Mycobacterium goodii (DSM 44492, ATCC 700504, CCUG 58730)

Name: Mycobacterium goodii (DSM 44492, ATCC 700504, CCUG 58730)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 135874

Type strain

Strain Designation M069

Culture col. no. DSM 44492 ATCC 700504 CCUG 58730 CDC 860673 M069 2 more

NCBI tax ID(s) 134601

Special Collections DSMZ CCUG JCM CIP

History DSMZ <- CIP <- J. F. Flanagan {1986}

Links

Mycobacterium goodii M069 is a human pathogen of the family Mycobacteriaceae.

human pathogen genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 46964

ATCC 700504,CIP 106349,DSM 44492,JCM 12689

@ref 20215

Last LPSN update 2026-05-29 08:38:40

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Mycobacteriales

Family Mycobacteriaceae

Genus Mycobacterium

Species Mycobacterium goodii

Full scientific name Mycobacterium goodii Brown et al. 1999

Synonyms (1)

"Mycolicibacterium goodii"

BacDive ID	Other strains from **Mycobacterium goodii** (1)	Type strain
154031	M. goodii CCUG 52054

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	positive	90.195
125438	positive	90.48

Multimedia

@ref:	64150
multimedia content:	DSM_44492.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_44492.jpg
caption:	Medium 250 37°C
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Medium link	Composition
64150	PEPTONE MEAT EXTRACT GLYCEROL AGAR (DSMZ Medium 250)	Medium recipe at MediaDive	Name: PEPTONE MEAT EXTRACT GLYCEROL AGAR (DSMZ Medium 250) Composition: Agar 20.0 g/l Proteose peptone no. 3 5.0 g/l Meat extract 3.0 g/l Glycerol Distilled water
64150	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
35129	MEDIUM 55 - for Mycobacterium

Culture temp

@ref	Growth	Type	Temperature (°C)
35129	positive	growth	30
64150	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	99.289

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host Body-Site	#Other	#Bone
#Host Body-Site	#Limb	#Foot
#Infection	#Inflammation	-
#Infection	#Patient	-

Isolation

@ref	Geographic location	Country	Country ISO 3 Code	Continent	Sample type	Host species
35129	Florida	USA	USA	North America
64150					patient with a post-traumatic osteomyelitis of the calcaneus (heel)	Homo sapiens

Interaction and safety

Risk assessment

@ref	Pathogenicity human	Pathogenicity animal	Biosafety level	Biosafety level comment
64150			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	ASM2237075v2 assembly for Mycolicibacterium goodii ATCC 700504	complete	GCA_022370755	134601.15	8111321690	134601	97.31
66792	ASM2582253v1 assembly for Mycolicibacterium goodii CCUG 58730	scaffold	GCA_025822535	134601.16	8115318315	134601	65.41

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
64150	Mycolicibacterium goodii strain ATCC 700504 16S ribosomal RNA gene, partial sequence	AY457079	1489		134601
124043	Mycobacterium goodii strain CIP 106349 16S ribosomal RNA gene, partial sequence.	AF547930	544		134601

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM2237075v2 assembly for Mycolicibacterium goodii ATCC 700504
NCBI: GCA_022370755

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.29	no
125439	gram_stain	BacteriaNetⓘ	positive	90.20	no
125439	motility	BacteriaNetⓘ	no	81.03	no
125439	spore_formation	BacteriaNetⓘ	no	83.47	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Mycobacterium goodii ATCC 700504
NCBI: GCA_022370755.2

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	90.48	no
125438	anaerobic	anaerobicⓘ	no	95.70	no
125438	aerobic	aerobicⓘ	yes	86.60	no
125438	spore-forming	spore-formingⓘ	no	59.39	no
125438	thermophilic	thermophileⓘ	no	95.50	yes
125438	flagellated	motile2+ⓘ	no	86.96	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Metabolism	Microbial desulfurization of gasoline in a Mycobacterium goodii X7B immobilized-cell system.	Li F, Xu P, Feng J, Meng L, Zheng Y, Luo L, Ma C.	Appl Environ Microbiol	10.1128/aem.71.1.276-281.2005	2005
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
	Complete Genome Sequences of 14 Nontuberculous Mycobacteria Type Strains.	Igarashi Y, Osugi A, Murase Y, Chikamatsu K, Shimomura Y, Hosoya M, Aono A, Morishige Y, Yamada H, Takaki A, Mitarai S.	Microbiol Resour Announc	10.1128/mra.01214-22	2023
Metabolism	Genome-guided and mass spectrometry investigation of natural products produced by a potential new actinobacterial strain isolated from a mangrove ecosystem in Futian, Shenzhen, China.	Hu D, Gao C, Sun C, Jin T, Fan G, Mok KM, Lee SM.	Sci Rep	10.1038/s41598-018-37475-w	2019
Phylogeny	Mycobacterium goodii endocarditis following mitral valve ring annuloplasty.	Parikh RB, Grant M.	Ann Clin Microbiol Antimicrob	10.1186/s12941-017-0190-4	2017
Phylogeny	Non-tuberculous Mycobacteria in South African Wildlife: Neglected Pathogens and Potential Impediments for Bovine Tuberculosis Diagnosis.	Gcebe N, Hlokwe TM.	Front Cell Infect Microbiol	10.3389/fcimb.2017.00015	2017
	Mycobacterium goodii infections associated with surgical implants at Colorado hospital.	Ferguson DD, Gershman K, Jensen B, Arduino MJ, Yakrus MA, Cooksey RC, Srinivasan A.	Emerg Infect Dis	10.3201/eid1010.040402	2004
	Genomics Insights into Mycolicibacterium Hassiacum Causing Infection in a Cat with Pyogranulomatous Dermatitis and Panniculitis.	Smedile D, Iurescia M, Carfora V, Cocumelli C, Palmerini T, Diaconu EL, Congiu I, Donati V, Stravino F, Sorbara L, Romano E, Caprioli A, Battisti A.	Pathogens	10.3390/pathogens13090785	2024
Phylogeny	Rapid identification of mycobacterial whole cells in solid and liquid culture media by matrix-assisted laser desorption ionization-time of flight mass spectrometry.	Lotz A, Ferroni A, Beretti JL, Dauphin B, Carbonnelle E, Guet-Revillet H, Veziris N, Heym B, Jarlier V, Gaillard JL, Pierre-Audigier C, Frapy E, Berche P, Nassif X, Bille E.	J Clin Microbiol	10.1128/jcm.01397-10	2010
Phylogeny	Mycobacterium appelbergii sp. nov., a Novel Species Isolated from a Drinking Water Fountain in a Rural Community.	Roxo IC, Alarico S, Fonseca A, Machado D, Maranha A, Tiago I, Duarte R, Empadinhas N.	Microorganisms	10.3390/microorganisms13061259	2025
Phylogeny	Mycobacterium wolinskyi sp. nov. and Mycobacterium goodii sp. nov., two new rapidly growing species related to Mycobacterium smegmatis and associated with human wound infections: a cooperative study from the International Working Group on Mycobacterial Taxonomy.	Brown BA, Springer B, Steingrube VA, Wilson RW, Pfyffer GE, Garcia MJ, Menendez MC, Rodriguez-Salgado B, Jost KC Jr, Chiu SH, Onyi GO, Bottger EC, Wallace RJ Jr	Int J Syst Bacteriol	10.1099/00207713-49-4-1493	1999

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 )
#35129	; Curators of the CIP;
#64150	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 44492
#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) .
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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 goodii (DSM 44492, ATCC 700504, CCUG 58730)

Name and taxonomic classification

Morphology

Cell morphology

Multimedia

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Isolation, sampling and environmental information

Isolation source categories

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_022370755

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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