Yersinia canariae (NCTC 14382, LMG 31573, SRR7544370T)

Name: Yersinia canariae (NCTC 14382, LMG 31573, SRR7544370T)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 167666

Type strain

Strain Designation SRR7544370T

Culture col. no. NCTC 14382 LMG 31573 SRR7544370T

NCBI tax ID(s) 2607663

Links

Yersinia canariae SRR7544370T is a prokaryote of the family Yersiniaceae.

genome sequence 16S sequence

Name and taxonomic classification

SI-ID 366403

LMG 31573,NCTC 14382

@ref 20215

Last LPSN update 2026-02-09 11:40:38

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Enterobacterales

Family Yersiniaceae

Genus Yersinia

Species Yersinia canariae

Full scientific name Yersinia canariae Nguyen et al. 2020

BacDive ID	Other strains from **Yersinia canariae** (2)	Type strain
171333	Y. canariae CIP 111846 (type strain)
177008	Y. canariae DSM 110737, IP 37834

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	100
125439	negative	96.5

Culture and growth conditions

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	96.5

Spore formation

@ref	Spore formation	Confidence
125439		93.9
125438		90.112

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM983141v1 assembly for Yersinia canariae NCTC 14382	complete	GCA_009831415	2607663.3	2891963959	2607663	99.18

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20215	Yersinia canariae clone 5 16S ribosomal RNA gene, partial sequence	MN434987	1558		2607663

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Yersinia canariae NCTC 14382
NCBI: GCA_009831415

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	93.90	no
125439	motility	BacteriaNetⓘ	yes	74.30	no
125439	gram_stain	BacteriaNetⓘ	negative	96.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	96.50	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Yersinia canariae NCTC 14382
NCBI: GCA_009831415.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	100.00	no
125438	anaerobic	anaerobicⓘ	no	96.13	no
125438	aerobic	aerobicⓘ	no	69.67	no
125438	spore-forming	spore-formingⓘ	no	90.11	no
125438	thermophilic	thermophileⓘ	no	99.50	no
125438	flagellated	motile2+ⓘ	yes	79.60	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Contribution of Stenotrophomonas maltophilia MfsC transporter to protection against diamide and the regulation of its expression by the diamide responsive repressor DitR.	Boonyakanog A, Charoenlap N, Chattrakarn S, Vattanaviboon P, Mongkolsuk S.	PLoS One	10.1371/journal.pone.0272388	2022
	Update on Accepted Novel Bacterial Isolates Derived from Human Clinical Specimens and Taxonomic Revisions Published in 2020 and 2021.	Munson E, Carroll KC.	J Clin Microbiol	10.1128/jcm.00282-22	2023
Phylogeny	Yersinia canariae sp. nov., isolated from a human yersiniosis case.	Nguyen SV, Greig DR, Hurley D, Donoghue O, Cao Y, McCabe E, Mitchell M, Schaffer K, Jenkins C, Fanning S	Int J Syst Evol Microbiol	10.1099/ijsem.0.004047	2020

References

#20215	Parte, A.C., Sardà Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Göker, M.: List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. IJSEM ( DOI 10.1099/ijsem.0.004332 )
#66792	Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg Overmann: Automatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information) .
#125438	Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann: Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets. 2024 ( DOI 10.1101/2024.08.12.607695 )
#125439	Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardy: deepG: Deep Learning for Genome Sequence Data. R package version 0.3.1 .
#126262	A. Lissin, I. Schober, J. F. Witte, H. Lüken, A. Podstawka, J. Koblitz, B. Bunk, P. Dawyndt, P. Vandamme, P. de Vos, J. Overmann, L. C. Reimer: StrainInfo—the central database for linked microbial strain identifiers. ( DOI 10.1093/database/baaf059 )

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Yersinia canariae (NCTC 14382, LMG 31573, SRR7544370T)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Physiology and metabolism

Oxygen tolerance

Spore formation

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_009831415

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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