Abrupt permafrost thaw triggers activity of copiotrophs and microbiome predators

Abstract

Permafrost soils store a substantial part of the global soil carbon and nitrogen. However, global warming causes abrupt erosion and gradual thaw, which make these stocks vulnerable to microbial decomposition into greenhouse gases. Here, we investigated the microbial response to abrupt in situ permafrost thaw. We sequenced the total RNA of a 1 m deep soil core consisting of up to 26′500-year-old permafrost material from an active abrupt erosion site. We analysed the microbial community in the active layer soil, the recently thawed, and the intact permafrost, and found maximum RNA: DNA ratios in recently thawed permafrost indicating a high microbial activity. In thawed permafrost, potentially copiotrophic Burkholderiales and Sphingobacteriales, but also microbiome predators dominated the community. Overall, both thaw-dependent and long-term soil properties significantly correlated with changes in community composition, as did microbiome predator abundance. Bacterial predators were dominated in shallower depths by Myxococcota, while protozoa, especially Cercozoa and Ciliophora, almost tripled in relative abundance in thawed layers. Our findings highlight the ecological importance of a diverse inter-kingdom and active microbial community highly abundant in abruptly thawing permafrost, as well as predation as potential biological control mechanism.

Investigating eukaryotic and prokaryotic diversity and functional potential in the cold and alkaline ikaite columns in Greenland

“…Demultiplexed raw reads from Illumina metagenome sequencing were run through the in-house TotalRNA bioinformatics pipeline v1.1.0 2 in order to trim the reads, perform quality control and assemble full-length rRNA genes. Information about program versions and flags are presented in detail on the Github page and on recent publications ( Jaarsma et al, 2023 ; Scheel et al, 2023 ). Briefly, trimmed reads were sorted into a “Small Subunit” Pool with SortMeRNA ( Kopylova et al, 2012 ) and the SILVA 138.1 SSU Ref NR 99 database, before being assembled in full-length rRNA contigs using MetaRib ( Xue et al, 2020 ) and taxonomically classified with CREST4 ( Lanzen et al, 2012 ) as described elsewhere ( Anwar et al, 2019 ).…”