Gemmobacter megaterium (DSM 26375, CGMCC 1.11024, JCM 18498)

Name: Gemmobacter megaterium (DSM 26375, CGMCC 1.11024, JCM 18498)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 24488

Type strain

Strain Designation CF17

Culture col. no. DSM 26375 CGMCC 1.11024 JCM 18498 CF17

NCBI tax ID(s) 1086013

Special Collections DSMZ JCM

History <- J. Liu, Zhejiang Univ., College of Life Scs., Hangzhou, China; CF17 <- F.-T. Chi X.-Q. Zhang CF17.

Links

Gemmobacter megaterium CF17 is a bacterium that was isolated from planktonic seaweed from coastal seawater.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 407198

JCM 18498,DSM 26375

@ref 20215

Last LPSN update 2026-02-09 11:23:59

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Rhodobacterales

Family Paracoccaceae

Genus Gemmobacter

Species Gemmobacter megaterium

Full scientific name Gemmobacter megaterium Liu et al. 2014

Synonyms (1)

Wagnerdoeblera megaterium

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	98.328
125439	negative	93.4

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
20578	BACTO MARINE BROTH (DIFCO 2216) (DSMZ Medium 514)		Medium recipe at MediaDive	Name: BACTO MARINE BROTH (DIFCO 2216) (DSMZ Medium 514) Composition: NaCl 19.45 g/l MgCl2 5.9 g/l Bacto peptone 5.0 g/l Na2SO4 3.24 g/l CaCl2 1.8 g/l Yeast extract 1.0 g/l KCl 0.55 g/l NaHCO3 0.16 g/l Fe(III) citrate 0.1 g/l KBr 0.08 g/l SrCl2 0.034 g/l H3BO3 0.022 g/l Na2HPO4 0.008 g/l Na-silicate 0.004 g/l NaF 0.0024 g/l (NH4)NO3 0.0016 g/l Distilled water
20578	ONR7a MEDIUM (DSMZ Medium 950)		Medium recipe at MediaDive	Name: ONR7a MEDIUM (DSMZ Medium 950; with strain-specific modifications) Composition: NaCl 22.79 g/l Agar 15.0 g/l Agarose 12.0 g/l MgCl2 x 6 H2O 11.18 g/l Sodium pyruvate 10.0 g/l Na2SO4 3.98 g/l CaCl2 x 2 H2O 1.46 g/l TAPSO 1.3 g/l KCl 0.72 g/l NH4Cl 0.27 g/l Na2HPO4 x 7 H2O 0.089 g/l NaBr 0.083 g/l NaHCO3 0.031 g/l H3BO3 0.027 g/l SrCl2 x 6 H2O 0.024 g/l NaF 0.0026 g/l FeCl2 x 4 H2O 0.002 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
20578	positive	growth	28
67770	positive	growth	27

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	97.7

Spore formation

@ref	Spore formation	Confidence
125438		90.927

Observation

67770

Observationquinones: Q-10

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	aerobactin biosynthesis	100	1 of 1
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	gluconeogenesis	100	8 of 8
66794	C4 and CAM-carbon fixation	100	8 of 8
66794	alginate biosynthesis	100	4 of 4
66794	valine metabolism	100	9 of 9
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	denitrification	100	2 of 2
66794	resorcinol degradation	100	2 of 2
66794	ppGpp biosynthesis	100	4 of 4
66794	coenzyme A metabolism	100	4 of 4
66794	acetoin degradation	100	3 of 3
66794	adipate degradation	100	2 of 2
66794	octane oxidation	100	3 of 3
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	cis-vaccenate biosynthesis	100	2 of 2
66794	folate polyglutamylation	100	1 of 1
66794	formaldehyde oxidation	100	3 of 3
66794	ethanol fermentation	100	2 of 2
66794	suberin monomers biosynthesis	100	2 of 2
66794	palmitate biosynthesis	100	22 of 22
66794	threonine metabolism	100	10 of 10
66794	L-lactaldehyde degradation	100	3 of 3
66794	phenylalanine metabolism	92.31	12 of 13
66794	leucine metabolism	92.31	12 of 13
66794	Entner Doudoroff pathway	90	9 of 10
66794	propionate fermentation	90	9 of 10
66794	serine metabolism	88.89	8 of 9
66794	chorismate metabolism	88.89	8 of 9
66794	allantoin degradation	88.89	8 of 9
66794	4-hydroxymandelate degradation	88.89	8 of 9
66794	molybdenum cofactor biosynthesis	88.89	8 of 9
66794	aspartate and asparagine metabolism	88.89	8 of 9
66794	CO2 fixation in Crenarchaeota	88.89	8 of 9
66794	lipid A biosynthesis	88.89	8 of 9
66794	glutathione metabolism	85.71	12 of 14
66794	glycolate and glyoxylate degradation	83.33	5 of 6
66794	tryptophan metabolism	81.58	31 of 38
66794	ethylmalonyl-CoA pathway	80	4 of 5
66794	methylglyoxal degradation	80	4 of 5
66794	phenylacetate degradation (aerobic)	80	4 of 5
66794	phenol degradation	80	16 of 20
66794	lipoate biosynthesis	80	4 of 5
66794	4-hydroxyphenylacetate degradation	80	8 of 10
66794	gallate degradation	80	4 of 5
66794	peptidoglycan biosynthesis	80	12 of 15
66794	alanine metabolism	79.31	23 of 29
66794	tyrosine metabolism	78.57	11 of 14
66794	photosynthesis	78.57	11 of 14
66794	d-mannose degradation	77.78	7 of 9
66794	NAD metabolism	77.78	14 of 18
66794	purine metabolism	75.53	71 of 94
66794	CMP-KDO biosynthesis	75	3 of 4
66794	isoleucine metabolism	75	6 of 8
66794	butanoate fermentation	75	3 of 4
66794	polyamine pathway	73.91	17 of 23
66794	3-phenylpropionate degradation	73.33	11 of 15
66794	methionine metabolism	73.08	19 of 26
66794	pentose phosphate pathway	72.73	8 of 11
66794	proline metabolism	72.73	8 of 11
66794	heme metabolism	71.43	10 of 14
66794	ubiquinone biosynthesis	71.43	5 of 7
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	citric acid cycle	71.43	10 of 14
66794	reductive acetyl coenzyme A pathway	71.43	5 of 7
66794	glutamate and glutamine metabolism	71.43	20 of 28
66794	pyrimidine metabolism	71.11	32 of 45
66794	lipid metabolism	70.97	22 of 31
66794	urea cycle	69.23	9 of 13
66794	vitamin B1 metabolism	69.23	9 of 13
66794	lysine metabolism	69.05	29 of 42
66794	non-pathway related	68.42	26 of 38
66794	oxidative phosphorylation	68.13	62 of 91
66794	acetyl CoA biosynthesis	66.67	2 of 3
66794	cyanate degradation	66.67	2 of 3
66794	flavin biosynthesis	66.67	10 of 15
66794	vitamin B6 metabolism	63.64	7 of 11
66794	arginine metabolism	62.5	15 of 24
66794	ketogluconate metabolism	62.5	5 of 8
66794	isoprenoid biosynthesis	61.54	16 of 26
66794	sulfate reduction	61.54	8 of 13
66794	cellulose degradation	60	3 of 5
66794	hydrogen production	60	3 of 5
66794	glycolysis	58.82	10 of 17
66794	histidine metabolism	58.62	17 of 29
66794	degradation of aromatic, nitrogen containing compounds	58.33	7 of 12
66794	tetrahydrofolate metabolism	57.14	8 of 14
66794	propanol degradation	57.14	4 of 7
66794	androgen and estrogen metabolism	56.25	9 of 16
66794	degradation of sugar alcohols	56.25	9 of 16
66794	cysteine metabolism	55.56	10 of 18
66794	quinate degradation	50	1 of 2
66794	phenylmercury acetate degradation	50	1 of 2
66794	selenocysteine biosynthesis	50	3 of 6
66794	myo-inositol biosynthesis	50	5 of 10
66794	aminopropanol phosphate biosynthesis	50	1 of 2
66794	ribulose monophosphate pathway	50	1 of 2
66794	glycine metabolism	50	5 of 10
66794	acetate fermentation	50	2 of 4
66794	biotin biosynthesis	50	2 of 4
66794	toluene degradation	50	2 of 4
66794	mannosylglycerate biosynthesis	50	1 of 2
66794	sulfopterin metabolism	50	2 of 4
66794	dTDPLrhamnose biosynthesis	50	4 of 8
66794	bile acid biosynthesis, neutral pathway	47.06	8 of 17
66794	nitrate assimilation	44.44	4 of 9
66794	benzoyl-CoA degradation	42.86	3 of 7
66794	vitamin K metabolism	40	2 of 5
66794	glycogen metabolism	40	2 of 5
66794	coenzyme M biosynthesis	40	4 of 10
66794	arachidonate biosynthesis	40	2 of 5
66794	metabolism of amino sugars and derivatives	40	2 of 5
66794	glycine betaine biosynthesis	40	2 of 5
66794	degradation of pentoses	39.29	11 of 28
66794	arachidonic acid metabolism	38.89	7 of 18
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	37.5	3 of 8
66794	carnitine metabolism	37.5	3 of 8
66794	degradation of sugar acids	36	9 of 25
66794	IAA biosynthesis	33.33	1 of 3
66794	(5R)-carbapenem carboxylate biosynthesis	33.33	1 of 3
66794	sphingosine metabolism	33.33	2 of 6
66794	methane metabolism	33.33	1 of 3
66794	vitamin B12 metabolism	32.35	11 of 34
66794	mevalonate metabolism	28.57	2 of 7
66794	degradation of hexoses	27.78	5 of 18
66794	d-xylose degradation	27.27	3 of 11
66794	dolichyl-diphosphooligosaccharide biosynthesis	27.27	3 of 11
66794	catecholamine biosynthesis	25	1 of 4
66794	methanogenesis from CO2	25	3 of 12
66794	lactate fermentation	25	1 of 4
66794	cyclohexanol degradation	25	1 of 4
66794	glycogen biosynthesis	25	1 of 4
66794	phosphatidylethanolamine bioynthesis	23.08	3 of 13
66794	ascorbate metabolism	22.73	5 of 22
66794	daunorubicin biosynthesis	22.22	2 of 9

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Marine
#Environmental	#Terrestrial	#Coast
#Host	#Algae	-

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
20578	planktonic seaweed from coastal seawater	East China Sea, Zhoushan sea area	China	CHN	Asia
67770	Coastal planktonic seaweeds	East China Sea

Taxonmaps

69479

Global distribution of 16S sequence JN620361 (>99% sequence identity) for Gemmobacter megaterium subclade from Microbeatlas

Aquatic Samples	85
Soil Samples	6
Animal Samples	17
Plant Samples	2
Total Samples	110

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
20578	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1463639v1 assembly for Gemmobacter megaterium CGMCC 1.11024	scaffold	GCA_014636395	1086013.8	8066316255	1086013	69.87
67770	IMG-taxon 2681813556 annotated assembly for Gemmobacter megaterium DSM 26375	contig	GCA_900156815	1086013.3	2681813556	1086013	69.4

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20578	Gemmobacter megaterium strain CF17 16S ribosomal RNA gene, partial sequence	JN620361	1428		1086013

GC content

@ref	GC-content (mol%)	Method
20578	61.4	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: Gemmobacter megaterium CGMCC 1.11024
NCBI: GCA_014636395

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	97.70	no
125439	gram_stain	BacteriaNetⓘ	negative	93.40	no
125439	motility	BacteriaNetⓘ	yes	69.80	no
125439	spore_formation	BacteriaNetⓘ	no	87.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Gemmobacter megaterium CGMCC 1.11024
NCBI: GCA_014636395.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.33	no
125438	anaerobic	anaerobicⓘ	no	91.99	no
125438	aerobic	aerobicⓘ	yes	82.43	no
125438	spore-forming	spore-formingⓘ	no	90.93	no
125438	thermophilic	thermophileⓘ	no	94.58	yes
125438	flagellated	motile2+ⓘ	no	55.33	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
Phylogeny	Gemmobacter megaterium sp. nov., isolated from coastal planktonic seaweeds.	Liu JJ, Zhang XQ, Chi FT, Pan J, Sun C, Wu M	Int J Syst Evol Microbiol	10.1099/ijs.0.050955-0	2013

References

#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 )
#20578	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 26375
#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) .
#66794	Antje Chang, Lisa Jeske, Sandra Ulbrich, Julia Hofmann, Julia Koblitz, Ida Schomburg, Meina Neumann-Schaal, Dieter Jahn, Dietmar Schomburg: BRENDA, the ELIXIR core data resource in 2021: new developments and updates. Nucleic Acids Res. 49: D498 - D508 2020 ( DOI 10.1093/nar/gkaa1025 , PubMed 33211880 )
#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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Gemmobacter megaterium (DSM 26375, CGMCC 1.11024, JCM 18498)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Pathway annotation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_014636395

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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