Dataset Information

Global Genome Mining Reveals the Distribution of Diverse Thioamidated RiPP Biosynthesis Gene Clusters.

ABSTRACT: Thioamidated ribosomally synthesized and post-translationally modified peptides (RiPPs) are recently characterized natural products with wide range of potent bioactivities, such as antibiotic, antiproliferative, and cytotoxic activities. These peptides are distinguished by the presence of thioamide bonds in the peptide backbone catalyzed by the YcaO-TfuA protein pair with its genes adjacent to each other. Genome mining has facilitated an in silico approach to identify biosynthesis gene clusters (BGCs) responsible for thioamidated RiPP production. In this work, publicly available genomic data was used to detect and illustrate the diversity of putative BGCs encoding for thioamidated RiPPs. AntiSMASH and RiPPER analysis identified 613 unique TfuA-related gene cluster families (GCFs) and 797 precursor peptide families, even on phyla where the presence of these clusters have not been previously described. Several additional biosynthesis genes are colocalized with the detected BGCs, suggesting an array of possible chemical modifications. This study shows that thioamidated RiPPs occupy a widely unexplored chemical landscape.

SUBMITTER: Malit JJL

PROVIDER: S-EPMC8120280 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Global Genome Mining Reveals the Distribution of Diverse Thioamidated RiPP Biosynthesis Gene Clusters.

Malit Jessie James Limlingan JJL Wu Chuanhai C Liu Ling-Li LL Qian Pei-Yuan PY

Frontiers in microbiology 20210430

Thioamidated ribosomally synthesized and post-translationally modified peptides (RiPPs) are recently characterized natural products with wide range of potent bioactivities, such as antibiotic, antiproliferative, and cytotoxic activities. These peptides are distinguished by the presence of thioamide bonds in the peptide backbone catalyzed by the YcaO-TfuA protein pair with its genes adjacent to each other. Genome mining has facilitated an <i>in silico</i> approach to identify biosynthesis gene cl ...[more]

PMID: 33995295

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Project description:Many ribosomally synthesized and posttranslationally modified peptide classes (RiPPs) are reliant on a domain called the RiPP recognition element (RRE). The RRE binds specifically to a precursor peptide and directs the posttranslational modification enzymes to their substrates. Given its prevalence across various types of RiPP biosynthetic gene clusters (BGCs), the RRE could theoretically be used as a bioinformatic handle to identify novel classes of RiPPs. In addition, due to the high affinity and specificity of most RRE-precursor peptide complexes, a thorough understanding of the RRE domain could be exploited for biotechnological applications. However, sequence divergence of RREs across RiPP classes has precluded automated identification based solely on sequence similarity. Here, we introduce RRE-Finder, a new tool for identifying RRE domains with high sensitivity. RRE-Finder can be used in precision mode to confidently identify RREs in a class-specific manner or in exploratory mode to assist in the discovery of novel RiPP classes. RRE-Finder operating in precision mode on the UniProtKB protein database retrieved ∼25,000 high-confidence RREs spanning all characterized RRE-dependent RiPP classes, as well as several yet-uncharacterized RiPP classes that require future experimental confirmation. Finally, RRE-Finder was used in precision mode to explore a possible evolutionary origin of the RRE domain. The results suggest RREs originated from a co-opted DNA-binding transcriptional regulator domain. Altogether, RRE-Finder provides a powerful new method to probe RiPP biosynthetic diversity and delivers a rich data set of RRE sequences that will provide a foundation for deeper biochemical studies into this intriguing and versatile protein domain.IMPORTANCE Bioinformatics-powered discovery of novel ribosomal natural products (RiPPs) has historically been hindered by the lack of a common genetic feature across RiPP classes. Herein, we introduce RRE-Finder, a method for identifying RRE domains, which are present in a majority of prokaryotic RiPP biosynthetic gene clusters (BGCs). RRE-Finder identifies RRE domains 3,000 times faster than current methods, which rely on time-consuming secondary structure prediction. Depending on user goals, RRE-Finder can operate in precision mode to accurately identify RREs present in known RiPP classes or in exploratory mode to assist with novel RiPP discovery. Employing RRE-Finder on the UniProtKB database revealed several high-confidence RREs in novel RiPP-like clusters, suggesting that many new RiPP classes remain to be discovered.

Dataset Information

Global Genome Mining Reveals the Distribution of Diverse Thioamidated RiPP Biosynthesis Gene Clusters.

Publications

Global Genome Mining Reveals the Distribution of Diverse Thioamidated RiPP Biosynthesis Gene Clusters.

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