TY - GEN A1 - Srivastava, Abhishek A1 - Murugaiyan, Jayaseelan A1 - Garcia, Juan A. L. A1 - De Corte, Daniele A1 - Hoetzinger, Matthias A1 - Eravci, Murat A1 - Weise, Christoph A1 - Kumar, Yadhu A1 - Roesler, Uwe A1 - Hahn, Martin W. A1 - Grossart, Hans-Peter T1 - Combined Methylome, Transcriptome and Proteome Analyses Document Rapid Acclimatization of a Bacterium to Environmental Changes T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Polynucleobacter asymbioticus strain QLW-P1DMWA-1T represents a group of highly successful heterotrophic ultramicrobacteria that is frequently very abundant (up to 70% of total bacterioplankton) in freshwater habitats across all seven continents. This strain was originally isolated from a shallow Alpine pond characterized by rapid changes in water temperature and elevated UV radiation due to its location at an altitude of 1300 m. To elucidate the strain’s adjustment to fluctuating environmental conditions, we recorded changes occurring in its transcriptomic and proteomic profiles under contrasting experimental conditions by simulating thermal conditions in winter and summer as well as high UV irradiation. To analyze the potential connection between gene expression and regulation via methyl group modification of the genome, we also analyzed its methylome. The methylation pattern differed between the three treatments, pointing to its potential role in differential gene expression. An adaptive process due to evolutionary pressure in the genus was deduced by calculating the ratios of non-synonymous to synonymous substitution rates for 20 Polynucleobacter spp. genomes obtained from geographically diverse isolates. The results indicate purifying selection. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1011 KW - DNA modification KW - gene expression KW - freshwater heterotrophic bacteria KW - UV radiation KW - purifying selection Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-481993 SN - 1866-8372 IS - 1011 ER - TY - JOUR A1 - Srivastava, Abhishek A1 - Murugaiyan, Jayaseelan A1 - Garcia, Juan A. L. A1 - De Corte, Daniele A1 - Hoetzinger, Matthias A1 - Eravci, Murat A1 - Weise, Christoph A1 - Kumar, Yadhu A1 - Roesler, Uwe A1 - Hahn, Martin W. A1 - Grossart, Hans-Peter T1 - Combined Methylome, Transcriptome and Proteome Analyses Document Rapid Acclimatization of a Bacterium to Environmental Changes JF - Frontiers in Microbiology N2 - Polynucleobacter asymbioticus strain QLW-P1DMWA-1T represents a group of highly successful heterotrophic ultramicrobacteria that is frequently very abundant (up to 70% of total bacterioplankton) in freshwater habitats across all seven continents. This strain was originally isolated from a shallow Alpine pond characterized by rapid changes in water temperature and elevated UV radiation due to its location at an altitude of 1300 m. To elucidate the strain’s adjustment to fluctuating environmental conditions, we recorded changes occurring in its transcriptomic and proteomic profiles under contrasting experimental conditions by simulating thermal conditions in winter and summer as well as high UV irradiation. To analyze the potential connection between gene expression and regulation via methyl group modification of the genome, we also analyzed its methylome. The methylation pattern differed between the three treatments, pointing to its potential role in differential gene expression. An adaptive process due to evolutionary pressure in the genus was deduced by calculating the ratios of non-synonymous to synonymous substitution rates for 20 Polynucleobacter spp. genomes obtained from geographically diverse isolates. The results indicate purifying selection. KW - DNA modification KW - gene expression KW - freshwater heterotrophic bacteria KW - UV radiation KW - purifying selection Y1 - 2020 U6 - https://doi.org/10.3389/fmicb.2020.544785 SN - 1664-302X VL - 11 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Ryngajllo, Malgorzata A1 - Childs, Liam H. A1 - Lohse, Marc A1 - Giorgi, Federico M. A1 - Lude, Anja A1 - Selbig, Joachim A1 - Usadel, Björn T1 - SLocX predicting subcellular localization of Arabidopsis proteins leveraging gene expression data JF - Frontiers in plant science N2 - Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the subcellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the subcellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mito-chondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel subcellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins. KW - subcellular localization KW - support vector machine KW - prediction KW - gene expression Y1 - 2011 U6 - https://doi.org/10.3389/fpls.2011.00043 SN - 1664-462X VL - 2 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Reim, Tina A1 - Thamm, Markus A1 - Rolke, Daniel A1 - Blenau, Wolfgang A1 - Scheiner, Ricarda T1 - Suitability of three common reference genes for quantitative real-time PCR in honey bees JF - Apidologie : a quality journal in bee science N2 - Honey bees are important model organisms for neurobiology, because they display a large array of behaviors. To link behavior with individual gene function, quantitative polymerase chain reaction is frequently used. Comparing gene expression of different individuals requires data normalization using adequate reference genes. These should ideally be expressed stably throughout lifetime. Unfortunately, this is frequently not the case. We studied how well three commonly used reference genes are suited for this purpose and measured gene expression in the brains of honey bees differing in age and social role. Although rpl32 is used most frequently, it only remains stable in expression between newly emerged bees, nurse-aged bees, and pollen foragers but shows a peak at the age of 12 days. The genes gapdh and ef1 alpha-f1, in contrast, are expressed stably in the brain throughout all age groups except newly emerged bees. According to stability software, gapdh was expressed most stably, followed by rpl32 and ef1 alpha-f1. KW - gene expression KW - quantitative PCR KW - reference gene KW - stability program KW - Apis mellifera Y1 - 2013 U6 - https://doi.org/10.1007/s13592-012-0184-3 SN - 0044-8435 VL - 44 IS - 3 SP - 342 EP - 350 PB - Springer CY - Paris ER - TY - THES A1 - Perscheid, Cindy T1 - Integrative biomarker detection using prior knowledge on gene expression data sets T1 - Integrative Biomarker-Erkennung auf Genexpressions-Daten mithilfe von biologischem Vorwissen N2 - Gene expression data is analyzed to identify biomarkers, e.g. relevant genes, which serve for diagnostic, predictive, or prognostic use. Traditional approaches for biomarker detection select distinctive features from the data based exclusively on the signals therein, facing multiple shortcomings in regards to overfitting, biomarker robustness, and actual biological relevance. Prior knowledge approaches are expected to address these issues by incorporating prior biological knowledge, e.g. on gene-disease associations, into the actual analysis. However, prior knowledge approaches are currently not widely applied in practice because they are often use-case specific and seldom applicable in a different scope. This leads to a lack of comparability of prior knowledge approaches, which in turn makes it currently impossible to assess their effectiveness in a broader context. Our work addresses the aforementioned issues with three contributions. Our first contribution provides formal definitions for both prior knowledge and the flexible integration thereof into the feature selection process. Central to these concepts is the automatic retrieval of prior knowledge from online knowledge bases, which allows for streamlining the retrieval process and agreeing on a uniform definition for prior knowledge. We subsequently describe novel and generalized prior knowledge approaches that are flexible regarding the used prior knowledge and applicable to varying use case domains. Our second contribution is the benchmarking platform Comprior. Comprior applies the aforementioned concepts in practice and allows for flexibly setting up comprehensive benchmarking studies for examining the performance of existing and novel prior knowledge approaches. It streamlines the retrieval of prior knowledge and allows for combining it with prior knowledge approaches. Comprior demonstrates the practical applicability of our concepts and further fosters the overall development and comparability of prior knowledge approaches. Our third contribution is a comprehensive case study on the effectiveness of prior knowledge approaches. For that, we used Comprior and tested a broad range of both traditional and prior knowledge approaches in combination with multiple knowledge bases on data sets from multiple disease domains. Ultimately, our case study constitutes a thorough assessment of a) the suitability of selected knowledge bases for integration, b) the impact of prior knowledge being applied at different integration levels, and c) the improvements in terms of classification performance, biological relevance, and overall robustness. In summary, our contributions demonstrate that generalized concepts for prior knowledge and a streamlined retrieval process improve the applicability of prior knowledge approaches. Results from our case study show that the integration of prior knowledge positively affects biomarker results, particularly regarding their robustness. Our findings provide the first in-depth insights on the effectiveness of prior knowledge approaches and build a valuable foundation for future research. N2 - Biomarker sind charakteristische biologische Merkmale mit diagnostischer oder prognostischer Aussagekraft. Auf der molekularen Ebene sind dies Gene mit einem krankheitsspezifischen Expressionsmuster, welche mittels der Analyse von Genexpressionsdaten identifiziert werden. Traditionelle Ansätze für diese Art von Biomarker Detection wählen Gene als Biomarker ausschließlich anhand der vorhandenen Signale im Datensatz aus. Diese Vorgehensweise zeigt jedoch Schwächen insbesondere in Bezug auf die Robustheit und tatsächliche biologische Relevanz der identifizierten Biomarker. Verschiedene Forschungsarbeiten legen nahe, dass die Berücksichtigung des biologischen Kontexts während des Selektionsprozesses diese Schwächen ausgleichen kann. Sogenannte wissensbasierte Ansätze für Biomarker Detection beziehen vorhandenes biologisches Wissen, beispielsweise über Zusammenhänge zwischen bestimmten Genen und Krankheiten, direkt in die Analyse mit ein. Die Anwendung solcher Verfahren ist in der Praxis jedoch derzeit nicht weit verbreitet, da existierende Methoden oft spezifisch für einen bestimmten Anwendungsfall entwickelt wurden und sich nur mit großem Aufwand auf andere Anwendungsgebiete übertragen lassen. Dadurch sind Vergleiche untereinander kaum möglich, was es wiederum nicht erlaubt die Effektivität von wissensbasierten Methoden in einem breiteren Kontext zu untersuchen. Die vorliegende Arbeit befasst sich mit den vorgenannten Herausforderungen für wissensbasierte Ansätze. In einem ersten Schritt legen wir formale und einheitliche Definitionen für vorhandenes biologisches Wissen sowie ihre flexible Integration in den Biomarker-Auswahlprozess fest. Der Kerngedanke unseres Ansatzes ist die automatisierte Beschaffung von biologischem Wissen aus im Internet frei verfügbaren Wissens-Datenbanken. Dies erlaubt eine Vereinfachung der Kuratierung sowie die Festlegung einer einheitlichen Definition für biologisches Wissen. Darauf aufbauend beschreiben wir generalisierte wissensbasierte Verfahren, welche flexibel auf verschiedene Anwendungsfalle anwendbar sind. In einem zweiten Schritt haben wir die Benchmarking-Plattform Comprior entwickelt, welche unsere theoretischen Konzepte in einer praktischen Anwendung realisiert. Comprior ermöglicht die schnelle Umsetzung von umfangreichen Experimenten für den Vergleich von wissensbasierten Ansätzen. Comprior übernimmt die Beschaffung von biologischem Wissen und ermöglicht dessen beliebige Kombination mit wissensbasierten Ansätzen. Comprior demonstriert damit die praktische Umsetzbarkeit unserer theoretischen Konzepte und unterstützt zudem die technische Realisierung und Vergleichbarkeit wissensbasierter Ansätze. In einem dritten Schritt untersuchen wir die Effektivität wissensbasierter Ansätze im Rahmen einer umfangreichen Fallstudie. Mithilfe von Comprior vergleichen wir die Ergebnisse traditioneller und wissensbasierter Ansätze im Kontext verschiedener Krankheiten, wobei wir für wissensbasierte Ansätze auch verschiedene Wissens-Datenbanken verwenden. Unsere Fallstudie untersucht damit a) die Eignung von ausgewählten Wissens-Datenbanken für deren Einsatz bei wissensbasierten Ansätzen, b) den Einfluss verschiedener Integrationskonzepte für biologisches Wissen auf den Biomarker-Auswahlprozess, und c) den Grad der Verbesserung in Bezug auf die Klassifikationsleistung, biologische Relevanz und allgemeine Robustheit der selektierten Biomarker. Zusammenfassend demonstriert unsere Arbeit, dass generalisierte Konzepte für biologisches Wissen und dessen vereinfachte Kuration die praktische Anwendbarkeit von wissensbasierten Ansätzen erleichtern. Die Ergebnisse unserer Fallstudie zeigen, dass die Integration von vorhandenem biologischen Wissen einen positiven Einfluss auf die selektierten Biomarker hat, insbesondere in Bezug auf ihre biologische Relevanz. Diese erstmals umfassenderen Erkenntnisse zur Effektivität von wissensbasierten Ansätzen bilden eine wertvolle Grundlage für zukünftige Forschungsarbeiten. KW - gene expression KW - biomarker detection KW - prior knowledge KW - feature selection KW - Biomarker-Erkennung KW - Merkmalsauswahl KW - Gen-Expression KW - biologisches Vorwissen Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-582418 ER - TY - JOUR A1 - Omidbakhshfard, Mohammad Amin A1 - Winck, Flavia Vischi A1 - Arvidsson, Samuel Janne A1 - Riano-Pachon, Diego M. A1 - Müller-Röber, Bernd T1 - A step-by-step protocol for formaldehyde-assisted isolation of regulatory elements from Arabidopsis thaliana JF - Journal of integrative plant biology N2 - The control of gene expression by transcriptional regulators and other types of functionally relevant DNA transactions such as chromatin remodeling and replication underlie a vast spectrum of biological processes in all organisms. DNA transactions require the controlled interaction of proteins with DNA sequence motifs which are often located in nucleosome-depleted regions (NDRs) of the chromatin. Formaldehyde-assisted isolation of regulatory elements (FAIRE) has been established as an easy-to-implement method for the isolation of NDRs from a number of eukaryotic organisms, and it has been successfully employed for the discovery of new regulatory segments in genomic DNA from, for example, yeast, Drosophila, and humans. Until today, however, FAIRE has only rarely been employed in plant research and currently no detailed FAIRE protocol for plants has been published. Here, we provide a step-by-step FAIRE protocol for NDR discovery in Arabidopsis thaliana. We demonstrate that NDRs isolated from plant chromatin are readily amenable to quantitative polymerase chain reaction and next-generation sequencing. Only minor modification of the FAIRE protocol will be needed to adapt it to other plants, thus facilitating the global inventory of regulatory regions across species. KW - Arabidopsis thaliana KW - chromatin KW - cis-regulatory elements KW - epigenomics KW - FAIRE-qPCR KW - FAIRE-seq KW - gene expression KW - gene regulatory network KW - transcription factor Y1 - 2014 U6 - https://doi.org/10.1111/jipb.12151 SN - 1672-9072 SN - 1744-7909 VL - 56 IS - 6 SP - 527 EP - 538 PB - Wiley-Blackwell CY - Hoboken ER - TY - GEN A1 - Machens, Fabian A1 - Balazadeh, Salma A1 - Müller-Röber, Bernd A1 - Messerschmidt, Katrin T1 - Synthetic Promoters and Transcription Factors for Heterologous Protein Expression in Saccharomyces cerevisiae N2 - Orthogonal systems for heterologous protein expression as well as for the engineering of synthetic gene regulatory circuits in hosts like Saccharomyces cerevisiae depend on synthetic transcription factors (synTFs) and corresponding cis-regulatory binding sites. We have constructed and characterized a set of synTFs based on either transcription activator-like effectors or CRISPR/Cas9, and corresponding small synthetic promoters (synPs) with minimal sequence identity to the host’s endogenous promoters. The resulting collection of functional synTF/synP pairs confers very low background expression under uninduced conditions, while expression output upon induction of the various synTFs covers a wide range and reaches induction factors of up to 400. The broad spectrum of expression strengths that is achieved will be useful for various experimental setups, e.g., the transcriptional balancing of expression levels within heterologous pathways or the construction of artificial regulatory networks. Furthermore, our analyses reveal simple rules that enable the tuning of synTF expression output, thereby allowing easy modification of a given synTF/synP pair. This will make it easier for researchers to construct tailored transcriptional control systems. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 393 KW - JUB1 KW - chimeric transcription factors KW - dead Cas9 KW - gene expression KW - synthetic biology KW - synthetic circuits KW - transcriptional regulation Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-403804 ER - TY - JOUR A1 - Machens, Fabian A1 - Balazadeh, Salma A1 - Müller-Röber, Bernd A1 - Messerschmidt, Katrin T1 - Synthetic Promoters and Transcription Factors for Heterologous Protein Expression in Saccharomyces cerevisiae JF - Frontiers in Bioengineering and Biotechnology N2 - Orthogonal systems for heterologous protein expression as well as for the engineering of synthetic gene regulatory circuits in hosts like Saccharomyces cerevisiae depend on synthetic transcription factors (synTFs) and corresponding cis-regulatory binding sites. We have constructed and characterized a set of synTFs based on either transcription activator-like effectors or CRISPR/Cas9, and corresponding small synthetic promoters (synPs) with minimal sequence identity to the host’s endogenous promoters. The resulting collection of functional synTF/synP pairs confers very low background expression under uninduced conditions, while expression output upon induction of the various synTFs covers a wide range and reaches induction factors of up to 400. The broad spectrum of expression strengths that is achieved will be useful for various experimental setups, e.g., the transcriptional balancing of expression levels within heterologous pathways or the construction of artificial regulatory networks. Furthermore, our analyses reveal simple rules that enable the tuning of synTF expression output, thereby allowing easy modification of a given synTF/synP pair. This will make it easier for researchers to construct tailored transcriptional control systems. KW - JUB1 KW - synthetic biology KW - transcriptional regulation KW - gene expression KW - synthetic circuits KW - dead Cas9 KW - chimeric transcription factors Y1 - 2017 U6 - https://doi.org/10.3389/fbioe.2017.00063 SN - 2296-4185 VL - 5 SP - 1 EP - 11 PB - Frontiers CY - Lausanne ER - TY - JOUR A1 - Klie, Sebastian A1 - Nikoloski, Zoran A1 - Selbig, Joachim T1 - Biological cluster evaluation for gene function prediction JF - Journal of computational biology N2 - Recent advances in high-throughput omics techniques render it possible to decode the function of genes by using the "guilt-by-association" principle on biologically meaningful clusters of gene expression data. However, the existing frameworks for biological evaluation of gene clusters are hindered by two bottleneck issues: (1) the choice for the number of clusters, and (2) the external measures which do not take in consideration the structure of the analyzed data and the ontology of the existing biological knowledge. Here, we address the identified bottlenecks by developing a novel framework that allows not only for biological evaluation of gene expression clusters based on existing structured knowledge, but also for prediction of putative gene functions. The proposed framework facilitates propagation of statistical significance at each of the following steps: (1) estimating the number of clusters, (2) evaluating the clusters in terms of novel external structural measures, (3) selecting an optimal clustering algorithm, and (4) predicting gene functions. The framework also includes a method for evaluation of gene clusters based on the structure of the employed ontology. Moreover, our method for obtaining a probabilistic range for the number of clusters is demonstrated valid on synthetic data and available gene expression profiles from Saccharomyces cerevisiae. Finally, we propose a network-based approach for gene function prediction which relies on the clustering of optimal score and the employed ontology. Our approach effectively predicts gene function on the Saccharomyces cerevisiae data set and is also employed to obtain putative gene functions for an Arabidopsis thaliana data set. KW - algorithms KW - biochemical networks KW - combinatorics KW - computational molecular biology KW - databases KW - functional genomics KW - gene expression KW - NP-completeness Y1 - 2014 U6 - https://doi.org/10.1089/cmb.2009.0129 SN - 1066-5277 SN - 1557-8666 VL - 21 IS - 6 SP - 428 EP - 445 PB - Liebert CY - New Rochelle ER - TY - JOUR A1 - Jbeily, Nayla A1 - Suckert, Iris A1 - Gonnert, Falk A. A1 - Acht, Benedikt A1 - Bockmeyer, Clemens L. A1 - Grossmann, Sascha D. A1 - Blaess, Markus F. A1 - Lüth, Anja A1 - Deigner, Hans-Peter A1 - Bauer, Michael A1 - Claus, Ralf A. T1 - Hyperresponsiveness of mice deficient in plasma-secreted sphingomyelinase reveals its pivotal role in early phase of host response JF - Journal of lipid research N2 - Plasma secretion of acid sphingomyelinase is a hallmark of cellular stress response resulting in the formation of membrane embedded ceramide-enriched lipid rafts and the reorganization of receptor complexes. Consistently, decompartmentalization of ceramide formation from inert sphingomyelin has been associated with signaling events and regulation of the cellular phenotype. Herein, we addressed the question of whether the secretion of acid sphingomyelinase is involved in host response during sepsis. We found an exaggerated clinical course in mice genetically deficient in acid sphingomyelinase characterized by an increased bacterial burden, an increased phagocytotic activity, and a more pronounced cytokine storm. Moreover, on a functional level, leukocyte-endothelial interaction was found diminished in sphingomyelinase-deficient animals corresponding to a distinct leukocytes' phenotype with respect to rolling and sticking as well as expression of cellular surface proteins.(jlr) We conclude that hydrolysis of membrane-embedded sphingomyelin, triggered by circulating sphingomyelinase, plays a pivotal role in the first line of defense against invading microorganisms. This function might be essential during the early phase of infection leading to an adaptive response of remote cells and tissues.-Jbeily, N., I. Suckert, F. A. Gonnert, B. Acht, C. L. Bockmeyer, S. D. Grossmann, M. F. Blaess, A. Lueth, H.-P. Deigner, M. Bauer, and R. A. Claus. Hyperresponsiveness of mice deficient in plasma-secreted sphingomyelinase reveals its pivotal role in early phase of host response. J. Lipid Res. 2013. 54: 410-424. KW - sphingomyelin phosphodiesterase 1 KW - inflammation KW - sepsis KW - gene expression KW - survival KW - leukocyte-endothelial interaction KW - trans-migration KW - organ failure Y1 - 2013 U6 - https://doi.org/10.1194/jlr.M031625 SN - 0022-2275 VL - 54 IS - 2 SP - 410 EP - 424 PB - American Society for Biochemistry and Molecular Biology CY - Bethesda ER -