Genome-scale metabolic models of Microbacterium species isolated from a high altitude desert environment
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The Atacama Desert is the most arid desert on Earth, focus of important research activities related to microbial biodiversity studies. In this context, metabolic characterization of arid soil bacteria is crucial to understand their survival strategies under extreme environmental stress. We investigated whether strain-specific features of two Microbacterium species were involved in the metabolic ability to tolerate/adapt to local variations within an extreme desert environment. Using an integrative systems biology approach we have carried out construction and comparison of genome-scale metabolic models (GEMs) of two Microbacterium sp., CGR1 and CGR2, previously isolated from physicochemically contrasting soil sites in the Atacama Desert. Despite CGR1 and CGR2 belong to different phylogenetic clades, metabolic pathways and attributes are highly conserved in both strains. However, comparison of the GEMs showed significant differences in the connectivity of specific metabolites related to pH tolerance and CO2 production. The latter is most likely required to handle acidic stress through decarboxylation reactions. We observed greater GEM connectivity within Microbacterium sp. CGR1 compared to CGR2, which is correlated with the capacity of CGR1 to tolerate a wider pH tolerance range. Both metabolic models predict the synthesis of pigment metabolites (beta -carotene), observation validated by HPLC experiments. Our study provides a valuable resource to further investigate global metabolic adaptations of bacterial species to grow in soils with different abiotic factors within an extreme environment.
FONDAP 15090007 Center for Genome Regulation (CGR) Apoyo a la Formacion de Redes Internacionales para Investigadores REDI170193 Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 1190742 1151384 1160802 3170523 Conicyt-PIA Program of the Center for Mathematical Modeling (CMM) UMI2807 UCHILE-CNRS AFB 170001 National Laboratory of High Performance Computing (NLHPC) at the CMM PIA ECM-02.-CONICYT
Artículo de publicación ISI
Quote ItemScientific Reports (2020) 10:5560
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