Dataset Information

Integrating highly quantitative proteomics and genome-scale metabolic modeling to study pH adaptation in the human pathogen Enterococcus faecalis.

ABSTRACT: Genome-scale metabolic models represent the entirety of metabolic reactions of an organism based on the annotation of the respective genome. These models commonly allow all reactions to proceed concurrently, disregarding the fact that at no point all proteins will be present in a cell. The metabolic reaction space can be constrained to a more physiological state using experimentally obtained information on enzyme abundances. However, high-quality, genome-wide protein measurements have been challenging and typically transcript abundances have been used as a surrogate for protein measurements. With recent developments in mass spectrometry-based proteomics, exemplified by SWATH-MS, the acquisition of highly quantitative proteome-wide data at reasonable throughput has come within reach. Here we present methodology to integrate such proteome-wide data into genome-scale models. We applied this methodology to study cellular changes in Enterococcus faecalis during adaptation to low pH. Our results indicate reduced proton production in the central metabolism and decreased membrane permeability for protons due to different membrane composition. We conclude that proteomic data constrain genome-scale models to a physiological state and, in return, genome-scale models are useful tools to contextualize proteomic data.

SUBMITTER: Großeholz R

PROVIDER: S-EPMC5516852 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Integrating highly quantitative proteomics and genome-scale metabolic modeling to study pH adaptation in the human pathogen <i>Enterococcus faecalis</i>.

Großeholz Ruth R Koh Ching-Chiek CC Veith Nadine N Fiedler Tomas T Strauss Madlen M Olivier Brett B Collins Ben C BC Schubert Olga T OT Bergmann Frank F Kreikemeyer Bernd B Aebersold Ruedi R Kummer Ursula U

NPJ systems biology and applications 20160908

Genome-scale metabolic models represent the entirety of metabolic reactions of an organism based on the annotation of the respective genome. These models commonly allow all reactions to proceed concurrently, disregarding the fact that at no point all proteins will be present in a cell. The metabolic reaction space can be constrained to a more physiological state using experimentally obtained information on enzyme abundances. However, high-quality, genome-wide protein measurements have been chall ...[more]

PMID: 28725473

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Project description:Enterococcus faecalis is a bacterial pathogen associated with both endodontic and systemic infections. The biofilm formation ability of E. faecalis plays a key role in its virulence and drug resistance attributes. The formation of E. faecalis biofilms on implanted medical devices often results in treatment failure. In the present study, we report protein markers associated with the biofilm formation ability of E. faecalis using iTRAQ-based quantitative proteomics approach. In order to elucidate the biofilm-associated protein markers, we investigated the proteome of strong and weak biofilm-forming E. faecalis clinical isolates in comparison with standard American Type Culture Collection (ATCC) control strains. Comparison of E. faecalis strong and weak biofilm-forming clinical isolates with ATCC control strains showed that proteins associated with shikimate kinase pathway and sulfate transport were up-regulated in the strong biofilm former, while proteins associated with secondary metabolites, cofactor biosynthesis, and tetrahydrofolate biosynthesis were down-regulated. In the weak biofilm former, proteins associated with nucleoside and nucleotide biosynthesis were up-regulated, whereas proteins associated with sulfate and sugar transport were down-regulated. Further pathway and gene ontology analyses revealed that the major differences in biofilm formation arise from differences in metabolic activity levels of the strong and weak biofilm formers, with higher levels of metabolic activity observed in the weak biofilm former. The differences in metabolic activity could therefore be a major determinant of the biofilm ability of E. faecalis The new markers identified from this study can be further characterized in order to understand their exact role in E. faecalis biofilm formation ability. This, in turn, can lead to numerous therapeutic benefits in the treatment of this oral and systemic pathogen. The data has been deposited to the ProteomeXchange with identifier PXD006542.

Dataset Information

Integrating highly quantitative proteomics and genome-scale metabolic modeling to study pH adaptation in the human pathogen Enterococcus faecalis.

Publications

Integrating highly quantitative proteomics and genome-scale metabolic modeling to study pH adaptation in the human pathogen <i>Enterococcus faecalis</i>.

Similar Datasets

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