Mycobacterium alsense (DSM 45230, CCUG 56586, TB 1906)

Name: Mycobacterium alsense (DSM 45230, CCUG 56586, TB 1906)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131575

Type strain

Strain Designation TB 1906

Culture col. no. DSM 45230 CCUG 56586 TB 1906 CCUG 55640 JCM 32215

NCBI tax ID(s) 324058

Special Collections DSMZ CCUG JCM Literature strains

History <- E. Richter,Forschungszentrum Borstel; TB 1906 <- Microbiology, Univ. Kiel <- S. Schubert CCUG 56586 <-- E. Richter; Natl. Ref. Center for Mycobacteria, Res. Center Borstel, Germany; TB 1906 <-- S. Schubert; Univ. of Kiel, Germany.

Links

Mycobacterium alsense TB 1906 is a mesophilic prokaryote that was isolated from sputum of patient with pulmonary disorder.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 397635

CT2017-00319,DSM 45230,CCUG 56586,CCUG 55640

@ref 20215

Last LPSN update 2026-02-09 11:31:30

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Mycobacteriales

Family Mycobacteriaceae

Genus Mycobacterium

Species Mycobacterium alsense

Full scientific name Mycobacterium alsense Tortoli et al. 2016

Synonyms (1)

"Mycobacterium alsiense"

Morphology

Cell morphology

@ref	Gram stain	Confidence	Motility
44061
125439	positive	91.8

Colony morphology

@ref	Colony color	Incubation period	Medium used
44061	pale-yellow	14 days	solid media

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
44061	solid media
22802	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
22802	positive	growth	37	mesophilic
44061	positive	growth	25-37	mesophilic
67770	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	98.6

Spore formation

@ref	Type of spore	Spore formation
44061	spore

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
44061	17632 ChEBI	nitrate	-	reduction
44061	53426 ChEBI	tween 80	-	hydrolysis

Enzymes

@ref	Value	Activity	Ec
44061	arylsulfatase	-	3.1.6.1
44061	beta-glucosidase	-	3.2.1.21
44061	urease	-	3.5.1.5

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host Body-Site	#Oral cavity and airways	#Airways
#Host Body Product	#Fluids	#Sputum
#Infection	#Patient	-

Isolation

@ref	Sample type	Sampling date	Country	Country ISO 3 Code	Continent
22802	sputum of patient with pulmonary disorder		Denmark	DNK	Europe
44061	sputum of patients with pulmonary disorder	2007	Denmark	DNK	Europe
67770	Sputum of a patient with a pulmonary disorder		Denmark	DNK	Europe

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
22802	2	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM2582320v1 assembly for Mycobacterium alsense CCUG 55640	contig	GCA_025823205	324058.7	8111687944	324058	71.32
67770	ASM208663v1 assembly for Mycobacterium alsense DSM 45230	contig	GCA_002086635	324058.3	8113349196	324058	46.2

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
22802	Mycobacterium alsense 16S rRNA gene, type strain TB 1906T	AJ938169	1535		324058

GC content

@ref	GC-content (mol%)	Method
67770	69.3	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Mycobacterium alsense DSM 45230
NCBI: GCA_002086635

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	61.40	no
125439	motility	BacteriaNetⓘ	no	64.70	no
125439	gram_stain	BacteriaNetⓘ	positive	91.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	98.60	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Mycobacterium alsense strain DSM 45230
PATRIC: 324058.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	87.49	no
125438	anaerobic	anaerobicⓘ	no	96.02	no
125438	spore-forming	spore-formingⓘ	no	63.80	no
125438	aerobic	aerobicⓘ	yes	73.94	no
125438	thermophilic	thermophileⓘ	no	94.50	no
125438	flagellated	motile2+ⓘ	no	87.00	yes

Literature

Topic	Title	Authors	Journal	DOI	Year
	The PE/PPE family proteins of Mycobacterium tuberculosis: evolution, function, and prospects for tuberculosis control.	Zhang Z, Dong L, Li X, Deng T, Wang Q.	Front Immunol	10.3389/fimmu.2025.1606311	2025
Phylogeny	Mycobacterium alsense sp. nov., a scotochromogenic slow grower isolated from clinical respiratory specimens.	Tortoli E, Richter E, Borroni E, Cabibbe AM, Capitolo E, Cittaro D, Engel R, Hendricks O, Hillemann D, Kristiansen JE, Mariottini A, Schubert S, Cirillo DM	Int J Syst Evol Microbiol	10.1099/ijsem.0.000744	2015

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 )
#22802	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 45230
#44061	Enrico Tortoli, Elvira Richter, Emanuele Borroni, Andrea M. Cabibbe, Eleonora Capitolo, Davide Cittaro, Regina Engel, Oliver Hendricks, Doris Hillemann, Jette E. Kristiansen, Alessandro Mariottini, Sabine Schubert and Daniela M. Cirillo: Mycobacterium alsense sp. nov., a scotochromogenic slow grower isolated from clinical respiratory specimens. IJSEM 66: 450 - 455 2016 ( DOI 10.1099/ijsem.0.000744 , PubMed 26545358 )
#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;
#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 alsense (DSM 45230, CCUG 56586, TB 1906)

Name and taxonomic classification

Morphology

Cell morphology

Colony morphology

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_025823205

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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