The Arctic snowpack microbial community highlighted by metagenomics and metatranscriptomics

• Main Authors: Maccario, Lorrie, Vogel, Timothy M., Larose, Catherine
• Other Authors: Ampère, Département Bioingénierie (BioIng), Ampère (AMPERE), École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2013
• Subjects: [SPI.NRJ]Engineering Sciences [physics]/Electric power; [SDE]Environmental Sciences; Arctic
• Online Access: https://hal.science/hal-00932231

International audience The Arctic seasonal snowpack can extend at times over a third of the Earth's land surface. This chemically dynamic environment interacts constantly with different environmental compartments such as the atmosphere, soil and snow meltwater, and thus, strongly influences the entire biosphere. However, the microbial community associated with this habitat and its potential role in biogeochemical cycling remains poorly understood. Previous studies based on 16S rRNA gene analysis revealed a high diversity of microorganisms within the snowpack. Here, we focused on both microbial community structure and function by applying a global approach using metagenomics and metatranscriptomics. From the 250 thousand sequence reads in all our snow metagenomes, the majority (between 58 and 88%) were unassigned to specific metabolic categories, which signals the lack of related functional data in sequence databases. However, snow metagenome analyses demonstrated major shifts in function distribution during the season indicating that the snowpack is a dynamic ecosystem. These changes seem to be related to fluctuations in environmental conditions as some chemical parameters, like mercury or methyl-mercury concentrations, were correlated with function abundance. Comparing snow metagenomes with publically available datasets from different ecosystems, we described the specific functional signature of snowpack microbial community. Some functions like oxidative stress response or lipopolysaccharides biosynthesis are more highly represented in snow metagenomes than in those from other ecosystems. These functions are probably related to how microorganisms cope with the harsh conditions (such as intense UV radiation and cold temperatures) characteristic of the Arctic snowpack. The extraction of mRNA from the Arctic snowpack for further metatranscriptomic analyses supports the hypothesis that microorganisms are metabolically active in the polar snow ecosystem. The expression pattern derived from the mRNA sequencing ...