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Approaches to the Analysis of Proteomics and Transcriptomics Data based on Statistical Methodology
(2014)
Recent developments in genomics and molecular biology led to the generation of an enormous amount of complex data of different origin. This is demonstrated by a number of published results from microarray experiments in Gene Expression Omnibus. The number was growing in exponential pace over the last decade. The challenge of interpreting these vast amounts of data from different technologies led to the development of new methods in the fields of computational biology and bioinformatics. Researchers often want to represent biological phenomena in the most detailed and comprehensive way. However, due to the technological limitations and other factors like limited resources this is not always possible. On one hand, more detailed and comprehensive research generates data of high complexity that is very often difficult to approach analytically, however, giving bioinformatics a chance to draw more precise and deeper conclusions. On the other hand, for low-complexity tasks the data distribution is known and we can fit a mathematical model. Then, to infer from this mathematical model, researchers can use well-known and standard methodologies. In return for using standard methodologies, the biological questions we are answering might not be unveiling the whole complexity of the biological meaning. Nowadays it is a standard that a biological study involves generation of large amounts of data that needs to be analyzed with a statistical inference. Sometimes data challenge researchers with low complexity task that can be performed with standard and popular methodologies as in Proteomic analysis of mouse oocytes reveals 28 candidate factors of the "reprogrammome". There, we established a protocol for proteomics data that involves preprocessing of the raw data and conducting Gene Ontology overrepresentation analysis utilizing hypergeometric distribution. In cases, where the data complexity is high and there are no published frameworks a researcher could follow, randomization can be an approach to exploit. In two studies by The mouse oocyte proteome escapes maternal aging and CellFateScout - a bioinformatics tool for elucidating small molecule signaling pathways that drive cells in a specific direction we showed how randomization can be performed for distinct complex tasks. In The mouse oocyte proteome escapes maternal aging we constructed a random sample of semantic similarity score between oocyte transcriptome and random transcriptome subset of oocyte proteome size. Therefore, we could calculate whether the proteome is representative of the trancriptome. Further, we established a novel framework for Gene Ontology overrepresentation that involves randomization testing. Every Gene Ontology term is tested whether randomly reassigning all gene labels of belonging to or not belonging to this term will decrease the overall expression level in this term. In CellFateScout - a bioinformatics tool for elucidating small molecule signaling pathways that drive cells in a specific direction we validated CellFateScout against other well-known bioinformatics tools. We stated the question whether our plugin is able to predict small molecule effects better in terms of expression signatures. For this, we constructed a protocol that uses randomization testing. We assess here if the small molecule effect described as a (set of) active signaling pathways, as detected by our plugin or other bioinformatics tools, is significantly closer to known small molecule targets than a random path.
Allicin (diallyl thiosulfinate) is the major thiol-reactive organosulfur compound produced by garlic plants (Allium sativum) upon tissue damage. Allicin exerts its strong antimicrobial activity against bacteria and fungi via S-thioallylation of protein thiols and low molecular weight thiols. Here, we investigated the effect of allicin on SARS-CoV-2 infected Vero E6 and Calu-3 cells. Toxicity tests revealed that Calu-3 cells showed greater allicin tolerance, probably due to >4-fold higher GSH levels compared to the very sensitive Vero E6 cells. Exposure of infected Vero E6 and Calu-3 cells to biocompatible allicin doses led to a ∼60–70% decrease of viral RNA and infectious viral particles. Label-free quantitative proteomics was used to investigate the changes in the Calu-3 proteome after SARS-CoV-2 infection and the effect of allicin on the host-virus proteome. SARS-CoV-2 infection of Calu-3 cells caused a strong induction of the antiviral interferon-stimulated gene (ISG) signature, including several antiviral effectors, such as cGAS, Mx1, IFIT, IFIH, IFI16, IFI44, OAS, and ISG15, pathways of vesicular transport, tight junctions (KIF5A/B/C, OSBPL2, CLTCL1, and ARHGAP17) and ubiquitin modification (UBE2L3/5), as well as reprogramming of host metabolism, transcription and translation. Allicin treatment of infected Calu-3 cells reduced the expression of IFN signaling pathways and ISG effectors and reverted several host pathways to levels of uninfected cells. Allicin further reduced the abundance of the structural viral proteins N, M, S and ORF3 in the host-virus proteome. In conclusion, our data demonstrate the antiviral and immunomodulatory activity of biocompatible doses of allicin in SARS-CoV-2-infected cell cultures. Future drug research should be directed to exploit the thiol-reactivity of allicin derivatives with increased stability and lower human cell toxicity as antiviral lead compounds.
The Gram-positive bacterium Bacillus licheniformis is an important industrial host for the production of enzymes. Genomic DNA arrays and proteomics are being used to investigate the physiology of this bacterium. A genome-wide transcriptional profiling analysis of the adaptation of B. licheniformis to phosphate starvation shows more than 100 induced genes. Most of strongly induced genes belong to the putative Pho regulon. The data of the transcriptome analysis have been verified by the analysis of the extracellular and cytoplasmic proteome. The main response of B. licheniformis to glucose starvation was a switch to the usage of alternative carbon sources. In addition, B. licheniformis seems to be using other organic substances like amino acids and lipids as carbon sources when subjected to glucose starvation. This was indicated by the induction of a high number of genes the proteins of which are involved in amino acid and lipid degradation. During nitrogen starvation genes necessary for the recruitment of nitrogen from alternative sources were induced, e.g. genes for nitrate and nitrite assimilation, several proteases and peptidases. Both starvation conditions led to a down-regulation of the transcription of most vegetative genes and subsequently to a reduced synthesis of the corresponding proteins. Only a few genes were induced by both starvation conditions like yvyD, citA and the methylcitrate shunt genes mmgD, mmgE and yqiQ. Data of this study use to better understand the physiology of this bacterium during fermentation processes and thus to identify and circumvent bottlenecks of B. licheniformis based bioprocesses. In addition, the phytase promoter was tested for the construction of an alternative phosphate regulated expression system for B. licheniformis.
Die chronische arterielle Hypertonie erhöht das Risiko für kardiovaskuläre Komplikationen wie Schlaganfall und Myokardinfarkt. In der Pathophysiologie dieser Komplikationen spielen Thrombozyten eine wesentliche Rolle. Hierbei gehen die meisten Experten derzeit davon aus, dass Thrombozyten mit den durch die Hypertonie geschädigten Gefäßwänden reagieren. Ziel unserer Untersuchungen war es, zu untersuchen, ob durch die Hypertonie auch Veränderungen in Thrombozyten entstehen. Thrombozyten zirkulieren im Kreislauf in engem Kontakt mit der Gefäßwand und reagieren sensibel auf hohe Scherkräfte und aktivierte Endothelzellen. Jede Aktivierung, auch in reversiblen Frühstadien führt dabei zu Veränderungen in der Proteinzusammensetzung der Thrombozyten, dem Proteom. Da sie keinen Kern haben, ist die Proteinneosynthese in Thrombozyten stark limitiert. So „speichern“ Thrombozyten Informationen über ihre Aktivierungshistorie während ihrer zehntägigen Überlebenszeit, da die veränderten Proteine nicht, oder nur sehr eingeschränkt durch neu synthetisierte Proteine ersetzt werden. Proteomics bietet einen Ansatz, über tausend Proteine gleichzeitig zu untersuchen. Mittels zweidimensionaler, differentieller in Gel Elektrophorese (2D-DIGE) kann dabei ein sensibler quantitativer Vergleich zweier Proben erfolgen. Die komplexe Methodik erfordert jedoch eine hochgradige Standardisierung der Versuchsgruppen. In diesem Projekt wurde daher ein Tiermodell verwendet, um die ca. 1000, mittels 2D-PAGE dargestellten Proteinspots des Thrombozytenzytosols auf hypertoniebedingte Veränderungen zu untersuchen. Dabei wurden zwei unterschiedliche Rattenmodelle der Hypertonie eingesetzt um die Aussagekraft zu erhöhen. Nach 14tägiger Hypertoniephase wurden 45 Proteinspots detektiert, deren Intensität in beiden Rattenmodellen signifikant verändert war. Die Identifikation dieser Spots mittels Massenspektrometrie zeigte neben spezifischen Thrombozytenproteinen v.a. Zytoskelett- und Zytoskelett -assoziierte Proteine. Wurde an die 14tägige Hypertoniephase eine 10tägige Erholungsphase angeschlossen, waren diese Veränderungen nicht mehr nachweisbar. Überraschenderweise waren die beobachteten Veränderungen unterdrückbar durch mehrmalige Blutentnahme vor- und während der Hypertoniephase. Dabei wurden 8 Tage vor-, sowie zweimal während der Hypertoniephase (Tage 3 und 10) 3 ml Blut entnommen. Die daraufhin durchgeführte Untersuchung auf Veränderungen des Thrombozytenproteoms durch Blutentnahmen an normotensiven Tieren zeigte ein Muster an Veränderungen, dass dem unter Hypertonie beobachteten entgegengesetzt war. Eine denkbare Ursache für diese Beobachtung ist, dass die Thrombozytopoese durch die mehrmaligen Blutverluste gesteigert wurde. Die so vermehrt ausgeschütteten „jungen“ Thrombozyten zeigen ein inverses Proteommuster, gegenüber den durch Hypertonie gestressten Thrombozyten. Um dieser Hypothese nachzugehen wurden Ratten mit dem Thrombopoetinrezeptoragonisten Romiplostim behandelt. Das Thrombozytenproteom von Ratten nach Stimulation der Thrombozytopoese ähnelt dem von Ratten nach mehrmaligen Blutentnahmen. Dies unterstützt unsere Hypothese, dass die durch Blutentnahmen bedingten Proteomveränderungen auf eine gesteigerte Thormobzytopoese zurückzuführen sind und damit auf das gesteigerte Vorkommen junger Thrombozyten im Blutkreislauf. Veränderungen des Thrombozytenproteoms, die in beiden Tiermodellen unter Hypertonie auftraten, können mit großer Sicherheit auf die Hypertonie zurückgeführt werden. Zu beachten ist allerdings, dass beide Modelle auf einer Aktivierung des Renin-Angiotensin-Aldosteron Systems (RAAS) basieren. Es kann also nicht differenziert werden, ob die Veränderungen durch die Hypertonie selbst oder durch das aktivierte RAAS verursacht wurden. Die Tiermodelle spiegeln somit nur eine Subgruppe der Hypertoniepatienten wider. Wir haben mit diesen Experimenten Thrombozyten-Proteine identifiziert, die sich durch einen erhöhten Blutdruck verändern. Diese Proteine sind daher potentielle Kandidaten für Biomarker, die eine Aussage über den Blutdruckverlauf der zurückliegenden Tage ermöglichen. Solch ein Marker, ähnlich dem HbA1c beim Diabetes mellitus, könnte die Hypertoniediagnostik erheblich erleichtern. Für die in dieser tierexperimentellen Studie identifizierten Proteine finden sich analoge Proteine in menschlichen Thrombozyten. Deren Veränderung durch Bluthochdruck sollte in Fall/Kontroll-Studien am Menschen untersucht werden. In Ergänzung zum im Journal of Hypertension veröffentlichten Artikel wird in der vorliegenden deutschen Zusammenfassung detaillierter auf die Methoden eingegangen. Darüber hinaus werden zusätzliche Aspekte in der Diskussion angesprochen.
Acidobacteria represents one of the most dominant bacterial groups across diverse ecosystems. However, insight into their ecology and physiology has been hampered by difficulties in cultivating members of this phylum. Previous cultivation efforts have suggested an important role of trace elements for the proliferation of Acidobacteria, however, the impact of these metals on their growth and metabolism is not known. In order to gain insight into this relationship, we evaluated the effect of trace element solution SL10 on the growth of two strains (5B5 and WH15) of Acidobacteria belonging to the genus Granulicella and studied the proteomic responses to manganese (Mn). Granulicella species had highest growth with the addition of Mn, as well as higher tolerance to this metal compared to seven other metal salts. Variations in tolerance to metal salt concentrations suggests that Granulicella sp. strains possess different mechanisms to deal with metal ion homeostasis and stress. Furthermore, Granulicella sp. 5B5 might be more adapted to survive in an environment with higher concentration of several metal ions when compared to Granulicella sp. WH15. The proteomic profiles of both strains indicated that Mn was more important in enhancing enzymatic activity than to protein expression regulation. In the genomic analyses, we did not find the most common transcriptional regulation of Mn homeostasis, but we found candidate transporters that could be potentially involved in Mn homeostasis for Granulicella species. The presence of such transporters might be involved in tolerance to higher Mn concentrations, improving the adaptability of bacteria to metal enriched environments, such as the decaying wood-rich Mn environment from which these two Granulicella strains were isolated.
Fibroblasts contribute to approximately 20% of the non-cardiomyocytic cells in the heart. They play important roles in the myocardial adaption to stretch, inflammation, and other pathophysiological conditions. Fibroblasts are a major source of extracellular matrix (ECM) proteins whose production is regulated by cytokines, such as TNF-α or TGF-β. The resulting myocardial fibrosis is a hallmark of pathological remodeling in dilated cardiomyopathy (DCM). Therefore, in the present study, the secretome and corresponding transcriptome of human cardiac fibroblasts from patients with DCM was investigated under normal conditions and after TNF-α or TGF-β stimulation. Secreted proteins were quantified via mass spectrometry and expression of genes coding for secreted proteins was analyzed via Affymetrix Transcriptome Profiling. Thus, we provide comprehensive proteome and transcriptome data on the human cardiac fibroblast’s secretome. In the secretome of quiescent fibroblasts, 58% of the protein amount belonged to the ECM fraction. Interestingly, cytokines were responsible for 5% of the total protein amount in the secretome and up to 10% in the corresponding transcriptome. Furthermore, cytokine gene expression and secretion were upregulated upon TNF-α stimulation, while collagen secretion levels were elevated after TGF-β treatment. These results suggest that myocardial fibroblasts contribute to pro-fibrotic and to inflammatory processes in response to extracellular stimuli.