Mycobacterium aichiense (DSM 44147, 49005, ATCC 27280)

Name: Mycobacterium aichiense (DSM 44147, 49005, ATCC 27280)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 8441

Type strain

Strain Designation 49005

Culture col. no. DSM 44147 49005 ATCC 27280 JCM 6376 NCTC 10820 3 more

NCBI tax ID(s) 1799

Special Collections DSMZ CCUG JCM CIP Wink compendium

History DSMZ <- P. Sander (Medizin. Hochschule Hannover) <- ATCC <- M. Tsukamura, 5545 JCM <-- M. Tsukamura 49005. CIP <- 2000, JCM <- M. Tsukamura: strain 49005

Links

Mycobacterium aichiense 49005 is an aerobe, Gram-positive, rod-shaped bacterium that was isolated from soil.

Gram-positive rod-shaped aerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 13224

LMG 19259,ATCC 27280,DSM 44147,JCM 6376,NCTC 10820,CCUG 37672,CIP 106808,CNCTC 7255

@ref 20215

Last LPSN update 2026-05-29 08:26:52

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Mycobacteriales

Family Mycobacteriaceae

Genus Mycobacterium

Species Mycobacterium aichiense

Full scientific name Mycobacterium aichiense (ex Tsukamura 1973) Tsukamura 1981

Synonyms (1)

Mycolicibacterium aichiense

Morphology

Cell morphology

@ref	Gram stain	Cell shape	Motility	Confidence
116165	positive	rod-shaped
125439	positive			94.736

Colony morphology

@ref	Colony color	Incubation period	Medium used
19844	Beige	10-14 days	5006
19844	Beige	10-14 days	BHI
19844	Beige	10-14 days	BUG
19844	Beige	10-14 days	MB7H9

Multimedia

@ref:	11524
multimedia content:	DSM_44147.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_44147.jpg
caption:	Medium 645 37°C
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Medium link	Composition
11524	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
19844	BUG
19844	BHI
19844	5006		Medium: 5006 Name: Composition (g/l) Sucrose 3,0 Dextrin 15,0 Meat extract 1,0 Yeast extract 2,0 Tryptone soy broth (Oxoid) 5,0 NaCl 0,5 K2HPO4 0,5 MgSO4 x 7 H2O 0,5 FeSO4 x 7 H2O 0,01 Agar 20,0 Preparation: Sterilisation: 20 minutes at 121°C pH before sterilisation: 7,3 Usage: Maintenance Organisms: All Actinomycetes
19844	MB7H9		Name: Middlebrook 7H9 (MB7H9) Broth Base Composition: Middelbrook 7H9 Broth Base 4.7 g/l Glycerol 2.0 g/l Casaminoacids 11.0 g/l Yeast extract 5.5 g/l Tween80 (20%) 2.5 g/l OADC-Enrichment 100 ml Agar 15.0 g/l Preparation: Dissolve in Milli-Q-H2O. Before Use add 10% OADC stock solution Sterilisation: 20 minutes at 121°C pH before sterilisation: Usage: Maintenance and revitalization Organisms: Mycobacteria OADC stock solution old broth-name: OADC-Stock Composition: Bovine Serum Albumin, fraction V 5 % 1% Oleic Acid in 0.2N NaOH 5ml Glucose 2 % NaCl 0.85 % Comments: Melt 1% Oleic Acid in 65°C water bath. Dissolve all ingredients in 700ml of ddH2O. Adjust volume to 1L. Filter sterilize and store at 4°C. -To make 1% Oleic Acid in 0.2N NaOH: Dissolve 5g oleic acid (ampule) in 500ml 0.2N NaOH (300ml ddH2O + 20ml NaOH + adjust volume to 500ml). Heat solution to 55°C for oleic acid to melt. Store at -20°C in 50ml aliquots. There is no need to sterilize this. Sterilisation: 20 minutes Temperature:121°C PH before: PH after: Biological details Culture type: suitable for: Mycobacteria
36367	MEDIUM 112 - for Janibacter		Distilled water make up to (1000.000 ml);Magnesium sulphate heptahydrate (1.000 g);Agar (20.000 g);Yeast extract (5.000 g);Peptone (10.000 g);Tween 80 (50.000 mg);Glycerol (2.000 g);Malt extract (5.000 g);Beef extract (2.000 g);Casamino acids (5.000 g);Ca
116165	CIP Medium 112	Medium recipe at CIP

Culture temp

@ref	Growth	Type	Temperature (°C)
11524	positive	growth	37
19844	positive	optimum	37
36367	positive	growth	37
53799	positive	growth	30-37
67770	positive	growth	37
116165	positive	growth	22-37
116165	negative	growth	10
116165	negative	growth	45

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
53799	aerobe
53799	microaerophile
125439	obligate aerobe	97.961

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
116165	606565 ChEBI	hippurate	-	hydrolysis
116165	17632 ChEBI	nitrate	-	reduction
116165	17632 ChEBI	nitrate	-	respiration
116165	16301 ChEBI	nitrite	-	reduction

Metabolite production

@ref	Chebi-ID	Metabolite	Production
116165	35581 ChEBI	indole

Enzymes

@ref	Value	Activity	Ec
68382	acid phosphatase	+	3.1.3.2	from API zym
68382	alkaline phosphatase	+	3.1.3.1	from API zym
68382	alpha-chymotrypsin	-	3.4.21.1	from API zym
68382	alpha-fucosidase	-	3.2.1.51	from API zym
68382	alpha-galactosidase	-	3.2.1.22	from API zym
68382	alpha-glucosidase	+	3.2.1.20	from API zym
68382	alpha-mannosidase	-	3.2.1.24	from API zym
68382	beta-galactosidase	-	3.2.1.23	from API zym
116165	beta-galactosidase	+	3.2.1.23
68382	beta-glucosidase	-	3.2.1.21	from API zym
68382	beta-glucuronidase	-	3.2.1.31	from API zym
116165	catalase	+	1.11.1.6
68382	cystine arylamidase	-	3.4.11.3	from API zym
68382	esterase (C 4)	+		from API zym
68382	esterase lipase (C 8)	+		from API zym
116165	gamma-glutamyltransferase	-	2.3.2.2
116165	gelatinase	-
68382	leucine arylamidase	+	3.4.11.1	from API zym
68382	lipase (C 14)	-		from API zym
68382	N-acetyl-beta-glucosaminidase	-	3.2.1.52	from API zym
68382	naphthol-AS-BI-phosphohydrolase	+		from API zym
116165	oxidase	-
68382	trypsin	-	3.4.21.4	from API zym
116165	urease	-	3.5.1.5
68382	valine arylamidase	-		from API zym

API zym

@ref	Control	Alkaline phosphatase	Esterase (C 4)	2-naphtyl caprylateEsterase Lipase (C 8)	Lipase (C 14)	L-leucyl-2-naphthylamideLeucine arylamidase	L-valyl-2-naphthylamideValine arylamidase	L-cystyl-2-naphthylamideCystine arylamidase	Trypsin	alpha- Chymotrypsin	Acid phosphatase	Naphthol-AS-BI-phosphateNaphthol-AS-BI-phosphohydrolase	alpha- Galactosidase	beta- Galactosidase	beta- Glucuronidase	alpha- Glucosidase	beta- Glucosidase	N-acetyl-beta- glucosaminidase	alpha- Mannosidase	alpha- Fucosidase
116165	-	+	+	+	-	+	-	-	-	-	+	+	-	-	-	+	-	-	-	-

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
11524	soil
53799	Soil
67770	Soil	Aichi Pref.	Japan	JPN	Asia
116165	Environment, Soil

Taxonmaps

69479

Global distribution of 16S sequence X55598 (>99% sequence identity) for Mycolicibacterium from Microbeatlas

Aquatic Samples	31
Soil Samples	136
Animal Samples	53
Plant Samples	152
Total Samples	372

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
11524	1	Risk group (German classification) According to TRBA 466
19844	1	Risk group (German classification) According to TRBA 466
116165	1	Risk group (French 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	ASM1072624v1 assembly for Mycolicibacterium aichiense JCM 6376	complete	GCA_010726245	1799.7	8110605888	1799	99.15
67770	49677_D01 assembly for Mycolicibacterium aichiense NCTC10820	contig	GCA_900453085	1799.5	2856228341	1799	78.69
66792	ASM2582221v1 assembly for Mycolicibacterium aichiense DSM 44147	contig	GCA_025822215	1799.10	8115256120	1799	62.37

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	M.aichiense 16S ribosomal RNA, part	X55598	1456		1799
20218	Mycobacterium aichiense strain DSM 44147 16S ribosomal RNA gene, partial sequence	AF547894	539		1799

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1072624v1 assembly for Mycolicibacterium aichiense JCM 6376
BV-BRC: 1799.7

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	97.96	no
125439	gram_stain	BacteriaNetⓘ	positive	94.74	no
125439	motility	BacteriaNetⓘ	no	89.72	no
125439	spore_formation	BacteriaNetⓘ	yes	35.58	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Mycolicibacterium aichiense JCM 6376
NCBI: GCA_010726245.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	89.70	no
125438	anaerobic	anaerobicⓘ	no	97.01	no
125438	aerobic	aerobicⓘ	yes	89.79	no
125438	spore-forming	spore-formingⓘ	no	54.77	no
125438	thermophilic	thermophileⓘ	no	96.00	yes
125438	flagellated	motile2+ⓘ	no	85.46	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
	Whole-Genome Sequencing of Alcaligenes faecalis HZ01, with Potential to Inhibit Nontuberculous Mycobacterial Growth.	Fernandes HMZ, Conceicao EC, da Silva SP, Machado E, Sisco MC, Sharma A, Lima KVB, da Conceicao ML, da Silva Carvalho AC, Miranda KR, Silva Duarte R, Alviano DS, da Silva Dias RC.	Microbiol Resour Announc	10.1128/mra.00521-21	2021
	In Vitro Activity of the Sudapyridine (WX-081) against Non-Tuberculous Mycobacteria Isolated in Beijing, China.	Zhu R, Shang Y, Chen S, Xiao H, Ren R, Wang F, Xue Y, Li L, Li Y, Chu N, Huang H.	Microbiol Spectr	10.1128/spectrum.01372-22	2022
	In vitro and intracellular inhibitory activities of nosiheptide against Mycobacterium abscessus.	Zhu R, Yu X, Zhang T, Kong Y, Wang F, Jia J, Xue Y, Huang H.	Front Microbiol	10.3389/fmicb.2022.926361	2022
Pathogenicity	In Vitro Activities of Bedaquiline and Delamanid against Nontuberculous Mycobacteria Isolated in Beijing, China.	Yu X, Gao X, Li C, Luo J, Wen S, Zhang T, Ma Y, Dong L, Wang F, Huang H.	Antimicrob Agents Chemother	10.1128/aac.00031-19	2019
Phylogeny	Biochip system for rapid and accurate identification of mycobacterial species from isolates and sputum.	Zhu L, Jiang G, Wang S, Wang C, Li Q, Yu H, Zhou Y, Zhao B, Huang H, Xing W, Mitchelson K, Cheng J, Zhao Y, Guo Y.	J Clin Microbiol	10.1128/jcm.00158-10	2010
	Genotypic variation and stability of four variable-number tandem repeats and their suitability for discriminating strains of Mycobacterium leprae.	Truman R, Fontes AB, De Miranda AB, Suffys P, Gillis T.	J Clin Microbiol	10.1128/jcm.42.6.2558-2565.2004	2004
	Compilation of small ribosomal subunit RNA structures.	Neefs JM, Van de Peer Y, De Rijk P, Chapelle S, De Wachter R.	Nucleic Acids Res	10.1093/nar/21.13.3025	1993

References

#11524	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 44147
#19844	Wink, J.: Compendium of Actinobacteria. HZI-Helmholtz-Centre for Infection Research, Braunschweig .
#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 )
#36367	; Curators of the CIP;
#53799	Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 37672
#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;
#68382	Automatically annotated from API zym .
#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 .
#116165	Collection of Institut Pasteur ; Curators of the CIP; CIP 106808
#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 aichiense (DSM 44147, 49005, ATCC 27280)

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

Enzymes

API zym

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_010726245

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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