Microbial diversity associated with the natural spring water of Western Himalayas

被引:0
|
作者
Oza Y. [1 ]
Karande M. [1 ]
Ghosh R. [1 ]
Rawat J.M. [2 ]
Purohit S. [3 ]
Rawat B. [4 ]
Zumla A. [5 ]
Sharma A. [1 ,4 ]
机构
[1] National Centre for Microbial Resource, National Centre for Cell Science, Maharashtra, Pune
[2] Department of Biotechnology, Graphic Era (deemed to be) University, Uttarakhand, Dehradun
[3] Uttarakhand Council for Biotechnology, Uttarakhand, Haldi, Pantnagar
[4] School of Agriculture, Graphic Era Hill University, Uttarakhand, Dehradun
[5] Department of Infection, Division of Infection and Immunity, NIHR Biomedical Research Centre, University College London, UCL Hospitals NHS Foundation Trust, London
来源
Vegetos | 2024年 / 37卷 / 5期
关键词
16S rRNA gene; Fungal communities; Targeted metagenomics; Water springs; Western himalayas;
D O I
10.1007/s42535-024-00942-z
中图分类号
学科分类号
摘要
Springs in the Himalayan landscape are vital sources of potable water for millions of inhabitants who use it for domestic and farming purposes. The rise in urbanization, pilgrimage and various other anthropogenic activities invariably result in microbial contamination. In this study, we conducted a microbiological examination of water samples collected from four distinct Himalayan springs, located in the Rudraprayag district of Uttarakhand. We employed targeted metagenomics, using 16S rRNA and Internal Transcribed Spacer (ITS) gene analysis, to elucidate the bacterial and fungal composition. Cumulatively, the high-throughput sequencing data from all four springs revealed the abundance of Proteobacteria (35.38%), followed by Fermicutes (22.47%), Acidobacteriota (14.73%), and Actinobacteriota (5.35%). Genus level analysis of bacterial communities revealed the prevalence of Tumebacillus (13.85%) and Massilia (12.97%). Mycobiome analysis demonstrated the dominance of the fungal phyla Ascomycota (72.11%), followed by Basidiomycota (16.04%), Mortierellomycota (9.21%), and Chytridiomycota (1.2%). We further analysed the microbial communities using marker gene (16S rRNA) data through PICRUSt and the KEGG database to identify the gene abundance associated with carbon metabolism. © The Author(s) under exclusive licence to Society for Plant Research 2024.
引用
收藏
页码:1795 / 1803
页数:8
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