Long-term enriched methanogenic communities from thermokarst lake sediments show species-specific responses to warming

Abstract

Thermokarst lakes are large potential greenhouse gas (GHG) sources in a changing Arctic. In a warming world, an increase in both organic matter availability and temperature is expected to boost methanogenesis and potentially alter the microbial community that controls GHG fluxes. These community shifts are, however, challenging to detect by resolution-limited 16S rRNA gene-based approaches. Here, we applied full metagenome sequencing on long-term thermokarst lake sediment enrichments on acetate and trimethylamine at 4°C and 10°C to unravel species-specific responses to the most likely Arctic climate change scenario. Substrate amendment was used to mimic the increased organic carbon availability upon permafrost thaw. By performing de novo assembly, we reconstructed five high-quality and five medium-quality metagenome-assembled genomes (MAGs) that represented 59% of the aligned metagenome reads. Seven bacterial MAGs belonged to anaerobic fermentative bacteria. Within the Archaea, the enrichment of methanogenic Methanosaetaceae/Methanotrichaceae under acetate amendment and Methanosarcinaceae under trimethylamine (TMA) amendment was not unexpected. Surprisingly, we observed temperature-specific methanogenic (sub)species responses with TMA amendment. These highlighted distinct and potentially functional climate-induced shifts could not be revealed with 16S rRNA gene-based analyses. Unraveling these temperature- and nutrient-controlled species-level responses is essential to better comprehend the mechanisms that underlie GHG production from Arctic lakes in a warming world.

Keywords: Arctic; global warming; methane; methanogens; permafrost; thermokarst lakes.

Figure 1.

Taxonomic distribution of archaeal 16S rRNA gene reads obtained from metagenomic datasets of methanogenic incubations with acetate, TMA and control at 4°C and 10°C. A total of 0.12% of reads were identified as 16S rRNA gene-containing sequences. The group ‘Others’ includes all taxonomic groups with a relative abundance <1% within the sample. Taxonomic identification is given up to family level. The Y-axis displays the relative abundance with 100% being the sum of metagenome-derived archaeal and bacterial 16S rRNA gene reads per sample, including non-classified reads (≤5%).

Figure 2.

Taxonomic distribution of bacterial 16S rRNA gene reads obtained from metagenomic datasets from methanogenic incubations with acetate, TMA and control incubations at 4°C and 10°C. A total of 0.12% of reads were identified as 16S rRNA gene-containing sequences. All taxonomic groups have a relative abundance of ≥1%. The group ‘Others’ includes all taxonomic groups with a relative abundance <1%. Taxonomic identification is given up to order level. The Y-axis displays the relative abundance with 100% being the sum of metagenome-derived archaeal and bacterial 16S rRNA gene reads per sample, including non-classified reads (≤5%).

Figure 3.

OrthoVenn2 diagram displaying orthologous gene clusters shared between the methanogen MAGs. The unique numbers in each circle display the singletons and between brackets paralogous gene clusters.