Voltage-gated sodium channels are crucial for pain perception. This is illustrated by several human genetic conditions that lead to either chronic pain or, vice versa, to congenital painlessness. The ...type of mutation, its impact on neuron excitability as well as the affected sodium channel subtype delineates a complex picture of the disorders. Genetic variants in sodium channels may affect the complex biophysical gating and also their trafficking, association with other proteins and more complex regulations of the channel protein and function, thus allowing us to explore the subtle but impactful effects of their dysregulation for human nociception. A detailed understanding of these pain disorders provides a unique chance to understand the detailed intricacies of nociception and pathological conditions such as neuropathic pain. With increasing awareness of the importance of sodium channel variants in neuropathic pain, more patients are genetically screened, sometimes identifying variants of unclear significance (VUS). Bioinformatic tools help to assess their potential disease causing impact, but functional studies using patch-clamp experiments in cell lines are needed to allow for reliable conclusions. Often cell lines are not sufficient to show a physiologically relevant phenotype and more complex, time intensive models, such as induced pluripotent stem cells (iPS-cells) are employed. A challenge remains to identify the role of each sodium channel VUS in the context of the detailed cellular genetic and functional context. To lay the grounds for such a detailed interpretation, we need a correlation of cellular function and genetic transcription on a single cell basis, as it is possible with the Patch-Seq technique. The more detailed our knowledge becomes on functional and genetic sensory neurons subtypes and their role in the generation of neuropathic pain, the more targeted the personal or population-based treatment can be.
Technical innovations in the last decade have allowed to sequence transcriptomes of single cells. Single-cell RNA-sequencing (scRNA-seq) has since then opened the window to a deeper understanding of ...cellular identity and is becoming a widely used method in molecular biology. In neuroscience, scRNA-seq has broad applications, for example in determining cellular diversity in different brain regions and in revealing transcriptomic variations across brain disorders. The method consists of several steps: isolation and lysis of single cells, reverse transcription of RNAs, amplification of cDNAs, and next-generation sequencing. The large datasets can subsequently be analysed using different bioinformatic tools to deduce biological meaning. Current developments aim to integrate scRNA-seq into cellular network analysis through multimodal analysis, spatial localisation and perturbation experiments, in order to understand brain physiology and pathology.
Abstract
Background
Oxygen availability and extracellular acidity both have a strong impact on growth and cultivation characteristics of eukaryotes, however they are often considered in isolation, ...whereby a single parameter is varied at a time to identify its impact, rendering the investigation of synergistic effects created by two or more factors non-achievable. This study identified the synergistic effect between environmental pH and oxygen levels on the physiological and cellular characteristics of the simplest eukaryote,
Saccharomyces cerevisiae
.
Materials and methods
The physiological, transcriptomic, and metabolic responses of yeast were investigated during batch growth in a 2 × 2 factorial design setting; environmental pH and oxygen availability were either controlled at their optimal settings, or allowed to follow their own course during cultivation.
Results
Synergistic effects had a significant impact on yeast physiology, which was provoked further by both the modulation of gene expression by transcription, and the modification of metabolite pools. Genes involved in cytoplasmic translation, the extracellular and intracellular amino acid and their precursor metabolite pools were significantly responsive to concurrent variations in these two factors.
Conclusion
The synergistic effect of extracellular acidity and oxygenation on eukaryotic landscape of growth-associated events was significantly more pronounced than their individual effects.
The subcellular organization of biomolecules such as proteins and nucleic acids is intimately linked to their biological functions. APEX2, an engineered ascorbate peroxidase that enables ...proximity‐dependent labeling of proteins in living cells, has emerged as a powerful tool for deciphering the molecular architecture of various subcellular structures. However, only phenolic compounds have thus far been employed as APEX2 substrates, and the resulting phenoxyl radicals preferentially react with electron‐rich amino acid residues. This narrow scope of substrates could potentially limit the application of APEX2. In this study, we screened a panel of aromatic compounds and identified biotin‐conjugated arylamines as novel probes with significantly higher reactivity towards nucleic acids. As a demonstration of the spatial specificity and depth of coverage in mammalian cells, we applied APEX2 labeling with biotin‐aniline (Btn‐An) in the mitochondrial matrix, capturing all 13 mitochondrial messenger RNAs and none of the cytoplasmic RNAs. APEX2‐mediated Btn‐An labeling of RNA is thus a promising method for mapping the subcellular transcriptome, which could shed light on its functions in cell physiology.
Eine Serie Biotin‐konjugierter aromatischer Sonden wurde synthetisiert und bezüglich der APEX2‐vermittelten Proximitätsmarkierung von Proteinen, DNA und RNA durchmustert. Hierbei erwies sich Biotin‐Anilin als effiziente Sonde zur Erfassung des subzellulären Transkriptoms in lebenden Zellen mit hoher räumlicher Spezifität.
Generationswechsel: Die direkte RNA‐Sequenzierung (DRS) ist eine neue Methode, die auf dem Prinzip der Einzelmolekülsequenzierung durch Synthese beruht. Diese Sequenzierungstechnik der nächsten ...Generation erfordert nur minimale RNA‐Mengen und hat das Potenzial, ohne vorherige Umschrift in cDNA Momentaufnahmen des Transkriptoms einer gegebenen Zellpopulation zu erstellen (Teilschritt siehe Bild; VT: virtuelles Terminatornucleotid).
In order to determine whether transcriptome data obtained by DNA microarray analysis could be used to identify the genes involved in target metabolite production, we tried to identify the genes ...involved in l-lactate production by l-lactate-producing recombinant Saccharomyces cerevisiae strains. We obtained DNA microarray data for these strains. Plasmids carrying lactic acid bacteria, bovine, and human l-lactate dehydrogenase (LDH) genes were introduced into PDC1-disrupted S. cerevisiae strains. l-Lactate productivity of the strains harboring the human and bovine LDH genes was higher than that of the strains harboring lactic acid bacteria LDH genes. DNA microarray analysis revealed that the expression of 388 genes was significantly altered in the strains with the human and bovine LDH genes. Of these, the l-lactate productivity of human LDH-harboring deletion strains of 289 genes was compared with that of the standard and 56 randomly selected deletion strains containing the same LDH gene to validate the effectiveness of DNA microarray analysis for identifying the genes responsible for l-lactate production in the recombinant strains. Only deletion strains of the genes selected on the basis of the DNA microarray data showed significantly altered l-lactate production as compared to the standard and the randomly selected deletion strains. Our results indicated that the genes related to l-lactate production could be successfully identified by selecting the genes that exhibited significantly altered expression on DNA microarray analysis, and the effectiveness of DNA microarray analysis for identifying the genes responsible for l-lactate production was discussed.
Only about 2% of the human genome constitute protein-coding genes - nevertheless, medical research has focused mainly on this portion in recent decades. Since up to 70% of the human genome is ...transcribed into RNA, the genome contains much more non-coding information than coding, which is present in the cell as non-coding RNA (ncRNA). Many of these ncRNAs are highly expressed, specifically regulated and evolutionarily conserved, arguing in favor of their functional significance. MicroRNAs are the most well-known ncRNAs, but many other long ncRNAs exist. Differential ncRNA or microRNA expression patterns correlate with diagnosis or prognosis in many tumor entities and can thus serve as an extensive source of new biomarkers. The expression of the long ncRNA MALAT1 correlates with tumor development, progression or survival in lung, liver and breast cancer. Functionally active ncRNAs can provide novel insights into the mechanisms underlying tumor development. The large number of different, often as yet unidentified ncRNAs promises new stimuli for the diagnosis, prognosis and therapy of many diseases.
Im gleichen Maße wie informatisches Wissen mehr und mehr in denwissenschaftlichen Alltag aller Lebenswissenschaften Einzug gehalten hat,hat sich der Schwerpunkt bioinformatischer Forschung in stärker ...mathematischund informatisch-orientierte Themengebiete verschoben. Bioinformatik heute istmehr als die computergestützte Verarbeitung großer Mengen an biologischenDaten, sondern hat einen entscheidenden Fokus auf der Modellierung komplexerbiologischer Systeme. Zur Anwendung kommen hierbei insbesondereTheorien aus dem Bereich der Stochastik und Statistik, des maschinellenLernens und der theoretischen Informatik.In der vorliegenden Dissertation beschreibe ich in Fallstudien die systematischeModellierung biologischer Systeme aus einem informatisch - mathematischenStandpunkt unter Anwendung von Verfahren aus den genanntenTeilbereichen und auf unterschiedlichen Ebenen biologischer Abstraktion.Ausgehend von der Sequenzinformation über Transkriptom, Metabolom undderen regulatorischer Interaktion hin zur Modellierung von Populationseffektenwerden hierbei aktuelle biologische Fragestellungen mit mathematisch- informatischen Modellen und einer Vielzahl experimenteller Datenkombiniert. Ein besonderer Augenmerk liegt dabei auf dem Vorgang derModellierung und des Modellbegriffs als solchem im Rahmen modernerbioinformatischer Forschung.Im Detail umfassen die Projekte (mehrere Publikationen) die Entwicklungeines neuen Ansatzes zur Einbettung und Visualisierung von MultiplenSequenz- und Sequenz-Strukturalignments, illustriert am Beispiel einesHemagglutininalignments unterschiedlicher H5N1 Varianten, sowie die Modellierungdes Transkriptoms von A. thaliana, bei welchem mit Hilfe einerkernelisierten nicht-parametrischen Metaanalyse neue, an der Infektionsabwehrbeteiligten, Gene ausfindig gemacht werden konnten. Desweiteren istuns mit Hilfe unserer Software YANAsquare eine detaillierte Untersuchungdes Metabolismus von L. monocytogenes unter Aktivierung desTranskriptionsfaktors prfA gelungen, dessen Vorhersagen durch experimentelle 13CIsotopologstudien belegt werden konnten. In einem Anschlußprojekt warder Zusammenhang zwischen Regulation des Metabolismus durch Regulationder Genexpression und der Fluxverteilung des metabolischen Steady-State-Netzwerks das Ziel. Die Modellierung eines komplexen organismischenPhänotyps, der Zellgrößenentwicklung der Diatomee Pseudo-nitzschiadelicatissima, schließt die Untersuchungen ab.
In the same way that informatical knowledge has made its way into almost allareas of research in the Life Sciences, the focus of bioinformatical researchhas shifted towards topics originating more in the fields of mathematicsand theoretical computer science. Bioinformatics today is more than thecomputer-driven processing of huge amounts of biological data, but it has aspecial focus on the emphmodelling of complex biological systems. Of specialimportance hereby are theories from stochastics and statistics, from the fieldof machine learning and theoretical computer science.In the following dissertation, I describe the systematic modelling of biological systems from an informatical-mathematical point of view in a casestudies approach, applying methods from the aforementioned areas of researchand on different levels of biological abstraction. Beginning with thesequence information itself, followed by the transcriptome, metabolome andthe interaction of both and finally population effects I show how current biologicalquestions can be tackled with mathematical models and combinedwith a variety of different experimental datasets. A special focus lieshereby on the procedure of modelling and the concept and notion of a model assuch in the framework of bioinformatical research.In more detail, the projects contained the development of a new approachfor embedding and visualizing Multiple Sequence and Structure Alignments,which was illustrated using a hemagglutinin alignment from different H5N1variants as an example. Furthermore we investigated the A. thaliana transcriptomeby means of a kernelized non-parametric meta-analysis, thus beingable to annotate several new genes as pathogen-defense related. Anothermajor part of this work was the modelling of the metabolic network of L.monocytogenes under activation of the transcription factor prfA, establishingpredictions which were later verified by experimental 13C isotopologuestudies. Following this project we investigated the relationship between theregulation of metabolism by changes in the cellular genexpression patternsand the flux distributions of the metabolic steady-state network. Modellingof a complex organismal property, the cell size development of the planktonicdiatom Pseudo-nitzschia delicatissima concludes this work.
