Agrococcus terreus (DSM 28114, CGMCC 1.6960, JCM 17488)

Name: Agrococcus terreus (DSM 28114, CGMCC 1.6960, JCM 17488)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 24181

Type strain

Strain Designation DNG5

Culture col. no. DSM 28114 CGMCC 1.6960 JCM 17488 NBRC 104260 DNG5

NCBI tax ID(s) 574649

Special Collections DSMZ JCM Literature strains

History DSMZ <- NBRC <- CGMCC 1.6960 <- J.-Y. Zhang, CAS; DNG5 JCM <-- CGMCC 1.6960 <-- J.-Y. Zhang et al. DNG5.

Links

Agrococcus terreus DNG5 is an aerobe, Gram-positive, rod-shaped bacterium that was isolated from forest soil.

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

Name and taxonomic classification

SI-ID 402013

NBRC 104260,JCM 17488,DSM 28114

@ref 20215

Last LPSN update 2026-05-29 08:30:34

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Micrococcales

Family Microbacteriaceae

Genus Agrococcus

Species Agrococcus terreus

Full scientific name Agrococcus terreus Zhang et al. 2010

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
29443	positive	0.8-1 µm	0.4-0.5 µm	rod-shaped
125438					93.5
125438	positive				93.628
125439	positive				94.812

Pigmentation

29443

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
20269	TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92)		Medium recipe at MediaDive	Name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Yeast extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
20269	positive	growth	28
29443	positive	growth	20-40
29443	positive	optimum	30
67770	positive	growth	28

Culture pH

@ref	Ability	Type	PH	PH range
29443	positive	optimum	7
29443	positive	growth	5.5-9	alkaliphile

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
29443	aerobe
125439	obligate aerobe	99.918

Spore formation

@ref	Spore formation	Confidence
125439		90.927

Halophily

@ref	Salt	Growth	Tested relation	Concentration
29443	NaCl	positive	growth	0-4 %
29443	NaCl	positive	optimum	1 %

Observation

@ref	Observation
29443	aggregates in chains
67770	quinones: MK-11, MK-10, MK-9

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
29443	22599 ChEBI	arabinose	+	carbon source
29443	4853 ChEBI	esculin	+	hydrolysis
29443	24265 ChEBI	gluconate	+	carbon source
29443	25115 ChEBI	malate	+	carbon source
29443	29864 ChEBI	mannitol	+	carbon source
29443	37684 ChEBI	mannose	+	carbon source

Enzymes

@ref	Value	Activity	Ec
29443	catalase	+	1.11.1.6

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Forest
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
20269	forest soil	Changbai Mountain	China	CHN	Asia
67770	Forest soil of the Changbai mountains		China	CHN	Asia

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
20269	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1464523v1 assembly for Agrococcus terreus CGMCC 1.6960	contig	GCA_014645235	574649.3	2995319386	574649	77
124043	ASM3953777v1 assembly for Agrococcus terreus JCM 17488	scaffold	GCA_039537775			574649	42.69

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20269	Agrococcus terreus strain DNG5 16S ribosomal RNA gene, partial sequence	FJ423764	1516		574649

GC content

@ref	GC-content (mol%)	Method
20269	67.2	thermal denaturation, midpoint method (Tm)
29443	75.9
67770	75.9	thermal denaturation, midpoint method (Tm)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1464523v1 assembly for Agrococcus terreus CGMCC 1.6960
NCBI: GCA_014645235

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	gram_stain	BacteriaNetⓘ	positive	94.81	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.92	no
125439	motility	BacteriaNetⓘ	no	63.90	no
125439	spore_formation	BacteriaNetⓘ	no	90.93	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Agrococcus terreus strain CGMCC 1.6960
PATRIC: 574649.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	93.63	yes
125438	anaerobic	anaerobicⓘ	no	97.06	yes
125438	spore-forming	spore-formingⓘ	no	76.99	no
125438	aerobic	aerobicⓘ	yes	87.61	yes
125438	thermophilic	thermophileⓘ	no	98.00	yes
125438	flagellated	motile2+ⓘ	no	93.50	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Agrococcus terreus sp. nov. and Micrococcus terreus sp. nov., isolated from forest soil.	Zhang JY, Liu XY, Liu SJ	Int J Syst Evol Microbiol	10.1099/ijs.0.013235-0	2009

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 )
#20269	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 28114
#25849	IJSEM 1897 2010 ( DOI 10.1099/ijs.0.013235-0 , PubMed 19783614 )
#29443	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 #25849
#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;
#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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Agrococcus terreus (DSM 28114, CGMCC 1.6960, JCM 17488)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Observation

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_014645235

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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