Knowledge-guided data mining on the standardized architecture of NRPS: Subtypes, novel motifs, and sequence entanglements

Author:

He RuolinORCID,Zhang Jinyu,Shao Yuanzhe,Gu Shaohua,Song ChenORCID,Qian LongORCID,Yin Wen-BingORCID,Li ZhiyuanORCID

Abstract

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.

Funder

Key Technologies Research and Development Program

National Natural Science Foundation of China

Clinical Medicine Plus X - Young Scholars Project, Peking University, the Fundamental Research Funds for the Central Universities

The Biological Resources Program, Chinese Academy of Sciences

Key Project of Frontier Science Research of Chinese Academy of Sciences

National Postdoctoral Program for Innovative Talents

Publisher

Public Library of Science (PLoS)

Subject

Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics

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