Amycolatopsis benzoatilytica (DSM 43387, ATCC 55165, CIP 109216)

Name: Amycolatopsis benzoatilytica (DSM 43387, ATCC 55165, CIP 109216)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 13257

Type strain

Strain Designation AK 16/65, N857

Culture col. no. DSM 43387 ATCC 55165 CIP 109216 IMRU 1389 JCM 13851 8 more

NCBI tax ID(s) 1089544 346045

Special Collections DSMZ JCM KCTC CIP JMRC

History DSMZ <- M. Goodfellow, N857 <- R.E. Gordon, IMRU <- J. Scharfen, AK 16/65, Institute for Epidemology and Microbiology, Prag JCM <-- DSM 43387 <-- M. Goodfellow N857 <-- R. E. Gordon IMRU 1389 <-- J. Scharfen AK 16/65.

Links

Amycolatopsis benzoatilytica AK 16/65 is a bacterium that was isolated from from a patient with submandibular mycetoma.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 40897

ATCC 35164,ATCC 35165,DSM 43387,DSM 46075,IMET 7511,KCTC 9414,IMET 1389,KCTC 9421,ATCC 55165,JCM 13851,CIP 109216

@ref 20215

Last LPSN update 2026-05-29 08:28:00

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Pseudonocardiales

Family Pseudonocardiaceae

Genus Amycolatopsis

Species Amycolatopsis benzoatilytica

Full scientific name Amycolatopsis benzoatilytica Majumdar et al. 2006

Morphology

Cell morphology

@ref	Gram stain	Confidence	Motility
125439	positive	97.41
125439		90.334

Multimedia

@ref:	11004
multimedia content:	DSM_43387.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_43387.jpg
caption:	Medium 553 28°C
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
11004	GPHF-MEDIUM (DSMZ Medium 553)		Medium recipe at MediaDive	Name: GPHF-MEDIUM (DSMZ Medium 553) Composition: Agar 20.0 g/l Glucose 10.0 g/l Beef extract 5.0 g/l Yeast extract 5.0 g/l Casein peptone 5.0 g/l CaCl2 x 2 H2O 0.74 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
11004	positive	growth	28
67770	positive	growth	28

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	99.006

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2
#Infection	#Disease
#Infection	#Patient
#Host Body-Site	#Oral cavity and airways

Isolation

@ref	Sample type	Host species	Country	Continent
11004	from a patient with submandibular mycetoma	Homo sapiens	Czechoslovakia	Europe
67770	Patient with submandibular mycetoma	Homo sapiens	Czechoslovakia	Europe

Taxonmaps

69479

Global distribution of 16S sequence AY957506 (>99% sequence identity) for Amycolatopsis from Microbeatlas

Aquatic Samples	27
Soil Samples	640
Animal Samples	69
Plant Samples	156
Total Samples	892

Interaction and safety

Risk assessment

@ref	Pathogenicity human	Biosafety level	Biosafety level comment
11004	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	ASM38391v1 assembly for Amycolatopsis benzoatilytica AK 16/65	scaffold	GCA_000383915	1089544.3	2517287020	1089544	77.71

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
11004	Amycolatopsis benzoatilytica strain DSM 43387 16S ribosomal RNA gene, partial sequence	AY957506	1417		346045

GC content

@ref	GC-content (mol%)	Method
67770	70	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM38391v1 assembly for Amycolatopsis benzoatilytica AK 16/65
NCBI: GCA_000383915

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.01	no
125439	motility	BacteriaNetⓘ	no	90.33	no
125439	gram_stain	BacteriaNetⓘ	positive	97.41	no
125439	spore_formation	BacteriaNetⓘ	yes	74.91	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Amycolatopsis benzoatilytica AK 16/65
PATRIC: 1089544.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	86.00	no
125438	anaerobic	anaerobicⓘ	no	96.88	no
125438	spore-forming	spore-formingⓘ	yes	77.56	no
125438	aerobic	aerobicⓘ	yes	88.55	no
125438	thermophilic	thermophileⓘ	no	97.50	no
125438	flagellated	motile2+ⓘ	no	89.60	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Actinomycetes as Producers of Biologically Active Terpenoids: Current Trends and Patents.	Tarasova EV, Luchnikova NA, Grishko VV, Ivshina IB.	Pharmaceuticals (Basel)	10.3390/ph16060872	2023
Enzymology	The genus Amycolatopsis: Indigenous plasmids, cloning vectors and gene transfer systems.	Malhotra S, Lal R.	Indian J Microbiol	10.1007/s12088-007-0003-0	2007
Phylogeny	Polyphasic approach of bacterial classification - An overview of recent advances.	Prakash O, Verma M, Sharma P, Kumar M, Kumari K, Singh A, Kumari H, Jit S, Gupta SK, Khanna M, Lal R.	Indian J Microbiol	10.1007/s12088-007-0022-x	2007
Genetics	Nucleotide sequence of plasmid pA387 of Amycolatopsis benzoatilytica and construction of a conjugative shuttle vector.	Malhotra S, Majumdar S, Kumar M, Bhasin VK, Gartemann KH, Lal R	J Basic Microbiol	10.1002/jobm.200700326	2008
Phylogeny	Reclassification of Amycolatopsis orientalis DSM 43387 as Amycolatopsis benzoatilytica sp. nov.	Majumdar S, Prabhagaran SR, Shivaji S, Lal R	Int J Syst Evol Microbiol	10.1099/ijs.0.63766-0	2006

References

#11004	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 43387
#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 )
#20216	Curators of the JMRC: Jena Microbial Resource Collection (JMRC):
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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 )

Content

About us

Amycolatopsis benzoatilytica (DSM 43387, ATCC 55165, CIP 109216)

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

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_000383915

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

Help

Social Media