Taxonomic and metabolic diversity of Actinomycetota isolated from faeces of a 28,000-year-old mammoth.

Ancient environmental samples, including permafrost soils and frozen animal remains, represent an archive with microbial communities that have barely been explored. This yet unexplored microbial world is a genetic resource that may provide us with new evolutionary insights into recent genomic changes, as well as novel metabolic pathways and chemistry. Here, we describe Actinomycetota Micromonospora, Oerskovia, Saccharopolyspora, Sanguibacter and Streptomyces species were successfully revived and their genome sequences resolved. Surprisingly, the genomes of these bacteria from an ancient source show a large phylogenetic distance to known strains and harbour many novel biosynthetic gene clusters that may well represent uncharacterised biosynthetic potential. Metabolic profiles of the strains display the production of known molecules like antimycin, conglobatin and macrotetrolides, but the majority of the mass features could not be dereplicated. Our work provides insights into Actinomycetota isolated from an ancient source, yielding unexplored genomic information that is not yet present in current databases.

nanoRAPIDS as an analytical pipeline for the discovery of novel bioactive metabolites in complex culture extracts at the nanoscale.

Microbial natural products form the basis of most of the antibiotics used in the clinic. The vast majority has not yet been discovered, among others because the hidden chemical space is obscured by previously identified (and typically abundant) antibiotics in culture extracts. Efficient dereplication is therefore key to the discovery of our future medicines. Here we present an analytical platform for the efficient identification and prioritization of low abundance bioactive compounds at nanoliter scale, called nanoRAPIDS. NanoRAPIDS encompasses analytical scale separation and nanofractionation of natural extracts, followed by the bioassay of interest, automated mass spectrometry identification, and Global Natural Products Social molecular networking (GNPS) for dereplication. As little as 10 µL crude extract is fractionated into 384 fractions. First, bioactive congeners of iturins and surfactins were identified in Bacillus, based on their bioactivity. Subsequently, bioactive molecules were identified in an extensive network of angucyclines elicited by catechol in cultures of Streptomyces sp. This allowed the discovery of a highly unusual N-acetylcysteine conjugate of saquayamycin, despite low production levels in an otherwise abundant molecular family. These data underline the utility and broad application of the technology for the prioritization of minor bioactive compounds in complex extracts.

Artificial intelligence for natural product drug discovery.

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation.

The ubiquitous catechol moiety elicits siderophore and angucycline production in Streptomyces.

Actinobacteria are a rich source of bioactive molecules, and genome sequencing has shown that the vast majority of their biosynthetic potential has yet to be explored. However, many of their biosynthetic gene clusters (BGCs) are poorly expressed in the laboratory, which prevents discovery of their cognate natural products. To exploit their full biosynthetic potential, better understanding of the signals that promote the expression of BGCs is needed. Here, we show that the human stress hormone epinephrine (adrenaline) elicits siderophore production by Actinobacteria. Catechol was established as the likely eliciting moiety, since similar responses were seen for catechol and for the catechol-containing molecules dopamine and catechin but not for related molecules. Exploration of the catechol-responsive strain Streptomyces sp. MBT84 using mass spectral networking revealed elicitation of a BGC that produces the angucycline glycosides aquayamycin, urdamycinone B and galtamycin C. Heterologous expression of the catechol-cleaving enzymes catechol 1,2-dioxygenase or catechol 2,3-dioxygenase counteracted the eliciting effect of catechol. Thus, our work identifies the ubiquitous catechol moiety as a novel elicitor of the expression of BGCs for specialized metabolites.

Ecology and genomics of Actinobacteria: new concepts for natural product discovery.

Actinobacteria constitute a highly diverse bacterial phylum with an unrivalled metabolic versatility. They produce most of the clinically used antibiotics and a plethora of other natural products with medical or agricultural applications. Modern 'omics'-based technologies have revealed that the genomic potential of Actinobacteria greatly outmatches the known chemical space. In this Review, we argue that combining insights into actinobacterial ecology with state-of-the-art computational approaches holds great promise to unlock this unexplored reservoir of actinobacterial metabolism. This enables the identification of small molecules and other stimuli that elicit the induction of poorly expressed biosynthetic gene clusters, which should help reinvigorate screening efforts for their precious bioactive natural products.