Mycobacterium senuense (DSM 44999, KCTC 19147, 05-832)

Name: Mycobacterium senuense (DSM 44999, KCTC 19147, 05-832)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 8556

Type strain

Strain Designation 05-832

Culture col. no. DSM 44999 KCTC 19147 05-832 JCM 16017

NCBI tax ID(s) 386913

Special Collections DSMZ JCM KCTC Literature strains

History <- H.-J. Kim; 05-832 KCTC 19147 <-- B.-J. Kim 05-832. <- BJ Kim, Seoul Natl. Univ.

Links

Mycobacterium senuense 05-832 is an aerobe, rod-shaped bacterium that was isolated from sputum.

rod-shaped aerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 402300

JCM 16017,KCTC 19147,DSM 44999

@ref 20215

Last LPSN update 2026-02-09 11:19:44

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Mycobacteriales

Family Mycobacteriaceae

Genus Mycobacterium

Species Mycobacterium senuense

Full scientific name Mycobacterium senuense Mun et al. 2008

Synonyms (1)

Mycolicibacter senuensis

Morphology

Cell morphology

@ref	Gram stain	Confidence	Cell shape
32358			rod-shaped
67771	positive
125439	positive	94.3
125438		90.5

Pigmentation

32358

Productionno

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
12231	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)
12231	positive	growth	37
32358	positive	growth	25-37
32358	positive	optimum	37
67770	positive	growth	37
67771	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
67771	aerobe
125439	obligate aerobe	99.2

Spore formation

32358

Spore formationno

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
32358	17632 ChEBI	nitrate	+	reduction

Enzymes

@ref	Value	Activity	Ec
32358	catalase	+	1.11.1.6
32358	pyrazinamidase	+	3.5.1.B15

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host Body Product	#Fluids	#Sputum

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
12231	sputum	Seoul	Republic of Korea	KOR	Asia
67770	Human sputum	Seoul	Republic of Korea	KOR	Asia
67771	From sputum		Republic of Korea	KOR	Asia

Interaction and safety

Risk assessment

@ref	Pathogenicity human	Biosafety level	Biosafety level comment
12231	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
66792	ASM1072322v1 assembly for Mycolicibacter senuensis JCM 16017	contig	GCA_010723225	386913.12	8075428451	386913	75.04
67770	ASM210188v1 assembly for Mycolicibacter senuensis DSM 44999	contig	GCA_002101885	386913.3	2865435581	386913	66.81

16S sequences

@ref	Description	Accession	Length	NCBI tax ID
20218	Mycobacterium senuense strain DSM 44999 16S ribosomal RNA gene, partial sequence	FJ268583	512	386913
20218	Mycobacterium senuense strain DSM44999 16S ribosomal RNA gene, partial sequence	JN571174	479	386913
12231	Mycobacterium senuense strain 05-832 16S ribosomal RNA gene, partial sequence	DQ536408	1527	386913

GC content

@ref	GC-content (mol%)	Method
67770	68.7	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Mycolicibacter senuensis JCM 16017
NCBI: GCA_010723225

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	67.80	no
125439	motility	BacteriaNetⓘ	no	77.10	no
125439	gram_stain	BacteriaNetⓘ	positive	94.30	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 senuense strain DSM 44999
PATRIC: 386913.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	88.19	yes
125438	anaerobic	anaerobicⓘ	no	94.10	no
125438	spore-forming	spore-formingⓘ	no	65.36	no
125438	aerobic	aerobicⓘ	yes	83.26	yes
125438	thermophilic	thermophileⓘ	no	94.81	no
125438	flagellated	motile2+ⓘ	no	90.50	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
Phylogeny	Mycobacterium senuense sp. nov., a slowly growing, non-chromogenic species closely related to the Mycobacterium terrae complex.	Mun HS, Park JH, Kim H, Yu HK, Park YG, Cha CY, Kook YH, Kim BJ	Int J Syst Evol Microbiol	10.1099/ijs.0.65374-0	2008

References

#12231	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 44999
#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 )
#28587	IJSEM 641 2008 ( DOI 10.1099/ijs.0.65374-0 , PubMed 18319471 )
#32358	Barberan A, Caceres Velazquez H, Jones S, Fierer N.: Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information. mSphere 2: 2017 ( DOI 10.1128/mSphere.00237-17 , PubMed 28776041 ) - originally annotated from #28587
#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;
#67771	Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC;
#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 senuense (DSM 44999, KCTC 19147, 05-832)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_010723225

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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