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Amplicon Sequence Collections

16S rRNA Gene Amplicon Data Set-Based Bacterial Diversity in a Water-Soil Sample from Pangong Tso Lake, a High-Altitude Grassland Lake of the Northwest Himalayas

Garima Bisht, Anuradha Sourirajan, David J. Baumler, Kamal Dev
Frank J. Stewart, Editor
Garima Bisht
aFaculty of Applied Sciences and Biotechnology, Shoolini University, Solan, Himachal Pradesh, India
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Anuradha Sourirajan
aFaculty of Applied Sciences and Biotechnology, Shoolini University, Solan, Himachal Pradesh, India
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David J. Baumler
bDepartment of Food Science and Nutrition, University of Minnesota—Twin Cities, St. Paul, Minnesota, USA
cMicrobial and Plant Genomic Institute, University of Minnesota—Twin Cities, St. Paul, Minnesota, USA
dBiotechnology Institute, University of Minnesota—Twin Cities, St. Paul, Minnesota, USA
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Kamal Dev
aFaculty of Applied Sciences and Biotechnology, Shoolini University, Solan, Himachal Pradesh, India
bDepartment of Food Science and Nutrition, University of Minnesota—Twin Cities, St. Paul, Minnesota, USA
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Frank J. Stewart
Georgia Institute of Technology
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DOI: 10.1128/MRA.01192-18
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ABSTRACT

We report here 16S rRNA-based bacterial diversity existing during freezing conditions in a high-altitude Himalayan lake through sequencing a 16S rRNA gene amplicon data set. A total of 121,857 high-quality reads were obtained; 40.78% of the bacterial population was classified to the genus level, while 1.26% was classified to the species level.

ANNOUNCEMENT

High-altitude lakes in the Himalayas represent unique areas of microbially biodiverse populations that are exposed to freezing temperatures, salinity, high UV radiation, low oxygen, and limited nutrients (1). Pangong Tso Lake (33.819770ʺN, 78.614501ʺE) is one such lake, situated at an elevation of about 4,350 m in the Northwest Himalayas. Metagenomic studies of such unique environments are gaining importance in providing a better understanding of microbial ecology and its applications to biotechnology (2–4). Unlike previous studies which explored the whole metagenome in a sample collected in the month of September (5), we collected a water-soil mixture (pH 9.0) aseptically underneath the frozen lake surface (1 foot depth; ice was broken to create a hole) using a sterile long-handled stainless steel ladle during the peak of winter (January; temperature of –10°C) to specifically identify bacterial diversity. The salinity of the water-soil slurry was determined by quantitation of ions using flame photometry (6). The water-soil slurry contained 29, 0.6, and 14.73 mmol per liter of sodium, potassium, and chloride ions, respectively. The total salinity of the water-soil slurry was ∼0.12%. The total genomic DNA was isolated from the water-soil mixture using a Nucleospin soil kit (TaKaRa Bio, Ltd.), and an A260/280 of ∼1.81 was quantified with a NanoDrop instrument. The amplicon library was prepared using a Nextera XT index kit (Illumina, Inc.). The primers for the amplification of the V3-V4 region of 16S rRNA genes (forward, GCCTACGGGNGGCWGCAG, and reverse, ACTACHVGGGTATCTAATCC) were designed at Eurofins. The V3-V4 region is highly variable and known to reveal microbially diverse populations (7). The amplicon library was purified using 1× AMPure XP beads, quantified using a Qubit fluorometer, and analyzed with a 4200 TapeStation system (Agilent Technologies) using D1000 screen tape following the manufacturer’s instructions. The library was loaded onto a MiSeq instrument (2 × 300 bp) at 10 to 20 pM for cluster generation and sequencing. The sequenced raw reads were processed to obtain high-quality (HQ) reads using Trimmomatic v0.35 (8) to remove adaptor sequences, ambiguous reads, and low-quality sequences (i.e., those with a more than 10% quality threshold [QV] of <20 Phred quality score). A total of 121,857 high-quality reads were obtained. The HQ reads were subjected to operational taxonomic unit (OUT) identification at 97% sequence similarity and taxonomic assignment of OTUs using the Greengenes database (16S/Archaea database) and the Quantitative Insights into Microbial Ecology (QIIME) module. Krona-based (9) diagram visualization showed that 99.22% of the microbially diverse population represents Bacteroidetes (35.97%), Firmicutes (31.27%), Proteobacteria (22.56%), Tenericutes (8.38%), and Planctomycetes (1.04%) at the phylum level (Fig. 1). The remaining microbially diverse population represents the phyla Verrucomicrobia (0.23%), Actinobacteria (0.23%), Spirochaetae (0.09%), Acidobacteria (0.09%), Cyanobacteria (0.05%), Gemmatimonadetes (0.03%), and Deinococcus-Thermus (0.03%) and the candidate phyla TM6 (0.02%) and SR1 (0.01%). A fraction of the population (0.05%) was unclassified even at the phylum level. Only 40.78% of the bacterial population was classified to the genus level, and 1.26%, representing Firmicutes (0.209088%), Proteobacteria (0.471663%), and Bacteroidetes (0.585932%), was classified to the species level (Table 1). About 2.70025771% and 0.068075174% were represented by members of the genera Halomonas and Marinomonas, respectively.

FIG 1
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FIG 1

Krona chart of the bacteria represented by 16S rRNA gene amplicon-based bacterial diversity in a soil-water sample from a high-altitude cold desert lake. Each circle represents the phylum, class, order, family, genus, and species from the inside to the outside of the circle, respectively, indicated by percent diversity based on the absolute number of representative bacteria.

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TABLE 1

Summary of bacteria identified to the species level from a 16S rRNA gene-based metagenomic study of a soil-water mixture from a high-altitude lake

Data availability.The 16S rRNA gene amplicon data set is available at NCBI (National Center for Biotechnology Information) under the SRA accession number SRP158149.

ACKNOWLEDGMENTS

We acknowledge Prem Kumar Khosla, vice chancellor, and the members of the yeast biology laboratory (YBL), Shoolini University, for supporting this project.

Funding for this work was provided by Shoolini University to K.D. to promote research under the Center for Omics and Biodiversity Research.

FOOTNOTES

    • Received 27 August 2018.
    • Accepted 24 September 2018.
    • Published 1 November 2018.
  • Copyright © 2018 Bisht et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

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16S rRNA Gene Amplicon Data Set-Based Bacterial Diversity in a Water-Soil Sample from Pangong Tso Lake, a High-Altitude Grassland Lake of the Northwest Himalayas
Garima Bisht, Anuradha Sourirajan, David J. Baumler, Kamal Dev
Microbiology Resource Announcements Nov 2018, 7 (17) e01192-18; DOI: 10.1128/MRA.01192-18

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16S rRNA Gene Amplicon Data Set-Based Bacterial Diversity in a Water-Soil Sample from Pangong Tso Lake, a High-Altitude Grassland Lake of the Northwest Himalayas
Garima Bisht, Anuradha Sourirajan, David J. Baumler, Kamal Dev
Microbiology Resource Announcements Nov 2018, 7 (17) e01192-18; DOI: 10.1128/MRA.01192-18
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