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Updated: Sep 28, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Correlational networking guides the discovery of unclustered lanthipeptide protease-encoding genes
Dan Xue1, Ethan A Older1, Zheng Zhong2,3
1Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC, USA.
Abstract:
Bacterial natural product biosynthetic genes, canonically clustered, have been increasingly found to rely on hidden enzymes encoded elsewhere in the genome for completion of biosynthesis. The study and application of lanthipeptides are frequently hindered by unclustered protease genes required for final maturation. Here, we establish a global correlation network bridging the gap between lanthipeptide precursors and hidden proteases. Applying our analysis to 161,954 bacterial genomes, we establish 5209 correlations between precursors and hidden proteases, with 91 prioritized. We use network predictions and co-expression analysis to reveal a previously missing protease for the maturation of class I lanthipeptide paenilan. We further discover widely distributed bacterial M16B metallopeptidases of previously unclear biological function as a new family of lanthipeptide proteases. We show the involvement of a pair of bifunctional M16B proteases in the production of previously unreported class III lanthipeptides with high substrate specificity. Together, these results demonstrate the strength of our correlational networking approach to the discovery of hidden lanthipeptide proteases and potentially other missing enzymes for natural products biosynthesis.
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