bioRxivMicrobiology
Type I toxin-antitoxin systems contribute to mobile genetic elements maintenance in Clostridioides difficile and can be used as a counter-selectable marker for chromosomal manipulation
J. Peltier, A. Hamiot, J. R. Garneau, P. Boudry, A. Maikova, L.-C. Fortier, B. Dupuy, O. Soutourina
Abstract
Toxin-antitoxin (TA) systems are widespread on mobile genetic elements as well as in bacterial chromosomes. According to the nature of the antitoxin and its mode of action for toxin inhibition, TA systems are subdivided into different types. The first type I TA modules were recently identified in the human enteropathogen Clostridioides (formerly Clostridium) difficile. In type I TA, synthesis of the toxin protein is prevented by the transcription of an antitoxin RNA during normal growth. Here, we report the characterization of five additional type I TA systems present within phiCD630-1 and phiCD630-2 prophage regions of C. difficile 630. Toxin genes encode 34 to 47 amino acid peptides and their ectopic expression in C. difficile induces growth arrest. Growth is restored when the antitoxin RNAs, transcribed from the opposite strand, are co-expressed together with the toxin genes. In addition, we show that type I TA modules located within the phiCD630-1 prophage contribute to its stability and mediate phiCD630-1 heritability. Type I TA systems were found to be widespread in genomes of C. difficile phages, further suggesting their functional importance. We have made use of a toxin gene from one of type I TA modules of C. difficile as a counter-selectable marker to generate an efficient mutagenesis tool for this bacterium. This tool enabled us to delete all identified toxin genes within the phiCD630-1 prophage, thus allowing investigation of the role of TA in prophage maintenance. Furthermore, we were able to delete the large 49 kb phiCD630-2 prophage region using this improved procedure.
- organism: C. elegans
- assay: proteomics
- research focus: cell type annotation
- research focus: gene regulatory network inference
- approach: experimental assay
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