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A Multi-Omics, Machine Learning-Aware, Genome-Wide Metabolic Model of Bacillus Subtilis Refines the Gene Expression and Cell Growth Prediction.
Bi, Xinyu; Cheng, Yang; Lv, Xueqin; Liu, Yanfeng; Li, Jianghua; Du, Guocheng; Chen, Jian; Liu, Long.
Afiliación
  • Bi X; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
  • Cheng Y; Science Center for Future Foods, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
  • Lv X; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
  • Liu Y; Science Center for Future Foods, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
  • Li J; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
  • Du G; Science Center for Future Foods, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
  • Chen J; Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
  • Liu L; Science Center for Future Foods, Ministry of Education, Jiangnan University, Wuxi, 214122, China.
Adv Sci (Weinh) ; : e2408705, 2024 Sep 17.
Article en En | MEDLINE | ID: mdl-39287062
ABSTRACT
Given the extensive heterogeneity and variability, understanding cellular functions and regulatory mechanisms through the analysis of multi-omics datasets becomes extremely challenging. Here, a comprehensive modeling framework of multi-omics machine learning and metabolic network models are proposed that covers various cellular biological processes across multiple scales. This model on an extensive normalized compendium of Bacillus subtilis is validated, which encompasses gene expression data from environmental perturbations, transcriptional regulation, signal transduction, protein translation, and growth measurements. Comparison with high-throughput experimental data shows that EM_iBsu1209-ME, constructed on this basis, can accurately predict the expression of 605 genes and the synthesis of 23 metabolites under different conditions. This study paves the way for the construction of comprehensive biological databases and high-performance multi-omics metabolic models to achieve accurate predictive analysis in exploring complex mechanisms of cell genotypes and phenotypes.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Adv Sci (Weinh) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Alemania
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Adv Sci (Weinh) Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Alemania