Evidence map›Paper›PMID 41648011›Full record

ArticleFrontiers in microbiology2025

Diverging contaminant profiles and prokaryotic assemblages in Arctic and Antarctic lake sediments.

Alessandro Ciro Rappazzo, Angelina Lo Giudice, Stefania Giannarelli, Carmen Rizzo, Alessio Tomei, Lisa Ghezzi, Warren R L Cairns, Maurizio Azzaro, Maria Papale

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Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Alessandro Ciro RappazzoInstitute of Polar Sciences, National Research Council (CNR-ISP), Messina, Italy.
Angelina Lo GiudiceInstitute of Polar Sciences, National Research Council (CNR-ISP), Messina, Italy.
Stefania GiannarelliDepartment of Chemistry and Industrial Chemistry, University of Pisa, Pisa, Italy.
Carmen RizzoInstitute of Polar Sciences, National Research Council (CNR-ISP), Messina, Italy.
Alessio TomeiDepartment of Earth Sciences, University of Pisa, Pisa, Italy.
Lisa GhezziDepartment of Earth Sciences, University of Pisa, Pisa, Italy.
Warren R L CairnsInstitute of Polar Sciences, National Research Council (CNR-ISP), Venice, Italy.
Maurizio AzzaroInstitute of Polar Sciences, National Research Council (CNR-ISP), Messina, Italy.
Maria PapaleInstitute of Polar Sciences, National Research Council (CNR-ISP), Messina, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Persistent organic pollutants (POPs) and trace metals are increasingly recognized as critical drivers of ecological change in polar environments. However, their combined impact on sediment microbial communities remains largely unexplored. Methods: We analyzed sediments from 12 high-latitude lakes and ponds, five from the Arctic (Svalbard) and seven from the Antarctic (South Shetland Islands/Deception Island), to examine contaminant profiles (polychlorinated biphenyls [PCBs] and trace metals) and prokaryotic community structure using 16S rRNA gene amplicon sequencing. Finally, we assessed the associations between the identified communities and detected pollutants, and compared these associations across lakes and sites. Results: The results revealed distinct chemical signatures between poles: Arctic sediments were mainly contaminated by polycyclic aromatic hydrocarbons (∑PAHs, 18.5-685.7 ppb; phenanthrene was the most abundant), whereas Antarctic sediments showed relatively higher concentrations of chlorobenzenes (∑CBs, 1.9-3.6 ppb) and polychlorinated biphenyls (∑PCBs, 0.9-1.4 ppb), with 2-methylnaphthalene as the most abundant PAH. Manganese was the most abundant metal in both regions, reaching 760 ppm in the Arctic, while elevated arsenic and lead characterized specific Antarctic sites. Amplicon sequencing identified five dominant phyla (i.e., Actinobacteriota, Bacteroidota, Alpha- and Gammaproteobacteria, and Desulfobacterota) with significant compositional shifts between poles. Discussion: Notably, the distinct contaminant signatures between regions appeared to be associated with shifts in microbial community composition, suggesting that both the type and intensity of POP and metal exposure may influence bacterial diversity and ecological functions in polar lake sediments. These findings provide a robust baseline for Arctic-Antarctic comparisons, positioning polar lakes as sensitive sentinels of contaminant-driven ecological change. They also underscore the urgent need for functional studies and long-term monitoring to evaluate ecosystem resilience under accelerating climate change.

Indexed as

AntarcticaArcticbacterial communitiesbiodiversitycontaminationheavy metalspersistent organic pollutantspolar lakes

Identifiers

PMID41648011
PMCPMC12869993

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.