Microbial genomes retrieved from High Arctic lake sediments encode for adaptation to cold and oligotrophic environments

Ruuskanen, Matti O.; Colby, Graham A.; Pierre, Kyra A. St.; Louis, Vincent L. St.; Aris‐Brosou, Stéphane; Poulain, Alexandre J.

doi:10.1002/lno.11334

Cited by 29 publications

(23 citation statements)

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“…To date, much of the research performed on microbial communities in Arctic lakes has been limited to studies that were mostly based on partial 16S rRNA gene sequencing (Stoeva et al, 2014 ; Mohit et al, 2017 ; Thaler et al, 2017 ; Ruuskanen et al, 2018 ; Cavaco et al, 2019 ). While these studies are useful to understand the structure of these microbial communities, they provide limited functional insights and can be biased as they often rely on sequence databases where environmental microbes, specifically from the Arctic, may be underrepresented (Ruuskanen et al, 2018 , 2019 ). More critically, being circumscribed both in space and in time, previous studies only offer snapshots of microbial communities and hence, have a limited power to predict how microbial communities might respond to climate change.…”

Section: Introductionmentioning

confidence: 99%

Warming Climate Is Reducing the Diversity of Dominant Microbes in the Largest High Arctic Lake

et al. 2020

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Temperatures in the Arctic are expected to increase dramatically over the next century, and transform high latitude watersheds. However, little is known about how microbial communities and their underlying metabolic processes will be affected by these environmental changes in freshwater sedimentary systems. To address this knowledge gap, we analyzed sediments from Lake Hazen, NU Canada. Here, we exploit the spatial heterogeneity created by varying runoff regimes across the watershed of this uniquely large high-latitude lake to test how a transition from low to high runoff, used as one proxy for climate change, affects the community structure and functional potential of dominant microbes. Based on metagenomic analyses of lake sediments along these spatial gradients, we show that increasing runoff leads to a decrease in taxonomic and functional diversity of sediment microbes. Our findings are likely to apply to other, smaller, glacierized watersheds typical of polar or high latitude ecosystems; we can predict that such changes will have far reaching consequences on these ecosystems by affecting nutrient biogeochemical cycling, the direction and magnitude of which are yet to be determined.

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Section: Introductionmentioning

confidence: 99%

Warming Climate Is Reducing the Diversity of Dominant Microbes in the Largest High Arctic Lake

et al. 2020

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“…These approaches can provide an unbiased and insightful view into microorganisms mediating and contributing to biogeochemical activities at a number of scales ranging from individual organisms to communities [ 7 – 9 ]. Recent studies have also enabled the recovery of hundreds to thousands of genomes from a single sample or environment [ 8 , 10 , 11 ]. However, analyses of ever-increasing datasets remain a challenge.…”

Section: Introductionmentioning

confidence: 99%

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

et al. 2022

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Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

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“…While more studies are starting to characterize the communities and genomes of viruses in extreme environments [21][22][23], only few, if any, describe their spillover risk. The High Arctic is of special interest as it is particularly affected by climate change, warming faster than the rest of the world [24][25][26][27]. Warming climate and rapid transitions of the environment increase the risks of spillover events by varying the global distributions and dynamics of viruses, and their reservoirs and vectors [28,29], as shown for arboviruses [30] and the Hendra virus [31].…”

Section: Introductionmentioning

confidence: 99%

Viral spillover risk increases with climate change in High Arctic lake sediments

Lemieux

Colby

Poulain

et al. 2021

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While many viruses have a single natural host, host restriction can be incomplete, hereby leading to spillovers to other host species, potentially causing significant diseases as it is the case with the Influenza A, Ebola, or the SARS-CoV-2 viruses. However, such spillover risks are difficult to quantify. As climate change is rapidly transforming environments, it is becoming critical to quantify the potential for spillovers, in an unbiased manner. For this, we resorted to a metagenomics approach, and focused on two environments in the High Arctic, soil and lake sediments from Lake Hazen. We used DNA and RNA sequencing to reconstruct the lake's virosphere and its range of eukaryotic hosts, and show that spillover risk is higher in lake sediments than in soil and increased with runoff from glacier melt - a proxy for climate change. Should climate change also shift species range of potential vectors northwards, the High Arctic could become fertile ground for emerging pandemics.

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Microbial genomes retrieved from High Arctic lake sediments encode for adaptation to cold and oligotrophic environments

Cited by 29 publications

References 88 publications

Warming Climate Is Reducing the Diversity of Dominant Microbes in the Largest High Arctic Lake

Warming Climate Is Reducing the Diversity of Dominant Microbes in the Largest High Arctic Lake

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Viral spillover risk increases with climate change in High Arctic lake sediments

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