Microbial genomics amidst the Arctic crisis

Abstract

The Arctic is warming - fast. Microbes in the Arctic play pivotal roles in feedbacks that magnify the impacts of Arctic change. Understanding the genome evolution, diversity and dynamics of Arctic microbes can provide insights relevant for both fundamental microbiology and interdisciplinary Arctic science. Within this synthesis, we highlight four key areas where genomic insights to the microbial dimensions of Arctic change are urgently required: the changing Arctic Ocean, greenhouse gas release from the thawing permafrost, 'biological darkening' of glacial surfaces, and human activities within the Arctic. Furthermore, we identify four principal challenges that provide opportunities for timely innovation in Arctic microbial genomics. These range from insufficient genomic data to develop unifying concepts or model organisms for Arctic microbiology to challenges in gaining authentic insights to the structure and function of low-biomass microbiota and integration of data on the causes and consequences of microbial feedbacks across scales. We contend that our insights to date on the genomics of Arctic microbes are limited in these key areas, and we identify priorities and new ways of working to help ensure microbial genomics is in the vanguard of the scientific response to the Arctic crisis.

Keywords: Arctic; climate change; microbial genomics; psychrophiles.

Fig. 1.

Ice-cold hot-spots of microbial change within the warming Arctic. The images demonstrate: a controlled release of methane-saturated groundwater from High Arctic permafrost (a); first year sea ice in winter (b); a marine-terminating glacier meeting open water in a High Arctic fjord in winter (c); cruise ship visitors at Ny Ålesund, a Svalbard settlement used for coal mining and scientific research for over a century (d); glacier algae growth and cryoconite accumulation in the Dark Zone of the Greenland Ice Sheet (e). All photographs are from the personal collection of A. Edwards.

Fig. 2.

Neighbour-joining tree of partial 16S rRNA gene sequences from isolates in culture from Arctic habitats that are also reported [169] as frequently occurring contaminants in sequenced negative controls. The tree comprises 52 alignable sequences from the 56 available isolate sequences drawn from the 92 genera named in table 1 of the paper by Salter et al. [169]. All seven of the groups with named genera listed by Salter et al. [169] are represented in cultures from Arctic environments. Actinobacteria , red; Alphaproteobacteria , blue; Betaproteobacteria , purple; Gammaproteobacteria , brown; Firmicutes , pink; Deinococcus - Thermus , green; and Bacteroidetes, gold. Scale shows nucleotide substitutions per site.

Fig. 3.

Example of in-field DNA sequencing and analysis. Working in a remote field camp on the Greenland Ice Sheet during the Arctic winter (a), it was possible to extract nucleic acids and sequence them in ambient temperatures of circa −20 °C by using freeze-dried reagents and adapted protocols for nanopore sequencing (b). In situ data processing and analysis (c) permitted a refined experimental strategy (d) for genome-centred metagenomic comparison of glacial habitats (e). Images (a) and (b) by J. M. Cook; images (c) and (d) by A. Edwards. Image (e) is representative of unpublished data from A. Edwards, M. C. Hay and J. M. Cook.

Fig. 4.

Arctic genomes across scales. Many critical processes [e.g. greenhouse gas (GHG) cycling] mediated by Arctic microbiota occur within environments that are extremely heterogeneous at the microscopic scale (a). In particular, these include interstitial spaces in otherwise frozen substrates (e.g. sea ice, permafrost, glacial ice) where micro-scale gradients in biomass or physical and chemical conditions are apparent. These are disrupted at the sample scale (b) by the requirement to collect sufficient biomass for (meta-) genomic analysis and the distortion incurred by bulk chemical analyses of substrates. At the plot scale (c), undersampling of spatial heterogeneity at the meso-scale poses a further challenge. Finally, upscaling to the landscape or regional scale from plot-scale studies (d) is hampered by spatial and temporal biases in sampling.

Fig. 5.

Arctic microbial genomics will require the fusion of improved reference data and the real-time capture of microbial drivers and responses to changes in the 21st century Arctic. WGA: Whole Genome Amplification.