Archangium sp. (DSM 52696, Cb g35)

Name: Archangium sp. (DSM 52696, Cb g35)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 3510

Type strain

Strain Designation Cb g35

Culture col. no. DSM 52696 Cb g35

NCBI tax ID(s) 1872627

Special Collections DSMZ Reichenbach collection

Links

Cb g35 is a mesophilic prokaryote that builds a fruiting body and was isolated from bark from big tree.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 216132

DSM 52696

@ref 20215

Last LPSN update 2025-12-16 09:47:34

Domain Pseudomonadati

Phylum Pseudomonadota

Class Deltaproteobacteria

Order Myxococcales

Family Archangiaceae

Genus Archangium

Full scientific name Archangium Jahn 1924 (Approved Lists 1980)

Synonyms (1)

Angiococcus

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	92.976
125439	positive	93.6

Multicellular morphology

@ref	Forms multicellular complex	Complex name
18281		fruiting body

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
14407	VY/2 AGAR (DSMZ Medium 9)		Medium recipe at MediaDive	Name: VY/2 AGAR (DSMZ Medium 9) Composition: Agar 15.0 g/l Baker's yeast 5.0 g/l CaCl2 x 2 H2O 1.36 g/l Vitamin B12 0.0005 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
14407	positive	growth	28	mesophilic

Physiology and metabolism

Compound production

14407

Compoundroimatacene

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Plants	#Tree
#Host Body-Site	#Plant	#Bark

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
14407	bark from big tree	Bangalore, Karnataka	India	IND	Asia

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM189614v1 assembly for Archangium sp. Cb G35	contig	GCA_001896145	1920190.3	2767802754	1920190	62.64

Genome browser: GCA_001896145

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Archangium sp. Cb G35
NCBI: GCA_001896145

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	71.60	no
125439	motility	BacteriaNetⓘ	no	81.50	no
125439	gram_stain	BacteriaNetⓘ	positive	93.60	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	86.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Archangium sp. Cb G35
PATRIC: 1920190.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	92.98	no
125438	anaerobic	anaerobicⓘ	no	87.52	no
125438	spore-forming	spore-formingⓘ	no	67.28	no
125438	aerobic	aerobicⓘ	yes	72.89	no
125438	thermophilic	thermophileⓘ	no	94.11	yes
125438	flagellated	motile2+ⓘ	yes	66.58	no

Literature

References

#14407	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 52696
#18281	Reichenbach, H.: Collection description and documentation of myxobacteria by H. Reichenbach, HZI (formerly GBF); Collection curr. located at the DSMZ . Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH:
#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 )
#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) .
#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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