Tandem mass spectral metabolic profiling of 54 actinobacterial strains and their 459 mutants.

Natural products encompass a diverse range of compounds with high impact applications in consumer care, agriculture and most notably, therapeutics. However, despite the expansive chemical repertoire indicated in genomic information of microbes, only a small subset can be obtained under laboratory conditions. To increase accessible chemical space and realize Nature's full chemical potential, a multi-pronged genetic- and cultivation-based strategy has been employed to activate and upregulate natural product biosyntheses in native and heterologous strains.

Exploring a general multi-pronged activation strategy for natural product discovery in Actinomycetes.

Natural products possess significant therapeutic potential but remain underutilized despite advances in genomics and bioinformatics. While there are approaches to activate and upregulate natural product biosynthesis in both native and heterologous microbial strains, a comprehensive strategy to elicit production of natural products as well as a generalizable and efficient method to interrogate diverse native strains collection, remains lacking. Here, we explore a flexible and robust integrase-mediated multi-pronged activation approach to reliably perturb and globally trigger antibiotics production in actinobacteria.

Dioxaphosphabicyclooctanes: small caged phosphines from tris(hydroxymethyl)phosphine.

Dioxaphosphabicyclo[2.2.2]octanes (L1-L4) have been prepared in a one-pot reaction from tris(hydroxymethyl)phosphine and various α,β-unsaturated ketones.

67 million natural product-like compound database generated via molecular language processing.

Natural products are a rich resource of bioactive compounds for valuable applications across multiple fields such as food, agriculture, and medicine. For natural product discovery, high throughput in silico screening offers a cost-effective alternative to traditional resource-heavy assay-guided exploration of structurally novel chemical space. In this data descriptor, we report a characterized database of 67,064,204 natural product-like molecules generated using a recurrent neural network trained on known natural products, demonstrating a significant 165-fold expansion in library size over the approximately 400,000 known natural products.

Cost-effective hybrid long-short read assembly delineates alternative GC-rich hosts for natural product discovery.

With the advent of rapid automated identification of biosynthetic gene clusters (BGCs), genomics presents vast opportunities to accelerate natural product (NP) discovery. However, prolific NP producers, , are exceptionally GC-rich (>80%) and highly repetitive within BGCs. These pose challenges in sequencing and high-quality genome assembly which are currently circumvented intensive sequencing.