Targeted metagenomics using probe capture detect a larger diversity of nitrogen and methane cycling genes in complex microbial communities than traditional metagenomics.

Siljanen HMP, Manoharan L, Hilts AS, Bagnoud A, Alves RJE, Jones CM, Kerou M, Sousa FL, Hallin S, Biasi C, Schleper C

ISME COMMUN. 5 (1) ycaf183 [2025-01-00; online 2025-11-01]

Microorganisms are key players in the global cycling of nitrogen and carbon, controlling their availability and fluxes, including the emissions of the powerful greenhouse gases nitrous oxide and methane. Standard sequencing methods often reveal only a limited fraction of their diversity, because of their low relative abundance, the insufficient sequencing depth of traditional metagenomes of complex communities, and limitations in coverage of DNA amplification-based assays. Here, we developed and tested a targeted metagenomics approach based on probe capture and hybridization to simultaneously characterize the diversity of multiple key metabolic genes involved in inorganic nitrogen and methane cycling. We designed comprehensive probe libraries for each of the 14 target marker genes comprising 264 111 unique probes. In validation experiments with mock communities, targeted metagenomics yielded gene profiles similar to the original communities. Only GC content had a small effect on probe efficiency, as low GC targets were less efficiently detected than those with high GC, within the mock communities. Furthermore, the relative abundances of the marker genes obtained using targeted or traditional shotgun metagenomics were significantly correlated. In addition, using archaeal amoA genes as a case-study, targeted metagenomics identified a substantially higher taxonomic diversity and a larger number of sequence reads per sample, yielding diversity estimates 28 or 1.24 times higher than shotgun metagenomics or amplicon sequencing, respectively. Our results show that targeted metagenomics complements current approaches to characterize key microbial populations and functional guilds in biogeochemical cycles in different ecosystems, enabling more detailed, simultaneous characterization of multiple functional genes.

Bioinformatics (NBIS) [Collaborative]

Bioinformatics Support and Infrastructure [Collaborative]

Bioinformatics Support, Infrastructure and Training [Collaborative]

PubMed 41221508

DOI 10.1093/ismeco/ycaf183

Crossref 10.1093/ismeco/ycaf183

pmc: PMC12598625
pii: ycaf183