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Record W4380885283 · doi:10.1186/s40793-023-00509-6

Distinct taxonomic and functional profiles of high Arctic and alpine permafrost-affected soil microbiomes

2023· article· en· W4380885283 on OpenAlexfundno aff
Ciro Sannino, Weihong Qi, Joel Rüthi, Beat Stierli, Beat Frey

Bibliographic record

VenueEnvironmental Microbiome · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersSwiss Federal Institute for Forest, Snow and Landscape ResearchEidgenössische Technische Hochschule ZürichBNP Paribas CardifGénome QuébecMcGill UniversitySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungSwiss Polar InstituteAarhus UniversitetNational Science Foundation
KeywordsPermafrostMicrobiomeArcticEcologyBiodiversityEnvironmental scienceBiologyGeographyBioinformatics

Abstract

fetched live from OpenAlex

BACKGROUND: Global warming is affecting all cold environments, including the European Alps and Arctic regions. Here, permafrost may be considered a unique ecosystem harboring a distinct microbiome. The frequent freeze-thaw cycles occurring in permafrost-affected soils, and mainly in the seasonally active top layers, modify microbial communities and consequently ecosystem processes. Although taxonomic responses of the microbiomes in permafrost-affected soils have been widely documented, studies about how the microbial genetic potential, especially pathways involved in C and N cycling, changes between active-layer soils and permafrost soils are rare. Here, we used shotgun metagenomics to analyze the microbial and functional diversity and the metabolic potential of permafrost-affected soil collected from an alpine site (Val Lavirun, Engadin area, Switzerland) and a High Arctic site (Station Nord, Villum Research Station, Greenland). The main goal was to discover the key genes abundant in the active-layer and permafrost soils, with the purpose to highlight the potential role of the functional genes found. RESULTS: We observed differences between the alpine and High Arctic sites in alpha- and beta-diversity, and in EggNOG, CAZy, and NCyc datasets. In the High Arctic site, the metagenome in permafrost soil had an overrepresentation (relative to that in active-layer soil) of genes involved in lipid transport by fatty acid desaturate and ABC transporters, i.e. genes that are useful in preventing microorganisms from freezing by increasing membrane fluidity, and genes involved in cell defense mechanisms. The majority of CAZy and NCyc genes were overrepresented in permafrost soils relative to active-layer soils in both localities, with genes involved in the degradation of carbon substrates and in the degradation of N compounds indicating high microbial activity in permafrost in response to climate warming. CONCLUSIONS: Our study on the functional characteristics of permafrost microbiomes underlines the remarkably high functional gene diversity of the High Arctic and temperate mountain permafrost, including a broad range of C- and N-cycling genes, and multiple survival and energetic metabolisms. Their metabolic versatility in using organic materials from ancient soils undergoing microbial degradation determine organic matter decomposition and greenhouse gas emissions upon permafrost thawing. Attention to their functional genes is therefore essential to predict potential soil-climate feedbacks to the future warmer climate.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.180
Teacher spread0.166 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations27
Published2023
Admission routes1
Has abstractyes

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