Non-ribosomal peptide synthetase (NRPS) is a diverse family of biosynthetic enzymes for the assembly of bioactive peptides. Despite advances in microbial sequencing, the lack of a consistent standard for annotating NRPS domains and modules has made data-driven discoveries challenging. To address this, we introduced a standardized architecture for NRPS, by using known conserved motifs to partition typical domains. This motif-and-intermotif standardization allowed for systematic evaluations of sequence properties from a large number of NRPS pathways, resulting in the most comprehensive cross-kingdom C domain subtype classifications to date, as well as the discovery and experimental validation of novel conserved motifs with functional significance. Furthermore, our coevolution analysis revealed important barriers associated with re-engineering NRPSs and uncovered the entanglement between phylogeny and substrate specificity in NRPS sequences. Our findings provide a comprehensive and statistically insightful analysis of NRPS sequences, opening avenues for future data-driven discoveries.

Bacterial social interactions play crucial roles in various ecological, medical, and biotechnological contexts. However, predicting these interactions from genome sequences is notoriously difficult. Here, we developed bioinformatic tools to predict whether secreted iron-scavenging siderophores stimulate or inhibit the growth of community members. Siderophores are chemically diverse and can be stimulatory or inhibitory depending on whether bacteria have or lack corresponding uptake receptors. We focused on 1928 representative Pseudomonas genomes and developed an experimentally validated coevolution algorithm to match encoded siderophore synthetases to corresponding receptor groups. We derived community-level iron interaction networks to show that siderophore-mediated interactions differ across habitats and lifestyles. Specifically, dense networks of siderophore sharing and competition were observed among environmental and nonpathogenic species, while small, fragmented networks occurred among human-associated and pathogenic species. Together, our sequence-to-ecology approach empowers the analyses of social interactions among thousands of bacterial strains and offers opportunities for targeted intervention to microbial communities.

Nonribosomal peptides are diverse natural products with important applications in medicine and agriculture. Bacterial and fungal genomes contain thousands of nonribosomal peptide biosynthetic gene clusters (BGCs) of unknown function, providing a promising resource for peptide discovery. Core structural features of such peptides can be inferred by predicting the substrate(s) of adenylation (A) domains in nonribosomal peptide synthetases (NRPSs). However, existing approaches to A domain prediction rely on limited datasets and often struggle with domains selecting large substrates or from less-studied taxa. Here, we systematically curate and computationally analyse 3,653 A domains and present two high-accuracy specificity predictors, PARAS and PARASECT. A type of A domain with unusually high L-tryptophan specificity was identified through the application of PARAS, and intact protein mass spectrometry to the corresponding NRPS showed it to direct the production of tryptopeptin-related metabolites in Streptomyces species. Together, these technologies will accelerate the characterisation of novel NRPSs and their metabolic products. PARAS and PARASECT are available at https://paras.bioinformatics.nl.

Nonribosomal peptides are diverse natural products with important applications in medicine and agriculture. Bacterial and fungal genomes contain thousands of nonribosomal peptide biosynthetic gene clusters (BGCs) of unknown function, providing a promising resource for peptide discovery. Core structural features of such peptides can be inferred by predicting the substrate(s) of adenylation (A) domains in nonribosomal peptide synthetases (NRPSs). However, existing approaches to A domain prediction rely on limited data sets and often struggle with domains selecting large substrates and domains from underrepresented taxa. Here, we systematically curate and computationally analyze 3653 A domains and present two high-accuracy specificity predictors, PARAS and PARASECT. A type of A domain with unusually high l-tryptophan specificity was identified through the application of PARAS. Cloning and expression of the biosynthetic gene cluster encoding the NRPS showed that it directs the biosynthesis of tryptopeptin-related metabolites in Streptomyces species. Together, these technologies will accelerate the characterization of novel NRPSs and their metabolic products. PARAS and PARASECT are available at https://paras.bioinformatics.nl.

Predicting bacterial social interactions from genome sequences is notoriously difficult. Here, we developed bioinformatic tools to predict whether secreted iron-scavenging siderophores stimulate or inhibit the growth of community members. Siderophores are chemically diverse and can be stimulatory or inhibitory depending on whether bacteria possess or lack corresponding uptake receptors. We focused on 1928 representative Pseudomonas genomes and developed a co-evolution algorithm to match all encoded siderophore synthetases to corresponding receptor gene groups with >90% accuracy based on experimental validation. We derived community-level iron interaction networks to show that selection for siderophore-mediated interactions differs across habitats and lifestyles. Specifically, dense networks of siderophore sharing and competition were observed among environmental (soil/water/plant) strains and non-pathogenic species, while only fragmented networks occurred among human-derived strains and pathogenic species. Altogether, our sequence-to-ecology approach empowers the analyses of social interactions among thousands of bacterial strains and uncovers ways for targeted intervention to microbial communities.

Fungi have evolved a plethora of functionally diverse secondary metabolites (SMs) to enhance their adaptation to various environments. To understand how structurally diverse metabolites contribute to fungal adaptation, we elucidate fungus-mycohost specific interactions mediated by a family of polypeptides, i.e. , peptaibols. We specified that peptaibol structural diversification was attributed to the nonspecific substrate recognition by the highly conserved peptaibol synthetases (PSs) in dead wood inhabiting mycoparasitic fungi from the genus Trichoderma . Exemplified by investigation of T. hypoxylon , we characterized a library of 19 amino acid residue peptaibols, named trichohypolins, containing 42 derivatives synthesized by a single PS enzyme (NPS1 _Th ). Elimination of trichohypolin production by the deletion of nps1 _Th reduced the inhibitory activities of T. hypoxylon on at least 15 saprotrophic host fungi, indicating that peptaibols are essential for interactions of Trichoderma spp. with their mycohosts. Different antagonistic effects of five trichohypolin subfractions SF1–SF5 and two pure compounds trichohypolins A ( 1 ) and B ( 2 ) on saprotrophic host fungi revealed specific activities of peptaibol derivatives in mediating fungus-mycohost interaction. Our study provides insights into the role of metabolic diversity of biosynthetic pathways in interfungal interactions.