Geomobilimonas luticola (DSM 24905, JCM 17780, OSK6)

Name: Geomobilimonas luticola (DSM 24905, JCM 17780, OSK6)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 23031

Type strain

Strain Designation OSK6

Culture col. no. DSM 24905 JCM 17780 OSK6

NCBI tax ID(s) 1114878

Special Collections DSMZ JCM Literature strains

History DSMZ <- K. Nakamura, Faculty Applied Biological Sci., Gifu Univ., Japan; OSK6 <- K. Nakamura {2011} JCM <-- K. Nakamura OSK6.

Links

Geomobilimonas luticola OSK6 is an anaerobe, Gram-negative, motile bacterium that was isolated from mud from lotus field.

Gram-negative motile rod-shaped anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 402242

JCM 17780,DSM 24905

@ref 20215

Last LPSN update 2026-05-29 08:30:21

Domain Bacteria

Phylum Thermodesulfobacteriota

Class Desulfuromonadia

Order Geobacterales

Family Geobacteraceae

Genus Geomobilimonas

Species Geomobilimonas luticola

Full scientific name Geomobilimonas luticola (Viulu et al. 2013) Xu et al. 2022

Synonyms (1)

Geobacter luticola

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Motility	Confidence
30588	negative	1.25 µm	0.3 µm	rod-shaped
125438	negative					96.528

Pigmentation

30588

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
19247	GEOANAEROBACTER MEDIUM (DSMZ Medium 838)		Medium recipe at MediaDive	Name: GEOANAEROBACTER MEDIUM (DSMZ Medium 838) Composition: Ferric citrate monohydrate 9.98004 g/l Na2CO3 1.49701 g/l Na-acetate 0.798403 g/l Na-ascorbate 0.798403 g/l KH2PO4 0.598802 g/l MgSO4 x 7 H2O 0.499002 g/l NH4Cl 0.299401 g/l CaCl2 x 2 H2O 0.0998004 g/l Na2-EDTA x 2 H2O 0.00518962 g/l FeCl2 x 4 H2O 0.00149701 g/l NaOH 0.000499002 g/l CoCl2 x 6 H2O 0.000189621 g/l MnCl2 x 4 H2O 9.98004e-05 g/l ZnCl2 6.98603e-05 g/l Na2MoO4 x 2 H2O 3.59281e-05 g/l NiCl2 x 6 H2O 2.39521e-05 g/l H3BO3 5.98802e-06 g/l Na2WO4 x 2 H2O 3.99202e-06 g/l Na2SeO3 x 5 H2O 2.99401e-06 g/l CuCl2 x 2 H2O 1.99601e-06 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
19247	positive	growth	30
30588	positive	growth	20-40
30588	positive	optimum	33.5
67770	positive	growth	30

Culture pH

@ref	Ability	Type	PH
30588	positive	optimum	7
30588	positive	growth	6.5-7.5

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
19247	anaerobe
30588	anaerobe
125439	obligate anaerobe	95.986

Spore formation

@ref	Spore formation	Confidence
125439		97.578

Observation

67770

Observationquinones: MK-8

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
30588	30089 ChEBI	acetate	+	carbon source
30588	24996 ChEBI	lactate	+	carbon source
30588	17632 ChEBI	nitrate	+	reduction
30588	15361 ChEBI	pyruvate	+	carbon source
30588	30031 ChEBI	succinate	+	carbon source

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Agriculture	#Field
#Environmental	#Terrestrial	#Mud (Sludge)
#Host	#Plants	#Aquatic plant

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
19247	mud from lotus field	Aichi Prefecture, Aisai	Japan	JPN	Asia
67770	Lotus field mud in Aichi		Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence AB682759 (>99% sequence identity) for Geobacter luticola subclade from Microbeatlas

Aquatic Samples	44
Soil Samples	66
Animal Samples	2
Plant Samples	4
Total Samples	116

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
19247	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	ASM1847690v1 assembly for Geomobilimonas luticola JCM 17780	contig	GCA_018476905	1114878.3	8002177184	1114878	70.85

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
19247	Geobacter luticola gene for 16S rRNA, partial sequence	AB682759	1478		1114878

GC content

@ref	GC-content (mol%)	Method
19247	59.7	high performance liquid chromatography (HPLC)
30588	59.7

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1847690v1 assembly for Geomobilimonas luticola JCM 17780
NCBI: GCA_018476905

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate anaerobe	95.99	no
125439	gram_stain	BacteriaNetⓘ	negative	72.40	no
125439	spore_formation	BacteriaNetⓘ	no	97.58	no
125439	motility	BacteriaNetⓘ	no	67.11	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Geobacter luticola strain JCM 17780
PATRIC: 1114878.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	96.53	no
125438	anaerobic	anaerobicⓘ	yes	72.75	yes
125438	spore-forming	spore-formingⓘ	no	81.98	no
125438	aerobic	aerobicⓘ	no	79.31	yes
125438	thermophilic	thermophileⓘ	no	90.72	yes
125438	flagellated	motile2+ⓘ	no	54.45	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Geobacter luticola sp. nov., an Fe(III)-reducing bacterium isolated from lotus field mud.	Viulu S, Nakamura K, Okada Y, Saitou S, Takamizawa K	Int J Syst Evol Microbiol	10.1099/ijs.0.039321-0	2012

References

#19247	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 24905
#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 )
#26919	IJSEM 442 2013 ( DOI 10.1099/ijs.0.039321-0 , PubMed 22493170 )
#30588	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 #26919
#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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Geomobilimonas luticola (DSM 24905, JCM 17780, OSK6)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Metabolite utilization

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_018476905

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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