Integrated 'Omics', Targeted Metabolite and Single-cell Analyses of Arctic Snow Algae Functionality and Adaptability.

Stefanie Lutz,Liane G Benning,Alexandre M Anesio,Katie Field

doi:10.3389/fmicb.2015.01323

Abstract

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.

Highlights

Snow algae are poly-extremophilic microalgae that thrive on snow fields and glaciers in polar and alpine regions
One reason could be the lack of appropriate reference genomes as currently, the closest fully sequenced green algal strain is Chlamydomonas reinhardtii (Merchant et al, 2007), a model organism for freshwater Chlorophyta adapted to mesophilic temperatures and not sharing common cryogenic adaptations. To close this gap we explored in this study the questions whether (a) the formation of green and red snow are linked or independent phenomena, (b) if and how the life stages of red and green snow algae differ, and (c) what the potential feedbacks are between the presence of algae and their physico-chemical environment, which is crucial for understanding the potential importance of glacial biomes for the export of metabolites to downstream ecosystems
Algal cell numbers were an order of magnitude higher in green snow (6 × 106 mL−1) compared to red snow (2 × 105 mL−1) and overall biomass was an order of magnitude higher in green snow (∼450 mm3 L−1, as opposed to ∼50 mm3 L−1) (Table 1)

Summary

Introduction

Snow algae are poly-extremophilic microalgae that thrive on snow fields and glaciers in polar and alpine regions They are prolific primary colonizers and producers (Lutz et al, 2014) despite being subjected to a multitude of harsh environmental conditions including low temperatures, high irradiation, freeze-thaw cycles, desiccation, low pH, and broad variation in the levels. As part of the life cycle and as a mechanism of protection from high irradiation, snow algae can adjust their pigmentation from predominantly chlorophylls (“green snow”) to carotenoids (“red snow”) (Remias et al, 2005). It is still unknown whether all green snow undergoes a transition to red snow or whether red and green snow represent two independent phenomena. The coloration causes a darkening of snow surfaces, which in turn decreases surface albedo and eventually may speed up melting processes (Thomas and Duval, 1995; Yallop et al, 2012; Benning et al, 2014; Lutz et al, 2014; Lutz et al, unpublished data)

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