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. 2018 May 25;9:1094.
doi: 10.3389/fmicb.2018.01094. eCollection 2018.

Clean Low-Biomass Procedures and Their Application to Ancient Ice Core Microorganisms

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Free PMC article

Clean Low-Biomass Procedures and Their Application to Ancient Ice Core Microorganisms

Zhi-Ping Zhong et al. Front Microbiol. .
Free PMC article

Abstract

Microorganisms in glacier ice provide tens to hundreds of thousands of years archive for a changing climate and microbial responses to it. Analyzing ancient ice is impeded by technical issues, including limited ice, low biomass, and contamination. While many approaches have been evaluated and advanced to remove contaminants on ice core surfaces, few studies leverage modern sequencing to establish in silico decontamination protocols for glacier ice. Here we sought to apply such "clean" sampling techniques with in silico decontamination approaches used elsewhere to investigate microorganisms archived in ice at ∼41 (D41, ∼20,000 years) and ∼49 m (D49, ∼30,000 years) depth in an ice core (GS3) from the summit of the Guliya ice cap in the northwestern Tibetan Plateau. Four "background" controls were established - a co-processed sterile water artificial ice core, two air samples collected from the ice processing laboratories, and a blank, sterile water sample - and used to assess contaminant microbial diversity and abundances. Amplicon sequencing revealed 29 microbial genera in these controls, but quantitative PCR showed that the controls contained about 50-100-times less 16S DNA than the glacial ice samples. As in prior work, we interpreted these low-abundance taxa in controls as "contaminants" and proportionally removed them in silico from the GS3 ice amplicon data. Because of the low biomass in the controls, we also compared prokaryotic 16S DNA amplicons from pre-amplified (by re-conditioning PCR) and standard amplicon sequencing, and found the resulting microbial profiles to be repeatable and nearly identical. Ecologically, the contaminant-controlled ice microbial profiles revealed significantly different microorganisms across the two depths in the GS3 ice core, which is consistent with changing climate, as reported for other glacier ice samples. Many GS3 ice core genera, including Methylobacterium, Sphingomonas, Flavobacterium, Janthinobacterium, Polaromonas, and Rhodobacter, were also abundant in previously studied ice cores, which suggests wide distribution across glacier environments. Together these findings help further establish "clean" procedures for studying low-biomass ice microbial communities and contribute to a baseline understanding of microorganisms archived in glacier ice.

Keywords: clean; glacier ice; in silico decontamination; low biomass; microbial community.

Figures

FIGURE 1
FIGURE 1
Location (A), sampling sites (B), and an overview of experimental design (C) for investigating the microbial communities of the GS3 ice core drilled from the Guliya ice cap. The sample names from this study are coded as follows for the example of D41_100_A: D41, the depth of the ice sample (41 m under the surface); 100, the ice volume for DNA extraction (100 ml). Abbreviations of two methods for concentrating cells: A, Amicon Ultra Concentrators; F, filters with 0.22-μm pore size. Three samples including D41_100_A, D41_50_F, and D41_20_A were collected from the same mixture of melted ice from 41.40 to 41.84 m deep, while D49_50_F was sampled from ice 49.51–49.90 m deep.
FIGURE 2
FIGURE 2
Microbial community structure of the 29 most abundant genera in the four “background” controls. Genera belonging to the same phylum are described under the phylum name. The “other genera/families” represent unclassified sequences and could not be assigned to a single genus/family. Genera previously reported as contaminant taxa are indicated in bold. The four “background” controls: Air_ColdRoom and Air_CleanRoom, two air samples collected from a cold and clean room, respectively, in which the ice samples were processed; Artificial_ice, an artificial ice sample made by sterile water and processed along with the glacier ice samples; Blank, a blank sample with 400 ml sterile water.
FIGURE 3
FIGURE 3
Heatmap showing the sequence number of each OTU per 30,000 sequences for the Guliya ice samples and “background” controls. All OTUs accounted for >1.0% of sequences (i.e., >300 sequences) in at least one sample. OTUs were defined as reads with 97% sequence similarity.
FIGURE 4
FIGURE 4
Microbial community structure of the 13 most abundant genera in the GS3 ice core samples. The “others” represent unclassified sequences and could not be assigned to a single genus.
FIGURE 5
FIGURE 5
Relationships between individual samples illustrated by PCoA plots (A) and UniFrac tree (UPGMA, B). Both analyses were performed on the basis of the weighted UniFrac metric. Symbols of the same color indicate samples from the same glacier/ice core: blue color, GS3; red, Geladangdong (GLDD) Glacier; green, Noijinkangsang (NJKS) Glacier; purple, Zuoqiupu (ZQP) Glacier; orange, North Greenland Eemian Ice Drilling (NEEM) ice core.

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