Abstract
Snow microorganisms play a significant role in climate change and affecting the snow melting rate in the Arctic and Antarctic regions. While research on algae inhabiting green and red snow has been performed extensively, bacteria dwelling in this biotope have been studied to a much lesser extent. In this study, we performed 16S rRNA gene amplicon sequencing of two green snow samples collected from the coastal area of the eastern part of Antarctica and conducted genotypic and phenotypic profiling of 45 fast‐growing bacteria isolated from these samples. 16S rRNA gene amplicon sequencing of two green snow samples showed that bacteria inhabiting these samples are mostly represented by families Burkholderiaceae (46.31%), Flavobacteriaceae (22.98%), and Pseudomonadaceae (17.66%). Identification of 45 fast‐growing bacteria isolated from green snow was performed using 16S rRNA gene sequencing. We demonstrated that they belong to the phyla Actinobacteria and Proteobacteria, and are represented by the genera Arthrobacter, Cryobacterium, Leifsonia, Salinibacterium, Paeniglutamicibacter, Rhodococcus, Polaromonas, Pseudomonas, and Psychrobacter. Nearly all bacterial isolates exhibited various growth temperatures from 4°C to 25°C, and some isolates were characterized by a high level of enzymatic activity. Phenotyping using Fourier transform infrared (FTIR) spectroscopy revealed a possible accumulation of intracellular polymer polyhydroxyalkanoates (PHA) or lipids in some isolates. The bacteria showed different lipids/PHA and protein profiles. It was shown that lipid/PHA and protein spectral regions are the most discriminative for differentiating the isolates.
Highlights
Snow cover in the Arctic and Antarctic regions is critically important for regulating the Earth's climate and biogeochemical cycles (Maccario et al, 2019)
We performed 16S rRNA gene amplicon sequencing of two green snow samples collected from the coastal area of the eastern part of Antarctica and conducted genotypic and phenotypic profiling of 45 fast-growing bacteria isolated from these samples. 16S rRNA gene amplicon sequencing of two green snow samples showed that bacteria inhabiting these samples are mostly represented by families Burkholderiaceae (46.31%), Flavobacteriaceae (22.98%), and Pseudomonadaceae (17.66%)
An amplicon sequence 16S rRNA gene analysis of bacterial communities of two Antarctic green snow samples showed that most bacteria inhabiting G.S.S1 were bacteria from the phylum Proteobacteria (51.09%) represented by the families Burkholderiaceae (32.85%) and Pseudomonadaceae (17.66%), phylum Bacteroidetes (31.49%) represented by the family Flavobacteriaceae (22.98%), and phylum Firmicutes (12.50%) represented by the family Clostridiaceae (10.00%), while G.S.S2 was characterized by a higher content of bacteria from phylum Proteobacteria (70.70%) represented by the families Burkholderiaceae (46.31%), Pseudomonadaceae (13.93%), and Enterobacteriaceae (6.94%) and lower content of bacteria from phylum Bacteroidetes (25.16%) represented by the families Weeksellaceae (10.65%), Sphingobacteriaceae (7.35%), and Flavobacteriaceae (6.92%) and phylum Firmicutes (2.99%) represented by the family
Summary
Snow cover in the Arctic and Antarctic regions is critically important for regulating the Earth's climate and biogeochemical cycles (Maccario et al, 2019). Algal snow blooms are coloring the melted snow in red or green colors because of their red or green pigments, which are produced as a result of either photosynthesis or protection from different environmental stress conditions, for example, a high level of UV radiation (Fujii et al, 2010). In this study,whe we utilized FTIR spectroscopy combined with a high-throughput micro-cultivation system (DuetzMTPS), recently developed by our group (Shapaval et al, 2010, Kosa et al, 2017a, Kosa et al, 2018a, Dzurendova et al, 2020a) allowed performing high-throughput biochemical phenotyping of the isolated green snow Antarctic bacteria grown on agar and broth media. To study the differences in the mbiochemical profile of the Antarctic green snow bacteria, visual inspection of the spectra was performed first and multivariate analysis was applied
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