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Connecting structure to function with the recovery of over 1000 high-quality metagenome-assembled genomes from activated sludge using long-read sequencing.

ABSTRACT: Microorganisms play crucial roles in water recycling, pollution removal and resource recovery in the wastewater industry. The structure of these microbial communities is increasingly understood based on 16S rRNA amplicon sequencing data. However, such data cannot be linked to functional potential in the absence of high-quality metagenome-assembled genomes (MAGs) for nearly all species. Here, we use long-read and short-read sequencing to recover 1083 high-quality MAGs, including 57 closed circular genomes, from 23 Danish full-scale wastewater treatment plants. The MAGs account for ~30% of the community based on relative abundance, and meet the stringent MIMAG high-quality draft requirements including full-length rRNA genes. We use the information provided by these MAGs in combination with >13 years of 16S rRNA amplicon sequencing data, as well as Raman microspectroscopy and fluorescence in situ hybridisation, to uncover abundant undescribed lineages belonging to important functional groups.

SUBMITTER: Singleton CM

PROVIDER: S-EPMC8012365 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Microorganisms produce a wide variety of secondary/specialized metabolites (SMs), the majority of which are yet to be discovered. These natural products play multiple roles in microbiomes and are important for microbial competition, communication, and success in the environment. SMs have been our major source of antibiotics and are used in a range of biotechnological applications. In silico mining for biosynthetic gene clusters (BGCs) encoding the production of SMs is commonly used to assess the genetic potential of organisms. However, as BGCs span tens to over 200 kb, identifying complete BGCs requires genome data that has minimal assembly gaps within the BGCs, a prerequisite that was previously only met by individually sequenced genomes. Here, we assess the performance of the currently available genome mining platform antiSMASH on 1,080 high-quality metagenome-assembled bacterial genomes (HQ MAGs) previously produced from wastewater treatment plants (WWTPs) using a combination of long-read (Oxford Nanopore) and short-read (Illumina) sequencing technologies. More than 4,200 different BGCs were identified, with 88% of these being complete. Sequence similarity clustering of the BGCs implies that the majority of this biosynthetic potential likely encodes novel compounds, and few BGCs are shared between genera. We identify BGCs in abundant and functionally relevant genera in WWTPs, suggesting a role of secondary metabolism in this ecosystem. We find that the assembly of HQ MAGs using long-read sequencing is vital to explore the genetic potential for SM production among the uncultured members of microbial communities. IMPORTANCE Cataloguing secondary metabolite (SM) potential using genome mining of metagenomic data has become the method of choice in bioprospecting for novel compounds. However, accurate biosynthetic gene cluster (BGC) detection requires unfragmented genomic assemblies, which have been technically difficult to obtain from metagenomes until very recently with new long-read technologies. Here, we determined the biosynthetic potential of activated sludge (AS), the microbial community used in resource recovery and wastewater treatment, by mining high-quality metagenome-assembled genomes generated from long-read data. We found over 4,000 BGCs, including BGCs in abundant process-critical bacteria, with no similarity to the BGCs of characterized products. We show how long-read MAGs are required to confidently assemble complete BGCs, and we determined that the AS BGCs from different studies have very little overlap, suggesting that AS is a rich source of biosynthetic potential and new bioactive compounds.

Dataset Information

Connecting structure to function with the recovery of over 1000 high-quality metagenome-assembled genomes from activated sludge using long-read sequencing.

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