Taxonomic Attribution of “Oscillatoriales” Strains within the Bacteriological System of Cyanobacteria: Identification Algorithm for Operational Genera View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-05

AUTHORS

N. V. Velichko, M. S. Emelijanova, S. G. Averina, A. A. Pinevich, A. V. Pinevich

ABSTRACT

In “Oscillatoriales” cyanobacteria (Cyanophyceae), relatively simple and uniform morphology superimposes on high genetic diversity that impedes reliable identification. The system of Cyanobacteria set forth in Bergey’s Manual of Systematic Bacteriology-2001/Systematics of Archaea and Bacteria-2015 deals with operational taxa—form-genera (“larger” genera represented by strains) unlike true cyanophycean genera represented by species. Form-genera were established on morphological criteria shared with Cyanophyceae, although they were typified by Pasteur Culture Collection (PCC) strains. Despite being important in determinative cyanobacteriology, old diagnoses of form-genera should be reappraised because, in them: (i) vague and/or ephemeral morphological characters are considered taxonomically significant; (ii) phylogenetic character, such as 16S rRNA gene sequence (16S) is missing. We identified 32 “Oscillatoriales” strains from CALU collection (St. Petersburg University, Russia) basing on core morphology traits, 16S of PCC type strains, and 16S from GenBank database. We proposed that, in experimentally oriented and ecology oriented studies, unequivocal identification can be attained via triple match: streamlined form-genus diagnosis— 16S of PCC reference strain—GenBank most similar 16S. Additionally, we traced the phylogeny of “Oscillatoriales” form-genera via 16S clustering and HIP1 fingerprinting, and suggested that these operational taxa should be replaced with monophyletic assemblages. Nucleotide sequence data reported are available in the GenBank database under the accession numbers KX263921−KX263950. More... »

PAGES

393-406

Journal

TITLE

Microbiology

ISSUE

3

VOLUME

87

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s0026261718030141

DOI

http://dx.doi.org/10.1134/s0026261718030141

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104354732


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