Shewanella algae (CCUG 39355, NCTC 10738, LMG 2265)

Name: Shewanella algae (CCUG 39355, NCTC 10738, LMG 2265)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 150237

Type strain

Culture col. no. CCUG 39355 NCTC 10738 LMG 2265 IAM 13614 JCM 20959

NCBI tax ID(s) 38313

Special Collections CCUG JCM

Links

Shewanella algae CCUG 39355 is a mesophilic prokaryote that was isolated from Feces.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 4966

LMG 2265,IAM 13614,NCTC 10738,CCUG 39355,NCIMB 11157,JCM 20959

@ref 20215

Last LPSN update 2025-12-16 10:06:03

Domain Pseudomonadati

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Alteromonadales

Family Shewanellaceae

Genus Shewanella

Species Shewanella algae

Full scientific name Shewanella algae corrig. Simidu et al. 1990

Synonyms (3)

Shewanella alga
Shewanella upenei
Shewanella haliotis

BacDive ID	Other strains from **Shewanella algae** (22)	Type strain
14062	S. algae OK-1, DSM 9167, ATCC 51192, IAM 14159, NCIMB ... (type strain)
134829	S. algae CIP 72.3
136012	S. algae CIP 101181
137124	S. algae X 127, 567, CIP 67.65
137515	S. algae CIP 68.20
138042	S. algae Monchausse, CIP 102575
138792	S. algae CIP 103562, ATCC 49138
141271	S. algae CCUG 526
141303	S. algae CCUG 789
142550	S. algae CCUG 12945
142836	S. algae CCUG 15259
143597	S. algae CCUG 20533
144446	S. algae CCUG 24987
149900	S. algae CCUG 38646
150853	S. algae CCUG 42567
152459	S. algae CCUG 46849
152943	S. algae CCUG 48086
153654	S. algae CCUG 50501
155108	S. algae CCUG 56496
161437	S. algae JCM 13988
161438	S. algae JCM 13989
171020	S. algae CIMB 04-7478, CRBIP17.140

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	99
125439	negative	99.9

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	25	mesophilic

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		99.4

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	formaldehyde oxidation	100	3 of 3
66794	enterobactin biosynthesis	100	3 of 3
66794	suberin monomers biosynthesis	100	2 of 2
66794	ppGpp biosynthesis	100	4 of 4
66794	methylglyoxal degradation	100	5 of 5
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	adipate degradation	100	2 of 2
66794	coenzyme A metabolism	100	4 of 4
66794	vitamin K metabolism	100	5 of 5
66794	biotin biosynthesis	100	4 of 4
66794	L-lactaldehyde degradation	100	3 of 3
66794	gluconeogenesis	100	8 of 8
66794	aerobactin biosynthesis	100	1 of 1
66794	folate polyglutamylation	100	1 of 1
66794	threonine metabolism	100	10 of 10
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	ubiquinone biosynthesis	100	7 of 7
66794	palmitate biosynthesis	100	22 of 22
66794	cis-vaccenate biosynthesis	100	2 of 2
66794	tetrahydrofolate metabolism	92.86	13 of 14
66794	photosynthesis	92.86	13 of 14
66794	Entner Doudoroff pathway	90	9 of 10
66794	CO2 fixation in Crenarchaeota	88.89	8 of 9
66794	valine metabolism	88.89	8 of 9
66794	chorismate metabolism	88.89	8 of 9
66794	lipid A biosynthesis	88.89	8 of 9
66794	serine metabolism	88.89	8 of 9
66794	C4 and CAM-carbon fixation	87.5	7 of 8
66794	glutamate and glutamine metabolism	85.71	24 of 28
66794	reductive acetyl coenzyme A pathway	85.71	6 of 7
66794	heme metabolism	85.71	12 of 14
66794	NAD metabolism	83.33	15 of 18
66794	pyrimidine metabolism	82.22	37 of 45
66794	pentose phosphate pathway	81.82	9 of 11
66794	purine metabolism	80.85	76 of 94
66794	peptidoglycan biosynthesis	80	12 of 15
66794	hydrogen production	80	4 of 5
66794	aspartate and asparagine metabolism	77.78	7 of 9
66794	molybdenum cofactor biosynthesis	77.78	7 of 9
66794	leucine metabolism	76.92	10 of 13
66794	phenylalanine metabolism	76.92	10 of 13
66794	alanine metabolism	75.86	22 of 29
66794	butanoate fermentation	75	3 of 4
66794	isoleucine metabolism	75	6 of 8
66794	glycogen biosynthesis	75	3 of 4
66794	sulfopterin metabolism	75	3 of 4
66794	acetate fermentation	75	3 of 4
66794	CMP-KDO biosynthesis	75	3 of 4
66794	lipid metabolism	74.19	23 of 31
66794	flavin biosynthesis	73.33	11 of 15
66794	proline metabolism	72.73	8 of 11
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	citric acid cycle	71.43	10 of 14
66794	propanol degradation	71.43	5 of 7
66794	propionate fermentation	70	7 of 10
66794	cysteine metabolism	66.67	12 of 18
66794	octane oxidation	66.67	2 of 3
66794	selenocysteine biosynthesis	66.67	4 of 6
66794	acetoin degradation	66.67	2 of 3
66794	glycolate and glyoxylate degradation	66.67	4 of 6
66794	d-mannose degradation	66.67	6 of 9
66794	tryptophan metabolism	65.79	25 of 38
66794	methionine metabolism	65.38	17 of 26
66794	glycolysis	64.71	11 of 17
66794	glutathione metabolism	64.29	9 of 14
66794	vitamin B6 metabolism	63.64	7 of 11
66794	oxidative phosphorylation	62.64	57 of 91
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	62.5	5 of 8
66794	vitamin B1 metabolism	61.54	8 of 13
66794	lipoate biosynthesis	60	3 of 5
66794	glycogen metabolism	60	3 of 5
66794	starch degradation	60	6 of 10
66794	histidine metabolism	58.62	17 of 29
66794	arginine metabolism	58.33	14 of 24
66794	non-pathway related	57.89	22 of 38
66794	isoprenoid biosynthesis	57.69	15 of 26
66794	tyrosine metabolism	57.14	8 of 14
66794	lysine metabolism	57.14	24 of 42
66794	degradation of sugar alcohols	56.25	9 of 16
66794	urea cycle	53.85	7 of 13
66794	sulfate reduction	53.85	7 of 13
66794	dTDPLrhamnose biosynthesis	50	4 of 8
66794	glycine metabolism	50	5 of 10
66794	carnitine metabolism	50	4 of 8
66794	aminopropanol phosphate biosynthesis	50	1 of 2
66794	ketogluconate metabolism	50	4 of 8
66794	cyclohexanol degradation	50	2 of 4
66794	mannosylglycerate biosynthesis	50	1 of 2
66794	pantothenate biosynthesis	50	3 of 6
66794	ethanol fermentation	50	1 of 2
66794	nitrate assimilation	44.44	4 of 9
66794	androgen and estrogen metabolism	43.75	7 of 16
66794	metabolism of amino sugars and derivatives	40	2 of 5
66794	arachidonate biosynthesis	40	2 of 5
66794	glycine betaine biosynthesis	40	2 of 5
66794	factor 420 biosynthesis	40	2 of 5
66794	gallate degradation	40	2 of 5
66794	polyamine pathway	39.13	9 of 23
66794	3-phenylpropionate degradation	33.33	5 of 15
66794	sphingosine metabolism	33.33	2 of 6
66794	cyanate degradation	33.33	1 of 3
66794	acetyl CoA biosynthesis	33.33	1 of 3
66794	arachidonic acid metabolism	33.33	6 of 18
66794	degradation of aromatic, nitrogen containing compounds	33.33	4 of 12
66794	IAA biosynthesis	33.33	1 of 3
66794	(5R)-carbapenem carboxylate biosynthesis	33.33	1 of 3
66794	coenzyme M biosynthesis	30	3 of 10
66794	vitamin B12 metabolism	29.41	10 of 34
66794	aclacinomycin biosynthesis	28.57	2 of 7
66794	degradation of hexoses	27.78	5 of 18
66794	dolichyl-diphosphooligosaccharide biosynthesis	27.27	3 of 11
66794	metabolism of disaccharids	27.27	3 of 11
66794	ascorbate metabolism	27.27	6 of 22
66794	degradation of pentoses	25	7 of 28
66794	lactate fermentation	25	1 of 4
66794	phenol degradation	25	5 of 20
66794	toluene degradation	25	1 of 4
66794	alginate biosynthesis	25	1 of 4
66794	catecholamine biosynthesis	25	1 of 4
66794	degradation of sugar acids	24	6 of 25
66794	phosphatidylethanolamine bioynthesis	23.08	3 of 13
66794	phenylpropanoid biosynthesis	23.08	3 of 13
66794	4-hydroxymandelate degradation	22.22	2 of 9

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host Body Product	#Gastrointestinal tract	#Feces (Stool)

Isolation

@ref	Sample type
54760	Feces
67770	Feces

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	53550_C01 assembly for Shewanella algae NCTC10738	contig	GCA_900457125	24.15	2859001387	38313	79.15

Genome browser: GCA_900457125

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Shewanella algae NCTC10738
NCBI: GCA_900457125

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.40	no
125439	motility	BacteriaNetⓘ	yes	84.70	no
125439	gram_stain	BacteriaNetⓘ	negative	99.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	74.00	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Shewanella putrefaciens strain NCTC10738
PATRIC: 24.15

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	99.00	no
125438	anaerobic	anaerobicⓘ	no	92.92	no
125438	spore-forming	spore-formingⓘ	no	89.95	no
125438	thermophilic	thermophileⓘ	no	99.50	yes
125438	aerobic	aerobicⓘ	yes	58.19	no
125438	flagellated	motile2+ⓘ	yes	88.24	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Genomic analysis reveals high intra-species diversity of Shewanella algae.	Huang Z, Yu K, Fu S, Xiao Y, Wei Q, Wang D.	Microb Genom	10.1099/mgen.0.000786	2022
Genetics	Comparative Genomics of Cyclic di-GMP Metabolism and Chemosensory Pathways in Shewanella algae Strains: Novel Bacterial Sensory Domains and Functional Insights into Lifestyle Regulation.	Martin-Rodriguez AJ, Higdon SM, Thorell K, Tellgren-Roth C, Sjoling A, Galperin MY, Krell T, Romling U.	mSystems	10.1128/msystems.01518-21	2022

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 )
#54760	Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 39355
#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;
#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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Shewanella algae (CCUG 39355, NCTC 10738, LMG 2265)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Spore formation

Pathway annotation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_900457125

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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