The Arctic is melting at an unprecedented rate and key drivers are changes in snow and ice albedo. Here we show that red snow, a common algal habitat blooming after the onset of melting, plays a crucial role in decreasing albedo. Our data reveal that red pigmented snow algae are cosmopolitan as well as independent of location-specific geochemical and mineralogical factors. The patterns for snow algal diversity, pigmentation and, consequently albedo, are ubiquitous across the Arctic and the reduction in albedo accelerates snow melt and increases the time and area of exposed bare ice. We estimated that the overall decrease in snow albedo by red pigmented snow algal blooms over the course of one melt season can be 13%. This will invariably result in higher melt rates. We argue that such a ‘bio-albedo' effect has to be considered in climate models.

We have assessed the microbial ecology on the surface of Mittivakkat glacier in SE-Greenland during the exceptional high melting season in July 2012 when the so far most extreme melting rate for the Greenland Ice Sheet has been recorded. By employing a complementary and multi-disciplinary field sampling and analytical approach, we quantified the dramatic changes in the different microbial surface habitats (green snow, red snow, biofilms, grey ice, cryoconite holes). The observed clear change in dominant algal community and their rapidly changing cryo-organic adaptation inventory was linked to the high melting rate. The changes in carbon and nutrient fluxes between different microbial pools (from snow to ice, cryoconite holes and glacial forefronts) revealed that snow and ice algae dominate the net primary production at the onset of melting, and that they have the potential to support the cryoconite hole communities as carbon and nutrient sources. A large proportion of algal cells is retained on the glacial surface and temporal and spatial changes in pigmentation contribute to the darkening of the snow and ice surfaces. This implies that the fast, melt-induced algal growth has a high albedo reduction potential, and this may lead to a positive feedback speeding up melting processes.

Glaciers and ice sheets, like other biomes, occupy a significant area of the planet and harbour biological communities with distinct interactions and feedbacks with their physical and chemical environment. In the case of the glacial biome, the biological processes are dominated almost exclusively by microbial communities. Habitats on glaciers and ice sheets with enough liquid water to sustain microbial activity include snow, surface ice, cryoconite holes, englacial systems and the interface between ice and overridden rock/soil. There is a remarkable similarity between the different specific glacial habitats across glaciers and ice sheets worldwide, particularly regarding their main primary producers and ecosystem engineers. At the surface, cyanobacteria dominate the carbon production in aquatic/sediment systems such as cryoconite holes, while eukaryotic Zygnematales and Chlamydomonadales dominate ice surfaces and snow dynamics, respectively. Microbially driven chemolithotrophic processes associated with sulphur and iron cycle and C transformations in subglacial ecosystems provide the basis for chemical transformations at the rock interface under the ice that underpin an important mechanism for the delivery of nutrients to downstream ecosystems. In this review, we focus on the main ecosystem engineers of glaciers and ice sheets and how they interact with their chemical and physical environment. We then discuss the implications of this microbial activity on the icy microbiome to the biogeochemistry of downstream ecosystems.

Algae are important primary colonizers of snow and glacial ice, but hitherto little is known about their ecology on Iceland's glaciers and ice caps. Due do the close proximity of active volcanoes delivering large amounts of ash and dust, they are special ecosystems. This study provides the first investigation of the presence and diversity of microbial communities on all major Icelandic glaciers and ice caps over a 3 year period. Using high-throughput sequencing of the small subunit ribosomal RNA genes (16S and 18S), we assessed the snow community structure and complemented these analyses with a comprehensive suite of physical-, geo-, and biochemical characterizations of the aqueous and solid components contained in snow and ice samples. Our data reveal that a limited number of snow algal taxa (Chloromonas polyptera, Raphidonema sempervirens and two uncultured Chlamydomonadaceae) support a rich community comprising of other micro-eukaryotes, bacteria and archaea. Proteobacteria and Bacteroidetes were the dominant bacterial phyla. Archaea were also detected in sites where snow algae dominated and they mainly belong to the Nitrososphaerales, which are known as important ammonia oxidizers. Multivariate analyses indicated no relationships between nutrient data and microbial community structure. However, the aqueous geochemical simulations suggest that the microbial communities were not nutrient limited because of the equilibrium of snow with the nutrient-rich and fast dissolving volcanic ash. Increasing algal secondary carotenoid contents in the last stages of the melt seasons have previously been associated with a decrease in surface albedo, which in turn could potentially have an impact on the melt rates of Icelandic glaciers.

Background Complete and contiguous genome assemblies greatly improve the quality of subsequent systems-wide functional profiling studies and the ability to gain novel biological insights. While a de novo genome assembly of an isolated bacterial strain is in most cases straightforward, more informative data about co-existing bacteria as well as synergistic and antagonistic effects can be obtained from a direct analysis of microbial communities. However, the complexity of metagenomic samples represents a major challenge. While third generation sequencing technologies have been suggested to enable finished metagenome-assembled genomes, to our knowledge, the complete genome assembly of all dominant strains in a microbiome sample has not been demonstrated. Natural whey starter cultures (NWCs) are used in cheese production and represent low-complexity microbiomes. Previous studies of Swiss Gruyère and selected Italian hard cheeses, mostly based on amplicon metagenomics, concurred that three species generally pre-dominate: Streptococcus thermophilus , Lactobacillus helveticus and Lactobacillus delbrueckii . Results Two NWCs from Swiss Gruyère producers were subjected to whole metagenome shotgun sequencing using the Pacific Biosciences Sequel and Illumina MiSeq platforms. In addition, longer Oxford Nanopore Technologies MinION reads had to be generated for one to resolve repeat regions. Thereby, we achieved the complete assembly of all dominant bacterial genomes from these low-complexity NWCs, which was corroborated by a 16S rRNA amplicon survey. Moreover, two distinct L. helveticus strains were successfully co-assembled from the same sample. Besides bacterial chromosomes, we could also assemble several bacterial plasmids and phages and a corresponding prophage. Biologically relevant insights were uncovered by linking the plasmids and phages to their respective host genomes using DNA methylation motifs on the plasmids and by matching prokaryotic CRISPR spacers with the corresponding protospacers on the phages. These results could only be achieved by employing long-read sequencing data able to span intragenomic as well as intergenomic repeats. Conclusions Here, we demonstrate the feasibility of complete de novo genome assembly of all dominant strains from low-complexity NWCs based on whole metagenomics shotgun sequencing data. This allowed to gain novel biological insights and is a fundamental basis for subsequent systems-wide omics analyses, functional profiling and phenotype to genotype analysis of specific microbial communities. Electronic supplementary material The online version of this article (10.1186/s12866-019-1500-0) contains supplementary material, which is available to authorized users.

SummaryDistinct microbial habitats on glacial surfaces are dominated by snow and ice algae, which are the critical players and the dominant primary colonisers and net producers during the melt season. Here for the first time we have evaluated the role of these algae in association with the full microbial community composition (i.e., algae, bacteria, archaea) in distinct surface habitats and on 12 glaciers and permanent snow fields in Svalbard and Arctic Sweden. We cross-correlated these data with the analyses of specific metabolites such as fatty acids and pigments, and a full suite of potential critical physico-chemical parameters including major and minor nutrients, and trace metals. It has been shown that correlations between single algal species, metabolites, and specific geochemical parameters can be used to unravel mixed metabolic signals in complex communities, further assign them to single species and infer their functionality. The data also clearly show that the production of metabolites in snow and ice algae is driven mainly by nitrogen and less so by phosphorus limitation. This is especially important for the synthesis of secondary carotenoids, which cause a darkening of glacial surfaces leading to a decrease in surface albedo and eventually higher melting rates.

Snow algae are poly-extremophilic microalgae and important primary colonizers and producers on glaciers and snow fields. Depending on their pigmentation they cause green or red mass blooms during the melt season. This decreases surface albedo and thus further enhances snow and ice melting. Although the phenomenon of snow algal blooms has been known for a long time, large aspects of their physiology and ecology sill remain cryptic. This study provides the first in-depth and multi-omics investigation of two very striking adjacent green and red snow fields on a glacier in Svalbard. We have assessed the algal community composition of green and red snow including their associated microbiota, i.e., bacteria and archaea, their metabolic profiles (targeted and non-targeted metabolites) on the bulk and single-cell level, and assessed the feedbacks between the algae and their physico-chemical environment including liquid water content, pH, albedo, and nutrient availability. We demonstrate that green and red snow clearly vary in their physico-chemical environment, their microbial community composition and their metabolic profiles. For the algae this likely reflects both different stages of their life cycles and their adaptation strategies. Green snow represents a wet, carbon and nutrient rich environment and is dominated by the algae Microglena sp. with a metabolic profile that is characterized by key metabolites involved in growth and proliferation. In contrast, the dry and nutrient poor red snow habitat is colonized by various Chloromonas species with a high abundance of storage and reserve metabolites likely to face upcoming severe conditions. Combining a multitude of techniques we demonstrate the power of such complementary approaches in elucidating the function and ecology of extremophiles such as green and red snow algal blooms, which play crucial roles in glacial ecosystems.

The Arctic is being disproportionally affected by climate change compared with other geographic locations, and is currently experiencing unprecedented melt rates. The Greenland Ice Sheet (GrIS) can be regarded as the largest supraglacial ecosystem on Earth, and ice algae are the dominant primary producers on bare ice surfaces throughout the course of a melt season. Ice-algal-derived pigments cause a darkening of the ice surface, which in turn decreases albedo and increases melt rates. The important role of ice algae in changing melt rates has only recently been recognized, and we currently know little about their community compositions and functions. Here, we present the first analysis of ice algal communities across a 100 km transect on the GrIS by high-throughput sequencing and subsequent oligotyping of the most abundant taxa. Our data reveal an extremely low algal diversity with Ancylonema nordenskiöldii and a Mesotaenium species being by far the dominant taxa at all sites. We employed an oligotyping approach and revealed a hidden diversity not detectable by conventional clustering of operational taxonomic units and taxonomic classification. Oligotypes of the dominant taxa exhibit a site-specific distribution, which may be linked to differences in temperatures and subsequently the extent of the melting. Our results help to better understand the distribution patterns of ice algal communities that play a crucial role in the GrIS ecosystem.