Methanosarcina mazei (DSM 9195, TMA, JCM 9314)

Name: Methanosarcina mazei (DSM 9195, TMA, JCM 9314)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 7106

Type strain

Strain Designation TMA

Culture col. no. DSM 9195 TMA JCM 9314 NBRC 101201

NCBI tax ID(s) 1293038 2209

Special Collections DSMZ JCM

Links

Methanosarcina mazei TMA is an anaerobe, mesophilic prokaryote that was isolated from paddy field soil.

anaerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 48592

DSM 9195,JCM 9314,NBRC 101201

@ref 20215

Last LPSN update 2025-12-16 09:48:29

Domain Methanobacteriati

Phylum Methanobacteriota

Class Methanosarcinia

Order Methanosarcinales

Family Methanosarcinaceae

Genus Methanosarcina

Species Methanosarcina mazei

Full scientific name Methanosarcina mazei corrig. (Barker 1936) Mah and Kuhn 1984

Synonyms (4)

Methanosarcina frisia
Methanococcus frisius
Methanosarcina mazeii
Methanococcus mazei

BacDive ID	Other strains from **Methanosarcina mazei** (13)	Type strain
7096	M. mazei S-6, DSM 2053, ATCC 43572, OCM 26, DSM 108209 (type strain)
7097	M. mazei Z-558, DSM 2244, OCM 92
7098	M. mazei MC3, DSM 2907, OCM 192
7099	M. mazei C16, DSM 3318, ATCC 43340, OCM 98
7100	M. mazei G1, DSM 3338, OCM 87
7101	M. mazei Gö1, DSM 3647, ATCC BAA-159, JCM 11833, ...
7102	M. mazei DSM 4556, ATCC 43573, OCM 34
7103	M. mazei T18, DSM 6300
7104	M. mazei Equi, DSM 7058, OCM 61
7105	M. mazei Gö1, DSM 7222
7107	M. mazei SarPi, DSM 10132
24166	M. mazei O1M9701, DSM 27785, OCM 748
164152	M. mazei JCM 31898, VKM B-2370

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	96.4

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
3509	METHANOSARCINA MEDIUM (DSMZ Medium 120)		Medium recipe at MediaDive	Name: METHANOSARCINA MEDIUM (DSMZ Medium 120; with strain-specific modifications) Composition: Trimethylamine-HCl 4.88281 g/l Na-acetate 2.44141 g/l NaCl 2.19727 g/l Casitone 1.95312 g/l Yeast extract 1.95312 g/l NaHCO3 1.95312 g/l MgSO4 x 7 H2O 0.488281 g/l NH4Cl 0.488281 g/l K2HPO4 0.341797 g/l Na2S x 9 H2O 0.292969 g/l L-Cysteine HCl x H2O 0.292969 g/l CaCl2 x 2 H2O 0.244141 g/l KH2PO4 0.224609 g/l HCl 0.00244141 g/l FeSO4 x 7 H2O 0.00195312 g/l FeCl2 x 4 H2O 0.00146484 g/l Sodium resazurin 0.000488281 g/l CoCl2 x 6 H2O 0.000185547 g/l MnCl2 x 4 H2O 9.76563e-05 g/l Pyridoxine hydrochloride 9.76563e-05 g/l ZnCl2 6.83594e-05 g/l Nicotinic acid 4.88281e-05 g/l (DL)-alpha-Lipoic acid 4.88281e-05 g/l Riboflavin 4.88281e-05 g/l p-Aminobenzoic acid 4.88281e-05 g/l Thiamine HCl 4.88281e-05 g/l Calcium D-(+)-pantothenate 4.88281e-05 g/l Na2MoO4 x 2 H2O 3.51562e-05 g/l NiCl2 x 6 H2O 2.34375e-05 g/l Biotin 1.95312e-05 g/l Folic acid 1.95312e-05 g/l H3BO3 5.85938e-06 g/l CuCl2 x 2 H2O 1.95313e-06 g/l Vitamin B12 9.76563e-07 g/l H2SO4 Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
3509	positive	growth	37	mesophilic
67770	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

3509

Oxygen toleranceanaerobe

Spore formation

@ref	Spore formation	Confidence
125439		94.4

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Agriculture	#Field
#Environmental	#Terrestrial	#Soil
#Host	#Plants	#Herbaceous plants (Grass,Crops)
#Condition	#Anoxic (anaerobic)	-
#Condition	#Humid	-

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
3509	paddy field soil	Fukuoka prefecture, Chikugo city	Japan	JPN	Asia
67770	Paddy field soil in Chikugo	Fukuoka	Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence AB065295 (>99% sequence identity) for Methanosarcina from Microbeatlas

Aquatic Samples	3372
Soil Samples	2215
Animal Samples	684
Plant Samples	931
Total Samples	7202

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
3509	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score	IMG accession
66792	ASM1966994v1 assembly for Methanosarcina mazei TMA	complete	GCA_019669945	2209.222	2209	96.47
66792	ASM2503588v1 assembly for Methanosarcina mazei TMA	chromosome	GCA_025035885	1434116.4	1434116	70.75
66792	ASM131586v1 assembly for Methanosarcina mazei JCM 9314	contig	GCA_001315865	1293038.3	1293038		2681813026

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	Methanosarcina mazei gene for 16S rRNA	AB065295	1439		2209

GC content

@ref	GC-content (mol%)	Method
3509	42.1	high performance liquid chromatography (HPLC)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Methanosarcina mazei strain TMA
PATRIC: 2209.222

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	85.20	no
125439	gram_stain	BacteriaNetⓘ	negative	96.40	no
125439	motility	BacteriaNetⓘ	no	81.70	no
125439	spore_formation	BacteriaNetⓘ	no	94.40	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methanosarcina mazei TMA
NCBI: GCA_019669945.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	67.20	no
125438	anaerobic	anaerobicⓘ	yes	85.45	yes
125438	aerobic	aerobicⓘ	no	89.79	yes
125438	spore-forming	spore-formingⓘ	no	82.34	no
125438	thermophilic	thermophileⓘ	no	83.64	yes
125438	flagellated	motile2+ⓘ	no	84.71	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Methanosarcina Spherical Virus, a Novel Archaeal Lytic Virus Targeting Methanosarcina Strains.	Weidenbach K, Nickel L, Neve H, Alkhnbashi OS, Kunzel S, Kupczok A, Bauersachs T, Cassidy L, Tholey A, Backofen R, Schmitz RA.	J Virol	10.1128/jvi.00955-17	2017
Enzymology	Identification of the gene for disaggregatase from Methanosarcina mazei.	Osumi N, Kakehashi Y, Matsumoto S, Nagaoka K, Sakai J, Miyashita K, Kimura M, Asakawa S.	Archaea	10.1155/2008/949458	2008
	Growth and activity of ANME clades with different sulfate and sulfide concentrations in the presence of methane.	Timmers PH, Widjaja-Greefkes HC, Ramiro-Garcia J, Plugge CM, Stams AJ.	Front Microbiol	10.3389/fmicb.2015.00988	2015
	Thiosulphate conversion in a methane and acetate fed membrane bioreactor.	Suarez-Zuluaga DA, Timmers PH, Plugge CM, Stams AJ, Buisman CJ, Weijma J.	Environ Sci Pollut Res Int	10.1007/s11356-015-5344-3	2016
Metabolism	Growth of anaerobic methane-oxidizing archaea and sulfate-reducing bacteria in a high-pressure membrane capsule bioreactor.	Timmers PH, Gieteling J, Widjaja-Greefkes HC, Plugge CM, Stams AJ, Lens PN, Meulepas RJ.	Appl Environ Microbiol	10.1128/aem.03255-14	2015
Metabolism	Bacteria mediate methylation of iodine in marine and terrestrial environments.	Amachi S, Kamagata Y, Kanagawa T, Muramatsu Y.	Appl Environ Microbiol	10.1128/aem.67.6.2718-2722.2001	2001
	Correlation of Key Physiological Properties of Methanosarcina Isolates with Environment of Origin.	Zhou J, Holmes DE, Tang HY, Lovley DR.	Appl Environ Microbiol	10.1128/aem.00731-21	2021

References

#3509	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 9195
#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 .
#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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Methanosarcina mazei (DSM 9195, TMA, JCM 9314)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_019669945

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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