Transfer of Pectobacterium carotovorum subsp. carotovorum strains isolated from potatoes grown at high altitudes to Pectobacterium peruviense sp. nov.
Małgorzata Waleron , Agnieszka Misztak , Michał Waleron , Martyna Franczuk , Bartosz Wielgomas , Krzysztof Waleron
AbstracttSeven Gram-negative, rod-shaped pectinolytic bacteria strains designated as IFB5227, IFB5228, IFB5229,IFB5230, IFB5231, IFB5232, IFB5636, isolated from potato tubers cultivated in Peru at high altitude(2400–3800 m) were subjected to polyphasic analyses that revealed their distinctiveness from the otherPectobacterium species. Phylogenetic analyses based on five housekeeping genes (gyrA, recA, recN, rpoAand rpoS) clearly showed strains separateness, simultaneously indicating Pectobacterium atrosepticum,Pectobacterium wasabiae, Pectobacterium parmentieri and Pectobacterium betavasculorum as the closestrelatives. In silico DNA–DNA hybridization of strain IFB5232Twith other Pectobacterium type strainsrevealed significant drop in DDH value below 70%, which is a prerequisite to distinguish Pectobacteriumperuviense. The ANI values supported the proposition of delineation of the P. peruviense. Genetic REP-PCRfingerprint and detailed MALDI-TOF MS proteomic profile sealed the individuality of the studied strains.However, phenotypic assays do not indicate immense differences. Provided results of analyses performed for seven Peruvian strains are the basis for novel speciesdistinction and reclassification of the strains IFB5227-5232 and IFB5636, previously classified as Pec-tobacterium carotovorum subsp. carotovorum. Here, we propose to establish the IFB5232 isolate as a typestrain (=PCM2893T= LMG30269T= SCRI179T) with the name Pectobacterium peruviense sp. nov.
|Journal series||Systematic and Applied Microbiology, ISSN 0723-2020|
|Publication size in sheets||0.5|
|Keywords in English||MLSA, ANI, is DNA-DNA hybridization, FAME, MALDI-TOF MS, potato pathogen|
|Score|| = 30.0, 01-06-2018, ArticleFromJournal|
= 35.0, 01-06-2018, ArticleFromJournal
|Publication indicators||: 2016 = 3.931 (2) - 2016=3.739 (5)|
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