Sequence-dependent model of genes with dual σ factor preference

Ines S.C. Baptista, Vinodh Kandavalli, Vatsala Chauhan, Mohamed N.M. Bahrudeen, Bilena L.B. Almeida, Cristina S.D. Palma, Suchintak Dash, Andre S. Ribeiro

    Research output: Contribution to journalArticleScientificpeer-review

    7 Citations (Scopus)
    10 Downloads (Pure)

    Abstract

    Escherichia coli uses σ factors to quickly control large gene cohorts during stress conditions. While most of its genes respond to a single σ factor, approximately 5% of them have dual σ factor preference. The most common are those responsive to both σ70, which controls housekeeping genes, and σ38, which activates genes during stationary growth and stresses. Using RNA-seq and flow-cytometry measurements, we show that ‘σ70+38 genes’ are nearly as upregulated in stationary growth as ‘σ38 genes’. Moreover, we find a clear quantitative relationship between their promoter sequence and their response strength to changes in σ38 levels. We then propose and validate a sequence dependent model of σ70+38 genes, with dual sensitivity to σ38 and σ70, that is applicable in the exponential and stationary growth phases, as well in the transient period in between. We further propose a general model, applicable to other stresses and σ factor combinations. Given this, promoters controlling σ70+38 genes (and variants) could become important building blocks of synthetic circuits with predictable, sequence-dependent sensitivity to transitions between the exponential and stationary growth phases.

    Original languageEnglish
    Article number194812
    JournalBiochimica et Biophysica Acta - Gene Regulatory Mechanisms
    Volume1865
    Issue number3
    DOIs
    Publication statusPublished - Apr 2022
    Publication typeA1 Journal article-refereed

    Keywords

    • Dual σ factor preference
    • E. coli
    • Flow cytometry
    • RNA-seq
    • Sequence-dependent gene expression model

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

    • Biophysics
    • Structural Biology
    • Biochemistry
    • Molecular Biology
    • Genetics

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