AUTHOR=Yount Nannette Y. , Weaver David C. , de Anda Jaime , Lee Ernest Y. , Lee Michelle W. , Wong Gerard C. L. , Yeaman Michael R. TITLE=Discovery of Novel Type II Bacteriocins Using a New High-Dimensional Bioinformatic Algorithm JOURNAL=Frontiers in Immunology VOLUME=11 YEAR=2020 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2020.01873 DOI=10.3389/fimmu.2020.01873 ISSN=1664-3224 ABSTRACT=
Antimicrobial compounds first arose in prokaryotes by necessity for competitive self-defense. In this light, prokaryotes invented the first host defense peptides. Among the most well-characterized of these peptides are class II bacteriocins, ribosomally-synthesized polypeptides produced chiefly by Gram-positive bacteria. In the current study, a tensor search protocol—the BACIIα algorithm—was created to identify and classify bacteriocin sequences with high fidelity. The BACIIα algorithm integrates a consensus signature sequence, physicochemical and genomic pattern elements within a high-dimensional query tool to select for bacteriocin-like peptides. It accurately retrieved and distinguished virtually all families of known class II bacteriocins, with an 86% specificity. Further, the algorithm retrieved a large set of unforeseen, putative bacteriocin peptide sequences. A recently-developed machine-learning classifier predicted the vast majority of retrieved sequences to induce negative Gaussian curvature in target membranes, a hallmark of antimicrobial activity. Prototypic bacteriocin candidate sequences were synthesized and demonstrated potent antimicrobial efficacy