Cite this strain

Cutibacterium acnes subsp. elongatum (NCTC 13655, JCM 18919)

Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 162345

Type strain

Culture col. no. NCTC 13655 JCM 18919

NCBI tax ID(s) 1734926

Special Collections JCM

Links

Name and taxonomic classification

Cutibacterium acnes subsp. elongatum JCM 18919 is a mesophilic bacterium that was isolated from Non-eczematous face skin of atopic dermatitis patient.

mesophilic genome sequence 16S sequence Bacteria

Culture Collection Numbers

NCTC 13655 JCM 18919

Last LPSN update 2024-12-09 10:52:32

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Propionibacteriales

Family Propionibacteriaceae

Genus Cutibacterium

Species Cutibacterium acnes subsp. elongatum

Full scientific name Cutibacterium acnes subsp. elongatum (Dekio et al. 2015) Dekio et al. 2019

Synonyms (1)

Propionibacterium acnes subsp. elongatum

BacDive ID	Other strains from **Cutibacterium acnes subsp. elongatum** (2)	Type strain
162335	C. acnes subsp. elongatum JCM 18909
162351	C. acnes subsp. elongatum JCM 18925

Morphology

Cell morphology

@ref	Motility	Confidence
125438		91.5
125439		90.9

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	37	mesophilic

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		97

Isolation, sampling and environmental information

Isolation

67770

Sample typeNon-eczematous face skin of atopic dermatitis patient

Taxonmaps

69479

Global distribution of 16S sequence AB777861 (>99% sequence identity) for Cutibacterium acnes from Microbeatlas

Aquatic Samples	7473
Soil Samples	3573
Animal Samples	47966
Plant Samples	1257
Total Samples	60269

Safety information

Sequence information

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Cutibacterium acnes gene for 16S ribosomal RNA, partial sequence, strain: K124	AB777861	1252		1734926

Genome sequences

@ref	Description	Accession	Assembly level	Database	NCBI tax ID
66792	Cutibacterium acnes strain JCM 18919 strain K124	1747.233	wgs	PATRIC	1747
67770	Cutibacterium acnes subsp. elongatum K124	GCA_003131265	contig		1734926

Genome-based predictions

Predictions

Predictions from Diaspora project based on:
Cutibacterium acnes subsp. elongatum K124
NCBI: GCA_003131265

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	97.00	no
125439	motility	BacteriaNetⓘ	no	77.30	no
125439	gram_stain	BacteriaNetⓘ	positive	90.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	83.60	no

Predictions from Diaspora project based on:
Cutibacterium acnes strain JCM 18919 strain K124
PATRIC: 1747.233

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	84.56	no
125438	anaerobic	anaerobicⓘ	no	66.57	no
125438	spore-forming	spore-formingⓘ	no	76.20	no
125438	aerobic	aerobicⓘ	no	64.46	no
125438	thermophilic	thermophileⓘ	no	90.50	no
125438	flagellated	motile2+ⓘ	no	91.50	no

External links

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Proposal of new combination, Cutibacterium acnes subsp. elongatum comb. nov., and emended descriptions of the genus Cutibacterium, Cutibacterium acnes subsp. acnes and Cutibacterium acnes subsp. defendens.	Dekio I, McDowell A, Sakamoto M, Tomida S, Ohkuma M	Int J Syst Evol Microbiol	10.1099/ijsem.0.003274	2019

Culture collection no.

Culture collection no.
NCTC 13655
JCM 18919

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) .
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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 .

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