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.