Sequence-dependent model of genes with dual σ factor preference

Abstract

Escherichia coli uses the ability of σ factors to recognize specific DNA sequences in order to quickly control large gene cohorts. While most genes respond to only one σ factor, approximately 5% have dual σ factor preference. The ones in significant numbers are ‘σ70+38 genes’, responsive to σ70, which controls housekeeping genes, as well as to σ38, which activates genes during stationary growth and stresses. We show that σ70+38 genes are almost as upregulated in stationary growth as genes responsive to σ38 alone. Also, their response strengths to σ38 are predictable from their promoter sequences. Next, we propose a sequence- and σ38 level-dependent, analytical model of σ70+38 genes applicable in the exponential, stationary, and in the transition period between the two growth phases. Finally, we propose a general model, applicable to other σ factors as well. This model can guide the design of synthetic circuits with sequence-dependent sensitivity and plasticity to transitions between the exponential and stationary growth phases.Author SummaryPresent challenges in Synthetic Biology include the design of genetic circuits that are robust to growth phase transitions and whose responsiveness is sequence-dependent, and, thus predictable prior to design. We present and validate an empirical-based, sequence-dependent analytical model of E. coli genes with dual responsiveness to the regulators σ70 and σ38. These genes, supported by our sequence-dependent model, could become building blocks for synthetic genetic circuits functional in both the exponential and the stationary growth phases.

The transcription factor network of E. coli steers global responses to shifts in RNAP concentration

“…We also considered that at ~180 min (Figure 2A) the cells are at late mid-log phase. Thus, measuring the effects of changing RNAP should occur prior to ~180 min, since leaving the mid-log phase will involve significant, unrelated genome-wide changes in RNA abundances (54)(55)(56)(57). From the point of view of cell divisions, from the moment when the RNAP starts changing up to the moment when we measure the short-and the mid-term changes in RNA abundances, on average, less than one cell cycle and less than two cell cycles should have passed, respectively.…”

Alteration of DNA supercoiling serves as a trigger of short-term cold shock repressed genes ofE. coli

“…RNA-seq *.fastq data and processed data under cold shock and novobiocin are deposited in NCBI GEO with accession code GSE194037. Meanwhile, since the raw RNAseq data (control condition) was already used in (113,114), please access it using its NCBI GEO accession code GSE183139. Another data package was deposited in Dryad with flow cytometry, microscopy, and plate reader data (DOI: 10.5061/dryad.pvmcvdnnm).…”