Abstract. Background: Bacterial toxin-antitoxin (TA) systems are formed by potent regulatory or suicide factors (toxins) and their short-lived inhibitors (antitoxins). Antitoxins are DNA-binding proteins and auto-repress transcription of TA operons. Transcription of multiple TA operons is activated in temporarily non-growing persister cells that can resist killing by antibiotics. Consequently, the antitoxin levels of persisters must have been dropped and toxins are released of inhibition. Results: Here, we describe transcriptional cross-activation between different TA systems of Escherichia coli. We find that the chromosomal relBEF operon is activated in response to production of the toxins MazF, MqsR, HicA, and HipA. Expression of the RelE toxin in turn induces transcription of several TA operons. We show that induction of mazEF during amino acid starvation depends on relBE and does not occur in a relBEF deletion mutant. Induction of TA operons has been previously shown to depend on Lon protease which is activated by polyphospate accumulation. We show that transcriptional cross-activation occurs also in strains deficient for Lon, ClpP, and HslV proteases and polyphosphate kinase. Furthermore, we find that toxins cleave the TA mRNA in vivo, which is followed by degradation of the antitoxin-encoding fragments and selective accumulation of the toxin-encoding regions. We show that these accumulating fragments can be translated to produce more toxin. Conclusion: Transcriptional activation followed by cleavage of the mRNA and disproportionate production of the toxin constitutes a possible positive feedback loop, which can fire other TA systems and cause bistable growth heterogeneity. Cross-interacting TA systems have a potential to form a complex network of mutually activating regulators in bacteria. © 2013 Kasari et al; licensee BioMed Central Ltd.
CITATION STYLE
Kasari, V., Mets, T., Tenson, T., & Kaldalu, N. (2013). Transcriptional cross-activation between toxin-antitoxin systems of Escherichia coli. BMC Microbiology, 13(1). https://doi.org/10.1186/1471-2180-13-45
Mendeley helps you to discover research relevant for your work.