Bioinformatic Mapping of Radical S-Adenosylmethionine-Dependent Ribosomally Synthesized and Post-Translationally Modified Peptides Identifies New Cα, Cβ, and Cγ-Linked Thioether-Containing Peptides

Abstract

Recently developed bioinformatic tools have bolstered the discovery of ribosomally synthesized and posttranslationally modified peptides (RiPPs). Using an improved version of Rapid ORF Description & Evaluation Online (RODEO 2.0), a biosynthetic gene cluster mining algorithm, we bioinformatically mapped the sactipeptide RiPP class via the radical S-adenosylmethionine (SAM) enzymes that form the characteristic sactionine (sulfur-to-alpha carbon) crosslinks between cysteine and acceptor residues. Hundreds of new sactipeptide biosynthetic gene clusters were uncovered and a novel sactipeptide "huazacin" with growth-suppressive activity against Listeria monocytogenes was characterized. Bioinformatic analysis further suggested that a group of sactipeptide-like peptides heretofore referred to as SCIFFs (six cysteines in forty-five residues) might not be sactipeptides as previously thought. Indeed, the bioinformatically-identified SCIFF

The manifold roles of microbial ribosomal peptide–based natural products in physiology and ecology

“…They are characterized by an intramolecular sulfur to ␣-carbon linkage between a cysteine and another residue ( Fig. 2) and, as such, are distinguished from lanthipeptides/lantibiotics (thioether linkages between ␤-carbons) and from sactipeptide-like peptides that contain sulfur to ␤or ␥-carbon linkages (93). The sactionine motif is established by a radical-based mechanism ensured by a radical SAM enzyme called sactisynthase.…”

“…, thurincin H from Bacillus thuringiensis SF361, the twopeptide thuricin CD from the human fecal isolate B. thuringiensis DPC 6431, and huazacin or thuricin Z from B. thuringiensis serovar Huazhongensis)(25,32,93,94). They have been found recently in Ruminococcus (ruminococcins from Ruminococcus gnavus isolated from the human microbiota)(32,33) and presumably in Staphylococcus (hyicin from Staphylococcus hyicus 4244).…”

Integration of machine learning and pan-genomics expands the biosynthetic landscape of RiPP natural products

“…Despite the extensive list of known classes and modifications, new RiPP classes are still being found. Newly identified RiPP classes often carry unusual modifications, such as D-amino acids 21 , addition of unnatural amino acids 22,23 , β-amino acids 24 , or new variants of thioether crosslinks 25,26 . These discoveries strongly indicate that the RiPP genomic landscape remains far from completely charted, and that novel types of RiPPs with new and unique biological activities may yet be uncovered.…”

RRE-Finder: A Genome-Mining Tool for Class-Independent RiPP Discovery

“…Included in these clusters are RRE-protein fusions that are not present in known classes, such as RRE-glycosyltransferase fusions and RRE-glutathione S-transferase fusions ( Figure S11, Table S10). Of the nine potential RiPP clusters shown in Figure S11, four contain genes encoding rSAM enzymes, which are common in several RiPP classes 25 .…”

“…However, efforts to bioinformatically predict RiPP BGCs lag behind those for predicting PKS/NRPS clusters, due to a lack of strongly conserved protein domains spanning multiple RiPP classes. Virtually no novel RiPP classes have been discovered using solely a bioinformatic approach: The ranthipeptide class was defined solely using bioinformatics, however this class had previously been predicted and misclassified as sactipeptides 25 . Furthermore, bioinformatics have been used to vastly expand known diversity within some classes-for example, the streptide class has been expanded to include enzymes that diverge from the class-defining Lys-Trp crosslinking enzymes 39,46 .…”