Methanobacterium veterum (DSM 19849, VKM B-2440, MK4)

Name: Methanobacterium veterum (DSM 19849, VKM B-2440, MK4)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 6949

Type strain

Strain Designation MK4

Culture col. no. DSM 19849 VKM B-2440 MK4

NCBI tax ID(s) 408577

Special Collections DSMZ Literature strains

Links

Methanobacterium veterum MK4 is an anaerobe, mesophilic, Gram-negative prokaryote that was isolated from ancient permafrost sediments.

Gram-negative rod-shaped anaerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 368575

DSM 19849,VKM B-2440

@ref 20215

Last LPSN update 2025-12-16 09:48:27

Domain Methanobacteriati

Phylum Methanobacteriota

Class Methanobacteria

Order Methanobacteriales

Family Methanobacteriaceae

Genus Methanobacterium

Species Methanobacterium veterum

Full scientific name Methanobacterium veterum Krivushin et al. 2010

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
29342	negative	5 µm	0.425 µm	rod-shaped
125439	negative				96
125438					90.875

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
8288	METHANOBACTERIUM ESPANOLAE MEDIUM (DSMZ Medium 506)		Medium recipe at MediaDive	Name: METHANOBACTERIUM ESPANOLAE MEDIUM (DSMZ Medium 506) Composition: Na-acetate x 3 H2O 2.4728 g/l Na2CO3 0.49456 g/l (NH4)2SO4 0.445104 g/l K2HPO4 0.286845 g/l Na2S x 9 H2O 0.24728 g/l L-Cysteine HCl x H2O 0.24728 g/l KH2PO4 0.178042 g/l MgSO4 x 7 H2O 0.0296736 g/l Nitrilotriacetic acid 0.0148368 g/l NaCl 0.0098912 g/l MnSO4 x H2O 0.0049456 g/l ZnSO4 x 7 H2O 0.00178042 g/l CoSO4 x 7 H2O 0.00178042 g/l CaCl2 x 2 H2O 0.00098912 g/l FeSO4 x 7 H2O 0.00098912 g/l Sodium resazurin 0.00049456 g/l NiCl2 x 6 H2O 0.000296736 g/l AlK(SO4)2 x 12 H2O 0.000197824 g/l CuSO4 x 5 H2O 9.8912e-05 g/l H3BO3 9.8912e-05 g/l Na2MoO4 x 2 H2O 9.8912e-05 g/l Pyridoxine hydrochloride 9.8912e-05 g/l Nicotinic acid 4.9456e-05 g/l (DL)-alpha-Lipoic acid 4.9456e-05 g/l Riboflavin 4.9456e-05 g/l Thiamine HCl 4.9456e-05 g/l Calcium D-(+)-pantothenate 4.9456e-05 g/l p-Aminobenzoic acid 4.9456e-05 g/l Biotin 1.97824e-05 g/l Folic acid 1.97824e-05 g/l Na2WO4 x 2 H2O 3.95648e-06 g/l Na2SeO3 x 5 H2O 2.96736e-06 g/l Vitamin B12 9.8912e-07 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
8288	positive	growth	28	mesophilic
29342	positive	growth	10-46
29342	positive	optimum	28	mesophilic

Culture pH

@ref	Ability	Type	PH	PH range
29342	positive	optimum	7.3
29342	positive	growth	5.2-9.4	alkaliphile

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance
8288	anaerobe
29342	anaerobe

Spore formation

@ref	Spore formation	Confidence
29342
125439		98.2

Halophily

@ref	Salt	Growth	Tested relation	Concentration
29342	NaCl	positive	growth	0-0.3 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
29342	30089 ChEBI	acetate	+	carbon source

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Permafrost
#Environmental	#Terrestrial	#Sediment

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
8288	ancient (3 million years old) permafrost sediments	Kolyma Lowland (70° 06' N 154° 04' E)	Russia	RUS	Asia	70.1	154.067 70.1/154.067

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
8288	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
66792	ASM74548v1 assembly for Methanobacterium veterum MK4	scaffold	GCA_000745485	408577.3	2582580744	408577	71.4
66792	ASM2711045v1 assembly for Methanobacterium veterum MK4	scaffold	GCA_027110455		8118917361	408577	66.54

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
8288	Methanobacterium veterum strain MK4 16S ribosomal RNA gene, partial sequence	EF016285	1347		408577

GC content

@ref	GC-content (mol%)	Method
8288	33.8±0.3	thermal denaturation, midpoint method (Tm)
29342	33.8

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Methanobacterium veterum MK4
NCBI: GCA_000745485

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	98.20	no
125439	motility	BacteriaNetⓘ	no	74.80	no
125439	gram_stain	BacteriaNetⓘ	negative	96.00	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	74.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methanobacterium veterum MK4
NCBI: GCA_000745485.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	65.31	yes
125438	anaerobic	anaerobicⓘ	yes	88.76	yes
125438	aerobic	aerobicⓘ	no	85.62	yes
125438	spore-forming	spore-formingⓘ	no	85.16	no
125438	thermophilic	thermophileⓘ	no	78.59	yes
125438	flagellated	motile2+ⓘ	no	90.88	yes

Literature

Topic	Title	Authors	Journal	DOI	Year
Metabolism	An Antarctic Extreme Halophile and Its Polyextremophilic Enzyme: Effects of Perchlorate Salts.	Laye VJ, DasSarma S.	Astrobiology	10.1089/ast.2017.1766	2018
Phylogeny	Methanobacterium veterum sp. nov., from ancient Siberian permafrost.	Krivushin KV, Shcherbakova VA, Petrovskaya LE, Rivkina EM	Int J Syst Evol Microbiol	10.1099/ijs.0.011205-0	2009

References

#8288	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 19849
#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 )
#29342	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 #25754 (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) .
#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 )

Rate our new design

Content

About us

Methanobacterium veterum (DSM 19849, VKM B-2440, MK4)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Metabolite utilization

Isolation, sampling and environmental information

Isolation source categories

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_000745485

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

Help

Social Media