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Microbial blooms colonize the Greenland Ice Sheet bare ice surface during the ablation season and significantly reduce its albedo. On the ice surface, microbes are exposed to high levels of irradiance, freeze–thaw cycles, and low nutrient concentrations. It is well known that microorganisms secrete metabolites to maintain homeostasis, communicate with other microorganisms, and defend themselves. Yet, the exometabolome of supraglacial microbial blooms, dominated by the pigmented glacier ice algae Ancylonema alaskanum and Ancylonema nordenskiöldii, remains thus far unstudied. Here, we use a high‐resolution mass spectrometry‐based untargeted metabolomics workflow to identify metabolites in the exometabolome of microbial blooms on the surface of the southern tip of the Greenland Ice Sheet. Samples were collected every 6 h across two diurnal cycles at 5 replicate sampling sites with high similarity in community composition, in terms of orders and phyla present. Time of sampling explained 46% (permutational multivariate analysis of variance [PERMANOVA], pseudo‐F = 3.7771, p = 0.001) and 27% (PERMANOVA, pseudo‐F = 1.8705, p = 0.001) of variance in the exometabolome across the two diurnal cycles. Annotated metabolites included riboflavin, lumichrome, tryptophan, and azelaic acid, all of which have demonstrated roles in microbe–microbe interactions in other ecosystems and should be tested for potential roles in the development of microbial blooms on bare ice surfaces. [ABSTRACT FROM AUTHOR]

Glacier and ice sheet surfaces host diverse communities of microorganisms whose activity (or inactivity) influences biogeochemical cycles and ice melting. Supraglacial microbes endure various environmental extremes including resource scarcity, frequent temperature fluctuations above and below the freezing point of water, and high UV irradiance during summer followed by months of total darkness during winter. One strategy that enables microbial life to persist through environmental extremes is dormancy, which despite being prevalent among microbial communities in natural settings, has not been directly measured and quantified in glacier surface ecosystems. Here, we use a combination of metabarcoding and metatranscriptomic analyses, as well as cell‐specific activity (BONCAT) incubations to assess the diversity and activity of microbial communities from glacial surfaces in Iceland and Greenland. We also present a new ecological model for glacier microorganisms and simulate physiological state‐changes in the glacial microbial community under idealized (i) freezing, (ii) thawing, and (iii) freeze–thaw conditions. We show that a high proportion (>50%) of bacterial cells are translationally active in‐situ on snow and ice surfaces, with Actinomycetota, Pseudomonadota, and Planctomycetota dominating the total and active community compositions, and that glacier microorganisms, even when frozen, could resume translational activity within 24 h after thawing. Our data suggest that glacial microorganisms respond rapidly to dynamic and changing conditions typical of their natural environment. We deduce that the biology and biogeochemistry of glacier surfaces are shaped by processes occurring over short (i.e., daily) timescales, and thus are susceptible to change following the expected alterations to the melt‐regime of glaciers driven by climate change. A better understanding of the activity of microorganisms on glacier surfaces is critical in addressing the growing concern of climate change in Polar regions, as well as for their use as analogues to life in potentially habitable icy worlds. [ABSTRACT FROM AUTHOR]

Summary: Snow algae are predicted to expand in polar regions due to climate warming, which can accelerate snowmelt by reducing albedo. Green snow frequently occurs near penguin colonies, and red snow distributes widely along ocean shores. However, the mechanisms underpinning the assemblage of algae and heterotrophs in colored snow remain poorly characterized.We investigated algal, bacterial, and fungal communities and their interactions in red and green snows in the Antarctic Peninsula using a high‐throughput sequencing method.We found distinct algal community structure in red and green snows, and the relative abundance of dominant taxa varied, potentially due to nutrient status differences. Contrastingly, red and green snows exhibited similar heterotrophic communities (bacteria and fungi), whereas the relative abundance of fungal pathogens was substantially higher in red snow by 3.8‐fold. Red snow exhibited a higher network complexity, indicated by a higher number of nodes and edges. Red snow exhibited a higher proportion of negative correlations among heterotrophs (62.2% vs 3.4%) and stronger network stability, suggesting the red‐snow network is more resistant to external disturbance.Our study revealed that the red snow microbiome exhibits a more stable microbial network than the green snow microbiome. [ABSTRACT FROM AUTHOR]