Mycobacterium kumamotonense (DSM 45093, CCUG 51961, GTC 2729)

Name: Mycobacterium kumamotonense (DSM 45093, CCUG 51961, GTC 2729)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 8555

Type strain

Culture col. no. DSM 45093 CCUG 51961 GTC 2729 JCM 13453 CST 7247

NCBI tax ID(s) 354243

Special Collections DSMZ CCUG JCM

Links

Mycobacterium kumamotonense DSM 45093 is an aerobe, mesophilic prokaryote that was isolated from sputa of a 57-year old Japanes woman.

aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 297259

CCUG 51961,JCM 13453,DSM 45093

@ref 20215

Last LPSN update 2025-12-16 09:48:52

Domain Bacillati

Phylum Actinomycetota

Class Actinomycetes

Order Mycobacteriales

Family Mycobacteriaceae

Genus Mycobacterium

Species Mycobacterium kumamotonense

Full scientific name Mycobacterium kumamotonense Masaki et al. 2007

Synonyms (1)

Mycolicibacter kumamotonensis

BacDive ID	Other strains from **Mycobacterium kumamotonense** (2)	Type strain
154840	M. kumamotonense CCUG 55375
155130	M. kumamotonense CCUG 56547

Morphology

Cell morphology

@ref	Motility	Confidence
125438		92

Colony morphology

59384

Incubation period7-10 days

Multimedia

@ref:	12335
multimedia content:	DSM_45093.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_45093.jpg
caption:	Medium 645 37°C
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
12335	MIDDLEBROOK MEDIUM (DSMZ Medium 645)		Medium recipe at MediaDive	Name: MIDDLEBROOK MEDIUM (DSMZ Medium 645) Composition: Bacto Middlebrook 7H10 agar 20.9945 g/l Glycerol Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
12335	positive	growth	37	mesophilic
59384	positive	growth	35	mesophilic
67770	positive	growth	35	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance
59384	aerobe
59384	microaerophile
125439	obligate aerobe

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68369	29016 ChEBI	arginine	-	hydrolysis	from API 20NE
68369	17634 ChEBI	D-glucose	-	assimilation	from API 20NE
68369	17634 ChEBI	D-glucose	-	fermentation	from API 20NE
68369	16899 ChEBI	D-mannitol	-	assimilation	from API 20NE
68369	16024 ChEBI	D-mannose	-	assimilation	from API 20NE
68369	27689 ChEBI	decanoate	-	assimilation	from API 20NE
68369	4853 ChEBI	esculin	-	hydrolysis	from API 20NE
68369	5291 ChEBI	gelatin	-	hydrolysis	from API 20NE
68369	30849 ChEBI	L-arabinose	-	assimilation	from API 20NE
68369	25115 ChEBI	malate	-	assimilation	from API 20NE
68369	17306 ChEBI	maltose	-	assimilation	from API 20NE
68369	59640 ChEBI	N-acetylglucosamine	-	assimilation	from API 20NE
68369	27897 ChEBI	tryptophan	-	energy source	from API 20NE
68369	16199 ChEBI	urea	-	hydrolysis	from API 20NE

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68369	35581 ChEBI	indole		from API 20NE

Metabolite tests

@ref	Chebi-ID	Metabolite	Indole test
68369	35581 ChEBI	indole	-	from API 20NE

Enzymes

@ref	Value	Activity	Ec
68369	arginine dihydrolase	-	3.5.3.6	from API 20NE
68369	beta-glucosidase	-	3.2.1.21	from API 20NE
68369	gelatinase	-		from API 20NE
68369	urease	-	3.5.1.5	from API 20NE

API 20NE

@ref	Reduction of nitratesNO3	TRP	GLU_ Ferm	ADH (Arg)	URE	ESC	GEL	PNPG	GLU_ Assim	ARA	MNE	MAN	NAG	MAL	GNT	CAP	ADI	MLT	CIT	PAC	OX
12335	+/-	-	-	-	-	-	-	-	-	-	-	-	-	-	+/-	-	+/-	-	-	-	not determinedn.d.

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Human	#Female
#Host Body Product	#Fluids	#Sputum

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
12335	sputa of a 57-year old Japanes woman	Kumamoto Prefecture	Japan	JPN	Asia
59384	Human sputum,57-yr-old female Japanese	Kumamoto	Japan	JPN	Asia
67770	Sputum of a 57-year-old Japanese woman with abnormal shadow by indirect X-ray

Taxonmaps

69479

Global distribution of 16S sequence AB239925 (>99% sequence identity) for Mycolicibacter from Microbeatlas

Aquatic Samples	718
Soil Samples	1498
Animal Samples	445
Plant Samples	80
Total Samples	2741

Interaction and safety

Risk assessment

@ref	Pathogenicity human	Biosafety level	Biosafety level comment
12335	yes, in single cases	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM208628v1 assembly for Mycolicibacter kumamotonensis DSM 45093	contig	GCA_002086285	354243.4	8066189206	354243	51.66
67770	ASM1009349v1 assembly for Mycolicibacter kumamotonensis CST 7247	scaffold	GCA_010093495	354243.11	8117009577	354243	10.77

Genome browser: GCA_002086285

16S sequences

@ref	Description	Accession	Length	NCBI tax ID
20218	Mycobacterium kumamotonense strain CCUG 51961 16S ribosomal RNA gene, partial sequence	EU191911	471	354243
20218	Mycobacterium kumamotonense strain DSM45093 16S ribosomal RNA gene, partial sequence	JN571176	479	354243
12335	Mycobacterium kumamotonense gene for 16S rRNA, partial sequence, strain:CST7274 (= GTC2729)	AB239925	1434	354243

GC content

@ref	GC-content (mol%)
12335	51.19
67770	67.4
67770	68.1

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Mycolicibacter kumamotonensis CST 7247
NCBI: GCA_010093495

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	71.40	no
125439	motility	BacteriaNetⓘ	no	59.10	no
125439	gram_stain	BacteriaNetⓘ	positive	85.70	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.20	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Mycobacterium kumamotonense strain DSM 45093
PATRIC: 354243.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	87.50	no
125438	anaerobic	anaerobicⓘ	no	93.80	yes
125438	spore-forming	spore-formingⓘ	no	66.89	no
125438	aerobic	aerobicⓘ	yes	83.65	no
125438	thermophilic	thermophileⓘ	no	95.92	yes
125438	flagellated	motile2+ⓘ	no	92.00	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Phylogenomics and Comparative Genomic Studies Robustly Support Division of the Genus Mycobacterium into an Emended Genus Mycobacterium and Four Novel Genera.	Gupta RS, Lo B, Son J.	Front Microbiol	10.3389/fmicb.2018.00067	2018
Phylogeny	Microbiological features and clinical relevance of new species of the genus Mycobacterium.	Tortoli E.	Clin Microbiol Rev	10.1128/cmr.00035-14	2014
	Pulmonary Mycobactetrium kumamotonense With Hepatosplenic Dissemination in an Immunocompetent Patient: A Case Report and Review.	Wang MS, Chang J, Whelan T, Liu B, Fitton K, Grondin JJ.	J Community Hosp Intern Med Perspect	10.55729/2000-9666.1503	2025
	A rare infective cause for recurrent exacerbations and poor asthma control - Mycobacterium kumamotonense.	Marshall BG, Keyvani P, Martineau AR.	JRSM Open	10.1177/20542704221124013	2022
	Organization and Characterization of the Promoter Elements of the rRNA Operons in the Slow-Growing Pathogen Mycobacterium kumamotonense.	Sanchez-Estrada R, Mendez-Guerrero O, Garcia-Morales L, Gonzalez-Y-Merchand JA, Cerna-Cortes JF, Menendez MC, Garcia MJ, Leon-Solis LE, Rivera-Gutierrez S.	Genes (Basel)	10.3390/genes14051023	2023
Phylogeny	Mycobacterium kumamotonense in the cervical region in an immunocompetent patient, clinical case report in Mexico.	Solis AH, Gonzalez-Villa M, Ramirez-Gonzalez JE, Colin-Munoz Y, Cicero-Sabido R.	J Infect Dev Ctries	10.3855/jidc.11935	2019
Phylogeny	Soft tissue infection caused by Mycolicibacter kumamotonensis.	Iemura-Kashiwagi M, Ito I, Ikeguchi R, Kadoya M, Iemura T, Yoshida S, Suzuki K, Hirai T.	J Infect Chemother	10.1016/j.jiac.2019.06.013	2020
	Microbiological profile of slow-growing non-tuberculous mycobacteria species other than Mycobacterium avium complex.	Fernandez-Pittol M, Batista S, Narvaez S, Roman A, San Nicolas L, Martinez D, Oliver L, Gonzalez-Moreno O, Martinez JA, Garcia F, Amaro-Rodriguez R, Soler N, Gene A, Gonzalez-Cuevas A, Tudo G, Gonzalez-Martin J.	Front Microbiol	10.3389/fmicb.2025.1572162	2025
Enzymology	Isolation of Mycobacterium kumamotonense from a patient with pulmonary infection and latent tuberculosis.	Kontos F, Mavromanolakis DN, Zande MC, Gitti ZG.	Indian J Med Microbiol	10.4103/0255-0857.180356	2016
	A case of novel, rapidly-growing Mycolicibacter kumamotonensis infection in a patient with severe pulmonary disease treated in New York City.	Weidmann MD, Wu Y, Wu F, Hapani DD, Green DA, Aaron JG, Berry GJ.	BMC Infect Dis	10.1186/s12879-022-07959-2	2023
Enzymology	[Identification of Mycobacterium spp. isolates using matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS)].	Amlerova J, Studentova V, Hrabak J.	Epidemiol Mikrobiol Imunol		2014
	Evaluation of MALDI Biotyper Mycobacteria Library for Identification of Nontuberculous Mycobacteria.	Toney NC, Zhu W, Jensen B, Gartin J, Anderson K, Lonsway D, Karlsson M, Rasheed JK.	J Clin Microbiol	10.1128/jcm.00217-22	2022
Enzymology	Mycobacterium arupense in Cancer Patients: An Emerging Infection or a Commensal Organism.	Al Hamal Z, Jordan M, Hachem RY, Alawami HM, Alburki AM, Yousif A, Deshmukh P, Jiang Y, Chaftari AM, Raad II.	Medicine (Baltimore)	10.1097/md.0000000000002691	2016
	A post-mortem study of respiratory disease in small mustelids in south-west England.	Simpson VR, Tomlinson AJ, Stevenson K, McLuckie JA, Benavides J, Dagleish MP.	BMC Vet Res	10.1186/s12917-016-0693-9	2016
Phylogeny	Utility of rpoB gene sequencing for identification of nontuberculous mycobacteria in the Netherlands.	de Zwaan R, van Ingen J, van Soolingen D.	J Clin Microbiol	10.1128/jcm.00233-14	2014
Genetics	Characterization of mycobacteria and mycobacteriophages isolated from compost at the São Paulo Zoo Park Foundation in Brazil and creation of the new mycobacteriophage Cluster U.	Lima-Junior JD, Viana-Niero C, Conde Oliveira DV, Machado GE, Rabello MC, Martins-Junior J, Martins LF, Digiampietri LA, da Silva AM, Setubal JC, Russell DA, Jacobs-Sera D, Pope WH, Hatfull GF, Leao SC.	BMC Microbiol	10.1186/s12866-016-0734-3	2016
Genetics	Genome-Based Taxonomic Classification of the Phylum Actinobacteria.	Nouioui I, Carro L, Garcia-Lopez M, Meier-Kolthoff JP, Woyke T, Kyrpides NC, Pukall R, Klenk HP, Goodfellow M, Goker M.	Front Microbiol	10.3389/fmicb.2018.02007	2018
Phylogeny	Mycobacterium kumamotonense Sp. Nov. recovered from clinical specimen and the first isolation report of Mycobacterium arupense in Japan: Novel slowly growing, nonchromogenic clinical isolates related to Mycobacterium terrae complex.	Masaki T, Ohkusu K, Hata H, Fujiwara N, Iihara H, Yamada-Noda M, Nhung PH, Hayashi M, Asano Y, Kawamura Y, Ezaki T	Microbiol Immunol	10.1111/j.1348-0421.2006.tb03865.x	2006
Phylogeny	Survey of 150 strains belonging to the Mycobacterium terrae complex and description of Mycobacterium engbaekii sp. nov., Mycobacterium heraklionense sp. nov. and Mycobacterium longobardum sp. nov.	Tortoli E, Gitti Z, Klenk HP, Lauria S, Mannino R, Mantegani P, Mariottini A, Neonakis I.	Int J Syst Evol Microbiol	10.1099/ijs.0.038737-0	2013
Phylogeny	Mycobacterium arupense, Mycobacterium heraklionense, and a Newly Proposed Species, "Mycobacterium virginiense" sp. nov., but Not Mycobacterium nonchromogenicum, as Species of the Mycobacterium terrae Complex Causing Tenosynovitis and Osteomyelitis.	Vasireddy R, Vasireddy S, Brown-Elliott BA, Wengenack NL, Eke UA, Benwill JL, Turenne C, Wallace RJ.	J Clin Microbiol	10.1128/jcm.00198-16	2016

References

#12335	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 45093
#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 )
#20218	Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.: StrainInfo introduces electronic passports for microorganisms.. Syst Appl Microbiol. 37: 42 - 50 2014 ( DOI 10.1016/j.syapm.2013.11.002 , PubMed 24321274 )
#59384	Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 51961
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#68369	Automatically annotated from API 20NE .
#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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Mycobacterium kumamotonense (DSM 45093, CCUG 51961, GTC 2729)

Name and taxonomic classification

Morphology

Cell morphology

Colony morphology

Multimedia

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Metabolite utilization

Metabolite production

Metabolite tests

Enzymes

API 20NE

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_002086285

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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