Evidence map›Paper›PMID 32778049›Full record

ArticleBMC microbiology2020

Metagenomics revealing molecular profiling of community structure and metabolic pathways in natural hot springs of the Sikkim Himalaya.

Nitish Sharma, Jitesh Kumar, Md Minhajul Abedin, Dinabandhu Sahoo, Ashok Pandey, Amit K Rai, Sudhir P Singh

Abstract read
In one paragraph

Article in BMC microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

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  8. Biology · 2025
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  12. Deciphering the microbial communities of alkaline hot spring in Panamik, Ladakh, India using a high-throughput sequencing approach.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2024
    Article
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  16. Post-monsoon seasonal variation of prokaryotic diversity in solfataric soil from the North Sikkim hot spring.International microbiology : the official journal of the Spanish Society for Microbiology · 2023
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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

7 authors.

Nitish SharmaCenter of Innovative and Applied Bioprocessing (DBT-CIAB), SAS Nagar, Mohali, India.
Jitesh KumarCenter of Innovative and Applied Bioprocessing (DBT-CIAB), SAS Nagar, Mohali, India.
Md Minhajul AbedinInstitute of Bioresources and Sustainable Development, Sikkim Centre, Tadong, Gangtok, India.
Dinabandhu SahooInstitute of Bioresources and Sustainable Development, Sikkim Centre, Tadong, Gangtok, India.
Ashok PandeyCSIR-Indian Institute of Toxicology Research, Lucknow, India.
Amit K RaiInstitute of Bioresources and Sustainable Development, Sikkim Centre, Tadong, Gangtok, India. amitrai.ibsd@gov.in.
Sudhir P SinghCenter of Innovative and Applied Bioprocessing (DBT-CIAB), SAS Nagar, Mohali, India. sudhirsingh@ciab.res.in.ORCID 0000-0001-5437-4292

Funding

Department of Biotechnology , Ministry of Science and Technology IBSD/A1/P (PH-2)/10
6 · The paper itself

Abstract

backgroundHimalaya is an ecologically pristine environment. The geo-tectonic activities have shaped various environmental niches with diverse microbial populations throughout the Himalayan biosphere region. Albeit, limited information is available in terms of molecular insights into the microbiome, including the uncultured microbes, of the Himalayan habitat. Hence, a vast majority of genomic resources are still under-explored from this region. Metagenome analysis has simplified the extensive in-depth exploration of diverse habitats. In the present study, the culture-independent whole metagenome sequencing methodology was employed for microbial diversity exploration and identification of genes involved in various metabolic pathways in two geothermal springs located at different altitudes in the Sikkim Himalaya.

resultsThe two hot springs, Polok and Reshi, have distinct abiotic conditions. The average temperature of Polok and Reshi was recorded to be 62 °C and 43 °C, respectively. Both the aquatic habitats have alkaline geochemistry with pH in the range of 7-8. Community profile analysis revealed genomic evidence of plentiful bacteria, with a minute fraction of the archaeal population in hot water reservoirs of Polok and Reshi hot spring. Mesophilic microbes belonging to Proteobacteria and Firmicutes phyla were predominant at both the sites. Polok exhibited an extravagant representation of Chloroflexi, Deinococcus-Thermus, Aquificae, and Thermotogae. Metabolic potential analysis depicted orthologous genes associated with sulfur, nitrogen, and methane metabolism, contributed by the microflora in the hydrothermal system. The genomic information of many novel carbohydrate-transforming enzymes was deciphered in the metagenomic description. Further, the genomic capacity of antimicrobial biomolecules and antibiotic resistance were discerned.

conclusionThe study provided comprehensive molecular information about the microbial treasury as well as the metabolic features of the two geothermal sites. The thermal aquatic niches were found a potential bioresource of biocatalyst systems for biomass-processing. Overall, this study provides the whole metagenome based insights into the taxonomic and functional profiles of Polok and Reshi hot springs of the Sikkim Himalaya. The study generated a wealth of genomic data that can be explored for the discovery and characterization of novel genes encoding proteins of industrial importance.

Indexed as

Metabolic Networks and PathwaysAltitudeBacteriaBacterial ProteinsHigh-Throughput Nucleotide SequencingHot SpringsMetagenomicsPhylogenySequence Analysis, DNABacterial ProteinsAntibiotic resistanceCAZymesFunctional potentialGlycosyltransferasesHot springsMetagenomicsTaxonomic profiling

Identifiers

PMID32778049
PMCPMC7418396

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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.