Long-Read Metagenomics of Marine Microbes Reveals Diversely Expressed Secondary Metabolites.

Abstract

Microbial secondary metabolites play crucial roles in microbial competition, communication, resource acquisition, antibiotic production, and a variety of other biotechnological processes. The retrieval of full-length BGC (biosynthetic gene cluster) sequences from uncultivated bacteria is difficult due to the technical constraints of short-read sequencing, making it impossible to determine BGC diversity. Using long-read sequencing and genome mining, 339 mainly full-length BGCs were recovered in this study, illuminating the wide range of BGCs from uncultivated lineages discovered in seawater from Aoshan Bay, Yellow Sea, China. Many extremely diverse BGCs were discovered in bacterial phyla such as Proteobacteria, Bacteroidota, Acidobacteriota, and Verrucomicrobiota as well as the previously uncultured archaeal phylum "Candidatus Thermoplasmatota." The data from metatranscriptomics showed that 30.1% of secondary metabolic genes were being expressed, and they also revealed the expression pattern of BGC core biosynthetic genes and tailoring enzymes. Taken together, our results demonstrate that long-read metagenomic sequencing combined with metatranscriptomic analysis provides a direct view into the functional expression of BGCs in environmental processes. IMPORTANCE Genome mining of metagenomic data has become the preferred method for the bioprospecting of novel compounds by cataloguing secondary metabolite potential. However, the accurate detection of BGCs requires unfragmented genomic assemblies, which have been technically difficult to obtain from metagenomes until recently with new long-read technologies. We used high-quality metagenome-assembled genomes generated from long-read data to determine the biosynthetic potential of microbes found in the surface water of the Yellow Sea. We recovered 339 highly diverse and mostly full-length BGCs from largely uncultured and underexplored bacterial and archaeal phyla. Additionally, we present long-read metagenomic sequencing combined with metatranscriptomic analysis as a potential method for gaining access to the largely underutilized genetic reservoir of specialized metabolite gene clusters in the majority of microbes that are not cultured. The combination of long-read metagenomic and metatranscriptomic analyses is significant because it can more accurately assess the mechanisms of microbial adaptation to the environment through BGC expression based on metatranscriptomic data.