bioRxivBioinformaticsPreprint
Identification of a botulinum neurotoxin-like gene cluster in Bacillus toyonensis
Xin WeiiD, Briallen LobbiD, Kang WangiD, Min DongiD, Andrew C. DoxeyiD
Abstract
Clostridial neurotoxins, which include botulinum neurotoxins (BoNTs) and tetanus neurotoxin (TeNT) are the most potent toxins known, and are the causative agents of the neuroparalytic diseases, botulism and tetanus. Until recently, the clostridial neurotoxin family was restricted to the genus Clostridium, but members of this protein family have been found in a growing number of non-Clostridium species including Weissella, Enterococcus, and Paraclostridium. Here, we report the bioinformatic identification and analysis of a novel clostridial neurotoxin homolog in a Bacillus toyonensis genome recently deposited into the NCBI Genbank database. This putative toxin shares 26-29% identity with its closest BoNT relatives, suggesting that it is likely a novel BoNT-like toxin. It possesses key functional motifs (e.g., HExxH) indicative of toxin protease activity, contains the four characteristic BoNT domains, and is located in a BoNT-like genomic neighborhood containing the upstream non-toxic non-hemagglutinin (NTNH) gene as well as several P47-related genes. Phylogenetically, the toxin clusters as a divergent member of the recently discovered lineage of BoNT-like toxins that includes BoNT/X, BoNT/En, and the insecticidal PMP1. Genomic analysis of the B. toyonensis isolate CH177 revealed additional virulence factors and toxin genes indicative of potential pathogenicity targeting an unknown host species. The Bacillus toyonensis BoNT-like protein (BTNT) adds to a growing number of non-clostridial BoNT-like toxins, adding further information on the intriguing phylogenetic distribution and evolutionary history of the most potent toxins known.
- organism: bacteria (other)
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: database / resource
- research focus: phylogenetics / evolution
- approach: statistical model
- approach: experimental assay
- Citations
- 5
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