Dataset Information

Genome-level transcription data of Yersinia pestis analyzed with a new metabolic constraint-based approach.

ABSTRACT:

Background

Constraint-based computational approaches, such as flux balance analysis (FBA), have proven successful in modeling genome-level metabolic behavior for conditions where a set of simple cellular objectives can be clearly articulated. Recently, the necessity to expand the current range of constraint-based methods to incorporate high-throughput experimental data has been acknowledged by the proposal of several methods. However, these methods have rarely been used to address cellular metabolic responses to some relevant perturbations such as antimicrobial or temperature-induced stress. Here, we present a new method for combining gene-expression data with FBA (GX-FBA) that allows modeling of genome-level metabolic response to a broad range of environmental perturbations within a constraint-based framework. The method uses mRNA expression data to guide hierarchical regulation of cellular metabolism subject to the interconnectivity of the metabolic network.

Results

We applied GX-FBA to a genome-scale model of metabolism in the gram negative bacterium Yersinia pestis and analyzed its metabolic response to (i) variations in temperature known to induce virulence, and (ii) antibiotic stress. Without imposition of any a priori behavioral constraints, our results show strong agreement with reported phenotypes. Our analyses also lead to novel insights into how Y. pestis uses metabolic adjustments to counter different forms of stress.

Conclusions

Comparisons of GX-FBA predicted metabolic states with fluxomic measurements and different reported post-stress phenotypes suggest that mass conservation constraints and network connectivity can be an effective representative of metabolic flux regulation in constraint-based models. We believe that our approach will be of aid in the in silico evaluation of cellular goals under different conditions and can be used for a variety of analyses such as identification of potential drug targets and their action.

SUBMITTER: Navid A

PROVIDER: S-EPMC3572438 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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Publications

Genome-level transcription data of Yersinia pestis analyzed with a new metabolic constraint-based approach.

Navid Ali A Almaas Eivind E

BMC systems biology 20121206

<h4>Background</h4>Constraint-based computational approaches, such as flux balance analysis (FBA), have proven successful in modeling genome-level metabolic behavior for conditions where a set of simple cellular objectives can be clearly articulated. Recently, the necessity to expand the current range of constraint-based methods to incorporate high-throughput experimental data has been acknowledged by the proposal of several methods. However, these methods have rarely been used to address cellul ...[more]

PMID: 23216785

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Project description:Earlier, we reported the identification of new virulence factors/mechanisms of Yersinia pestis using an in vivo signature-tagged mutagenesis (STM) screening approach. From this screen, the role of rbsA, which encodes an ATP-binding protein of ribose transport system, and vasK, an essential component of the type VI secretion system (T6SS), were evaluated in mouse models of plague and confirmed to be important during Y. pestis infection. However, many of the identified genes from the screen remained uncharacterized. In this study, in-frame deletion mutants of ypo0815, ypo2884, ypo3614-3168 (cyoABCDE), and ypo1119-1120, identified from the STM screen, were generated. While ypo0815 codes for a general secretion pathway protein E (GspE) of the T2SS, the ypo2884-encoded protein has homology to the βγ crystallin superfamily, cyoABCDE codes for the cytochrome o oxidase operon, and the ypo1119-1120 genes are within the Tol-Pal system which has multiple functions. Additionally, as our STM screen identified three T6SS-associated genes, and, based on in silico analysis, six T6SS clusters and multiple homologs of the T6SS effector hemolysin-coregulated protein (Hcp) exist in Y. pestis CO92, we also targeted these T6SS clusters and effectors for generating deletion mutants. These deletion mutant strains exhibited varying levels of attenuation (up to 100%), in bubonic or pneumonic murine infection models. The attenuation could be further augmented by generation of combinatorial deletion mutants, namely ΔlppΔypo0815, ΔlppΔypo2884, ΔlppΔcyoABCDE, ΔvasKΔhcp6, and Δypo2720-2733Δhcp3. We earlier showed that deletion of the lpp gene, which encodes Braun lipoprotein (Lpp) and activates Toll-like receptor-2, reduced virulence of Y. pestis CO92 in murine models of bubonic and pneumonic plague. The surviving mice infected with ΔlppΔcyoABCDE, ΔvasKΔhcp6, and Δypo2720-2733Δhcp3 mutant strains were 55-100% protected upon subsequent re-challenge with wild-type CO92 in a pneumonic model. Further, evaluation of the attenuated T6SS mutant strains in vitro revealed significant alterations in phagocytosis, intracellular survival in murine macrophages, and their ability to induce cytotoxic effects on macrophages. The results reported here provide further evidence of the utility of the STM screening approach for the identification of novel virulence factors and to possibly target such genes for the development of novel live-attenuated vaccine candidates for plague.

Dataset Information

Genome-level transcription data of Yersinia pestis analyzed with a new metabolic constraint-based approach.

Background

Results

Conclusions

Publications

Genome-level transcription data of Yersinia pestis analyzed with a new metabolic constraint-based approach.

Similar Datasets

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