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A landscape of cellular aggregation of Rhizobium etli CFN42 by a transcriptomic approach

ABSTRACT: Dna microarray technology was used to survey changes in gene expression in R. etli CFN42 in biofilm formation In these organisms, two main phases, biofilm and planktonic, have been identified. In this work, using microarray assays, we evaluated global gene expression in biofilm and planktonic growth phases in rich medium, in the bacterium Rhizobium etli CFN42.

ORGANISM(S): Rhizobium etli CFN 42

PROVIDER: GSE67656 | GEO | 2016/04/15

SECONDARY ACCESSION(S): PRJNA280576

REPOSITORIES: GEO

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Project description:Resendis-Antonio2007 - Genome-scale metabolic network of Rhizobium etli (iOR363) This model is described in the article: Metabolic reconstruction and modeling of nitrogen fixation in Rhizobium etli. Resendis-Antonio O, Reed JL, Encarnación S, Collado-Vides J, Palsson BØ. PLoS Comput. Biol. 2007 Oct; 3(10): 1887-1895 Abstract: Rhizobiaceas are bacteria that fix nitrogen during symbiosis with plants. This symbiotic relationship is crucial for the nitrogen cycle, and understanding symbiotic mechanisms is a scientific challenge with direct applications in agronomy and plant development. Rhizobium etli is a bacteria which provides legumes with ammonia (among other chemical compounds), thereby stimulating plant growth. A genome-scale approach, integrating the biochemical information available for R. etli, constitutes an important step toward understanding the symbiotic relationship and its possible improvement. In this work we present a genome-scale metabolic reconstruction (iOR363) for R. etli CFN42, which includes 387 metabolic and transport reactions across 26 metabolic pathways. This model was used to analyze the physiological capabilities of R. etli during stages of nitrogen fixation. To study the physiological capacities in silico, an objective function was formulated to simulate symbiotic nitrogen fixation. Flux balance analysis (FBA) was performed, and the predicted active metabolic pathways agreed qualitatively with experimental observations. In addition, predictions for the effects of gene deletions during nitrogen fixation in Rhizobia in silico also agreed with reported experimental data. Overall, we present some evidence supporting that FBA of the reconstructed metabolic network for R. etli provides results that are in agreement with physiological observations. Thus, as for other organisms, the reconstructed genome-scale metabolic network provides an important framework which allows us to compare model predictions with experimental measurements and eventually generate hypotheses on ways to improve nitrogen fixation. This model is hosted on BioModels Database and identified by: MODEL1507180006. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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A landscape of cellular aggregation of Rhizobium etli CFN42 by a transcriptomic approach

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