bioRxiv Science⌕ Search

Biology subjects

Hilts, A. S.

Publications and source records attributed to Hilts, A. S..

2 recordsLinked to original sources

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

Microorganisms are key players in the global cycling of nitrogen (N) and carbon (C), controlling their availability and fluxes, including the emissions of the powerful greenhouse gases nitrous oxide (N2O) and methane (CH4). Characterizing the microbial functional guilds driving these processes is crucial for understanding ecosystem functioning and predicting their responses to environmental changes. Standard sequence-based characterization methods often reveal only a limited fraction of their diversity in nature because of their low relative abundance, the insufficient sequencing depth of traditional metagenomes of complex communities, and limitations in coverage of PCR-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 N and CH4 cycling. We designed comprehensive probe libraries for each of the 14 target marker genes comprising 264,000 unique probes. These probes were used to selectively enrich the target genes in shotgun metagenomic libraries. In validation experiments with the mock communities of known microorganisms, targeted metagenomics yielded gene profiles similar to those of 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 from agricultural and wetland soils were significantly correlated, indicating that the targeted approach did not introduce significant quantitative bias. In addition, using archaeal amoA genes as a case-study, targeted metagenomics identified 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. Notably, shotgun metagenomics detected only three out of the 84 amoA gene phylotypes detected using targeted metagenomics. 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. Manuscript contribution to the fieldMetagenomic sequencing often yields limited numbers of sequences of rare microbial taxa or functional genes, preventing in-depth analyses of specific populations and functional groups. Amplicon-based approaches enable the higher diversity coverage of target populations, but the drawback is the difficulty in designing unbiased primers that cover the highest intra-group diversity. Targeted metagenomics overcomes these challenges and results in similar community structure as traditional amplicon sequencing, while expanding the sequence space in a less biased metagenomic-based approach. Therefore, targeted metagenomics is an invaluable tool for studying the diversity of specific populations within complex natural microbiomes. Here, we present and evaluate a probe library designed for targeted metagenomics of nitrogen and methane cycling genes in complex communities.

microbiology↗

Adapting macroecology to microbiology: using occupancy modelling to assess functional profiles across metagenomes

Metagenomic sequencing provides information on the metabolic capacities and taxonomic affiliations for members of a microbial community. When assessing metabolic functions in a community, missing genes in pathways can occur in two ways: the genes may legitimately be missing from the community whose DNA was sequenced, or the genes were missed during shotgun sequencing or failed to assemble, and thus the metabolic capacity of interest is wrongly absent from the sequence data. Here, we borrow and adapt occupancy modelling from macroecology to provide mathematical context to metabolic predictions from metagenomes. We review the five assumptions underlying occupancy modelling through the lens of microbial community sequence data. Using the methane cycle, we apply occupancy modelling to examine the presence and absence of methanogenesis and methanotrophy genes from nearly 10,000 metagenomes spanning global environments. We determine that methanogenesis and methanotrophy are positively correlated across environments, and note that the lack of available standardized metadata for most metagenomes is a significant hindrance to large-scale statistical analyses. We present this adaptation of macroecologys occupancy modelling to metagenomics as a tool for assessing presence/absence of traits in environmental microbiological surveys. We further initiate a call for stronger metadata standards to accompany metagenome deposition, to enable robust statistical approaches in the future.

microbiology↗