Project description: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. Overall design: Three independent biological materials with one dyeswap were performed.
Project description:The NifA-RpoN complex is a master regulator of the nitrogen fixation genes in alpha-proteobacteria. Based on the complete Rhizobium etli genome sequence, we constructed the R. etli CFN42 oligonucleotide (70 mer) microarray, and utilized this tool to survey changes in gene expression in R. etli CFN42 wild type compared with NifA CFNX247 mutant strain in symbiosis with Phaseolus vulgaris. As expected, the genes associated with a NifA and RpoN binding sites were downregulated in the NifA mutant strain. Overall design: Three independent biological materials with one dyeswap were performed.
Project description:89 small non-coding RNAs (ncRNAs) were identified in the soil-dwelling alpha-proteobacterium Rhizobium etli by comparing an extensive compilation of ncRNA predictions to intergenic expression data of a whole-genome tiling array. The differential expression levels of some of these ncRNAs during free-living growth and during interaction with the eukaryotic host plant may indicate a role in adaptation to changing environmental conditions. Overall design: In order to study expression in the free-living state, wild-type R. etli CFN42 was grown at 30˚C in acid minimal salts medium supplied with 10 mM NH4Cl and 10 mM succinate while monitoring the optical density (OD) of the culture. Samples were taken at OD600 = 0.3, 0.7 and 6 hours after reaching the maximum OD, representing early/late exponential and stationary phase, respectively. In order to study gene expression during host-associated growth, common bean plants (Phaseolus vulgaris cv. Limburgse vroege) were cultivated and inoculated as described previously. Nodules were harvested 2 and 3 weeks after inoculation and the bacteroids were purified by differential centrifugation.
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):
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
and identified by:
To cite BioModels Database, please use:
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
Public Domain Dedication for more information.