Models

Dataset Information

0

Liu2019 - Clostridium ljungdahlii metabolism model


ABSTRACT: The unique capability of acetogens to ferment a broad range of substrates renders them ideal candidates for the biotechnological production of commodity chemicals. In particular the ability to grow with H2:CO2 or syngas (a mixture of H2/CO/CO2) makes these microorganisms ideal chassis for sustainable bioproduction. However, advanced design strategies for acetogens are currently hampered by incomplete knowledge about their physiology and our inability to accurately predict phenotypes. Here we describe the reconstruction of a novel genome-scale model of metabolism and macromolecular synthesis (ME-model) to gain new insights into the biology of the model acetogen Clostridium ljungdahlii. The model represents the first ME-model of a Gram-positive bacterium and captures all major central metabolic, amino acid, nucleotide, lipid, major cofactors, and vitamin synthesis pathways as well as pathways to synthesis RNA and protein molecules necessary to catalyze these reactions, thus significantly broadens the scope and predictability. Use of the model revealed how protein allocation and media composition influence metabolic pathways and energy conservation in acetogens and accurately predicted secretion of multiple fermentation products. Predicting overflow metabolism is of particular interest since it enables new design strategies, e.g. the formation of glycerol, a novel product for C. ljungdahlii, thus broadening the metabolic capability for this model microbe. Furthermore, prediction and experimental validation of changing secretion rates based on different metal availability opens the window into fermentation optimization and provides new knowledge about the proteome utilization and carbon flux in acetogens.

SUBMITTER: Rodrigo Santibanez  

PROVIDER: MODEL2204200003 | BioModels | 2024-01-11

REPOSITORIES: BioModels

Similar Datasets

2008-01-18 | GSE10194 | GEO
2016-04-30 | GSE80822 | GEO
2014-03-31 | E-GEOD-44845 | biostudies-arrayexpress
2010-05-26 | E-GEOD-10194 | biostudies-arrayexpress
2015-05-05 | E-GEOD-68489 | biostudies-arrayexpress
2023-05-10 | PXD040151 | Pride
2015-05-05 | E-GEOD-68490 | biostudies-arrayexpress
2024-02-13 | PXD046155 | Pride
2023-11-27 | MODEL2204190002 | BioModels