Evidence map›Paper›PMID 41194004›Full record

ArticleBMC genomics2025

Reconstruction and application of a genome-scale metabolic model for Streptococcus suis.

Nan Xu, Jiaqi Kang, Chengkun Zheng, Linyao Zhou, Cong Gao, Minliang Guo

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Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Nan XuCollege of Bioscience and Biotechnology, Yangzhou University, Yangzhou, Jiangsu, 225009, China.
Jiaqi KangCollege of Bioscience and Biotechnology, Yangzhou University, Yangzhou, Jiangsu, 225009, China.
Chengkun ZhengCollege of Bioscience and Biotechnology, Yangzhou University, Yangzhou, Jiangsu, 225009, China.
Linyao ZhouCollege of Bioscience and Biotechnology, Yangzhou University, Yangzhou, Jiangsu, 225009, China.
Cong GaoSchool of Biotechnology, Jiangnan University, Wuxi, Jiangsu, 214122, China. conggao@jiangnan.edu.cn.
Minliang GuoCollege of Bioscience and Biotechnology, Yangzhou University, Yangzhou, Jiangsu, 225009, China. guoml@yzu.edu.cn.

Funding

National Key Research and Development Program of China 2020YFA0908300National Natural Science Foundation of China 22278350
6 · The paper itself

Abstract

backgroundsStreptococcus suis is an emerging zoonotic bacterial disease with increasing prevalence in the human population and is one of the most important bacterial infections in pig husbandry. There is still a lack of a thorough understanding of S. suis metabolism and the connection between metabolism and virulence.

resultsA genome-scale metabolic model iNX525, which included 525 genes, 708 metabolites, and 818 reactions, was manually constructed with a 74% overall MEMOTE score. The flux balance analysis results of the model exhibited good agreement with growth phenotypes under different nutrient conditions and genetic disturbances. The model predictions aligned with 71.6%, 76.3%, and 79.6% of the gene essentiality predictions from three mutant screens. The model was then used to analyze virulence factors and related synthetic pathways. One hundred and thirty-one virulence-linked genes were found by comparing to virulence factor databases, and among them, seventy-nine virulence-linked genes were in 167 metabolic reactions in model iNX525. One hundred and one of the metabolic genes were predicted to affect the formation of nine virulence-linked small molecules. Complex interrelationships between growth- and virulence-associated pathways were evaluated, and 26 genes were found to be essential for both cell growth and virulence factor production. Among these, eight enzymes and metabolites were identified as antibacterial drug targets, focusing on the biosynthesis of capsular polysaccharides and peptidoglycans.

conclusionOverall, the metabolic model iNX525 provides a high-quality platform for systematic elucidation of the metabolism of S. suis.

Indexed as

Genome, BacterialGenomicsModels, BiologicalStreptococcus suisMetabolic Networks and PathwaysVirulenceVirulence FactorsVirulence FactorsAntimicrobial targetsStreptococcus suisVirulence factor

Identifiers

PMID41194004
PMCPMC12590895

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