Hierarchical expression of genes controlled by the Bacillus subtilis global regulatory protein CodY.
Global regulators that bind strategic metabolites allow bacteria to adapt rapidly to dynamic environments by coordinating the expression of many genes. We report an approach for determining gene regulation hierarchy using the regulon of the Bacillus subtilis global regulatory protein CodY as proof of principle. In theory, this approach can be used to measure the dynamics of any bacterial transcriptional regulatory network that is affected by interaction with a ligand. In B. subtilis, CodY controls dozens of genes, but the threshold activities of CodY required to regulate each gene are unknown. We hypothesized that targets of CodY are differentially regulated based on varying affinity for the protein's many binding sites. We used RNA sequencing to determine the transcription profiles of B. subtilis strains expressing mutant CodY proteins with different levels of residual activity. In parallel, we quantified intracellular metabolites connected to central metabolism. Strains producing CodY variants F71Y, R61K, and R61H retained varying degrees of partial activity relative to the WT protein, leading to gene-specific, differential alterations in transcript abundance for the 223 identified members of the CodY regulon. Using liquid chromatography coupled to MS, we detected significant increases in branched-chain amino acids and intermediates of arginine, proline, and glutamate metabolism, as well as decreases in pyruvate and glycerate as CodY activity decreased. We conclude that a spectrum of CodY activities leads to programmed regulation of gene expression and an apparent rerouting of carbon and nitrogen metabolism, suggesting that during changes in nutrient availability, CodY prioritizes the expression of specific pathways.
Department of Molecular Biology and Microbiology, Tufts University School of Medicine, Boston, MA 02111;
Shaun R
SR
Brinsmade
Division of Infectious Diseases, Department of Medicine, Weill Cornell Medical College, New York, NY 10065;
Elizabeth L
EL
Alexander
The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142; and.
Jonathan
J
Livny
Departments of Biomedical Engineering and.
Arion I
AI
Stettner
Departments of Biomedical Engineering andBiology andBioinformatics Program, Boston University, Boston, MA 02215.
Daniel
D
Segrè
Division of Infectious Diseases, Department of Medicine, Weill Cornell Medical College, New York, NY 10065;
Kyu Y
KY
Rhee
Department of Molecular Biology and Microbiology, Tufts University School of Medicine, Boston, MA 02111; linc.sonenshein@tufts.edu.
Abraham L
AL
Sonenshein
D001120:Arginine / Q000096:biosynthesis; D001412:Bacillus subtilis / Q000235:genetics* / Q000378:metabolism; D001426:Bacterial Proteins / Q000235:genetics* / Q000378:metabolism; D002244:Carbon / Q000378:metabolism; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D015964:Gene Expression Regulation, Bacterial; D018698:Glutamic Acid / Q000096:biosynthesis; D008024:Ligands; D017423:Sequence Analysis, RNA; D000637:Transaminases / Q000378:metabolism; D014157:Transcription Factors / Q000235:genetics* / Q000378:metabolism
D001426:Bacterial Proteins; D008024:Ligands; D014157:Transcription Factors; D018698:Glutamic Acid; D002244:Carbon; D001120:Arginine; D000637:Transaminases
BCAA; ILV; RNA-seq; metabolite analysis