Uncovering Methane Sink Potential and Habitat Preferences of Methanotrophs in Denmark

Methane is a potent greenhouse gas with a global warming potential 80 times higher than CO2 on a 20-year time scale. Mitigation of methane is essential to limit increase in global surface temperatures below the critical threshold of 1.5-2°C. To address this issue, it is essential to understand the diversity and biogeography of methanotrophs, the microorganisms responsible for lowering emissions by oxidising methane. The current understanding of methanotrophs relies largely on isolates. Considering the diversity discovered within the functional genes for methane oxidation, it is evident that several groups have not yet been described, lacking both isolates and genome representatives. This is especially the case for atmospheric methane oxidisers, being of particular interest from a methane mitigation perspective. Historically, methanotrophs have been identified by the marker genes pmoA and mmoX, encoding two isoforms of methane monooxygenase. However, pmoA and mmoX share sequence similarity to monooxygenases oxidising non-methane compounds. This complicates identification based solely on marker genes and requires detailed information on gene phylogeny and metabolic potential. Furthermore, methanotrophs display species-level variation in substrate affinity and pathways employed for assimilation of compounds such as carbon, nitrogen, and sulphur. Defining the core genome within novel species and investigating the ecological relevance of the accessory genome could prove pivotal in understanding this important group of GHG-mitigators. A comprehensive dataset of 10,000 Danish shallow metagenomes (the Microflora Danica project) has set the stage for selecting soil samples for long-read sequencing, based on the presence of methanotrophy marker genes. We managed to populate poorly described parts of the methanotroph tree of life with HQ MAGs, including, but not restricted to novel species of atmospheric methane oxidisers. In combination with the extensive dataset of 10,000 shallow metagenomes, we aim to establish an association between novel methanotrophs, genomic variation, habitat preferences, and geographical distribution on a national scale.