title: Towards a comprehensive understanding of Bacillus subtilis cell physiology by physiological proteomics.
abstract: Using Bacillus subtilis as a model system for functional genomics, this review will provide insights how proteomics can be used to bring the virtual life of genes to the real life of proteins. Physiological proteomics will generate a new and broad understanding of cellular physiology because the majority of proteins synthesized in the cell can be visualized. From a physiological point of view two major proteome fractions can be distinguished: proteomes of growing cells and proteomes of nongrowing cells. In the main analytical window almost 50% of the vegetative proteome expressed in growing cells of B. subtilis were identified. This proteomic view of growing cells can be employed for analyzing the regulation of entire metabolic pathways and thus opens the chance for a comprehensive understanding of metabolism and growth processes of bacteria. Proteomics, on the other hand, is also a useful tool for analyzing the adaptational network of nongrowing cells that consists of several partially overlapping regulation groups induced by stress/starvation stimuli. Furthermore, proteomic signatures for environmental stimuli can not only be applied to predict the physiological state of cells, but also offer various industrial applications from fermentation monitoring up to the analysis of the mode of action of drugs. Even if DNA array technologies currently provide a better overview of the gene expression profile than proteome approaches, the latter address biological problems in which they can not be replaced by mRNA profiling procedures. This proteomics of the second generation is a powerful tool for analyzing global control of protein stability, the protein interaction network, protein secretion or post-translational modifications of proteins on the way towards the elucidation of the mystery of life.
authors.affiliation: Institute for Microbiology, Erst-Moritz-Arndt-University, Greifswald, Germany. hecker@uni-greifswald.de
authors.forename: Michael
authors.initials: M
authors.lastname: Hecker
authors.forename: Uwe
authors.initials: U
authors.lastname: Völker
mesh_terms: D001412:Bacillus subtilis / Q000378:metabolism*; D001426:Bacterial Proteins / Q000737:chemistry; D015180:Electrophoresis, Gel, Two-Dimensional; D020869:Gene Expression Profiling; D015964:Gene Expression Regulation, Bacterial; D016680:Genome, Bacterial; D005947:Glucose / Q000737:chemistry / Q000378:metabolism; D007700:Kinetics; D008954:Models, Biological; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D018384:Oxidative Stress; D040081:Protein Array Analysis; D011499:Protein Processing, Post-Translational; D020543:Proteome; D040901:Proteomics / Q000379:methods*; D012323:RNA Processing, Post-Transcriptional; D012333:RNA, Messenger / Q000378:metabolism; D013997:Time Factors
chemical_list: D001426:Bacterial Proteins; D020543:Proteome; D012333:RNA, Messenger; D005947:Glucose