Investigating the biosynthetic potential of an Antarctic soil through metagenomics, cultivation, and heterologous expression

The growing problem of antibiotic resistance has led to the exploration of uncultured bacteria as sources of new antimicrobials. Metagenomic sequencing studies of samples from different environments have reported evidence of high biosynthetic gene cluster (BGC) diversity in metagenomes, and metagenomic library studies have yielded several novel natural products. However, accessing these compounds remains challenging. The constraints of short-read sequencing mean that the assembly of full-length BGC sequences from uncultured bacteria is nigh impossible, thus making assessment of BGC diversity difficult and downstream cloning infeasible. Conversely, metagenomic library approaches suffer from a bias towards known compounds as well as difficulties with expressing recovered BGCs. In the present work, a three-pronged approach was taken to access the biosynthetic diversity of bacteria from an Antarctic soil: A hybrid shotgun metagenome was sequenced and BGCs cloned and expressed, a novel regulatory gene-based screen for libraries was developed, and a number of isolates were obtained by culturing. Through metagenomic sequencing, many highly divergent BGCs were found in phyla such as Acidobacteriota and Verrucomicrobiota, but also the methanotrophic gammaproteobacterial order UBA7966. Sequencing of isolates obtained from the same soil indicated little overlap between the biosynthetic potential of readily cultured and uncultured bacteria. Several metagenomic BGCs were PCR-amplified, cloned and expressed in Pseudomonas and Streptomyces. While the sequencing of Streptomyces exconjugants showed that many inserts were truncated, a phenotype was observed in Pseudomonas. The library screening approach was validated in isolates, but the targets were absent in the metagenomic library used. In conclusion, the results uncover the rich diversity of BGCs from uncultured lineages present in the soil, show the potential of long-read sequencing to recover full-length BGCs from uncultured soil bacteria and demonstrate the feasibility of cloning them. However, they also indicate the necessity of refined molecular tools for successful heterologous expression of metagenomic BGCs

Biosynthetic potential of uncultured Antarctic soil bacteria revealed through long-read metagenomic sequencing

The growing problem of antibiotic resistance has led to the exploration of uncultured bacteria as potential sources of new antimicrobials. PCR amplicon analyses and short-read sequencing studies of samples from different environments have reported evidence of high biosynthetic gene cluster (BGC) diversity in metagenomes, indicating their potential for producing novel and useful compounds. However, recovering full-length BGC sequences from uncultivated bacteria remains a challenge due to the technological restraints of short-read sequencing, thus making assessment of BGC diversity difficult. Here, long-read sequencing and genome mining were used to recover >1400 mostly full-length BGCs that demonstrate the rich diversity of BGCs from uncultivated lineages present in soil from Mars Oasis, Antarctica. A large number of highly divergent BGCs were not only found in the phyla Acidobacteriota, Verrucomicrobiota and Gemmatimonadota but also in the actinobacterial classes Acidimicrobiia and Thermoleophilia and the gammaproteobacterial order UBA7966. The latter furthermore contained a potential novel family of RiPPs. Our findings underline the biosynthetic potential of underexplored phyla as well as unexplored lineages within seemingly well-studied producer phyla. They also showcase long-read metagenomic sequencing as a promising way to access the untapped genetic reservoir of specialised metabolite gene clusters of the uncultured majority of microbes

N-acetyl-cysteinylated streptophenazines from Streptomyces

Here, we describe two N-acetyl-cysteinylated streptophenazines (1 and 2) produced by the soil-derived Streptomyces sp. ID63040 and identified through a metabolomic approach. These metabolites attracted our interest due to their low occurrence frequency in a large library of fermentation broth extracts and their consistent presence in biological replicates of the producer strain. The compounds were found to possess broad-spectrum antibacterial activity while exhibiting low cytotoxicity. The biosynthetic gene cluster from Streptomyces sp. ID63040 was found to be highly similar to the streptophenazine reference cluster in the MIBiG database, which originates from the marine Streptomyces sp. CNB-091. Compounds 1 and 2 were the main streptophenazine products from Streptomyces sp. ID63040 at all cultivation times but were not detected in Streptomyces sp. CNB-091. The lack of obvious candidates for cysteinylation in the Streptomyces sp. ID63040 biosynthetic gene cluster suggests that the N-acetyl-cysteine moiety derives from cellular functions, most likely from mycothiol. Overall, our data represent an interesting example of how to leverage metabolomics for the discovery of new natural products and point out the often-neglected contribution of house-keeping cellular functions to natural product diversification

MIBiG 3.0 : a community-driven effort to annotate experimentally validated biosynthetic gene clusters

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/