The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

A Single-Cell View of the BtsSR/YpdAB Pyruvate Sensing Network in Escherichia coli and Its Biological Relevance

Fluctuating environments and individual physiological diversity force bacteria to constantly adapt and optimize the uptake of substrates. We focus here on two very similar two-component systems (TCSs) of Escherichia coli belonging to the LytS/LytTR family: BtsS/BtsR (formerly YehU/YehT) and YpdA/YpdB. Both TCSs respond to extracellular pyruvate, albeit with different affinities, typically during postexponential growth, and each system regulates expression of a single transporter gene, yjiY and yhjX, respectively. To obtain insights into the biological significance of these TCSs, we analyzed the activation of the target promoters at the single-cell level. We found unimodal cell-to-cell variability; however, the degree of variance was strongly influenced by the available nutrients and differed between the two TCSs. We hypothesized that activation of either of the TCSs helps individual cells to replenish carbon resources. To test this hypothesis, we compared wild-type cells with the btsSR ypdAB mutant under two metabolically modulated conditions: protein overproduction and persister formation. Although all wild-type cells were able to overproduce green fluorescent protein (GFP), about half of the btsSR ypdAB population was unable to overexpress GFP. Moreover, the percentage of persister cells, which tolerate antibiotic stress, was significantly lower in the wild-type cells than in the btsSR ypdAB population. Hence, we suggest that the BtsS/BtsR and YpdA/YpdB network contributes to a balancing of the physiological state of all cells within a population