Brian O. Bachmann

@brianobachmann.bsky.social

Prof. Chemical Biology, PI the Vanderbilt Laboratory for Biosynthetic Studies. Posting natural product tilted human chemical biology, biosynthesis, synthetic biology, and discovery. He/him.

A new entry in ML prediction of adenylation domain selectivity in nonribosomal peptide synthetases using a protein language model. Interestingly, it boasts 92% accuracy. Compare to the 25 year old Stachelhaus code (a type of homology modeling) at 89% accuracy. #secmet

NRPStransformer, an Accurate Adenylation Domain Specificity Prediction Algorithm for Genome Mining of Nonribosomal Peptides

Nonribosomal peptides serve as pivotal sources for drug discovery. Accurate prediction of the substrate specificity of adenylation domains in nonribosomal peptide synthetases is crucial for genome mining of nonribosomal peptides, yet current prediction methods fall short in accuracy. In this work, we analyzed 4,100 adenylation domains from documented nonribosomal peptide synthetases and found that the flavodoxin-like subdomain universally governs substrate specificity in all bacterial adenylation domains and that its phylogenetic analysis can correlate the sequences of adenylation domains and their substrate specificity. Leveraging the sequences within the flavodoxin-like subdomain, we developed a substrate specificity prediction algorithm using a protein language model, achieving 92% overall prediction accuracy for 43 frequently observed amino acids, significantly improving the prediction reliability. The efficacy of our prediction tool was validated through targeted genome mining, which led to the discovery of novel antimicrobial peptides. Our work lays a foundation to understand the sequence-to-function relationship of the bacterial adenylation domain and will facilitate the exploitation of nonribosomal peptides. NRPStransformer is available at http://www.nrpstransformer.cn.

pubs.acs.org

Happy to share our newest manuscript about the discovery and hererologous expression of metanodin, a new lassopeptide with unprecedented structural features directly from soil metagenomes. pubs.acs.org/doi/full/10.... #secmet #lassopeptides #syntheticbiology

Discovery and Heterologous Expression of the Soil Metagenome-Derived Lasso Peptide Metanodin with an Unprecedented Ring Structure

Culture-independent metagenomic approaches have proven to be effective tools for identifying previously hidden biosynthetic gene clusters (BGCs) encoding novel natural products with potential medical relevance. However, producing these compounds remains challenging as metagenomic BGCs often originate from organisms phylogenetically distant from available heterologous hosts. Lasso peptides, a subclass of ribosomally synthesized and post-translationally modified peptide (RiPP) natural products, exhibit diverse bioactivities, yet no lasso peptide has previously been discovered directly from a metagenome. Here, we report the discovery and heterologous expression of the first soil metagenome-derived lasso peptide. Expression of its biosynthetic gene cluster in Escherichia coli, followed by mass spectrometry analysis, strongly supported the predicted amino acid sequence and lasso structure of the peptide. Notably, this lasso peptide is the first to feature asparagine as the ring-forming residue at position one. Taxonomic analysis of the corresponding BGC identified an uncultivated member of the Steroidobacterales family (Gammaproteobacteria) as the closest known relative of the potential native host. These findings underscore the potential of metagenomic genome mining to reveal structurally novel RiPPs and to expand our understanding of the natural diversity of lasso peptides.

pubs.acs.org

We put together this protocol in part to encourage broader adoption of Multiplexed Activity Metabolomics, an engine for functional metabolomics of all types including specialized metabolite discovery. We enjoy knowing if metabolite is active before isolating it, and so should you! #natprod

Multiplexed cytometry for single cell chemical biology

Flow cytometry has great potential for screening in translational research areas due to its deep quantification of cellular features, ability to colle…

sciencedirect.com