期刊
MICROBIOLOGICAL RESEARCH
卷 276, 期 -, 页码 -出版社
ELSEVIER GMBH
DOI: 10.1016/j.micres.2023.127485
关键词
Corynebacterium glutamicum; Transcriptional regulatory network; Machine learning; Independence component analysis; IModulons discovery
类别
Gene expression in bacteria is regulated by multiple transcription factors. In this study, we used independent component analysis to analyze the gene expression profile of Corynebacterium glutamicum and constructed a quantitative transcriptional regulatory network. We identified potential targets for transcription factors and observed changes in the network under different growth and environmental conditions.
Gene expression in bacteria is regulated by multiple transcription factors. Clarifying the regulation mechanism of gene expression is necessary to understand bacterial physiological activities. To further understand the structure of the transcriptional regulatory network of Corynebacterium glutamicum, we applied independent component analysis, an unsupervised machine learning algorithm, to the high-quality C. glutamicum gene expression profile which includes 263 samples from 29 independent projects. We obtained 87 robust independent regulatory modules (iModulons). These iModulons explain 76.7% of the variance in the expression profile and constitute the quantitative transcriptional regulatory network of C. glutamicum. By analyzing the constituent genes in iModulons, we identified potential targets for 20 transcription factors. We also captured the changes in iModulon activities under different growth rates and dissolved oxygen concentrations, demonstrating the ability of iModulons to comprehensively interpret transcriptional responses to environmental changes. In summary, this study provides a genome-scale quantitative transcriptional regulatory network for C. glutamicum and informs future research on complex changes in the transcriptome.
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