Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome

Rychel, Kevin; Sastry, Anand V.; Palsson, Bernhard O.

doi:10.1038/s41467-020-20153-9

Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome

Journal Article · Thu Dec 10 23:00:00 EST 2020 · Nature Communications

DOI:https://doi.org/10.1038/s41467-020-20153-9· OSTI ID:1816212

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Univ. of California, San Diego, La Jolla, CA (United States). Dept. of Bioengineering; OSTI
Univ. of California, San Diego, La Jolla, CA (United States). Dept. of Bioengineering
Univ. of California, San Diego, La Jolla, CA (United States). Dept. of Bioengineering; Univ. of California, San Diego, La Jolla, CA (United States). Dept. of Pediatrics; Novo Nordisk Foundation Center for Biosustainability, Lyngby (Denmark)

The transcriptional regulatory network (TRN) of Bacillus subtilis coordinates cellular functions of fundamental interest, including metabolism, biofilm formation, and sporulation. Here, we use unsupervised machine learning to modularize the transcriptome and quantitatively describe regulatory activity under diverse conditions, creating an unbiased summary of gene expression. We obtain 83 independently modulated gene sets that explain most of the variance in expression and demonstrate that 76% of them represent the effects of known regulators. The TRN structure and its condition-dependent activity uncover putative or recently discovered roles for at least five regulons, such as a relationship between histidine utilization and quorum sensing. The TRN also facilitates quantification of population-level sporulation states. As this TRN covers the majority of the transcriptome and concisely characterizes the global expression state, it could inform research on nearly every aspect of transcriptional regulation in B. subtilis.

View Accepted Manuscript (DOE)

Research Organization:: Univ. of San Diego, San Diego, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities Division

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1816212

Journal Information:: Nature Communications, Journal Name: Nature Communications Journal Issue: 1 Vol. 11; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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