Amycolatopsis granulosa (NCIMB 14709, NRRL B-24844, DSM 45669)

Name: Amycolatopsis granulosa (NCIMB 14709, NRRL B-24844, DSM 45669)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 133703

Type strain

Strain Designation GY307

Culture col. no. NCIMB 14709 NRRL B-24844 DSM 45669 GY307

NCBI tax ID(s) 185684

Special Collections DSMZ Literature strains

Links

Amycolatopsis granulosa GY307 is an aerobe, spore-forming, mesophilic prokaryote that was isolated from soil.

spore-forming Gram-positive rod-shaped aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 402420

NCIMB 14709,DSM 45669

@ref 20215

Last LPSN update 2025-12-16 10:01:51

Domain Bacillati

Phylum Actinomycetota

Class Actinomycetes

Order Pseudonocardiales

Family Pseudonocardiaceae

Genus Amycolatopsis

Species Amycolatopsis granulosa

Full scientific name Amycolatopsis granulosa Zucchi et al. 2012

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
30219	positive	1.1 µm	0.45 µm	rod-shaped
125438					91
125439	positive				99.8

Pigmentation

30219

Productionyes

Multimedia

@ref:	18034
multimedia content:	DSM_45669.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_45669.jpg
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
18034	GYM STREPTOMYCES MEDIUM (DSMZ Medium 65)		Medium recipe at MediaDive	Name: GYM STREPTOMYCES MEDIUM (DSMZ Medium 65) Composition: Agar 18.0 g/l Malt extract 10.0 g/l Yeast extract 4.0 g/l Glucose 4.0 g/l CaCO3 2.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
18034	positive	growth	28	mesophilic
30219	positive	growth	20-50

Culture pH

@ref	Ability	Type	PH
30219	positive	growth	05-07

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
30219	aerobe
125438	aerobe	90.876
125439	obligate aerobe	99.7

Spore formation

30219

Spore formationyes

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
30219	28757 ChEBI	fructose	+	carbon source
30219	37684 ChEBI	mannose	+	carbon source

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
30219	soil
18034	arid soil	Marla	Australia	AUS	Australia and Oceania

Taxonmaps

69479

Global distribution of 16S sequence AF466101 (>99% sequence identity) for Amycolatopsis from Microbeatlas

Aquatic Samples	2
Soil Samples	63
Animal Samples	6
Plant Samples	7
Total Samples	78

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
18034	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	ASM1175874v1 assembly for Amycolatopsis granulosa DSM 45669	contig	GCA_011758745	185684.3	2821246215	185684	78.17

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
18034	Amycolatopsis granulosa 16S ribosomal RNA gene, partial sequence	AF466101	1421		185684

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Amycolatopsis granulosa DSM 45669
NCBI: GCA_011758745

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	66.00	no
125439	motility	BacteriaNetⓘ	no	82.20	no
125439	gram_stain	BacteriaNetⓘ	positive	99.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Amycolatopsis granulosa strain DSM 45669
PATRIC: 185684.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	89.62	no
125438	anaerobic	anaerobicⓘ	no	97.37	yes
125438	spore-forming	spore-formingⓘ	yes	75.62	no
125438	aerobic	aerobicⓘ	yes	90.88	yes
125438	thermophilic	thermophileⓘ	no	93.47	no
125438	flagellated	motile2+ⓘ	no	91.00	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Transcriptome	Insight into Different Stages of Steroid Degradation in Thermophilic Saccharopolyspora hirsuta VKM Ac-666^T Strain.	Lobastova T, Fokina V, Pozdnyakova-Filatova I, Tarlachkov S, Shutov A, Donova M.	Int J Mol Sci	10.3390/ijms232416174	2022
	Steroid Metabolism in Thermophilic Actinobacterium Saccharopolyspora hirsuta VKM Ac-666^T.	Lobastova T, Fokina V, Tarlachkov S, Shutov A, Bragin E, Kazantsev A, Donova M.	Microorganisms	10.3390/microorganisms9122554	2021
Phylogeny	Amycolatopsis granulosa sp. nov., Amycolatopsis ruanii sp. nov. and Amycolatopsis thermalba sp. nov., thermophilic actinomycetes isolated from arid soils.	Zucchi TD, Tan GYA, Bonda ANV, Frank S, Kshetrimayum JD, Goodfellow M	Int J Syst Evol Microbiol	10.1099/ijs.0.031039-0	2011

References

#18034	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 45669
#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 )
#30219	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 #26562 (see below)
#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) .
#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 )

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Amycolatopsis granulosa (NCIMB 14709, NRRL B-24844, DSM 45669)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Multimedia

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Metabolite utilization

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_011758745

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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