Dataset Information

Integration of Biomass Formulations of Genome-Scale Metabolic Models with Experimental Data Reveals Universally Essential Cofactors in Prokaryotes.

ABSTRACT: The composition of a cell in terms of macromolecular building blocks and other organic molecules underlies the metabolic needs and capabilities of a species. Although some core biomass components such as nucleic acids and proteins are evident for most species, the essentiality of the pool of other organic molecules, especially cofactors and prosthetic groups, is yet unclear. Here we integrate biomass compositions from 71 manually curated genome-scale models, 33 large-scale gene essentiality datasets, enzyme-cofactor association data and a vast array of publications, revealing universally essential cofactors for prokaryotic metabolism and also others that are specific for phylogenetic branches or metabolic modes. Our results revise predictions of essential genes in Klebsiella pneumoniae and identify missing biosynthetic pathways in models of Mycobacterium tuberculosis. This work provides fundamental insights into the essentiality of organic cofactors and has implications for minimal cell studies as well as for modeling genotype-phenotype relations in prokaryotic metabolic networks.

SUBMITTER: Xavier JC

PROVIDER: S-EPMC5249239 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Integration of Biomass Formulations of Genome-Scale Metabolic Models with Experimental Data Reveals Universally Essential Cofactors in Prokaryotes.

Xavier Joana C JC Patil Kiran Raosaheb KR Rocha Isabel I

Metabolic engineering 20161208

The composition of a cell in terms of macromolecular building blocks and other organic molecules underlies the metabolic needs and capabilities of a species. Although some core biomass components such as nucleic acids and proteins are evident for most species, the essentiality of the pool of other organic molecules, especially cofactors and prosthetic groups, is yet unclear. Here we integrate biomass compositions from 71 manually curated genome-scale models, 33 large-scale gene essentiality data ...[more]

PMID: 27939572

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Project description:In Candida albicans, the transcription factor Upc2 is central to the regulation of ergosterol biosynthesis. UPC2-activating mutations contribute to azole resistance, whereas disruption increases azole susceptibility. In the present study, we investigated the relationship of UPC2 to fluconazole susceptibility, particularly in azole-resistant strains. In addition to the reduced fluconazole MIC previously observed with UPC2 disruption, we observed a lower minimum fungicidal concentration (MFC) for a upc2M-NM-^T/M-NM-^T mutant than for its azole-susceptible parent, SC5314. Moreover, the upc2M-NM-^T/M-NM-^T mutant was unable to grow on a solid medium containing 10 M-BM-5g/ml fluconazole and exhibited increased susceptibility and a clear zone of inhibition by Etest. Time-kill analysis showed higher fungistatic activity against the upc2M-NM-^T/M-NM-^T mutant than against SC5314. UPC2 disruption in strains carrying specific resistance mutations also resulted in reduced MICs and MFCs. UPC2 disruption in a highly azole resistant clinical isolate containing multiple resistance mechanisms likewise resulted in a reduced MIC and MFC. This mutant was unable to grow on a solid medium containing 10 M-BM-5g/ml fluconazole and exhibited increased susceptibility and a clear zone of inhibition by Etest. Time-kill analysis showed increased fungistatic activity against the upc2M-NM-^T/M-NM-^T mutant in the resistant background. Microarray analysis showed attenuated induction by fluconazole of genes involved in sterol biosynthesis, iron transport, or iron homeostasis in the absence of UPC2. Taken together, these data demonstrate that the UPC2 transcriptional network is universally essential for azole resistance in C. albicans and represents an attractive target for enhancing azole antifungal activity. We examined the genome-wide gene expression profiles of the wild-type parent strain SC5314 and its upc2M-NM-^T/M-NM-^T derivative in response to fluconazole in order to identify genes whose expression in response to fluconazole is influenced by Upc2.

Dataset Information

Integration of Biomass Formulations of Genome-Scale Metabolic Models with Experimental Data Reveals Universally Essential Cofactors in Prokaryotes.

Publications

Integration of Biomass Formulations of Genome-Scale Metabolic Models with Experimental Data Reveals Universally Essential Cofactors in Prokaryotes.

Similar Datasets

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