Amycolatopsis nivea (KCTC 39515, CCTCC AA 201402, BCRC 16980)

Name: Amycolatopsis nivea (KCTC 39515, CCTCC AA 201402, BCRC 16980)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 163847

Type strain

Culture col. no. KCTC 39515 CCTCC AA 201402 BCRC 16980 JCM 30652

NCBI tax ID(s) 1644109

Special Collections JCM KCTC

Links

Amycolatopsis nivea JCM 30652 is a mesophilic prokaryote that was isolated from Sediment of the Yellow River in Henan Province.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 27562

KCTC 39515

@ref 20215

Last LPSN update 2025-12-16 10:09:19

Domain Bacillati

Phylum Actinomycetota

Class Actinomycetes

Order Pseudonocardiales

Family Pseudonocardiaceae

Genus Amycolatopsis

Species Amycolatopsis nivea

Full scientific name Amycolatopsis nivea Niu et al. 2020

Morphology

Cell morphology

@ref	Confidence	Gram stain
125438	90.1
125439	98.9	positive
125439	92.7

Culture and growth conditions

Culture temp

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

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	aerobe	90.305
125439	obligate aerobe	96.7

Observation

67770

Observationquinones: MK-9(H₄)

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
67770	Sediment of the Yellow River in Henan Province	China	CHN	Asia

Taxonmaps

69479

Global distribution of 16S sequence KP232907 (>99% sequence identity) for Amycolatopsis from Microbeatlas

Aquatic Samples	6
Soil Samples	225
Animal Samples	93
Plant Samples	115
Total Samples	439

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM452223v1 assembly for Amycolatopsis nivea CFH S0261	scaffold	GCA_004522235	1644109.3	2899385652	1644109	50.51

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Amycolatopsis nivea 16S ribosomal RNA gene, partial sequence	KP232907	1477		1644109

GC content

@ref	GC-content (mol%)	Method
67770	69.5	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Amycolatopsis nivea CFH S0261
NCBI: GCA_004522235

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	80.20	no
125439	motility	BacteriaNetⓘ	no	92.70	no
125439	gram_stain	BacteriaNetⓘ	positive	98.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	96.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Amycolatopsis sp. CFH S0261
PATRIC: 1644109.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	87.01	no
125438	anaerobic	anaerobicⓘ	no	97.85	no
125438	spore-forming	spore-formingⓘ	yes	81.88	no
125438	aerobic	aerobicⓘ	yes	90.31	no
125438	thermophilic	thermophileⓘ	no	97.50	yes
125438	flagellated	motile2+ⓘ	no	90.10	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Amycolatopsis dendrobii sp. nov., an endophytic actinomycete isolated from Dendrobium heterocarpum Lindl.	Tedsree N, Tanasupawat S, Sritularak B, Kuncharoen N, Likhitwitayawuid K	Int J Syst Evol Microbiol	10.1099/ijsem.0.004902	2021
Phylogeny	Amycolatopsis nivea sp. nov., isolated from a Yellow River sample.	Niu MM, Ming H, Cheng LJ, Zhao ZL, Ji WL, Li M, Yi BF, Xia TT, Nie GX	Int J Syst Evol Microbiol	10.1099/ijsem.0.004134	2020

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 )
#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 )

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Amycolatopsis nivea (KCTC 39515, CCTCC AA 201402, BCRC 16980)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Oxygen tolerance

Observation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_004522235

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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