Hierarchical expression of genes controlled by the Bacillus subtilis global regulatory protein CodY

Abstract

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.

Keywords: BCAA; ILV; RNA-seq; metabolite analysis.

Fig. 1.

Reductions in transcription factor activity generate a diverse set of responses throughout the CodY regulon. RPKMO values for 197 differentially expressed targets with values >10 in at least one strain were plotted as a percentage of maximal expression (i.e., expression in the codY null mutant for negatively regulated genes and expression in the WT for positively regulated genes). Some CodY target genes, including adcA, frlR, rpmE2, rpsN, trpD, yczL, yrpE, ybfAB, yciABC, yjbA, and yrhP, were omitted because the data were not reproducible or the patterns were complex. Note that the positions of the point mutant strains on the x axis are arbitrary and are not meant to imply a linear relationship between position and residual CodY activity. Data points are the means of two independent experiments.

Fig. 2.

Graded response to changes in CodY activity is revealed by k-means clustering. Genes repressed by CodY were distributed to 10 clusters (clusters 1–10, red), and genes activated by CodY were distributed to four clusters (clusters 11–14, blue). Reading from cluster 1–10 and from cluster 11–14, gene clusters that responded to modest changes in CodY activity precede those that only responded to more substantial changes in activity. The relative positioning of clusters 6 and 7 was arbitrary.

Fig. 3.

CodY represses certain amino acid utilization genes less stringently than glutamate and arginine biosynthesis genes. All data here and in subsequent figures are presented as the means of at least two independent experiments. (A) Histidine, proline, and arginine are degraded to glutamate or to glutamate plus ammonium ion. (Urea is released as the first step in arginine degradation and is then degraded by urease to ammonia and CO₂.) α-KG, α-ketoglutarate. (B) CodY-repressed targets coding for enzymes for degradation of histidine (hutP), citrulline (rocB), urea (ureA), and proline (ycgMN, also known as putBC), as well as CodY-repressed targets coding for biosynthesis of arginine (argC) and glutamate (gltA), are shown. (C) Heat map displays the relationship between relative levels of CodY activity and key metabolites of amino acid metabolism (Dataset S6). Changes in the abundance of each metabolite are color-coded, with red indicating an increase in intracellular abundance relative to the baseline (abundance in the WT) on a log(2) scale. p, level of statistical significance by Cuzick’s nonparametric test for trend of the abundance of each metabolite in WT (SRB109), R61K (SRB361), R61H (SRB465), and null (SRB268) strains; p*, the adjusted P value after correction for multiple hypothesis testing (65). P values in red typeface indicate the level of significance in the WT vs. codY null mutant determined by a Mann–Whitney U test but do not show a dose-dependent relationship by Cuzick’s test of trend across all isolates. NS, not significant.

Fig. 4.

CodY prioritizes BCAA aminotransferase gene expression. (A) YbgE, YwaA, and Bcd mediate interconversion of α-keto acids (BCKAs) and their cognate amino acids (BCAAs). (B) CodY regulates the expression of bcd indirectly. Inactivation of CodY leads to increased synthesis of Ile and Val, both of which can activate BkdR, the positive regulator of bcd. (C) ywaA and bcd were substantially derepressed when CodY activity was mildly reduced, whereas ybgE was derepressed more than 50% only in the strain lacking CodY activity. (D) Heat map displays the relationship between strains with varying levels of CodY activity and the fate of pyruvate. Changes in the abundance of each metabolite (Dataset S6) are color-coded, with red and blue indicating an increase or decrease in intracellular abundance, respectively, relative to the baseline (abundance in the WT) on a log(2) scale. Strains and statistical testing are presented as described in the legend for Fig. 3.

Fig. 5.

CodY regulates carbon overflow metabolism and reutilization of overflow metabolites. (A) Metabolic paths to and from pyruvate. The terms “out” and “in” denote extracellular and intracellular lactate, respectively. Reactions of the Krebs cycle are shaded in gray. (B) Extent of expression of four genes that represent carbon overflow metabolism (ackA) and overflow metabolite reutilization (acsA, lutP, and citB) is depicted as a percentage of maximal expression. A reduction in CodY activity reduced expression of ackA, but increased expression of acsA, lutP, and citB.