Počet záznamů: 1  

Artificial neural network analysis of microbial diversity in the central and southern Adriatic Sea

  1. 1.
    SYSNO ASEP0546615
    Druh ASEPJ - Článek v odborném periodiku
    Zařazení RIVJ - Článek v odborném periodiku
    Poddruh JČlánek ve WOS
    NázevArtificial neural network analysis of microbial diversity in the central and southern Adriatic Sea
    Tvůrce(i) Šantić, D. (HR)
    Piwosz, K. (PL)
    Matic, F. (HR)
    Tomas, A. V. (HR)
    Arapov, J. (HR)
    Dean, Jason Lawrence (MBU-M)
    Šolić, M. (HR)
    Koblížek, Michal (MBU-M) RID, ORCID
    Kušpilić, G. (HR)
    Šestanović, S. (HR)
    Číslo článku11186
    Zdroj.dok.Scientific Reports. - : Nature Publishing Group - ISSN 2045-2322
    Roč. 11, č. 1 (2021)
    Poč.str.15 s.
    Jazyk dok.eng - angličtina
    Země vyd.GB - Velká Británie
    Klíč. slovaaerobic anoxygenic phototrophs ; mediterranean sea ; surface waters ; picoplankton distribution ; community composition ; temporal variability ; seasonal-changes ; coastal waters ; bacteria ; bacterioplankton
    Vědní obor RIVEE - Mikrobiologie, virologie
    Obor OECDMicrobiology
    CEPGJ18-14095Y GA ČR - Grantová agentura ČR
    Způsob publikováníOpen access
    Institucionální podporaMBU-M - RVO:61388971
    UT WOS000658391200016
    EID SCOPUS85107002023
    DOI10.1038/s41598-021-90863-7
    AnotaceBacteria are an active and diverse component of pelagic communities. The identification of main factors governing microbial diversity and spatial distribution requires advanced mathematical analyses. Here, the bacterial community composition was analysed, along with a depth profile, in the open Adriatic Sea using amplicon sequencing of bacterial 16S rRNA and the Neural gas algorithm. The performed analysis classified the sample into four best matching units representing heterogenic patterns of the bacterial community composition. The observed parameters were more differentiated by depth than by area, with temperature and identified salinity as important environmental variables. The highest diversity was observed at the deep chlorophyll maximum, while bacterial abundance and production peaked in the upper layers. The most of the identified genera belonged to Proteobacteria, with uncultured AEGEAN-169 and SAR116 lineages being dominant Alphaproteobacteria, and OM60 (NOR5) and SAR86 being dominant Gammaproteobacteria. Marine Synechococcus and Cyanobium-related species were predominant in the shallow layer, while Prochlorococcus MIT 9313 formed a higher portion below 50 m depth. Bacteroidota were represented mostly by uncultured lineages (NS4, NS5 and NS9 marine lineages). In contrast, Actinobacteriota were dominated by a candidatus genus Ca. Actinomarina. A large contribution of Nitrospinae was evident at the deepest investigated layer. Our results document that neural network analysis of environmental data may provide a novel insight into factors affecting picoplankton in the open sea environment.
    PracovištěMikrobiologický ústav
    KontaktEliška Spurná, eliska.spurna@biomed.cas.cz, Tel.: 241 062 231
    Rok sběru2022
    Elektronická adresahttps://www.nature.com/articles/s41598-021-90863-7
Počet záznamů: 1  

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