Chromobacterium amazonense (DSM 26508, CBMAI 310)

Name: Chromobacterium amazonense (DSM 26508, CBMAI 310)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131375

Type strain

Culture col. no. DSM 26508 CBMAI 310

NCBI tax ID(s) 1382803

Special Collections DSMZ

History <- F. Fantinatti-Garboggini, CPQBA/Unicamp, Div. de Recursos Microbianos, Campinas, Brazil; CBMAI 310

Links

Chromobacterium amazonense DSM 26508 is a mesophilic prokaryote that was isolated from river water.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 210562

CBMAI 310,DSM 26508

@ref 20215

Last LPSN update 2026-02-09 11:31:27

Domain Bacteria

Phylum Pseudomonadota

Class Betaproteobacteria

Order Neisseriales

Family Chromobacteriaceae

Genus Chromobacterium

Species Chromobacterium amazonense

Full scientific name Chromobacterium amazonense Menezes et al. 2015

BacDive ID	Other strains from **Chromobacterium amazonense** (1)	Type strain
157071	C. amazonense CCUG 69338

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	98.994
125439	negative	99.9
125439		94.2

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
22602	R2A MEDIUM (DSMZ Medium 830)		Medium recipe at MediaDive	Name: R2A MEDIUM (DSMZ Medium 830) Composition: Agar 15.0 g/l Casamino acids 0.5 g/l Starch 0.5 g/l Glucose 0.5 g/l Proteose peptone 0.5 g/l Yeast extract 0.5 g/l K2HPO4 0.3 g/l Na-pyruvate 0.3 g/l MgSO4 x 7 H2O 0.05 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
22602	positive	growth	28	mesophilic
22602	positive	growth	25

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		99.8

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68369	17128 ChEBI	adipate	-	assimilation	from API 20NE
68369	29016 ChEBI	arginine	+	hydrolysis	from API 20NE
68369	17634 ChEBI	D-glucose	+	assimilation	from API 20NE
68369	17634 ChEBI	D-glucose	+	fermentation	from API 20NE
68369	16899 ChEBI	D-mannitol	-	assimilation	from API 20NE
68369	16024 ChEBI	D-mannose	-	assimilation	from API 20NE
68369	27689 ChEBI	decanoate	-	assimilation	from API 20NE
68369	4853 ChEBI	esculin	-	hydrolysis	from API 20NE
68369	5291 ChEBI	gelatin	+	hydrolysis	from API 20NE
68369	24265 ChEBI	gluconate	+	assimilation	from API 20NE
68369	30849 ChEBI	L-arabinose	-	assimilation	from API 20NE
68369	25115 ChEBI	malate	+	assimilation	from API 20NE
68369	17306 ChEBI	maltose	-	assimilation	from API 20NE
68369	59640 ChEBI	N-acetylglucosamine	+	assimilation	from API 20NE
68369	17632 ChEBI	nitrate	-	reduction	from API 20NE
68369	27897 ChEBI	tryptophan	-	energy source	from API 20NE
68369	16199 ChEBI	urea	-	hydrolysis	from API 20NE

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68369	35581 ChEBI	indole		from API 20NE

Metabolite tests

@ref	Chebi-ID	Metabolite	Indole test
68369	35581 ChEBI	indole	-	from API 20NE

Enzymes

@ref	Value	Activity	Ec
68369	arginine dihydrolase	+	3.5.3.6	from API 20NE
68369	beta-glucosidase	-	3.2.1.21	from API 20NE
68369	cytochrome oxidase	+	1.9.3.1	from API 20NE
68369	gelatinase	+		from API 20NE
68369	urease	-	3.5.1.5	from API 20NE

API 20NE

@ref	Reduction of nitratesNO3	TRP	GLU_ Ferm	ADH (Arg)	URE	ESC	GEL	PNPG	GLU_ Assim	ARA	MNE	MAN	NAG	MAL	GNT	CAP	ADI	MLT	CIT	PAC	OX
22602	-	-	+	+	-	-	+	-	+	-	-	-	+	-	+	-	-	+	+	-	+

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#River (Creek)

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
22602	river water	Amazona, Rio Preto da Eva, Rio Negro (2°42'09'' S 59°42'05''W)	Brazil	BRA	Middle and South America	-2.7025	-59.7014 -2.7025/-59.7014

Taxonmaps

69479

Global distribution of 16S sequence KF137653 (>99% sequence identity) for Chromobacterium from Microbeatlas

Aquatic Samples	3701
Soil Samples	1022
Animal Samples	4631
Plant Samples	999
Total Samples	10353

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
22602	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	ASM185556v1 assembly for Chromobacterium amazonense DSM 26508	contig	GCA_001855565	1382803.3	2896398972	1382803	68.61

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
22602	Chromobacterium amazonense 16S ribosomal RNA gene, partial sequence	KF137653	1498		1382803

GC content

@ref	GC-content (mol%)	Method
22602	68.7	fluorimetric

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Chromobacterium amazonense DSM 26508
NCBI: GCA_001855565

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.80	no
125439	motility	BacteriaNetⓘ	yes	94.20	no
125439	gram_stain	BacteriaNetⓘ	negative	99.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative aerobe	70.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Chromobacterium amazonense strain DSM 26508
PATRIC: 1382803.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.99	no
125438	anaerobic	anaerobicⓘ	no	92.35	no
125438	spore-forming	spore-formingⓘ	no	89.22	no
125438	aerobic	aerobicⓘ	yes	54.62	no
125438	thermophilic	thermophileⓘ	no	95.34	yes
125438	flagellated	motile2+ⓘ	yes	77.36	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Whole genome sequencing data of Chromobacterium amazonense BASUSDA_45 isolated from soil in Bangladesh capable of degrading pesticide.	Rahman MA, Sujon KM, Habib MT, Forhad Hossain M, Ferdaus KMKB, Hoque KMF, Ferdousi Z, Reza MA.	Data Brief	10.1016/j.dib.2022.108853	2023
	Identification of 2,4-diacetylphloroglucinol production in the genus Chromobacterium.	Johnson ET, Bowman MJ, Gomes RP, Carneiro LC, Dunlap CA.	Sci Rep	10.1038/s41598-023-41277-0	2023
	Insights into the Genome Sequence of Chromobacterium amazonense Isolated from a Tropical Freshwater Lake.	Santos AB, Costa PS, do Carmo AO, da Rocha Fernandes G, Scholte LLS, Ruiz J, Kalapothakis E, Chartone-Souza E, Nascimento AMA.	Int J Genomics	10.1155/2018/1062716	2018
Metabolism	The Antibacterial and Anti-Eukaryotic Type VI Secretion System MIX-Effector Repertoire in Vibrionaceae.	Dar Y, Salomon D, Bosis E.	Mar Drugs	10.3390/md16110433	2018
	Chromobacterium alticapitis sp. nov. and Chromobacterium sinusclupearum sp. nov. isolated from wild cranberry bogs in the Cape Cod National Seashore, USA.	O'Hara-Hanley K, Harrison A, Soby SD.	Int J Syst Evol Microbiol	10.1099/ijsem.0.005410	2022
Phylogeny	Chromobacterium phragmitis sp. nov., isolated from estuarine marshes.	Blackburn MB, Farrar RR Jr, Sparks ME, Kuhar D, Mowery JD, Mitchell A, Gundersen-Rindal DE	Int J Syst Evol Microbiol	10.1099/ijsem.0.003508	2019
Phylogeny	Chromobacterium amazonense sp. nov. isolated from water samples from the Rio Negro, Amazon, Brazil.	Menezes CB, Tonin MF, Correa DB, Parma M, de Melo IS, Zucchi TD, Destefano SA, Fantinatti-Garboggini F	Antonie Van Leeuwenhoek	10.1007/s10482-015-0397-3	2015

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 )
#22602	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 26508
#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) .
#68369	Automatically annotated from API 20NE .
#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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Chromobacterium amazonense (DSM 26508, CBMAI 310)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Spore formation

Metabolite utilization

Metabolite production

Metabolite tests

Enzymes

API 20NE

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_001855565

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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