Evidence map›Paper›PMID 42304204›Full record

ArticleBMC microbiology2026

Unveiling microbial communities and biogeochemical cycles in Antarctic colored snow.

Xiaohan Ai, Ze Ren, Changzi Liu, Chunmei Zhang, Huirong Li, Haitao Ding, Yong Yu, Wei Luo, Yonghong Bi

Abstract read
In one paragraph

Article in BMC microbiology, 2026. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xiaohan Ai *Key Laboratory for Polar Science, Polar Research Institute of China, Ministry of Natural Resources, Shanghai, 200136, China.
Ze Ren *State Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China.
Changzi LiuState Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.
Chunmei ZhangHubei Key Laboratory of Edible Wild Plants Conservation and Utilization, College of Life Sciences, Hubei Normal University, Huangshi, 435002, China.
Huirong LiKey Laboratory for Polar Science, Polar Research Institute of China, Ministry of Natural Resources, Shanghai, 200136, China.
Haitao DingKey Laboratory for Polar Science, Polar Research Institute of China, Ministry of Natural Resources, Shanghai, 200136, China.
Yong YuKey Laboratory for Polar Science, Polar Research Institute of China, Ministry of Natural Resources, Shanghai, 200136, China.
Wei LuoKey Laboratory for Polar Science, Polar Research Institute of China, Ministry of Natural Resources, Shanghai, 200136, China. luowei@pric.org.cn.
Yonghong BiState Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China. biyh@ihb.ac.cn.

Funding

National Key Research and Development Program of China 2022YFC2807605National Natural Science Foundation of China 31971477National Natural Science Foundation of China 91851201the Key Laboratory of Polar Science, MNR, Polar Research Institute of China KP202101the MNR Key Laboratory of Marine Eco-Environmental Science and Technology, China MEEST-2022-03
6 · The paper itself

Abstract

Snow cover, the extensive terrestrial habitat in Antarctica, sometimes exhibits vivid coloration, yet the structure and function of its microbial communities remain poorly characterized. Using metagenomic sequencing of red snow (RS) and green snow (GS) from the Fildes Peninsula, we found that bacterial, eukaryotic, and archaeal relative abundances were 85.82%, 13.52% and 0.16%, respectively. β-Diversity differed significantly between RS and GS across these three domains (P < 0.05). Dominant bacterial phyla included Bacteroidota (RS: 62.61%; GS: 38.72%) and Pseudomonadota (RS: 32.80%; GS: 54.10%). Among eukaryotes, Chlorophyta (RS: 58.10%; GS: 52.98%) and Basidiomycota (RS: 14.80%; GS: 8.08%) were prevalent. Nanobdellota dominated archaea, with lower abundance in RS than GS. In the algal community, Sanguina, Gonium and Chloromonas were significantly enriched in red snow, while Chlorella and Micractinium were enriched in green snow (P < 0.05). Marker genes associated with carbon (C), nitrogen (N), phosphorus (P) and sulfur (S) cycles were identified in green and red snow. Aerobic respiration and phosphate regulation were significantly enriched in red snow, while CO oxidation, fermentation, and denitrification were significantly enriched in green snow. Key microbial genera associated with these functional pathways also varied. In the denitrification of red snow, Stutzerimonas was the most abundant genus, while Janthinobacterium was abundant in green snow. Nitrification-related genes were detected only in red snow based on the present metagenomic data. The network of the red snow microbial community was potentially more complex and resistant based on topology, which not only benefited its own long-term survival but might also have potentially influenced the positive feedback effect of snowmelt by maintaining a low-albedo snow surface. This provided an ecological implication under climate warming: the expansion of red snow patches showed the potential to the increase nitrate runoff export, which would affect nitrogen nutrient levels in coastal Antarctic waters. Overall, this study used metagenomics to compare the multidomain (bacteria, archaea and eukaryotes) composition and diversity between red snow and green snow, and directly linked key microbial taxa with functional genes of biogeochemical cycles. This study provided new insights into the biological characteristics and functional potential of Antarctic colored snow.

Indexed as

ArchaeaBacteriaMicrobiotaSnowAntarctic RegionsBiodiversityCarbonColorEcosystemEukaryotaFungiMetagenomeMetagenomicsNitrogenPhylogenyCarbonNitrogenAntarcticaBiogeochemical cyclesColored snowCo-occurrence networkMicrobial communities

Identifiers

PMID42304204
PMCPMC13508198

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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.