Metabolic reconstruction and modeling of nitrogen fixation in Rhizobium etli.

TitleMetabolic reconstruction and modeling of nitrogen fixation in Rhizobium etli.
Publication TypeJournal Article
Year of Publication2007
AuthorsResendis-Antonio O, Reed JL, Encarnación S, Collado-Vides J, Palsson BØ
JournalPLoS computational biology
Volume3
Issue10
Pagination1887-95
PubMed Date2007 Oct
ISSN1553-7358
KeywordsGene Expression Regulation, Bacterial, Genome, Bacterial, Metabolic Networks and Pathways, Models, Biological, Nitrogen Fixation, Rhizobium etli, Symbiosis
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.

Alternate JournalPLoS Comput. Biol.
PubMed ID17922569

Location

Location

417 Powell-Focht Bioengineering Hall

9500 Gilman Drive La Jolla, CA 92093-0412

Contact Us

Contact Us

In Silico Lab:  858-822-1144

Wet Lab:  858-246-1625

FAX:   858-822-3120

Website Concerns: sbrgit@ucsd.edu

User Login