Endometabolic profiling of pigmented glacier ice algae: the impact of sample processing.

INTRODUCTION: Glacier ice algae, mainly Ancylonema alaskanum and Ancylonema nordenskiöldi, bloom on Greenland Ice Sheet bare ice surfaces. They significantly decrease surface albedo due to their purple-brown pigmentation, thus increasing melt. Little is known about their metabolic adaptation and factors controlling algal growth dynamics and pigment formation. A challenge in obtaining such data is the necessity of melting samples, which delays preservation and introduces bias to metabolomic analysis. There is a need to evaluate the physiological response of algae to melting and establish consistent sample processing strategies for metabolomics of ice microbial communities. OBJECTIVES: To address the impact of sample melting procedure on metabolic characterization and establish a processing and analytical workflow for endometabolic profiling of glacier ice algae. METHODS: We employed untargeted, high-resolution mass spectrometry and tested the effect of sample melt temperature (10, 15, 20 °C) and processing delay (up to 49 h) on the metabolome and lipidome, and complemented this approach with cell counts (FlowCam), photophysiological analysis (PAM) and diversity characterization. RESULTS AND CONCLUSION: We putatively identified 804 metabolites, with glycerolipids, glycerophospholipids and fatty acyls being the most prominent superclasses (> 50% of identified metabolites). Among the polar metabolome, carbohydrates and amino acid-derivatives were the most abundant. We show that 8% of the metabolome is affected by melt duration, with a pronounced decrease in betaine membrane lipids and pigment precursors, and an increase in phospholipids. Controlled fast melting at 10 °C resulted in the highest consistency, and is our recommendation for future supraglacial metabolomics studies.

Giant viral signatures on the Greenland ice sheet.

BACKGROUND: Dark pigmented snow and glacier ice algae on glaciers and ice sheets contribute to accelerating melt. The biological controls on these algae, particularly the role of viruses, remain poorly understood. Giant viruses, classified under the nucleocytoplasmic large DNA viruses (NCLDV) supergroup (phylum Nucleocytoviricota), are diverse and globally distributed. NCLDVs are known to infect eukaryotic cells in marine and freshwater environments, providing a biological control on the algal population in these ecosystems. However, there is very limited information on the diversity and ecosystem function of NCLDVs in terrestrial icy habitats. RESULTS: In this study, we investigate for the first time giant viruses and their host connections on ice and snow habitats, such as cryoconite, dark ice, ice core, red and green snow, and genomic assemblies of five cultivated Chlorophyta snow algae. Giant virus marker genes were present in almost all samples; the highest abundances were recovered from red snow and the snow algae genomic assemblies, followed by green snow and dark ice. The variety of active algae and protists in these GrIS habitats containing NCLDV marker genes suggests that infection can occur on a range of eukaryotic hosts. Metagenomic data from red and green snow contained evidence of giant virus metagenome-assembled genomes from the orders Imitervirales, Asfuvirales, and Algavirales. CONCLUSION: Our study highlights NCLDV family signatures in snow and ice samples from the Greenland ice sheet. Giant virus metagenome-assembled genomes (GVMAGs) were found in red snow samples, and related NCLDV marker genes were identified for the first time in snow algal culture genomic assemblies; implying a relationship between the NCLDVs and snow algae. Metatranscriptomic viral genes also aligned with metagenomic sequences, suggesting that NCLDVs are an active component of the microbial community and are potential "top-down" controls of the eukaryotic algal and protistan members. This study reveals the unprecedented presence of a diverse community of NCLDVs in a variety of glacial habitats dominated by algae.

Active and dormant microorganisms on glacier surfaces.

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.

Seasonality of Glacial Snow and Ice Microbial Communities.

Blooms of microalgae on glaciers and ice sheets are amplifying surface ice melting rates, which are already affected by climate change. Most studies on glacial microorganisms (including snow and glacier ice algae) have so far focused on the spring and summer melt season, leading to a temporal bias, and a knowledge gap in our understanding of the variations in microbial diversity, productivity, and physiology on glacier surfaces year-round. Here, we investigated the microbial communities from Icelandic glacier surface snow and bare ice habitats, with sampling spanning two consecutive years and carried out in both winter and two summer seasons. We evaluated the seasonal differences in microbial community composition using Illumina sequencing of the 16S rRNA, 18S rRNA, and ITS marker genes and correlating them with geochemical signals in the snow and ice. During summer, Chloromonas, Chlainomonas, Raphidonema, and Hydrurus dominated surface snow algal communities, while Ancylonema and Mesotaenium dominated the surface bare ice habitats. In winter, algae could not be detected, and the community composition was dominated by bacteria and fungi. The dominant bacterial taxa found in both winter and summer samples were Bacteriodetes, Actinobacteria, Alphaproteobacteria, and Gammaproteobacteria. The winter bacterial communities showed high similarities to airborne and fresh snow bacteria reported in other studies. This points toward the importance of dry and wet deposition as a wintertime source of microorganisms to the glacier surface. Winter samples were also richer in nutrients than summer samples, except for dissolved organic carbon-which was highest in summer snow and ice samples with blooming microalgae, suggesting that nutrients are accumulated during winter but primarily used by the microbial communities in the summer. Overall, our study shows that glacial snow and ice microbial communities are highly variable on a seasonal basis.

DNA/RNA Preservation in Glacial Snow and Ice Samples.

The preservation of nucleic acids for high-throughput sequencing is an ongoing challenge for field scientists. In particular, samples that are low biomass, or that have to be collected and preserved in logistically challenging environments (such as remote sites or during long sampling campaigns) can pose exceptional difficulties. With this work, we compare and assess the effectiveness of three preservation methods for DNA and RNA extracted from microbial communities of glacial snow and ice samples. Snow and ice samples were melted and filtered upon collection in Iceland, and filters were preserved using: (i) liquid nitrogen flash freezing, (ii) storage in RNAlater, or (iii) storage in Zymo DNA/RNA Shield. Comparative statistics covering nucleic acid recovery, sequencing library preparation, genome assembly, and taxonomic diversity were used to determine best practices for the preservation of DNA and RNA samples from these environments. Our results reveal that microbial community composition based on DNA was comparable at the class level across preservation types. Based on extracted RNA, the taxonomic composition of the active community was primarily driven by the filtered sample volume (i.e., biomass content). In low biomass samples (where <200 ml of sample volume was filtered) the taxonomic and functional signatures trend toward the composition of the control samples, while in samples where a larger volume (more biomass) was filtered our data showed comparable results independent of preservation type. Based on all comparisons our data suggests that flash freezing of filters containing low biomass is the preferred method for preserving DNA and RNA (notwithstanding the difficulties of accessing liquid nitrogen in remote glacial field sites). Generally, RNAlater and Zymo DNA/RNA Shield solutions work comparably well, especially for DNA from high biomass samples, but Zymo DNA/RNA Shield is favored due to its higher yield of preserved RNA. Biomass quantity from snow and ice samples appears to be the most important factor in regards to the collection and preservation of samples from glacial environments.