Yersinia pestis (ATCC 19428, CIP 80.26, NCTC 5923)

Name: Yersinia pestis (ATCC 19428, CIP 80.26, NCTC 5923)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 166619

Type strain

Culture col. no. ATCC 19428 CIP 80.26 NCTC 5923

NCBI tax ID(s) 632 385964

Special Collections CIP

Links

Yersinia pestis ATCC 19428 is a bacterium of the family Yersiniaceae.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 58407

CCUG 2713,ATCC 19428,NCTC 5923,CIP 80.26

@ref 20215

Last LPSN update 2026-02-09 11:40:22

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Enterobacterales

Family Yersiniaceae

Genus Yersinia

Species Yersinia pestis

Full scientific name Yersinia pestis (Lehmann and Neumann 1896) van Loghem 1944 (Approved Lists 1980)

Synonyms (2)

"Bacterium pestis"
Yersinia pseudotuberculosis subsp. pestis

BacDive ID	Other strains from **Yersinia pestis** (1)	Type strain
146798	Y. pestis CCUG 32133, CIP 109701

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	99.735
125439	negative	96.9

Culture and growth conditions

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		98
125438		90.784

Isolation, sampling and environmental information

Taxonmaps

69479

Global distribution of 16S sequence AF366383 (>99% sequence identity) for Yersiniaceae from Microbeatlas

Aquatic Samples	5584
Soil Samples	1734
Animal Samples	23907
Plant Samples	2111
Total Samples	33336

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
20215	3	Risk group

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	57940_B01 assembly for Yersinia pestis NCTC5923	contig	GCA_900460465	632.457	8117909240	632	76.44

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20215	Yersinia pestis 16S ribosomal RNA gene, partial sequence	AF366383	1461		632

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Yersinia pestis NCTC5923
NCBI: GCA_900460465

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	98.00	no
125439	motility	BacteriaNetⓘ	yes	76.70	no
125439	gram_stain	BacteriaNetⓘ	negative	96.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	86.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Yersinia pestis strain NCTC5923
PATRIC: 632.457

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	99.74	no
125438	anaerobic	anaerobicⓘ	no	97.21	no
125438	spore-forming	spore-formingⓘ	no	90.78	no
125438	aerobic	aerobicⓘ	no	61.67	no
125438	thermophilic	thermophileⓘ	no	99.00	no
125438	flagellated	motile2+ⓘ	yes	77.44	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Enzymology	Rapid and sensitive detection of Yersinia pestis by lateral-flow assay in simulated clinical samples.	Hsu HL, Chuang CC, Liang CC, Chiao DJ, Wu HL, Wu YP, Lin FP, Shyu RH.	BMC Infect Dis	10.1186/s12879-018-3315-2	2018
Phylogeny	Francisella tularensis molecular typing using differential insertion sequence amplification.	Larson MA, Fey PD, Bartling AM, Iwen PC, Dempsey MP, Francesconi SC, Hinrichs SH.	J Clin Microbiol	10.1128/jcm.00033-11	2011
Enzymology	Detection of Francisella tularensis in biological specimens using a capture enzyme-linked immunosorbent assay, an immunochromatographic handheld assay, and a PCR.	Grunow R, Splettstoesser W, McDonald S, Otterbein C, O'Brien T, Morgan C, Aldrich J, Hofer E, Finke EJ, Meyer H.	Clin Diagn Lab Immunol	10.1128/cdli.7.1.86-90.2000	2000
	Common evolutionary origin for the unstable virulence plasmid pMUM found in geographically diverse strains of Mycobacterium ulcerans.	Stinear TP, Hong H, Frigui W, Pryor MJ, Brosch R, Garnier T, Leadlay PF, Cole ST.	J Bacteriol	10.1128/jb.187.5.1668-1676.2005	2005
Metabolism	Polypectate digestion by Yersinia.	von Riesen VL.	J Clin Microbiol	10.1128/jcm.2.6.552-553.1975	1975
	Identification of capsule-forming Bacillus anthracis spores with the PCR and a novel dual-probe hybridization format.	Reif TC, Johns M, Pillai SD, Carl M.	Appl Environ Microbiol	10.1128/aem.60.5.1622-1625.1994	1994
	Development and Inter-Laboratory Validation of Diagnostics Panel for Detection of Biothreat Bacteria Based on MOL-PCR Assay.	Jelinkova P, Hrdy J, Markova J, Dresler J, Pajer P, Pavlis O, Branich P, Borilova G, Reichelova M, Babak V, Reslova N, Kralik P.	Microorganisms	10.3390/microorganisms9010038	2020
	Bacterial phylogenetic tree construction based on genomic translation stop signals.	Xu L, Kuo J, Liu JK, Wong TY.	Microb Inform Exp	10.1186/2042-5783-2-6	2012

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) .
#69479	João F Matias Rodrigues, Janko Tackmann,Gregor Rot, Thomas SB Schmidt, Lukas Malfertheiner, Mihai Danaila,Marija Dmitrijeva, Daniela Gaio, Nicolas Näpflin and Christian von Mering. University of Zurich.: MicrobeAtlas 1.0 beta .
#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 pestis (ATCC 19428, CIP 80.26, NCTC 5923)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_900460465

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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