Sphingobium indicum (MTCC 9456, CCM 7544, F2)

Name: Sphingobium indicum (MTCC 9456, CCM 7544, F2)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 133671

Type strain

Strain Designation F2

Culture col. no. MTCC 9456 CCM 7544 F2

NCBI tax ID(s) 332055

Special Collections Literature strains

Links

Sphingobium indicum F2 is an aerobe, Gram-negative, rod-shaped bacterium that was isolated from HCH dumpsite.

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

Name and taxonomic classification

SI-ID 28316

MTCC 9456

@ref 20215

Last LPSN update 2026-05-29 08:38:09

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Sphingomonadales

Family Sphingomonadaceae

Genus Sphingobium

Species Sphingobium indicum

Full scientific name Sphingobium indicum Pal et al. 2005

Synonyms (4)

Sphingobium lucknowense
Sphingobium francense
Sphingobium japonicum
Sphingobium chinhatense

BacDive ID	Other strains from **Sphingobium indicum** (3)	Type strain
14184	S. indicum B90A, DSM 16412, CCM 7286, MTCC 6364, CIP ... (type strain)
14185	S. indicum UT26, DSM 16413, CCM 7287, MTCC 6362, CIP ...
23269	S. indicum Sp+, DSM 26779, CCM 7288, MTCC 6363, CCUG ...

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
30054	negative	1.5 µm	0.6-0.7 µm	rod-shaped
125438	negative				93.042
125439	negative				97.34

Pigmentation

30054

Productionyes

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
30054	positive	optimum	28

Culture pH

@ref	Ability	Type	PH
30054	positive	optimum	7

Physiology and metabolism

Oxygen tolerance

30054

Oxygen toleranceaerobe

Spore formation

@ref	Spore formation	Confidence
30054
125439		99.3

Halophily

@ref	Salt	Growth	Tested relation	Concentration
30054	NaCl	positive	optimum	2 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
30054	22599 ChEBI	arabinose	+	carbon source
30054	28260 ChEBI	galactose	+	carbon source
30054	17234 ChEBI	glucose	+	carbon source
30054	17716 ChEBI	lactose	+	carbon source
30054	17306 ChEBI	maltose	+	carbon source
30054	37684 ChEBI	mannose	+	carbon source
30054	26546 ChEBI	rhamnose	+	carbon source
30054	27082 ChEBI	trehalose	+	carbon source
30054	18222 ChEBI	xylose	+	carbon source

Enzymes

@ref	Value	Activity	Ec
30054	cytochrome oxidase	+	1.9.3.1

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2
#Engineered	#Built environment

Isolation

30054

Sample typeHCH dumpsite

Taxonmaps

69479

Global distribution of 16S sequence EF534725 (>99% sequence identity) for Sphingobium from Microbeatlas

Aquatic Samples	363
Soil Samples	78
Animal Samples	118
Plant Samples	77
Total Samples	636

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
124043	ASM4242747v1 assembly for Sphingobium indicum CCM 7544	contig	GCA_042427475			332055	69.61
124043	ASM4243306v1 assembly for Sphingobium indicum CCM 7544	contig	GCA_042433065			332055	53.94
66792	ASM63357v2 assembly for Sphingobium indicum F2	contig	GCA_000633575	1450518.5	2579779071	1450518	32.26

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
30054	Sphingobium lucknowense F2 16S ribosomal RNA gene, partial sequence	EF534725	1436		1450518

GC content

30054

GC-content (mol%)65.7

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM4242747v1 assembly for Sphingobium indicum CCM 7544
NCBI: GCA_042427475

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	73.65	no
125439	gram_stain	BacteriaNetⓘ	negative	97.34	no
125439	motility	BacteriaNetⓘ	yes	66.74	no
125439	spore_formation	BacteriaNetⓘ	no	99.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Sphingobium indicum F2 F2
NCBI: GCA_000633575.2

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	93.04	yes
125438	anaerobic	anaerobicⓘ	no	86.60	yes
125438	aerobic	aerobicⓘ	yes	72.10	no
125438	spore-forming	spore-formingⓘ	no	86.24	yes
125438	thermophilic	thermophileⓘ	no	95.08	yes
125438	flagellated	motile2+ⓘ	no	73.31	yes

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Analysis of 1,000+ Type-Strain Genomes Substantially Improves Taxonomic Classification of Alphaproteobacteria.	Hordt A, Lopez MG, Meier-Kolthoff JP, Schleuning M, Weinhold LM, Tindall BJ, Gronow S, Kyrpides NC, Woyke T, Goker M.	Front Microbiol	10.3389/fmicb.2020.00468	2020
Phylogeny	Sphingobium lucknowense sp. nov., a hexachlorocyclohexane (HCH)-degrading bacterium isolated from HCH-contaminated soil.	Garg N, Bala K, Lal R	Int J Syst Evol Microbiol	10.1099/ijs.0.028886-0	2011

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 )
#26415	IJSEM 618 2012 ( DOI 10.1099/ijs.0.028886-0 , PubMed 21551337 )
#30054	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 #26415
#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) .
#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 .
#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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Sphingobium indicum (MTCC 9456, CCM 7544, F2)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_042427475

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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