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Bitte verwenden Sie diesen Link, wenn Sie dieses Dokument zitieren oder verlinken wollen: https://nbn-resolving.org/urn:nbn:de:gbv:9-001812-5

Multi-omics based characterization of various stress responses in Bacillus subtilis

  • The soil bacterium Bacillus subtilis is capable of surviving most of the ensuing environmental stress conditions. The dynamic nature of the soil habitat is manifested with varying amounts of nutrients, frequent flooding, drying and variation of other growth parameters like temperature, acidity, aeration etc. In order to survive in these conditions, B. subtilis has evolved to employ very complex adaptational responses. These adaptational responses are often multi-faceted; hence comprehensive understanding of the adaptational responses requires generation and integration of data on multi-omics level. Hence, multi-omics based detailed analysis was performed for the molecules involved in the central carbon metabolism (CCM) and proline biosynthesis pathway. In the current study two major stress conditions were extensively investigated: 1) energy limitation/starvation which is achieved by limiting glucose in the growth medium, 2) osmostress resulting from frequent drying out of soil which is simulated by adding 1.2 M NaCl to the growth medium. In addition to osmostress, the naturally available osmoprotectant glycine betaine (GB) was supplemented to understand the simultaneous influence of osmostress and osmoprotection on cellular physiology. To measure absolute protein abundances by mass spectrometry, a targeted approach (SRM –single reaction monitoring) using stable heavy isotope labeled artificial standard proteins known as QconCATs was optimized and implemented in the current study. The SRM technique in combination with QconCAT provided absolute quantitative data with high dynamic range for the 45 targeted CCM proteins. Transcriptome data was obtained from microarray analysis. The resulting data were integrated with the other omics data sets obtained by metabolome and flux analysis. As part of a joint study conducted by the BaCell-SysMO and BaSysBio consortia which aimed for the genome wide mapping of transcription units and previously unannotated RNAs of B. subtilis by means of tiling array hybridizations, mRNA samples from growth at high and low temperatures (51°C and 16°C) and in the presence of 1.2 M NaCl, shake flask experiments during transition from exponential growth to the stationary phase, and high density batch fermentation. Time course analysis of B. subtilis transitioning from exponential to stationary phase was investigated by high cell density fed-batch fermentation (glucose limitation) and batch fermentation (glucose exhaustion) with glucose as a limiting factor. A multi-omics analysis of the CCM for the batch fermentation was performed and the time course data was integrated and visualized. In conclusion, pathway based multi-omics data were generated, integrated and visualized as a prerequisite for systems biology approaches and for a better understanding of the complex adaptational responses of B. subtilis.
  • Der Gram-positive Bodenorganismus Bacillus subtilis muss in seinem natürlichen Habitat, dem Boden, eine Vielzahl von Stressbedingungen überleben. Um diese Anpassungen zu verstehen wurde in dieser Arbeit eine multi-omics Analyse mit Fokus auf den zentralen Kohlenstoff Metabolismus durchgeführt. Hierbei wurde insbesondere die Anpassung an hohe Osmolaritäten unter natürlichen, Glukose limitierten, und Laborbedingungen, mit ausreichend vorhandener Glukose, betrachtet. Weiterhin wurde die Auswirkung des kompatiblen Solutes Glycin-Betain betrachtet. Neben der Transkiptomanalyse mitteln Microarrays und der absolute Quantifizierung der Proteine mittels LC-ESI-MS/MS, wurden stöchiometrische Daten der Proteinmengen der Proteine des zentralen Kohlenstoff Metabolismus und der Enzyme der Prolin Biosynthese erhoben. Hierzu wurden vier QconCAT Proteine (Quantification Concatemer) mit Peptiden der Zielproteine entworfen und als interne Standardproteine in einer SRM (Single Reaction Monitoring) Analyse eingesetzt. Zusammenfassend wurden die Datensätze aus Transkriptom, Proteom and Metabolom integriert und mit den ebenfalls erhobenen und Flux-Analysen verglichen.

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Author: Praveen Kumar Sappa
Advisor:Prof. Dr. Uwe Völker
Document Type:Doctoral Thesis
Date of Publication (online):2014/04/30
Granting Institution:Ernst-Moritz-Arndt-Universität, Mathematisch-Naturwissenschaftliche Fakultät (bis 31.05.2018)
Date of final exam:2014/04/24
Release Date:2014/04/30
Tag:Bacillus subtilis, Central carbon metabolism, Multi-omics, Osmostress, SRM (single reaction monitoring), adaptational responses
GND Keyword:Anpassungsreaktionen, Bacillus subtilis, Multi-omics, Osmostress, SRM (single reaction monitoring), Zentralkohlenstoffmetabolismus
Faculties:Universitätsmedizin / Arbeitsgruppe "Funktionelle Genomforschung"
DDC class:500 Naturwissenschaften und Mathematik / 570 Biowissenschaften; Biologie
MSC-Classification:92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92Cxx Physiological, cellular and medical topics / 92C40 Biochemistry, molecular biology
92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92Cxx Physiological, cellular and medical topics / 92C42 Systems biology, networks
92-XX BIOLOGY AND OTHER NATURAL SCIENCES / 92Dxx Genetics and population dynamics / 92D20 Protein sequences, DNA sequences