Discovery of Streptomyces species CS-62, a novel producer of the Acinetobacter baumannii selective antibiotic factumycin.

Narrow-spectrum antibiotics are of great interest given their ability to spare the microbiome and decrease widespread antibiotic resistance compared to broad-spectrum antibiotics. Herein, we screened an in-house library of Actinobacteria strains for selective activity against Acinetobacter baumannii and successfully identified Streptomyces sp. CS-62 as a producer of a natural product with this valuable activity. Analysis of the cultures via high-resolution mass spectrometry and tandem mass spectrometry, followed by comparison with molecules in the Natural Product Atlas and the Global Natural Products Social Molecular Networking platform, suggested a novel natural product. Genome mining analysis initially supported the production of a novel kirromycin derivative. Isolation and structure elucidation via mass spectrometry and Nuclear Magnetic Resonance (NMR) analyses revealed that the active natural product was the known natural product factumycin, exposing omissions and errors in the consulted databases. While public databases are generally very useful for avoiding rediscovery of known molecules, rediscovery remains a problem due to public databases either being incomplete or having errors that result in failed dereplication. Overall, the work describes the ongoing problem of dereplication and the continued need for public database curation.

Genome sequences of 70 multidrug-resistant Gram-negative isolates in high-risk neonates in the Northeast of Mexico.

Infections by multidrug-resistant pathogens are steadily increasing worldwide. A considerable proportion of neonatal intensive care admissions have a bacterial infection with multidrug-resistant bacteria during their hospital stay. In this work, we report draft genome sequences of 70 selected isolates from high-risk neonates in the Northeast of Mexico.

Actinomycetota bioprospecting from ore-forming environments.

Natural products from Actinomycetota have served as inspiration for many clinically relevant therapeutics. Despite early triumphs in natural product discovery, the rate of unearthing new compounds has decreased, necessitating inventive approaches. One promising strategy is to explore environments where survival is challenging. These harsh environments are hypothesized to lead to bacteria developing chemical adaptations (e.g. natural products) to enable their survival. This investigation focuses on ore-forming environments, particularly fluoride mines, which typically have extreme pH, salinity and nutrient scarcity. Herein, we have utilized metagenomics, metabolomics and evolutionary genome mining to dissect the biodiversity and metabolism in these harsh environments. This work has unveiled the promising biosynthetic potential of these bacteria and has demonstrated their ability to produce bioactive secondary metabolites. This research constitutes a pioneering endeavour in bioprospection within fluoride mining regions, providing insights into uncharted microbial ecosystems and their previously unexplored natural products.

Biosynthetic novelty index reveals the metabolic potential of rare actinobacteria isolated from highly oligotrophic sediments.

Calculations predict that testing of 5 000-10 000 molecules and >1 billion US dollars (£0.8 billion, £1=$1.2) are required for one single drug to come to the market. A solution to this problem is to establish more efficient protocols that reduce the high rate of re-isolation and continuous rediscovery of natural products during early stages of the drug development process. The study of 'rare actinobacteria' has emerged as a possible approach for increasing the discovery rate of drug leads from natural sources. Here, we define a simple genomic metric, defined as biosynthetic novelty index (BiNI), that can be used to rapidly rank strains according to the novelty of the subset of encoding biosynthetic clusters. By comparing a subset of high-quality genomes from strains of different taxonomic and ecological backgrounds, we used the BiNI score to support the notion that rare actinobacteria encode more biosynthetic gene cluster (BGC) novelty. In addition, we present the isolation and genomic characterization, focused on specialized metabolites and phenotypic screening, of two isolates belonging to genera Lentzea and Actinokineospora from a highly oligotrophic environment. Our results show that both strains harbour a unique subset of BGCs compared to other members of the genera Lentzea and Actinokineospora. These BGCs are responsible for potent antimicrobial and cytotoxic bioactivity. The experimental data and analysis presented in this study contribute to the knowledge of genome mining analysis in rare actinobacteria and, most importantly, can serve to direct sampling efforts to accelerate early stages of the drug discovery pipeline.

Phylogenetic classification of natural product biosynthetic gene clusters based on regulatory mechanisms.

The natural products (NPs) biosynthetic gene clusters (BGCs) represent the adapting biochemical toolkit for microorganisms to thrive different microenvironments. Despite their high diversity, particularly at the genomic level, detecting them in a shake-flask is challenging and remains the primary obstacle limiting our access to valuable chemicals. Studying the molecular mechanisms that regulate BGC expression is crucial to design of artificial conditions that derive on their expression. Here, we propose a phylogenetic analysis of regulatory elements linked to biosynthesis gene clusters, to classify BGCs to regulatory mechanisms based on protein domain information. We utilized Hidden Markov Models from the Pfam database to retrieve regulatory elements, such as histidine kinases and transcription factors, from BGCs in the MIBiG database, focusing on actinobacterial strains from three distinct environments: oligotrophic basins, rainforests, and marine environments. Despite the environmental variations, our isolated microorganisms share similar regulatory mechanisms, suggesting the potential to activate new BGCs using activators known to affect previously characterized BGCs.