Microbial Natural Products and Biosynthesis

The paper discovers the biosynthetic pathway for the non-canonical amino acid pazamine, involving a radical halogenase and a PLP-dependent enzyme, and shows its potential agricultural applications.

This paper identifies a complex regulatory network controlling density-dependent saquayamycin production in Streptomyces, involving Lsr2, PhoRP, and other regulators.

The paper shows that Lrp activates aroX and npsA genes involved in tilivalline biosynthesis in K. oxytoca, reducing cytotoxicity in its absence.

The paper investigates how structural diversity in polyketide antibiotics arises through differential enoylreductase recruitment and module iteration in trans-acyltransferase polyketide synthases.

The paper analyzes 2,371 Streptomyces genomes to refine biosynthetic gene cluster (BGC) diversity using MASH-clusters and reveals conserved genomic structures suggesting vertical inheritance.

The paper uses independent component analysis to characterize the transcriptional regulatory network of Streptomyces albidoflavus and identifies iModulons that describe its activity across growth conditions.

The paper develops a flexible DNA assembly toolkit for gene cluster engineering in Streptomyces to enhance natural product production.

This study uses genomic analysis of Streptomyces to identify novel antimicrobial compounds with low resistance potential, leveraging bioinformatics tools and AI predictions.

The paper introduces the Natural Products Discovery Center, releasing 8490 sequenced Actinobacteria strains and highlighting their taxonomic and biosynthetic diversity.

The paper introduces a simplified one-step extraction and diffusion assay to test the antimicrobial potential of three bacterial species against human pathogens.

This study identifies SirE as a negative regulator of bacteria-induced activation of the ors gene cluster in Aspergillus nidulans, showing that its deletion allows gene cluster activation without bacterial presence.

This study introduces AtropoFinder, a machine learning tool that identifies atropopeptide biosynthetic gene clusters and expands the known chemical diversity of this RiPP family.

ABC-HuMi catalogs 19,218 biosynthetic gene clusters from the human microbiome, offering a comprehensive resource for exploring bioactive compound potential.

The paper introduces a high-throughput platform for discovering bioactive natural products from Streptomyces by combining computational prediction, cloning, and heterologous expression of biosynthetic gene clusters.

This study mines Salinispora genomes to identify secondary metabolite biosynthetic gene clusters and carbohydrate-active enzymes, revealing potential for new drug development.

The paper introduces network analysis methods to identify exogenous compounds that trigger specialized metabolite production in fungi and distinguish unknown analytes.

This study analyzes the genome and transcriptome of the fungal endophyte Alternaria burnsii NCIM 1409 to understand camptothecin biosynthesis and its defense mechanisms.

This study reveals the molecular mechanism of SARP transcriptional activation using cryo-EM, showing how SAS interacts with DNA and RNAP to facilitate antibiotic biosynthesis.

This paper introduces guidelines for optimizing type S non-ribosomal peptide synthetases to improve production yields of artificial non-ribosomal peptides.

CLOCI identifies gene clusters using co-occurrence and orthology proxies, revealing noncanonical clusters and improving detection of known functional classes.

The paper reports directed evolution of an NRPS adenylation domain to incorporate piperazic acid, demonstrating that low-throughput methods can alter NRPS substrate specificity.

The paper uses metagenomic domain substitution to generate novel non-ribosomal peptides by screening over 1,000 domains in a pyoverdine NRPS, resulting in 16 distinct products.

This paper introduces SanntiS, a machine learning tool for identifying biosynthetic gene clusters in genomic and metagenomic data, and demonstrates its ability to predict a large number of novel BGCs with experimental validation.

This paper introduces a self-supervised learning approach to detect and classify biosynthetic gene clusters in microbial genomes using masked language models trained on protein domains.

The paper introduces a standardized NRPS architecture using conserved motifs, leading to new subtype classifications, novel motifs, and insights into reengineering challenges.

This paper isolates a new Streptomyces species from a deep-sea sponge and identifies six unique biosynthetic gene clusters through comparative analysis.

CAGECAT enables rapid homology searches and visualization of gene clusters across genomes, aiding in the discovery of novel metabolites through comparative analysis.

The paper introduces lsaBGC, a bioinformatics tool for analyzing BGCs in skin microbiomes, revealing evolutionary patterns and novel SNVs in key species.

This paper combines microbial and chemical synthesis to efficiently produce plitidepsin, achieving high yields and new analogues with anticancer and antiviral activities.

The paper shows that bursts in biosynthetic gene cluster transcription in Sorangium sp. correlate with natural compound production, challenging the idea that BGCs are preferentially expressed under nutrient limitation.