Cite this strain

(DSM 102363, Root267)

Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131583

Type strain

Strain Designation Root267

Culture col. no. DSM 102363 Root267

NCBI tax ID(s) 1872122

Special Collections DSMZ Arabidopsis

Links

Name and taxonomic classification

Root267 is a mesophilic, Gram-negative bacterium that was isolated from roots of Arabidopsis thaliana ecotype Shakdara .

Gram-negative mesophilic genome sequence Bacteria

SI-ID 404999

DSM 102363

Last LPSN update 2024-12-09 10:49:04

Domain Bacteria

Phylum Pseudomonadota

Class Betaproteobacteria

Order Burkholderiales

Family Comamonadaceae

Genus Acidovorax

Full scientific name Acidovorax Willems et al. 1990

Synonyms (2)

Paenacidovorax
Paracidovorax

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	99.5
125438	negative	96

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
23379	NUTRIENT AGAR (DSMZ Medium 1)		Medium recipe at MediaDive	Name: NUTRIENT AGAR (DSMZ Medium 1) Composition: Agar 15.0 g/l Peptone 5.0 g/l Meat extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
23379	positive	growth	28	mesophilic

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		99.2

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Plants	#Herbaceous plants (Grass,Crops)
#Host Body-Site	#Plant	#Root (Rhizome)

Isolation

@ref	Sample type	Host species	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
23379	roots of Arabidopsis thaliana ecotype Shakdara (Sha)	Arabidopsis thaliana	Potsdam, Golm district (52.416N 12.968E)	Germany	DEU	Europe	52.416	12.968 52.416/12.968

Safety information

Sequence information

Genome sequences

@ref	Description	Accession	Assembly level	Database	NCBI tax ID
66792	Acidovorax sp. Root267	GCA_001429215	scaffold		1736505
66792	Acidovorax sp. Root267	1736505.3	wgs	PATRIC	1736505
66792	Acidovorax sp. Root267	2643221717	draft	JGI IMG/M	1736505

Genome-based predictions

Predictions

Predictions from Diaspora project based on:
Acidovorax sp. Root267
NCBI: GCA_001429215

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.20	no
125439	motility	BacteriaNetⓘ	yes	88.20	no
125439	gram_stain	BacteriaNetⓘ	negative	99.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	77.90	no

Predictions from Diaspora project based on:
Acidovorax sp. Root267 Root267
NCBI: GCA_001429215.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	96.00	no
125438	anaerobic	anaerobicⓘ	no	96.95	no
125438	aerobic	aerobicⓘ	yes	89.32	no
125438	spore-forming	spore-formingⓘ	no	88.47	no
125438	thermophilic	thermophileⓘ	no	99.00	yes
125438	flagellated	motile2+ⓘ	yes	83.56	no

External links

Straininfo Link

@ref	Straininfo	Culture collections
89989	404999	DSM 102363

Culture collection no.

Culture collection no.
DSM 102363
Root267

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 )
#23379	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 102363
#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) .
#89989	Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J.: StrainInfo: A central database for resolving microbial strain identifiers . ( DOI 10.60712/SI-ID404999.1 )
#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 .

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