Methylorubrum thiocyanatum (DSM 11490, ATCC 700647, ALL/SCN-P)

Name: Methylorubrum thiocyanatum (DSM 11490, ATCC 700647, ALL/SCN-P)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 7172

Type strain

Strain Designation ALL/SCN-P

Culture col. no. DSM 11490 ATCC 700647 ALL/SCN-P VKM B-2197 NCIMB 13651 1 more

NCBI tax ID(s) 1236972 47958

Special Collections DSMZ JCM

History DSMZ <- D.P. Kelly, strain ALL/SCN-P JCM <-- NCIMB 13651 <-- DSM 11490 <-- D. P. Kelly strain ALL/SCN-P.

Links

Methylorubrum thiocyanatum ALL/SCN-P is a bacterium that was isolated from soil around root balls of Allium aflatunense.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 45442

ATCC 700647,NCIMB 13651,JCM10893,VKM B-2197,DSM 11490

@ref 20215

Last LPSN update 2026-05-29 08:26:35

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Hyphomicrobiales

Family Methylobacteriaceae

Genus Methylorubrum

Species Methylorubrum thiocyanatum

Full scientific name Methylorubrum thiocyanatum (Wood et al. 1999) Green and Ardley 2018

Synonyms (1)

Methylobacterium thiocyanatum

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	92.114

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
4386	METHYLOBACTERIUM THIOCYANATUM MEDIUM (DSMZ Medium 805)		Medium recipe at MediaDive	Name: METHYLOBACTERIUM THIOCYANATUM MEDIUM (DSMZ Medium 805) Composition: Agar 15.0 g/l Na2HPO4 x 2 H2O 7.9 g/l Glucose 4.5 g/l K2HPO4 1.5 g/l KSCN 0.25 g/l MgSO4 x 7 H2O 0.1 g/l FeSO4 x 7 H2O 0.02 g/l Distilled water
4386	NUTRIENT AGAR (DSMZ Medium 1)		Medium recipe at MediaDive	Name: NUTRIENT AGAR (DSMZ Medium 1; with strain-specific modifications) Composition: Agar 15.0 g/l Methanol 10.0 g/l Peptone 5.0 g/l Meat extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
4386	positive	growth	30
67770	positive	growth	30

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	93.706

Spore formation

@ref	Spore formation	Confidence
125439		98.899

Observation

67770

Observationquinones: Q-10

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Soil
#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
4386	soil around root balls of Allium aflatunense	Allium aflatunense	Warwickshire	United Kingdom	GBR	Europe
67770	Soil from around the roots of Allium aflatunense	Allium aflatunense

Taxonmaps

69479

Global distribution of 16S sequence U58018 (>99% sequence identity) for Methylorubrum from Microbeatlas

Aquatic Samples	23711
Soil Samples	23280
Animal Samples	47578
Plant Samples	16159
Total Samples	110728

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
4386	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
124043	ASM1413864v1 assembly for Methylorubrum thiocyanatum DSM 11490	contig	GCA_014138645	47958.4	2861691609	47958	71.21
66792	ASM2217978v1 assembly for Methylorubrum thiocyanatum JCM 10893	contig	GCA_022179785	47958.5	8113989201	47958	64.91
66792	ASM131087v1 assembly for Methylorubrum thiocyanatum JCM 10893	contig	GCA_001310875	1236972.3	2728369660	1236972	0

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	Methylobacterium thiocyanatum 16S ribosomal RNA gene, complete sequence	U58018	1447		47958
20218	Methylobacterium thiocyanatum gene for 16S ribosomal RNA, partial sequence, strain:DSM 11490	AB175646	1435		47958

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1413864v1 assembly for Methylorubrum thiocyanatum DSM 11490
NCBI: GCA_014138645

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	93.71	no
125439	gram_stain	BacteriaNetⓘ	negative	85.38	no
125439	motility	BacteriaNetⓘ	yes	46.91	no
125439	spore_formation	BacteriaNetⓘ	no	98.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methylobacterium thiocyanatum JCM 10893
PATRIC: 1236972.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	92.11	no
125438	anaerobic	anaerobicⓘ	no	88.07	no
125438	spore-forming	spore-formingⓘ	no	88.25	no
125438	aerobic	aerobicⓘ	yes	78.95	no
125438	thermophilic	thermophileⓘ	no	96.58	yes
125438	flagellated	motile2+ⓘ	yes	62.83	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Bacteria and Metabolic Potential in Karst Caves Revealed by Intensive Bacterial Cultivation and Genome Assembly.	Zhu HZ, Zhang ZF, Zhou N, Jiang CY, Wang BJ, Cai L, Wang HM, Liu SJ.	Appl Environ Microbiol	10.1128/aem.02440-20	2021
	Summary of Novel Bacterial Isolates Derived from Human Clinical Specimens and Nomenclature Revisions Published in 2018 and 2019.	Munson E, Carroll KC.	J Clin Microbiol	10.1128/jcm.01309-20	2021
Genetics	Comprehensive Comparative Genomics and Phenotyping of Methylobacterium Species.	Alessa O, Ogura Y, Fujitani Y, Takami H, Hayashi T, Sahin N, Tani A.	Front Microbiol	10.3389/fmicb.2021.740610	2021
Phylogeny	Review of the genus Methylobacterium and closely related organisms: a proposal that some Methylobacterium species be reclassified into a new genus, Methylorubrum gen. nov.	Green PN, Ardley JK	Int J Syst Evol Microbiol	10.1099/ijsem.0.002856	2018
Phylogeny	Sphingomonas lacusdianchii sp. nov., an attached bacterium inhibited by metabolites from its symbiotic cyanobacterium.	Wang X, Xiao Y, Deng Y, Sang X, Deng QL, Wang L, Yang YW, Zhang BH, Zhang YQ.	Appl Microbiol Biotechnol	10.1007/s00253-024-13081-x	2024
Metabolism	Pseudomonas qingdaonensis sp. nov., an aflatoxin-degrading bacterium, isolated from peanut rhizospheric soil.	Wang MQ, Wang Z, Yu LN, Zhang CS, Bi J, Sun J.	Arch Microbiol	10.1007/s00203-019-01636-w	2019
Phylogeny	Methylobacterium pseudosasae sp. nov., a pink-pigmented, facultatively methylotrophic bacterium isolated from the bamboo phyllosphere.	Madhaiyan M, Poonguzhali S	Antonie Van Leeuwenhoek	10.1007/s10482-013-0085-0	2013
Metabolism	A novel pink-pigmented facultative methylotroph, Methylobacterium thiocyanatum sp. nov., capable of growth on thiocyanate or cyanate as sole nitrogen sources.	Wood AP, Kelly DP, McDonald IR, Jordan SL, Morgan TD, Khan S, Murrell JC, Borodina E	Arch Microbiol	10.1007/s002030050554	1998

References

#4386	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 11490
#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 )
#20218	Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.: StrainInfo introduces electronic passports for microorganisms.. Syst Appl Microbiol. 37: 42 - 50 2014 ( DOI 10.1016/j.syapm.2013.11.002 , PubMed 24321274 )
#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) .
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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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Methylorubrum thiocyanatum (DSM 11490, ATCC 700647, ALL/SCN-P)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_014138645

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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