Rhizorhabdus histidinilytica (DSM 24951, CCM 7545, MTCC 9473)

Name: Rhizorhabdus histidinilytica (DSM 24951, CCM 7545, MTCC 9473)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 14262

Type strain

Strain Designation UM2

Culture col. no. DSM 24951 CCM 7545 MTCC 9473 UM2

NCBI tax ID(s) 439228

Special Collections DSMZ Literature strains

Links

Rhizorhabdus histidinilytica UM2 is an aerobe, Gram-negative, motile prokaryote that was isolated from contaminated soil from hexachlorocyclohexane dump site.

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

Name and taxonomic classification

SI-ID 28182

MTCC 9473

@ref 20215

Last LPSN update 2025-12-16 09:50:18

Domain Pseudomonadati

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Sphingomonadales

Family Sphingomonadaceae

Genus Rhizorhabdus

Species Rhizorhabdus histidinilytica

Full scientific name Rhizorhabdus histidinilytica (Nigam et al. 2010) Hördt et al. 2020

Synonyms (1)

Sphingomonas histidinilytica

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape
29228	negative	1.4 µm	0.4 µm	rod-shaped
125438	negative
125439	negative

Pigmentation

29228

Productionyes

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
29228	positive	growth	04-40
29228	positive	optimum	28

Culture pH

@ref	Ability	Type	PH
29228	positive	optimum	7.5

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance
29228	aerobe
125439	obligate aerobe

Spore formation

@ref	Spore formation
29228
125438
125439

Halophily

@ref	Salt	Growth	Tested relation	Concentration
29228	NaCl	positive	optimum	1.5 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
29228	22599 ChEBI	arabinose	+	carbon source
29228	16296 ChEBI	D-tryptophan	+	carbon source
29228	27570 ChEBI	histidine	+	carbon source
29228	37684 ChEBI	mannose	+	carbon source
29228	28053 ChEBI	melibiose	+	carbon source
29228	17632 ChEBI	nitrate	+	reduction
29228	18257 ChEBI	ornithine	+	carbon source
29228	26271 ChEBI	proline	+	carbon source
29228	17822 ChEBI	serine	+	carbon source

Enzymes

@ref	Value	Activity	Ec
29228	catalase	+	1.11.1.6

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2
#Engineered	#Contamination
#Environmental	#Terrestrial

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
17806	contaminated soil from hexachlorocyclohexane dump site	Uttar Pradesh, Lucknow, Ummari village	India	IND	Asia

Taxonmaps

69479

Global distribution of 16S sequence EF530202 (>99% sequence identity) for Sphingomonas from Microbeatlas

Aquatic Samples	171
Soil Samples	335
Animal Samples	94
Plant Samples	56
Total Samples	656

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
17806	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	NCBI tax ID	Score
124043	ASM4264758v1 assembly for Rhizorhabdus histidinilytica CCM 7545	contig	GCA_042647585	439228	77.81
66792	IMG-taxon 2706795026 annotated assembly for Rhizorhabdus histidinilytica UM2	contig	GCA_900167915	439228	67.79
124043	ASM4243302v1 assembly for Rhizorhabdus histidinilytica CCM 7545	scaffold	GCA_042433025	439228	42.04
124043	ASM4268388v1 assembly for Rhizorhabdus histidinilytica CCM 7545	contig	GCA_042683885	439228	9.81

Genome browser: GCA_042647585

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
17806	Sphingomonas histidinilytica strain UM2 16S ribosomal RNA gene, partial sequence	EF530202	1394		439228

GC content

29228

GC-content (mol%)66.9

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Rhizorhabdus histidinilytica UM2
NCBI: GCA_900167915

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	97.90	no
125439	motility	BacteriaNetⓘ	yes	68.30	no
125439	gram_stain	BacteriaNetⓘ	negative	98.40	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	98.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Rhizorhabdus histidinilytica UM2
NCBI: GCA_900167915.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.59	yes
125438	anaerobic	anaerobicⓘ	no	96.14	yes
125438	aerobic	aerobicⓘ	yes	88.56	no
125438	spore-forming	spore-formingⓘ	no	91.49	yes
125438	thermophilic	thermophileⓘ	no	94.66	no
125438	flagellated	motile2+ⓘ	yes	70.44	no

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

References

#17806	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 24951
#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 )
#29228	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 #25649 (see below)
#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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Rhizorhabdus histidinilytica (DSM 24951, CCM 7545, MTCC 9473)

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

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_042647585

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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