxidant response. A wide range of proteins is subject to succination, including enzymes, adipokines, cytoskeletal proteins and ER chaperones with functional cysteine residues. There is also significant overlap between succinated and glutathionylated proteins, and with proteins containing cysteine residues that are readily oxidized to the sulfenic (cysteic) acid. Succination of adipocyte proteins is inhibited by uncouplers, which discharge the mitochondrial membrane potential (Δψm) and by ER stress inhibitors. 2SC serves as a biomarker of mitochondrial stress or dysfunction in chronic diseases, such as obesity, diabetes and cancer, and recent studies suggest that succination is a mechanistic link between mitochondrial dysfunction, oxidative and ER stress, and cellular progression toward apoptosis. In this article, we review the history of the succinated proteome and the challenges associated with measuring this non-enzymatic post-translational modification of proteins by proteomics approaches.
Eremeev, Grigory [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)
Nb3Sn is a promising superconducting material for SRF applications and has the potential to exceed the limitations of niobium. We have used the recently commissioned Nb3Sn coating system to investigate Nb3Sn coatings on several single cell cavities by applying the same coating procedure on several different single cells with different history and pre-coating surface preparation. We report on our findings with four 1.5 GHz CEBAF-shape single cell and one 1.3 GHz ILC-shape single cavities that were coated, inspected, and tested.
Griffin, Timothy J.
Human saliva holds tremendous potential for transforming disease and health diagnostics given its richness of molecular information and non-invasive collection. Enumerating its molecular constituents is an important first step towards reaching this potential. Among the molecules in saliva, proteins and peptides arguably have the most value: they can directly indicate biochemical functions linked to a health condition/disease state, and they are attractive targets for biomarker assay development. However, cataloging and defining the human salivary proteome is challenging given the dynamic, chemically heterogeneous and complex nature of the system. In addition, the overall human saliva proteome is composed of several "sub-proteomes" which include: intact full length proteins, proteins carrying post-translational modifications (PTMs), low molecular weight peptides, and the metaproteome, derived from protein products from nonhuman organisms (e.g. microbes) present in the oral cavity. Presented here will be a summary of communal efforts to meet the challenge of characterizing the multifaceted saliva proteome, focusing on the use of mass spectrometry as the proteomic technology of choice. Implications of these efforts to characterize the salivary proteome in the context of disease diagnostics will also be discussed.
Statistical process control is a well-established and respected method which provides a general purpose, and consistent framework for monitoring and improving the quality of a process. It is routinely used in many industries where the quality of final products is critical and is often required in clinical diagnostic laboratories [1,2]. To date, the methodology has been little utilised in research proteomics. It has been shown to be capable of delivering quantitative QC procedures for qualitative clinical assays  making it an ideal methodology to apply to this area of biological research. To introduce statistical process control as an objective strategy for quality control and show how it could be used to benefit proteomics researchers and enhance the quality of the results they generate. We demonstrate that rules which provide basic quality control are easy to derive and implement and could have a major impact on data quality for many studies. Statistical process control is a powerful tool for investigating and improving proteomics research work-flows. The process of characterising measurement systems and defining control rules forces the exploration of key questions that can lead to significant improvements in performance. This work asserts that QC is essential to proteomics discovery experiments. Every experimenter must know the current capabilities of their measurement system and have an objective means for tracking and ensuring that performance. Proteomic analysis work-flows are complicated and multi-variate. QC is critical for clinical chemistry measurements and huge strides have been made in ensuring the quality and validity of results in clinical biochemistry labs. This work introduces some of these QC concepts and works to bridge their use from single analyte QC to applications in multi-analyte systems. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 The Author. Published by Elsevier
Park, Jungkap; Piehowski, Paul D.; Wilkins, Christopher; Zhou, Mowei; Mendoza, Joshua; Fujimoto, Grant M.; Gibbons, Bryson C.; Shaw, Jared B.; Shen, Yufeng; Shukla, Anil K.; Moore, Ronald J.; Liu, Tao; Petyuk, Vladislav A.; Tolić, Nikola; Paša-Tolić, Ljiljana; Smith, Richard D.; Payne, Samuel H.; Kim, Sangtae
Top-down proteomics involves the analysis of intact proteins. This approach is very attractive as it allows for analyzing proteins in their endogenous form without proteolysis, preserving valuable information about post-translation modifications, isoforms, proteolytic processing or their combinations collectively called proteoforms. Moreover, the quality of the top-down LC-MS/MS datasets is rapidly increasing due to advances in the liquid chromatography and mass spectrometry instrumentation and sample processing protocols. However, the top-down mass spectra are substantially more complex compare to the more conventional bottom-up data. To take full advantage of the increasing quality of the top-down LC-MS/MS datasets there is an urgent need to develop algorithms and software tools for confident proteoform identification and quantification. In this study we present a new open source software suite for top-down proteomics analysis consisting of an LC-MS feature finding algorithm, a database search algorithm, and an interactive results viewer. The presented tool along with several other popular tools were evaluated using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.
Guo, Baoshan; Lei, Cheng; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke
The development of reliable, sustainable, and economical sources of alternative fuels to petroleum is required to tackle the global energy crisis. One such alternative is microalgal biofuel, which is expected to play a key role in reducing the detrimental effects of global warming as microalgae absorb atmospheric CO 2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid amounts and fail to characterize a diverse population of microalgal cells with single-cell resolution in a non-invasive and interference-free manner. Here high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy was demonstrated. In particular, Euglena gracilis, an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement), within lipid droplets was investigated. The optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch quantitative phase microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase maps of every single cell at a high throughput of 10,000 cells/s, enabling accurate cell classification without the need for fluorescent staining. Specifically, the dataset was used to characterize heterogeneous populations of E. gracilis cells under two different culture conditions (nitrogen-sufficient and nitrogen-deficient) and achieve the cell classification with an error rate of only 2.15%. The method holds promise as an effective analytical tool for microalgae-based biofuel production. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.
Mason, Olivia U.; Hazen, Terry C.; Borglin, Sharon; Chain, Patrick S. G.; Dubinsky, Eric A.; Fortney, Julian L.; Han, James; Holman, Hoi-Ying N.; Hultman, Jenni; Lamendella, Regina; Mackelprang, Rachel; Malfatti, Stephanie; Tom, Lauren M.; Tringe, Susannah G.; Woyke, Tanja; Zhou, Jizhong; Rubin, Edward M.; Jansson, Janet K.
The Deepwater Horizon oil spill in the Gulf of Mexico resulted in a deep-sea hydrocarbon plume that caused a shift in the indigenous microbial community composition with unknown ecological consequences. Early in the spill history, a bloom of uncultured, thus uncharacterized, members of the Oceanospirillales was previously detected, but their role in oil disposition was unknown. Here our aim was to determine the functional role of the Oceanospirillales and other active members of the indigenous microbial community using deep sequencing of community DNA and RNA, as well as single-cell genomics. Shotgun metagenomic and metatranscriptomic sequencing revealed that genes for motility, chemotaxis and aliphatic hydrocarbon degradation were significantly enriched and expressed in the hydrocarbon plume samples compared with uncontaminated seawater collected from plume depth. In contrast, although genes coding for degradation of more recalcitrant compounds, such as benzene, toluene, ethylbenzene, total xylenes and polycyclic aromatic hydrocarbons, were identified in the metagenomes, they were expressed at low levels, or not at all based on analysis of the metatranscriptomes. Isolation and sequencing of two Oceanospirillales single cells revealed that both cells possessed genes coding for n-alkane and cycloalkane degradation. Specifically, the near-complete pathway for cyclohexane oxidation in the Oceanospirillales single cells was elucidated and supported by both metagenome and metatranscriptome data. The draft genome also included genes for chemotaxis, motility and nutrient acquisition strategies that were also identified in the metagenomes and metatranscriptomes. These data point towards a rapid response of members of the Oceanospirillales to aliphatic hydrocarbons in the deep sea.
Bozem, Monika; Knapp, Phillip; Mirčeski, Valentin; Slowik, Ewa J; Bogeski, Ivan; Kappl, Reinhard; Heinemann, Christian; Hoth, Markus
H 2 O 2 is produced by all eukaryotic cells under physiological and pathological conditions. Due to its enormous relevance for cell signaling at low concentrations and antipathogenic function at high concentrations, precise quantification of extracellular local H 2 O 2 concentrations ([H 2 O 2 ]) originating from single cells is required. Using a scanning electrochemical microscope and bare platinum disk ultramicroelectrodes, we established sensitive long-term measurements of extracellular [H 2 O 2 ] kinetics originating from single primary human monocytes (MCs) ex vivo. For the electrochemical techniques square wave voltammetry, cyclic and linear scan voltammetry, and chronoamperometry, detection limits for [H 2 O 2 ] were determined to be 5, 50, and 500 nM, respectively. Following phorbol ester stimulation, local [H 2 O 2 ] 5-8 μm above a single MC increased by 3.4 nM/s within the first 10 min before reaching a plateau. After extracellular addition of H 2 O 2 to an unstimulated MC, the local [H 2 O 2 ] decreased on average by 4.2 nM/s due to degradation processes of the cell. Using the scanning mode of the setup, we found that H 2 O 2 is evenly distributed around the producing cell and can still be detected up to 30 μm away from the cell. The electrochemical single-cell measurements were validated in MC populations using electron spin resonance spectroscopy and the Amplex ® UltraRed assay. Innovation and Conclusion: We demonstrate a highly sensitive, spatially, and temporally resolved electrochemical approach to monitor dynamics of production and degradation processes for H 2 O 2 separately. Local extracellular [H 2 O 2 ] kinetics originating from single cells is quantified in real time. Antioxid. Redox Signal. 00, 000-000.
Parks, Donovan H.; Imelfort, Michael; Skennerton, Connor T.; Hugenholtz, Philip; Tyson, Gene W.
Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities. PMID:25977477
YI Ping; LI Li; YAO Hong; ZHOU Yuan-guo; DENG Bing; CHEN Zhu-qin
Objective:To evaluate the possibility of the technology involving PEP and RDB for detecting β-thalassaemia multipoint mutations from a single cell simultaneously. Methods: A set of allele specific oligonucleotide (ASO) probes used for detecting 8 familiar β-thalassaemia mutations (CD41-42, IVS- Ⅱ -654, CD17, TATA box nt-28, CD71-72, TATA box nt-29, CD26, IVS- Ⅰ -5) were immobilized on a strip of nylon membrane. The genome of a individual cell was amplified by primer extension preamplification (PEP) with the mixture of15-base random oligonucleotides. The aliquots from PEP were used to amplify the objective gene fractions of β-thalassaemia gene by nested or semi-nested PCR. The membrane was hybridized with the final amplified products and then treated with Streptavidin-HRP and color development.Results :Totally 30 lymphocytes were picked up from blood samples of 1 healthy female and 4 patients with known β-thalassaemia mutations respectively. Each single lymphocyte was lysed in the proteinase K buffer. The amplification efficacy was 94.0% and alle drop-out(ADO) rate was 8.0%. Revert dot blot (RDB) was applied to the final amplified products from the 5 participants. The results of diagnosis were the same to the expected, and their genotypes were N/N, CD17 (A→T)/N, IVS- Ⅱ -654(C→T)/CD17(A → T), CD41-42 (-CTTT)/N and TATA box nt-28 (A→G)/N, respectively. Conclusion: The technology involving PEP and RDB could detectmultiple β-thalassaemia mutations from a single cell simultaneously,and the research provides experimental evidences for the feasibility of applying PEP and DNA array technology to screening multiple genetic mutations from a single cell, and will be applied to preimplantation genetic diagnosis and non-invasive prenatal diagnosis for β-thalassaemia.
Wei, Jiangyong; Hu, Xiaohua; Zou, Xiufen; Tian, Tianhai
Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information. This work designs an integrated approach to reverse-engineer gene networks for regulating early blood development based on singel-cell experimental observations. The wanderlust algorithm is initially used to develop the pseudo-trajectory for the activities of a number of genes. Since the gene expression data in the developed pseudo-trajectory show large fluctuations, we then use Gaussian process regression methods to smooth the gene express data in order to obtain pseudo-trajectories with much less fluctuations. The proposed integrated framework consists of both bioinformatics algorithms to reconstruct the regulatory network and mathematical models using differential equations to describe the dynamics of gene expression. The developed approach is applied to study the network regulating early blood cell development. A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes. Numerical results suggests that the proposed model is able to match experimental data very well. We also examine the networks with more regulatory relations and numerical results show that more regulations may exist. We test the possibility of auto-regulation but numerical simulations do not support the positive auto-regulation. In addition, robustness is used as an importantly additional criterion to select candidate
Anton A Nizhnikov
Full Text Available Despite extensive study, progress in elucidation of biological functions of amyloids and their role in pathology is largely restrained due to the lack of universal and reliable biochemical methods for their discovery. All biochemical methods developed so far allowed only identification of glutamine/asparagine-rich amyloid-forming proteins or proteins comprising amyloids that form large deposits. In this article we present a proteomic approach which may enable identification of a broad range of amyloid-forming proteins independently of specific features of their sequences or levels of expression. This approach is based on the isolation of protein fractions enriched with amyloid aggregates via sedimentation by ultracentrifugation in the presence of strong ionic detergents, such as sarkosyl or SDS. Sedimented proteins are then separated either by 2D difference gel electrophoresis or by SDS-PAGE, if they are insoluble in the buffer used for 2D difference gel electrophoresis, after which they are identified by mass-spectrometry. We validated this approach by detection of known yeast prions and mammalian proteins with established capacity for amyloid formation and also revealed yeast proteins forming detergent-insoluble aggregates in the presence of human huntingtin with expanded polyglutamine domain. Notably, with one exception, all these proteins contained glutamine/asparagine-rich stretches suggesting that their aggregates arose due to polymerization cross-seeding by human huntingtin. Importantly, though the approach was developed in a yeast model, it can easily be applied to any organism thus representing an efficient and universal tool for screening for amyloid proteins.
The author briefly describes a stochastic model for radiation effects in single cells, discusses some results based on this model and then raises several questions which need further attention. While the ultimate goal is to develop appropriate stochastic models of phenomena arising in irradiated experimental animals, the present concern however is limited to irradiation effects on cells of some homogeneous tissue. The basic assumptions underlying the stochastic model are presented. Some of the model implications are compared with empirical findings in the literature. The question of whether or not a primary particle of UV radiation generates any secondary particles is also considered. (Auth.)
Remacle, Françoise; Levine, Raphael D
The response of protein signalization networks to perturbations is analysed from single cell measurements. This experimental approach allows characterizing the fluctuations in protein expression levels from cell to cell. The analysis is based on an information theoretic approach grounded in thermodynamics leading to a quantitative version of Le Chatelier principle which allows to predict the molecular response. Two systems are investigated: human macrophages subjected to lipopolysaccharide challenge, analogous to the immune response against Gram-negative bacteria and the response of the proteins involved in the mTOR signalizing network of GBM cancer cells to changes in partial oxygen pressure. © 2014 médecine/sciences – Inserm.
Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan
In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.
Marcelina Cardoso Dos Santos
Full Text Available We propose a new strategy to evaluate adhesion strength at the single cell level. This approach involves variable-angle total internal reflection fluorescence microscopy to monitor in real time the topography of cell membranes, i.e. a map of the membrane/substrate separation distance. According to the Boltzmann distribution, both potential energy profile and dissociation energy related to the interactions between the cell membrane and the substrate were determined from the membrane topography. We have highlighted on glass substrates coated with poly-L-lysine and fibronectin, that the dissociation energy is a reliable parameter to quantify the adhesion strength of MDA-MB-231 motile cells.
Deeley, J.O.T.; Moore, J.L.
The results obtained by a microgel electrophoresis are comparable to conventional gel electrophoresis and elution techniques (Singh et al, 1989), DNA precipitation, alkali unwinding and cell clonogenicity assays (Olive et al, 1990). Since single cells are assessed, microgel electrophoresis is particularly appropriate for end-points such as the intercell variation in response. The simplicity, low cost and rapidity of microgel electrophoresis compared with other assays makes it particularly attractive for assessing the effects on DNA of radiation and other genotoxic agents on the general population. (Author)
Wang Yan; Li Deguan; Liu Jianfeng; Chu Liping; Liu Qiang
Objective: To assess the non-target effect of ionizing radiation by single cell gel electrophoresis (SCGE). Methods: Cross incubated the irradiated( 137 Cs; 2Gy) or non-irradiated lymphocytes of human peripheral blood in the irradiated or non-irradiated plasma respectively, then, assess the DNA damage of lymphocytes using SCGE analysis. Results: The lymphocytes incubated in the irradiated plasma presented more obvious DNA damage than the incubated in the non-irradiated plasma dose (P<0.05). Conclusion: The non-target effect of ionizing radiation can be assessed by SCGE, and the results confirm that cytokines may play a great role in it. (authors)
In the framework of improvement of cavity electropolishing, modelling permits to evaluate some parameters not easily accessible by experiments and can also help us to guide them. Different laboratories (DESY, Fermilab) work on electro or chemical polishing modelling with different approaches and softwares. At CEA Saclay, COMSOL software is used to model horizontal electropolishing of cavity in two dimensions. The goal of this study has been motivated by improvement of our electropolishing setup by modifying the arrival of the acid. The influence of a protuberant cathode has been evaluated and compared for different shapes of single cell cavities: TESLA, ILC Low Loss (LL ILC ), and ILC Reentrant (RE ILC ). (author)
Weng, Yaochung; Delgado, Francisco Feijó; Son, Sungmin; Burg, Thomas P; Wasserman, Steven C; Manalis, Scott R
We present two methods by which single cells can be mechanically trapped and continuously monitored within the suspended microchannel resonator (SMR) mass sensor. Since the fluid surrounding the trapped cell can be quickly and completely replaced on demand, our methods are well suited for measuring changes in cell size and growth in response to drugs or other chemical stimuli. We validate our methods by measuring the density of single polystyrene beads and Saccharomyces cerevisiae yeast cells with a precision of approximately 10(-3) g cm(-3), and by monitoring the growth of single mouse lymphoblast cells before and after drug treatment.
Kremb, Stephan Georg; Voolstra, Christian R.
Natural products (NPs) are highly evolved molecules making them a valuable resource for new therapeutics. Here we demonstrate the usefulness of broad-spectrum phenotypic profiling of NP-induced perturbations on single cells with imaging-based High
Eckhardt, Adam; Jágr, Michal; Pataridis, Statis; Mikšík, Ivan
The unique pulp-dentin complex demonstrates strong regenerative potential, which enables it to respond to disease and traumatic injury. Identifying the proteins of the pulp-dentin complex is crucial to understanding the mechanisms of regeneration, tissue calcification, defense processes, and the reparation of dentin by dental pulp. The lack of knowledge of these proteins limits the development of more efficient therapies. The proteomic profile of human tooth pulp was investigated and compared with the proteome of human dentin and blood. The samples of tooth pulp were obtained from 5 sound permanent human third molars of 5 adults (n = 5). The extracted proteins were separated by 2-dimensional gel electrophoresis, analyzed by nano-liquid chromatography tandem mass spectrometry, and identified by correlating mass spectra to the proteomic databases. A total of 342 proteins were identified with high confidence, and 2 proteins were detected for the first time in an actual human sample. The identified tooth pulp proteins have a variety of functions: structural, catalytic, transporter, protease activity, immune response, and many others. In a comparison with dentin and blood plasma, 140 (pulp/dentin) shared proteins were identified, 37 of which were not observed in plasma. It can be suggested that they might participate in the unique pulp-dentin complex. This proteomic investigation of human tooth pulp, together with the previously published study of human dentin, is one of the most comprehensive proteome lists of human teeth to date. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.
Jodar, Meritxell; Soler-Ventura, Ada; Oliva, Rafael
Semen is a complex body fluid containing an admixture of spermatozoa suspended in secretions from the testes and epididymis which are mixed at the time of ejaculation with secretions from other accessory sex glands such as the prostate and seminal vesicles. High-throughput technologies have revealed that, contrary to the idea that sperm cells are simply a silent delivery vehicle of the male genome to the oocyte, the sperm cells in fact provide both a specific epigenetically marked DNA together with a complex population of proteins and RNAs crucial for embryogenesis. Similarly, -omic technologies have also enlightened that seminal fluid seems to play a much greater role than simply being a medium to carry the spermatozoa through the female reproductive tract. In the present review, we briefly overview the sperm cell biology, consider the key issues in sperm and seminal fluid sample preparation for high-throughput proteomic studies, describe the current state of the sperm and seminal fluid proteomes generated by high-throughput proteomic technologies and provide new insights into the potential communication between sperm and seminal fluid. In addition, comparative proteomic studies open a window to explore the potential pathogenic mechanisms of infertility and the discovery of potential biomarkers with clinical significance. The review updates the numerous proteomics studies performed on semen, including spermatozoa and seminal fluid. In addition, an integrative analysis of the testes, sperm and seminal fluid proteomes is also included providing insights into the molecular mechanisms that regulate the generation, maturation and transit of spermatozoa. Furthermore, the compilation of several differential proteomic studies focused on male infertility reveals potential pathways disturbed in specific subtypes of male infertility and points out towards future research directions in the field. Copyright © 2016 Elsevier B.V. All rights reserved.