ArticleScientific reports2026
Metagenomic analysis of bacterial diversity, antibiotic resistance, and functional profiles in the ice core samples from two glaciers of Sikkim Himalaya.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Glaciers cover a substantial portion of the world and are home to various biological populations. The Himalayas constitute the largest glaciated region outside the poles; hence, they are regarded as "The Third Pole" of the World. There are around 84 glaciers in the Teesta basin (Sikkim Himalaya). There is substantially less data available on the microbial diversity embedded in the glacial ice core samples of the Sikkim Himalaya, as well as their physico-chemistry and potential geomorphological hazards related to their retreat or decrease in snow-line cover. The present study aims to evaluate the microbial diversity in the glacier ice core region and the study area; therefore, two glaciers in the Sikkim Himalaya were chosen: Frey-Peak and Rathong Glacier. The bacterial diversity analysis reveals the prevalence of various phyla, including Pseudomonadota, Actinomycetota, Bacillota, and Bacteroidota. The random forest model reveals the significant contributions of various elements, including Na, Mg, K, Ca, and Zn, to the alpha diversity of the studied glaciers. Among physicochemical parameters, pH was found to contribute the most in shaping bacterial diversity. Cluster of Orthologous Groups (COG) analysis underscored a predominance of genes associated with amino acids (23.5%), carbohydrates (18.93%), lipids (10.88%), energy (17.26%), coenzymes (9.38%), and ion transport/metabolism (14.71%). KEGG (Kyoto Encyclopedia of Genes and Genomes) Orthology (KO) analysis revealed the presence of 4,915 to 96,954 genes. Interestingly, the metagenomic analysis revealed the presence of specific species of Bradyrhizobium, Beijerinckia, Burkholderia, and Corynebacterium, which are associated with nitrogen metabolism, suggesting their potential involvement in biogeochemical processes. Additionally, a total of 59 to 419 bacterial genes related to sulphur metabolism were deduced through the KEGG functional analysis. The study detected the presence of various antibiotic resistance genes corresponding to different classes of antibiotics, including aminoglycoside, tetracycline, fluoroquinolone, macrolide, and erythromycin. Network analysis reveals that antibiotic resistance genes primarily interact with the phyla Pseudomonadota, Bacillota, and Actinomycetota. The melting of glaciers, a significant effect of climate change, may release contaminants, antibiotic resistance genes, and pathogenic bacteria into free-flowing rivers, potentially impacting human health.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.