ArticleBMC systems biology2018
Reconstruction of a genome-scale metabolic model for Actinobacillus succinogenes 130Z.
Article in BMC systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Enhanced Succinate Production inBiotech (Basel (Switzerland)) · 2025Article
- Construction and Characterization of Novel Shuttle Expression Vectors for Actinobacillus succinogenes.Biotechnology and applied biochemistry · 2025Article
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- Article
- Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.Microbiology spectrum · 2024Article
- Integrating microbial abundance time series with fermentation dynamics of the rumen microbiome via mathematical modelling.PloS one · 2024Article
- Article
- Towards applications of genome-scale metabolic model-based approaches in designing synthetic microbial communities.Quantitative biology (Beijing, China) · 2023Review
- merlin, an improved framework for the reconstruction of high-quality genome-scale metabolic models.Nucleic acids research · 2022Article
- Flux prediction using artificial neural network (ANN) for the upper part of glycolysis.PloS one · 2019Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundActinobacillus succinogenes is a promising bacterial catalyst for the bioproduction of succinic acid from low-cost raw materials. In this work, a genome-scale metabolic model was reconstructed and used to assess the metabolic capabilities of this microorganism under producing conditions.
resultsThe model, iBP722, was reconstructed based on the functional reannotation of the complete genome sequence of A. succinogenes 130Z and manual inspection of metabolic pathways, covering 1072 enzymatic reactions associated with 722 metabolic genes that involve 713 metabolites. The highly curated model was effective in capturing the growth of A. succinogenes on various carbon sources, as well as the SA production under various growth conditions with fair agreement between experimental and predicted data. Calculated flux distributions under different conditions show that a number of metabolic pathways are affected by the activity of some metabolic enzymes at key nodes in metabolism, including the transport mechanism of carbon sources and the ability to fix carbon dioxide.
conclusionsThe established genome-scale metabolic model can be used for model-driven strain design and medium alteration to improve succinic acid yields.
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