Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy
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 r...
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Online Access: | http://hdl.handle.net/11695/95811 https://doi.org/10.1186/s13213-020-01604-6 https://link.springer.com/article/10.1186/s13213-020-01604-6 |
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ftunivmoliseiris:oai:iris.unimol.it:11695/95811 2024-04-14T08:08:31+00:00 Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy Pamela Monaco Fabio Divino Gino Naclerio Antonio Bucci Monaco, Pamela Divino, Fabio Naclerio, Gino Bucci, Antonio 2020 http://hdl.handle.net/11695/95811 https://doi.org/10.1186/s13213-020-01604-6 https://link.springer.com/article/10.1186/s13213-020-01604-6 eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000588090700001 volume:70 issue:63 numberofpages:11 journal:ANNALS OF MICROBIOLOGY http://hdl.handle.net/11695/95811 doi:10.1186/s13213-020-01604-6 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85095696216 https://link.springer.com/article/10.1186/s13213-020-01604-6 Snow Microbial communities Next-Generation Sequencing Record snowfall Diversity indices Similarity indices info:eu-repo/semantics/article 2020 ftunivmoliseiris https://doi.org/10.1186/s13213-020-01604-6 2024-03-21T18:08:48Z 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 ... Article in Journal/Newspaper Arctic Università degli Studi del Molise: IRIS Arctic Annals of Microbiology 70 1 |
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Open Polar |
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Università degli Studi del Molise: IRIS |
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ftunivmoliseiris |
language |
English |
topic |
Snow Microbial communities Next-Generation Sequencing Record snowfall Diversity indices Similarity indices |
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Snow Microbial communities Next-Generation Sequencing Record snowfall Diversity indices Similarity indices Pamela Monaco Fabio Divino Gino Naclerio Antonio Bucci Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy |
topic_facet |
Snow Microbial communities Next-Generation Sequencing Record snowfall Diversity indices Similarity indices |
description |
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 ... |
author2 |
Monaco, Pamela Divino, Fabio Naclerio, Gino Bucci, Antonio |
format |
Article in Journal/Newspaper |
author |
Pamela Monaco Fabio Divino Gino Naclerio Antonio Bucci |
author_facet |
Pamela Monaco Fabio Divino Gino Naclerio Antonio Bucci |
author_sort |
Pamela Monaco |
title |
Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy |
title_short |
Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy |
title_full |
Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy |
title_fullStr |
Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy |
title_full_unstemmed |
Microbial community analysis with a specific statistical approach after a record breaking snowfall in Southern Italy |
title_sort |
microbial community analysis with a specific statistical approach after a record breaking snowfall in southern italy |
publishDate |
2020 |
url |
http://hdl.handle.net/11695/95811 https://doi.org/10.1186/s13213-020-01604-6 https://link.springer.com/article/10.1186/s13213-020-01604-6 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000588090700001 volume:70 issue:63 numberofpages:11 journal:ANNALS OF MICROBIOLOGY http://hdl.handle.net/11695/95811 doi:10.1186/s13213-020-01604-6 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85095696216 https://link.springer.com/article/10.1186/s13213-020-01604-6 |
op_doi |
https://doi.org/10.1186/s13213-020-01604-6 |
container_title |
Annals of Microbiology |
container_volume |
70 |
container_issue |
1 |
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1796305942291152896 |