Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy

Abstract

Abstract Purpose Snow and ice ecosystems present unexpectedly high microbial abundance and diversity. Although arctic and alpine snow environments have been intensively investigated from a microbiological point of view, few studies have been conducted in the Apennines. Accordingly, the main purpose of this research was to analyze the microbial communities of the snow collected in two different locations of Capracotta municipality (Southern Italy) after a snowfall record occurred on March 2015 (256 cm of snow in less than 24 h). Methods Bacterial communities were analyzed by the Next-Generation Sequencing techniques. Furthermore, a specific statistical approach for taxonomic hierarchy data was introduced, both for the assessment of diversity within microbial communities and the comparison between different microbiotas. In general, diversity and similarity indices are more informative when computed at the lowest level of the taxonomic hierarchy, the species level. This is not the case with microbial data, for which the species level is not necessarily the most informative. Indeed, the possibility to detect a large number of unclassified records at every level of the hierarchy (even at the top) is very realistic due to both the partial knowledge about the cultivable fraction of microbial communities and limitations to taxonomic assignment connected to the quality and completeness of the 16S rRNA gene reference databases. Thus, a global approach considering information from the whole taxonomic hierarchy was adopted in order to obtain a more consistent assessment of the biodiversity. Result The main phyla retrieved in the investigated snow samples were Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes. Interestingly, DNA from bacteria adapted to thrive at low temperatures, but also from microorganisms normally associated with other habitats, whose presence in the snow could be justified by wind-transport, was found. Biomolecular investigations and statistical data analysis showed relevant differences in terms of biodiversity, composition, and distribution of bacterial species between the studied snow samples. Conclusion The relevance of this research lies in the expansion of knowledge about microorganisms associated with cold environments in contexts poorly investigated such as the Italian Apennines, and in the development of a global statistical approach for the assessment of biological diversity and similarity of microbial communities as an additional tool to be usefully combined with the barcoding methods.