Comparative metagenomics of two shallow marine microbial communities in western Greenland

Daniel G. Dick

doi:10.33265/polar.v45.12710

Daniel G. Dick School of Earth, Environment & Society, McMaster University, Hamilton, ON, Canada

DOI: https://doi.org/10.33265/polar.v45.12710

Keywords: Psychrophiles, sea ice, Sisimiut, Ilulissat, eDNA, chemolithotrophic taxa, ice-associated bacteria

Abstract

Metagenomic profiles of marine microbial communities from Greenlandic coastal waters remain scarce, despite the central role played by this region in discussions of global climate change. This study characterizes the taxonomic and functional structure of two near-shore shallow marine fjord mouth microbial communities from sites in western Greenland that differ in sea-surface temperatures, mean annual ice-coverage levels and annual glacial meltwater flux rates. Results indicate limited taxonomic and functional overlap between these two locations, with significant differences in the normalized abundance of 3372 species (25% of observed taxa) and 620 functional genes (49% of functional genes observed). At Sisimiut, a typical open-water “Baffin Bay” site characterized by moderate sea-surface temperatures, minimal annual sea-ice cover and limited glacial input, the metagenome is dominated by diverse chemolithotrophic taxa, including sulphate-reducing, nitrogen-fixing and methanogenic lineages. At the Ilulissat Icefjord, where low sea-surface temperatures, high turbidity, low salinity and strong glacial influences prevail, the community is less diverse and is dominated by psychrophilic (cold-adapted) bacteria such as Colwellia hornerae PAMC 20917. Functional profiles further distinguish these sites: the Ilulissat metagenome is enriched in genes common to ice-associated and cold-adapted metabolisms (e.g., exopolysaccharide biosynthesis, dimethyl-sulphide and dimethylsulfoniopropionate cycling), whereas these genes are comparatively rare at Sisimiut. Together, these data sets provide a descriptive baseline for these two sites and a framework for future comparative studies in the region.

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References

Anderson M.J. 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecology 26, 32–46, doi: 10.1111/j.1442-9993.2001.01070.pp.x.

Avcı B., Hahnke R.L., Chafee M., Fischer T., Gruber-Vodicka H., Tegetmeyer H.E., Harder J., Fuchs B.M., Amann R.I. & Teeling H. 2016. Genomic and physiological analyses of “Reinekea forsetii” reveal a versatile opportunistic lifestyle during spring algae blooms. Environmental Microbiology 19, 1209–1221, doi: 10.1111/1462-2920.13646.

Baker M.R. 2021. Contrast of warm and cold phases in the Bering Sea to understand spatial distributions of Arctic and sub-Arctic gadids. Polar Biology 44, 1083–1105, doi: 10.1007/s00300-021-02856-x.

Boetius A., Anesio A.M., Deming J.W., Mikucki J.A. & Rapp J.Z. 2015. Microbial ecology of the cryosphere: sea ice and glacial habitats. Nature Reviews Microbiology 13, 677–690, doi: 10.1038/nrmicro3522.

Bolger A.M., Lohse M. & Usadel B. (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120, doi: 10.1093/bioinformatics/btu170.

Bowman J.S. 2015. The relationship between sea ice bacterial community structure and biogeochemistry: a synthesis of current knowledge and known unknowns. Elementa: Science of the Anthropocene 3, article no. 000072, doi: 10.12952/journal.elementa.000072.

Bray J.R. & Curtis J.T. 1957. An ordination of the upland forest communities of southern Wisconsin. Ecological Monographs 27, 326–349, doi: 10.2307/1942268.

Buongiorno J., Herbert L.C., Wehrmann L.M., Michaud A.B., Laufer K., Røy H., Jørgensen B.B., Szynkiewicz A., Faiia A., Yeager K.M., Schindler K. & Lloyd K.G. 2019. Complex microbial communities drive iron and sulfur cycling in Arctic fjord sediments. Applied and Environmental Microbiology 84, e00949-19, doi: 10.1128/AEM.00949-19.

Clarke E.L., Taylor L.J., Zhao C., Connell A., Lee J.-J., Fett B., Bushman F.D. & Bittinger K. 2019. Sunbeam: an extensible pipeline for analyzing metagenomic sequencing experiments. Microbiome 7, article no. 46, doi: 10.1186/s40168-019-0658-x.

CMEMS (Copernicus Marine Environment Monitoring Service) no date a. Copernicus Global Ocean Colour (Copernicus-GlobColour), Bio-Geo-Chemical, L4 (monthly and interpolated) from Satellite Observations (1997-ongoing). Copernicus Marine Service Information. Marine Data Store, doi: 10.48670/moi-00281. Accessed on the internet at https://data.marine.copernicus.eu/product/OCEANCOLOUR_GLO_BGC_L4_MY_009_104/description on 31 July 2025.

CMEMS (Copernicus Marine Environment Monitoring Service) no date b. Copernicus Global Ocean Physics Analysis and Forecast. E.U. Copernicus Marine Service Information. Marine Data Store, doi: 10.48670/moi-00016. Accessed on the internet at https://data.marine.copernicus.eu/product/GLOBAL_ANALYSISFORECAST_PHY_001_024/description on 31 July 2025.

Eronen-Rasimus E., Luhtanen A.-M., Rintala J.-M., Delille B., Dieckmann G., Karkman A. & Tison J.-L. 2017. An active bacterial community linked to high chl-a concentrations in Antarctic winter-pack ice and evidence for the development of an anaerobic sea-ice bacterial community. The ISME Journal 11, 2345–2355, doi: 10.1038/ismej.2017.96.

Freer J.J., Daase M. & Tarling G.A. 2021. Modelling the biogeographic boundary shift of Calanus finmarchicus reveals drivers of Arctic Atlantification by subarctic zooplankton. Global Change Biology 28, 429–440, doi: 10.1111/gcb.15937.

Gladish C.V., Holland D.M., Rosing-Asvid A., Behrens J.W. & Boje J. 2015. Oceanic boundary conditions for Jakobshavn Glacier. Part I: variability and renewal of Ilulissat Icefjord waters, 2001-14. Journal of Physical Oceanography 45, 3–32, doi: 10.1175/JPO-D-14-0044.1.

Glombitza C., Jaussi M., Røy H., Seidenkrantz M.-S., Lomstein B.A. & Jørgensen B.B. 2015. Formate, acetate, and propionate as substrates for sulfate reduction in sub-Arctic sediments of southwest Greenland. Frontiers in Microbiology 6, article no. 846, doi: 10.3389/fmicb.2015.00846.

Good S., Fiedler E., Mao C., Martin M.J., Maycock A., Reid R., Roberts-Jones J., Searle T., Waters J., While J. & Worsfold M. 2020. The current configuration of the OSTIA System for Operational Production of Foundation Sea Surface Temperature and Ice Concentration Analyses. Remote Sensing 12, article no. 720, doi: 10.3390/rs12040720.

Heide-Jørgensen M.P., Laidre K.L., Logsdon M.L. & Nielsen T.G. 2007. Springtime coupling between chlorophyll a, sea ice and sea surface temperature in Disko Bay, west Greenland. Progress in Oceanography 73, 79–95, doi: 10.1016/j.pocean.2007.01.006.

Hutchins D.A. & Fu F. 2017. Microorganisms and ocean global change. Nature Microbiology 2, article no. 17058, doi: 10.1038/nmicrobiol.2017.58.

Kim H., Park A.K., Lee J.H., Kim H.-W. & Shin S.C. 2018. Complete genome sequence of Colwellia hornerae PAMC 20917, a cold-active enzyme-producing bacterium isolated from the Arctic Ocean sediment. Marine Genomics 41, 54–56, doi: 10.1016/j.margen.2018.03.004.

Kleindienst S., Herbst F.-A., Stagars M., von Netzer F., von Bergen M., Seifert J., Peplies J., Amann R., Musat F., Lueders T. & Knittel K. 2014. Diverse sulfate-reducing bacteria of the Desulfosarcina/Desulfococcus clade are the key alkane degraders at marine seeps. The ISME Journal 10, 2029–2044, doi: 10.1038/ismej.2014.51.

Kruskal W.H. & Wallis W.A. 1952. Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association 47, 583–621, doi: 10.1080/01621459.1952.10483441.

Lauritano C., Rizzo C., Lo Giudice A. & Saggiomo M. 2020. Physiological and molecular responses to main environmental stressors of microalgae and bacteria in polar marine environments. Microorganisms 8, article no. 1957, doi: 10.3390/microorganisms8121957.

Lenoir J. & Svenning J.-C. 2015. Climate-related range shifts—a global multidimensional synthesis and new research directions. Ecography 38, 15–28, doi: 10.1111/ecog.00967.

Love M.I., Huber W. & Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 15, article no. 550, doi: 10.1186/s13059-014-0550-8.

Maccario L., Carpenter S.D., Deming J.W., Vogel T.M. & Larose C. 2019. Sources and selection of snow-specific microbial communities in a Greenlandic sea ice snow cover. Scientific Reports 9, article no. 2290, doi: 10.1038/s41598-019-38744-y.

Macias-Fauria M. & Post E. 2018. Effects of sea ice on Arctic biota: an emerging crisis discipline. Biology Letters 14, article no. 20170702, doi: 10.1098/rsbl.2017.0702.

Maltby J., Steinle L., Löscher C.R., Bange H.W., Fischer M.A., Schmidt M. & Treude T. 2018. Microbial methanogenesis in the sulfate-reducing zone of sediments in the Eckernförde Bay, SW Baltic Sea. Biogeosciences 15, 137–157, doi: 10.5194/bg-15-137-2018.

Martin M. 2015. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet Journal 17, 10–12, doi: 10.14806/ej.17.1.200.

Møller E.F., Christensen A., Larsen J., Mankoff K.D., Ribergaard M.H., Sejr M., Wallhead P. & Maar M. 2023. The sensitivity of primary productivity in Disko Bay, a coastal Arctic ecosystem, to changes in freshwater discharge and sea ice cover. Ocean Science 19, 403–420, doi: 10.5194/os-19-403-2023.

Oksanen J., Simpson G., Blanchet F., Kindt R., Legendre P., Minchin P., O’Hara R., Solymos P., Stevens M., Szoecs E., Wagner H., Barbour M., Bedward M., Bolker B., Borcard D., Carvalho G., Chirico M., De Caceres M., Durand S., Evangelista H., FitzJohn R., Friendly M., Furneaux B., Hannigan G., Hill M., Lahti L., McGlinn D., Ouellette M., Ribeiro C.E., Smith T., Stier A., Ter Braak C. & Weedon J. 2024. vegan: Community Ecology Package. R package version 2.6-6. Accessed on the internet at https://CRAN.R-project.org/package=vegan on 06 June 2024.

Overbeek R., Olson R., Pusch G.D., Olsen G.J., Davis J.J., Disz Y., Edwards R.A., Gerdes S., Parrello B., Shukla M., Vonstein V., Wattam A.R., Xia F. & Stevens R. 2013. The SEED and Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Research 41, D206–D214, doi: 10.1093/nar/gkt1226.

Rodriguez-R L.M. & Konstantinidis K.T. 2014. Estimating coverage in metagenomic data sets and why it matters. The ISME Journal 8, 2349–2351, doi: 10.1038/ismej.2014.76.

Seabra R., Wethey D.S., Santos A.M. & Lima F.P. 2015. Understanding complex biogeographic responses to climate change. Scientific Reports 5, article no. 12930, doi: 10.1038/srep12930.

Sha L., Jiang H., Siedenkrantz M.-S., Li D., Andresen C.S., Knudsen K.L., Liu Y. & Zhao M. 2017. A record of Holocene sea-ice variability off west Greenland and its potential forcing factors. Palaeogeography Palaeoclimatology Palaeoecology 475, 115–124, doi: 10.1016/j.palaeo.2017.03.022.

Shannon C.E. 1948. A mathematical theory of communication. The Bell System Technical Journal 27, 379–423, doi: 10.1002/j.1538-7305.1948.tb01338.x.

Silva G.G.Z., Green K.T., Dutilh B.E. & Edwards R.A. 2016. SUPER-FOCUS: a tool for agile functional analysis of shotgun metagenomic data. Bioinformatics 32, 354–361, doi: 10.1093/bioinformatics/btv584.

Teng Z.-J., Qin Q.-L., Zhang W., Li J., Fu H.-H., Wang P., Lan M., Luo G., He J., McMinn A., Wang M., Chen X.-L., Zhang Y.-Z., Chen Y. & Li C.-Y. 2021. Biogeographic traits of dimethyl sulfide and dimethylsulfoniopropionate cycling in polar oceans. Microbiome 9, article no. 207, doi: 10.1186/s40168-021-01153-3.

Tomanek L. 2008. The importance of physiological limits in determining biogeographical range shifts due to global climate change: the heat-shock response. Physiological and Biochemical Zoology 81, 709–717, doi: 10.1086/590163.

Trivedi C.B., Keuschnig C., Larose C., Rissi D.V., Mourot R., Bradley J.A., Winkel M. & Benning L.G. 2022. DNA/RNA preservation in glacial snow and ice samples. Frontiers in Microbiology 13, article no. 894893, doi: 10.3389/fmicb.2022.894893.

Wald A. 1943. Tests of statistical hypotheses concerning several parameters when the number of observations is large. Transactions of the American Mathematical Society 54, 426–482, doi: 10.2307/1990256.

Watanabe M., Higashioka Y., Kojima H. & Fukui M. 2017. Desulfosarcina widdelii sp. nov. and Desulfosarcina alkanivorans sp. nov., hydrocarbon-degrading sulfate-reducing bacteria isolated from marine sediment and emended description of the genus Desulfosarcina. International Journal of Systematic and Evolutionary Microbiology 67, 2994–2997, doi: 10.1099/ijsem.0.002062.

Welsh D.T. 2000. Ecological significance of compatible solute accumulation by micro-organisms: from single cells to global climate. FEMS Microbiology Reviews 3, 263–290, doi: 10.1111/j.1574-6976.2000.tb00542.x.

Wood D.E., Lu J. & Langmead B. 2019. Improved metagenomic analysis with Kraken 2. Genome Biology 20, article no. 257, doi: 10.1186/s13059-019-1891-0.

Yergeau E., Michel C., Tremblay J., Niemi A., King T.L., Wyglinski J., Lee K. & Greer C.W. 2017. Metagenomic survey of the taxonomic and functional microbial communities of seawater and sea ice from the Canadian Arctic. Scientific Reports 7, article no. 42242, doi: 10.1038/srep42242.