Acinetobacter nectaris (CCUG 68431, CIP 110549, DSM 29975)

Name: Acinetobacter nectaris (CCUG 68431, CIP 110549, DSM 29975)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 130450

Type strain

Culture col. no. CCUG 68431 CIP 110549 DSM 29975 CECT 8127 LMG 26958 1 more

NCBI tax ID(s) 1392540 1219382

Special Collections DSMZ CCUG CIP Literature strains

Links

Acinetobacter nectaris CCUG 68431 is an aerobe, mesophilic, Gram-negative prokaryote that was isolated from Floral nectar of the plant species Muscari comosum.

Gram-negative ovoid-shaped aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 379900

LMG 26958,CECT 8127,CIP 110549,DSM 29975,CCUG 68431

@ref 20215

Last LPSN update 2025-12-16 10:01:00

Domain Pseudomonadati

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Pseudomonadales

Family Moraxellaceae

Genus Acinetobacter

Species Acinetobacter nectaris

Full scientific name Acinetobacter nectaris Álvarez-Pérez et al. 2013

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape
30741	negative	1.5 µm	1.5 µm	ovoid-shaped
125438	negative
125439	negative
121255				oval-shaped

Colony morphology

@ref	Incubation period
21451	1-2 days
63485	1 day

Pigmentation

30741

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Composition
42140	MEDIUM 29- Brain heart agar	Distilled water make up to (1000.000 ml);Brain heart infusion agar (52.000 g)
21451	TRYPTICASE SOY BROTH AGAR (DSMZ Medium 535)	Name: TRYPTICASE SOY BROTH AGAR (DSMZ Medium 535) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Distilled water
21451	NUTRIENT AGAR (DSMZ Medium 1)	Name: NUTRIENT AGAR (DSMZ Medium 1) Composition: Agar 15.0 g/l Peptone 5.0 g/l Meat extract 3.0 g/l Distilled water
121255	CIP Medium 29

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
21451	positive	growth	30	mesophilic
30741	positive	optimum	25-30	mesophilic
42140	positive	growth	25	mesophilic
63485	positive	growth	30	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance
30741	aerobe
63485	aerobe
125439	obligate aerobe

Spore formation

@ref	Spore formation
30741
125438
125439

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68369	17128 ChEBI	adipate	-	assimilation	from API 20NE
68369	29016 ChEBI	arginine	-	hydrolysis	from API 20NE
30741	22653 ChEBI	asparagine	+	carbon source
30741	35391 ChEBI	aspartate	+	carbon source
68369	17634 ChEBI	D-glucose	+	assimilation	from API 20NE
68369	17634 ChEBI	D-glucose	+	fermentation	from API 20NE
68369	16899 ChEBI	D-mannitol	-	assimilation	from API 20NE
68369	16024 ChEBI	D-mannose	-	assimilation	from API 20NE
68369	27689 ChEBI	decanoate	-	assimilation	from API 20NE
68369	4853 ChEBI	esculin	-	hydrolysis	from API 20NE
30741	28757 ChEBI	fructose	+	carbon source
68369	5291 ChEBI	gelatin	-	hydrolysis	from API 20NE
68369	24265 ChEBI	gluconate	+	assimilation	from API 20NE
30741	29987 ChEBI	glutamate	+	carbon source
68369	30849 ChEBI	L-arabinose	-	assimilation	from API 20NE
30741	25115 ChEBI	malate	+	carbon source
68369	25115 ChEBI	malate	+	assimilation	from API 20NE
68369	17306 ChEBI	maltose	-	assimilation	from API 20NE
30741	37684 ChEBI	mannose	+	carbon source
68369	59640 ChEBI	N-acetylglucosamine	-	assimilation	from API 20NE
68369	17632 ChEBI	nitrate	-	reduction	from API 20NE
30741	26271 ChEBI	proline	+	carbon source
30741	30031 ChEBI	succinate	+	carbon source
30741	17992 ChEBI	sucrose	+	carbon source
68369	27897 ChEBI	tryptophan	-	energy source	from API 20NE
68369	16199 ChEBI	urea	-	hydrolysis	from API 20NE

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68369	35581 ChEBI	indole		from API 20NE

Metabolite tests

@ref	Chebi-ID	Metabolite	Indole test
68369	35581 ChEBI	indole	-	from API 20NE

Enzymes

@ref	Value	Activity	Ec
68369	arginine dihydrolase	-	3.5.3.6	from API 20NE
68369	beta-glucosidase	-	3.2.1.21	from API 20NE
21451	catalase	+	1.11.1.6
30741	catalase	+	1.11.1.6
68369	gelatinase	-		from API 20NE
68369	urease	-	3.5.1.5	from API 20NE

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	cis-vaccenate biosynthesis	100	2 of 2
66794	adipate degradation	100	2 of 2
66794	ppGpp biosynthesis	100	4 of 4
66794	acetoin degradation	100	3 of 3
66794	valine metabolism	100	9 of 9
66794	palmitate biosynthesis	100	22 of 22
66794	ethanol fermentation	100	2 of 2
66794	formaldehyde oxidation	100	3 of 3
66794	coenzyme A metabolism	100	4 of 4
66794	biotin biosynthesis	100	4 of 4
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	acetate fermentation	100	4 of 4
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	suberin monomers biosynthesis	100	2 of 2
66794	taurine degradation	100	1 of 1
66794	folate polyglutamylation	100	1 of 1
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	tetrahydrofolate metabolism	92.86	13 of 14
66794	vitamin B1 metabolism	92.31	12 of 13
66794	serine metabolism	88.89	8 of 9
66794	CO2 fixation in Crenarchaeota	88.89	8 of 9
66794	chorismate metabolism	88.89	8 of 9
66794	lipid A biosynthesis	88.89	8 of 9
66794	isoleucine metabolism	87.5	7 of 8
66794	gluconeogenesis	87.5	7 of 8
66794	photosynthesis	85.71	12 of 14
66794	ubiquinone biosynthesis	85.71	6 of 7
66794	glutamate and glutamine metabolism	85.71	24 of 28
66794	heme metabolism	85.71	12 of 14
66794	propanol degradation	85.71	6 of 7
66794	vitamin B6 metabolism	81.82	9 of 11
66794	Entner Doudoroff pathway	80	8 of 10
66794	methylglyoxal degradation	80	4 of 5
66794	peptidoglycan biosynthesis	80	12 of 15
66794	threonine metabolism	80	8 of 10
66794	allantoin degradation	77.78	7 of 9
66794	molybdenum cofactor biosynthesis	77.78	7 of 9
66794	NAD metabolism	77.78	14 of 18
66794	phenylalanine metabolism	76.92	10 of 13
66794	purine metabolism	75.53	71 of 94
66794	CMP-KDO biosynthesis	75	3 of 4
66794	sulfopterin metabolism	75	3 of 4
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	75	6 of 8
66794	flavin biosynthesis	73.33	11 of 15
66794	alanine metabolism	72.41	21 of 29
66794	cysteine metabolism	72.22	13 of 18
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	citric acid cycle	71.43	10 of 14
66794	sulfate reduction	69.23	9 of 13
66794	non-pathway related	68.42	26 of 38
66794	cyanate degradation	66.67	2 of 3
66794	octane oxidation	66.67	2 of 3
66794	aspartate and asparagine metabolism	66.67	6 of 9
66794	L-lactaldehyde degradation	66.67	2 of 3
66794	methionine metabolism	65.38	17 of 26
66794	pyrimidine metabolism	64.44	29 of 45
66794	proline metabolism	63.64	7 of 11
66794	pentose phosphate pathway	63.64	7 of 11
66794	tryptophan metabolism	63.16	24 of 38
66794	C4 and CAM-carbon fixation	62.5	5 of 8
66794	ketogluconate metabolism	62.5	5 of 8
66794	leucine metabolism	61.54	8 of 13
66794	lipid metabolism	61.29	19 of 31
66794	glycogen metabolism	60	3 of 5
66794	degradation of aromatic, nitrogen containing compounds	58.33	7 of 12
66794	isoprenoid biosynthesis	57.69	15 of 26
66794	glutathione metabolism	57.14	8 of 14
66794	reductive acetyl coenzyme A pathway	57.14	4 of 7
66794	tyrosine metabolism	57.14	8 of 14
66794	d-mannose degradation	55.56	5 of 9
66794	oxidative phosphorylation	54.95	50 of 91
66794	lysine metabolism	54.76	23 of 42
66794	phenylpropanoid biosynthesis	53.85	7 of 13
66794	urea cycle	53.85	7 of 13
66794	histidine metabolism	51.72	15 of 29
66794	glycine metabolism	50	5 of 10
66794	phenylmercury acetate degradation	50	1 of 2
66794	arginine metabolism	50	12 of 24
66794	pantothenate biosynthesis	50	3 of 6
66794	propionate fermentation	50	5 of 10
66794	quinate degradation	50	1 of 2
66794	glycogen biosynthesis	50	2 of 4
66794	glycolysis	47.06	8 of 17
66794	3-phenylpropionate degradation	46.67	7 of 15
66794	d-xylose degradation	45.45	5 of 11
66794	arachidonic acid metabolism	44.44	8 of 18
66794	nitrate assimilation	44.44	4 of 9
66794	arachidonate biosynthesis	40	2 of 5
66794	factor 420 biosynthesis	40	2 of 5
66794	4-hydroxyphenylacetate degradation	40	4 of 10
66794	lipoate biosynthesis	40	2 of 5
66794	glycine betaine biosynthesis	40	2 of 5
66794	degradation of hexoses	38.89	7 of 18
66794	androgen and estrogen metabolism	37.5	6 of 16
66794	metabolism of disaccharids	36.36	4 of 11
66794	sulfoquinovose degradation	33.33	1 of 3
66794	selenocysteine biosynthesis	33.33	2 of 6
66794	acetyl CoA biosynthesis	33.33	1 of 3
66794	IAA biosynthesis	33.33	1 of 3
66794	enterobactin biosynthesis	33.33	1 of 3
66794	glycolate and glyoxylate degradation	33.33	2 of 6
66794	sphingosine metabolism	33.33	2 of 6
66794	chlorophyll metabolism	33.33	6 of 18
66794	(5R)-carbapenem carboxylate biosynthesis	33.33	1 of 3
66794	starch degradation	30	3 of 10
66794	coenzyme M biosynthesis	30	3 of 10
66794	degradation of pentoses	28.57	8 of 28
66794	cyclohexanol degradation	25	1 of 4
66794	lactate fermentation	25	1 of 4
66794	toluene degradation	25	1 of 4
66794	carnitine metabolism	25	2 of 8
66794	degradation of sugar alcohols	25	4 of 16
66794	phenol degradation	25	5 of 20
66794	butanoate fermentation	25	1 of 4
66794	bile acid biosynthesis, neutral pathway	23.53	4 of 17
66794	phosphatidylethanolamine bioynthesis	23.08	3 of 13
66794	ascorbate metabolism	22.73	5 of 22
66794	4-hydroxymandelate degradation	22.22	2 of 9
66794	daunorubicin biosynthesis	22.22	2 of 9

API 20NE

@ref	Reduction of nitratesNO3	TRP	GLU_ Ferm	ADH (Arg)	URE	ESC	GEL	PNPG	GLU_ Assim	ARA	MNE	MAN	NAG	MAL	GNT	CAP	ADI	MLT	CIT	PAC	OX
21451	-	-	+	-	-	-	-	-	+	-	-	-	-	-	+	-	-	+	-	-	not determinedn.d.

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Plants	#Herbaceous plants (Grass,Crops)
#Host Body-Site	#Plant	#Flower
#Host Body Product	#Plant	#Nectar

Isolation

@ref	Sample type	Host species	Geographic location	Country	Country ISO 3 Code	Continent
21451	Floral nectar of the plant species Muscari comosum	Muscari comosum	Hinojos (Huelva)	Spain	ESP	Europe
63485	Floral nectar,plant species Muscari comosum		Huelva	Spain	ESP	Europe
121255	Plant, Floral nectar of wild mediterranean insect-pollinated plants. host plant = Muscari comosum		Hinojos (Huelva, Spain)	Spain	ESP	Europe

Taxonmaps

69479

Global distribution of 16S sequence JQ771132 (>99% sequence identity) for Acinetobacter nectaris from Microbeatlas

Aquatic Samples	1357
Soil Samples	310
Animal Samples	3298
Plant Samples	510
Total Samples	5475

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
21451	1	Risk group (German classification)
121255	1	Risk group (French classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	Acin_nect_CIP110549_V2 assembly for Acinetobacter nectaris CIP 110549	scaffold	GCA_000488215	1392540.3	2582580904	1392540	64.99

Genome browser: GCA_000488215

16S sequences

@ref	Description	Accession	Length	NCBI tax ID
21451	Acinetobacter nectaris strain SAP 763.2 16S ribosomal RNA gene, partial sequence	JQ771132	1498	1392540
124043	Acinetobacter boissieri strain SAP 320.1 16S ribosomal RNA gene, partial sequence.	JQ771129	1498	1219382
124043	Acinetobacter boissieri strain SAP 320.1 16S ribosomal RNA gene, partial sequence.	JQ771130	1499	1219382
124043	Acinetobacter boissieri strain SAP 320.1 16S ribosomal RNA gene, partial sequence.	JQ771131	1498	1219382
124043	Acinetobacter boissieri strain SAP 320.1 16S ribosomal RNA gene, partial sequence.	JQ771133	1498	1219382
124043	Acinetobacter boissieri strain SAP 320.1 16S ribosomal RNA gene, partial sequence.	JQ771134	1498	1219382
124043	Acinetobacter boissieri strain SAP 320.1 16S ribosomal RNA gene, partial sequence.	JQ771135	1497	1219382

GC content

21451

GC-content (mol%)36.6

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Acinetobacter nectaris CIP 110549
NCBI: GCA_000488215

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	98.30	no
125439	motility	BacteriaNetⓘ	yes	74.00	no
125439	gram_stain	BacteriaNetⓘ	negative	99.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	97.60	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Acinetobacter nectaris CIP 110549 CIP 110549
NCBI: GCA_000488215.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	99.99	yes
125438	anaerobic	anaerobicⓘ	no	96.56	yes
125438	aerobic	aerobicⓘ	yes	80.13	yes
125438	spore-forming	spore-formingⓘ	no	95.77	yes
125438	thermophilic	thermophileⓘ	no	99.50	yes
125438	flagellated	motile2+ⓘ	no	72.37	no

Literature

Title	Authors	Journal	DOI	Year
Hydrogel Design Based on Bacterial Exopolysaccharides: The Biomedical Promise of Levan.	Popa AI, Carpa R, Farkas A.	Int J Mol Sci	10.3390/ijms262210828	2025
Effect of bacteria type and sucrose concentration on levan yield and its molecular weight.	Gonzalez-Garcinuno A, Tabernero A, Sanchez-Alvarez JM, Galan MA, Martin Del Valle EM.	Microb Cell Fact	10.1186/s12934-017-0703-z	2017
Inoculation of pear flowers with Metschnikowia reukaufii and Acinetobacter nectaris enhances attraction of honeybees and hoverflies, but does not increase fruit and seed set.	Colda A, Bossaert S, Verreth C, Vanhoutte B, Honnay O, Keulemans W, Lievens B.	PLoS One	10.1371/journal.pone.0250203	2021
Pollen-Microbe Interactions in Nectar Weakly Influence Bee Foraging Behavior.	Ekemezie SC, Davis CC, Russo MV, Carpenter LP, Russell AL.	Integr Comp Biol	10.1093/icb/icaf017	2025
Nitrogen Assimilation Varies Among Clades of Nectar- and Insect-Associated Acinetobacters.	Alvarez-Perez S, Tsuji K, Donald M, Van Assche A, Vannette RL, Herrera CM, Jacquemyn H, Fukami T, Lievens B.	Microb Ecol	10.1007/s00248-020-01671-x	2021
Lactiplantibacillus plantarum dfa1 reduces obesity caused by a high carbohydrate diet by modulating inflammation and gut microbiota.	Ondee T, Pongpirul K, Wongsaroj L, Senaprom S, Wattanaphansak S, Leelahavanichkul A.	Sci Rep	10.1038/s41598-025-10435-x	2025
Demethylation Inhibitor Fungicides Have a Significantly Detrimental Impact on Population Growth and Composition of Nectar Microbial Communities.	Quevedo-Caraballo S, Roldan A, Alvarez-Perez S.	Microb Ecol	10.1007/s00248-024-02477-x	2024
A quantitative survey of the blueberry (Vaccinium spp.) culturable nectar microbiome: variation between cultivars, locations, and farm management approaches.	Rering CC, Rudolph AB, Li QB, Read QD, Munoz PR, Ternest JJ, Hunter CT.	FEMS Microbiol Ecol	10.1093/femsec/fiae020	2024
Nectar compounds impact bacterial and fungal growth and shift community dynamics in a nectar analog.	Mueller TG, Francis JS, Vannette RL.	Environ Microbiol Rep	10.1111/1758-2229.13139	2023
Effects of a supplemented diet containing 7 probiotic strains (Honeybeeotic) on honeybee physiology and immune response: analysis of hemolymph cytology, phenoloxidase activity, and gut microbiome.	Robino P, Galosi L, Bellato A, Vincenzetti S, Gonella E, Ferrocino I, Serri E, Biagini L, Roncarati A, Nebbia P, Menzio C, Rossi G.	Biol Res	10.1186/s40659-024-00533-x	2024
Holobiont Urbanism: sampling urban beehives reveals cities' metagenomes.	Henaff E, Najjar D, Perez M, Flores R, Woebken C, Mason CE, Slavin K.	Environ Microbiome	10.1186/s40793-023-00467-z	2023
Melipona stingless bees and honey microbiota reveal the diversity, composition, and modes of symbionts transmission.	Cerqueira AES, Lima HS, Silva LCF, Veloso TGR, de Paula SO, Santana WC, da Silva CC.	FEMS Microbiol Ecol	10.1093/femsec/fiae063	2024
Wide-ranging consequences of priority effects governed by an overarching factor.	Chappell CR, Dhami MK, Bitter MC, Czech L, Herrera Paredes S, Barrie FB, Calderon Y, Eritano K, Golden LA, Hekmat-Scafe D, Hsu V, Kieschnick C, Malladi S, Rush N, Fukami T.	Elife	10.7554/elife.79647	2022
Genomic profiling of bacterial and fungal communities and their predictive functionality during pulque fermentation by whole-genome shotgun sequencing.	Chacon-Vargas K, Torres J, Giles-Gomez M, Escalante A, Gibbons JG.	Sci Rep	10.1038/s41598-020-71864-4	2020
Studies on solvent precipitation of levan synthesized using Bacillus subtilis MTCC 441.	Chidambaram JSCA, Veerapandian B, Sarwareddy KK, Mani KP, Shanmugam SR, Venkatachalam P.	Heliyon	10.1016/j.heliyon.2019.e02414	2019
Potential effects of nectar microbes on pollinator health.	Martin VN, Schaeffer RN, Fukami T.	Philos Trans R Soc Lond B Biol Sci	10.1098/rstb.2021.0155	2022
Bacterial communities of indoor surface of stingless bee nests.	de Sousa LP.	PLoS One	10.1371/journal.pone.0252933	2021
Microbial diversity in the floral nectar of Linaria vulgaris along an urbanization gradient.	Bartlewicz J, Lievens B, Honnay O, Jacquemyn H.	BMC Ecol	10.1186/s12898-016-0072-1	2016
Opuntia streptacantha: a coadjutor in the treatment of diabetes mellitus.	Meckes-Lozyoa M, Roman-Ramos R.	Am J Chin Med	10.1142/s0192415x86000181	1986
The genomic diversification of the whole Acinetobacter genus: origins, mechanisms, and consequences.	Touchon M, Cury J, Yoon EJ, Krizova L, Cerqueira GC, Murphy C, Feldgarden M, Wortman J, Clermont D, Lambert T, Grillot-Courvalin C, Nemec A, Courvalin P, Rocha EP.	Genome Biol Evol	10.1093/gbe/evu225	2014
Acinetobacter pollinis sp. nov., Acinetobacter baretiae sp. nov. and Acinetobacter rathckeae sp. nov., isolated from floral nectar and honey bees.	Alvarez-Perez S, Baker LJ, Morris MM, Tsuji K, Sanchez VA, Fukami T, Vannette RL, Lievens B, Hendry TA.	Int J Syst Evol Microbiol	10.1099/ijsem.0.004783	2021
Acinetobacter apis sp. nov., isolated from the intestinal tract of a honey bee, Apis mellifera.	Kim PS, Shin NR, Kim JY, Yun JH, Hyun DW, Bae JW	J Microbiol	10.1007/s12275-014-4078-0	2014
Acinetobacter nectaris sp. nov. and Acinetobacter boissieri sp. nov., isolated from floral nectar of wild Mediterranean insect-pollinated plants.	Alvarez-Perez S, Lievens B, Jacquemyn H, Herrera CM	Int J Syst Evol Microbiol	10.1099/ijs.0.043489-0	2012

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 )
#21451	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 29975
#30741	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 #27072 (see below)
#42140	; Curators of the CIP;
#63485	Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 68431
#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 )
#68369	Automatically annotated from API 20NE .
#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 .
#121255	Collection of Institut Pasteur ; Curators of the CIP; CIP 110549
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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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Acinetobacter nectaris (CCUG 68431, CIP 110549, DSM 29975)

Name and taxonomic classification

Morphology

Cell morphology

Colony morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Metabolite utilization

Metabolite production

Metabolite tests

Enzymes

Pathway annotation

API 20NE

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_000488215

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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