Fusobacterium nucleatum (CCUG 32879, DSM 19679, ATCC 51191)

Name: Fusobacterium nucleatum (CCUG 32879, DSM 19679, ATCC 51191)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 5762

Type strain

Strain Designation LH 37

Culture col. no. CCUG 32879 DSM 19679 ATCC 51191 CIP 104879 JCM 11025 2 more

NCBI tax ID(s) 997347 76859

Special Collections DSMZ CCUG JCM CIP Literature strains

Links

Fusobacterium nucleatum LH 37 is an anaerobe, mesophilic, Gram-negative prokaryote that was isolated from animal colon.

Gram-negative anaerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 42851

ATCC 51191,NCTC 12276,CCUG 32879,CIP 104879,JCM 11025,DSM 8253,DSM 19679

@ref 20215

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

Domain Fusobacteriati

Phylum Fusobacteriota

Class Fusobacteriia

Order Fusobacteriales

Family Fusobacteriaceae

Genus Fusobacterium

Species Fusobacterium nucleatum

Full scientific name Fusobacterium nucleatum Knorr 1922 (Approved Lists 1980)

Synonyms (6)

Fusobacterium nucleatum subsp. fusiforme
"Fusobacterium fusiforme"
Fusobacterium nucleatum subsp. vincentii
Fusobacterium vincentii
Fusobacterium animalis
Fusobacterium nucleatum subsp. animalis

BacDive ID	Other strains from **Fusobacterium nucleatum** (9)	Type strain
142753	F. nucleatum CCUG 14448
142924	F. nucleatum CCUG 15725
142925	F. nucleatum CCUG 15758
151510	F. nucleatum CCUG 44169
152134	F. nucleatum CCUG 45873
154184	F. nucleatum CCUG 52678
154363	F. nucleatum CCUG 53249
155322	F. nucleatum CCUG 57321
156450	F. nucleatum CCUG 61856

Morphology

Cell morphology

@ref	Gram stain	Cell shape	Motility
22916	negative
121369	negative	rod-shaped

Colony morphology

@ref	Colony color	Colony shape	Incubation period
8250			2-3 days
22916	translucent white	round
51232			2 days

Culture and growth conditions

Culture medium

@ref	Name	Medium link	Composition
8250	COLUMBIA BLOOD MEDIUM (DSMZ Medium 693)	Medium recipe at MediaDive	Name: COLUMBIA BLOOD MEDIUM (DSMZ Medium 693) Composition: Defibrinated sheep blood 50.0 g/l Columbia agar base
8250	CHOPPED MEAT MEDIUM WITH CARBOHYDRATES (DSMZ Medium 110)	Medium recipe at MediaDive	Name: CHOPPED MEAT MEDIUM WITH CARBOHYDRATES (DSMZ Medium 110) Composition: Ground beef 500.0 g/l Casitone 30.0 g/l Agar 15.0 g/l K2HPO4 5.0 g/l Yeast extract 5.0 g/l D-Glucose 4.0 g/l Starch 1.0 g/l Maltose 1.0 g/l Cellobiose 1.0 g/l L-Cysteine HCl 0.5 g/l Ethanol 0.19 g/l Vitamin K3 0.05 g/l Hemin 0.005 g/l Sodium resazurin 0.0005 g/l Vitamin K1 NaOH Distilled water
41358	MEDIUM 20 - for Anaerobic bacteria		Agar (15.000 g);Glucose (5.000 g);Yeast extract (20.000 g);Tryptone (30.000 g);Cysteine hydrochloride (0.500 g);distilled water (1000.000 ml);Hemin solution -M00149 (25.000 ml)
121369	CIP Medium 20	Medium recipe at CIP

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
8250	positive	growth	37	mesophilic
41358	positive	growth	37	mesophilic
51232	positive	growth	37	mesophilic
67770	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
8250	anaerobe
51232	anaerobe
125438	anaerobe	90.375
125439	facultative anaerobe	96.8

Murein

@ref	Murein short key	Type
22916	A51	A1delta Lan-direct

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
22916	29016 ChEBI	arginine	+	growth
68380	29016 ChEBI	arginine	-	hydrolysis	from API rID32A
22916	15356 ChEBI	cysteine	+	growth
68380	16024 ChEBI	D-mannose	-	fermentation	from API rID32A
22916	29987 ChEBI	glutamate	+/-	growth
22916	27570 ChEBI	histidine	+	growth
68380	17632 ChEBI	nitrate	-	reduction	from API rID32A
68380	16634 ChEBI	raffinose	-	fermentation	from API rID32A
68380	27897 ChEBI	tryptophan	+	energy source	from API rID32A
68380	16199 ChEBI	urea	-	hydrolysis	from API rID32A

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68380	35581 ChEBI	indole		from API rID32A

Metabolite tests

@ref	Chebi-ID	Metabolite	Indole test
68380	35581 ChEBI	indole	+	from API rID32A

Enzymes

@ref	Value	Activity	Ec
68380	alanine arylamidase	-	3.4.11.2	from API rID32A
68380	alkaline phosphatase	-	3.1.3.1	from API rID32A
68380	alpha-arabinosidase	-	3.2.1.55	from API rID32A
68380	alpha-fucosidase	-	3.2.1.51	from API rID32A
68380	alpha-galactosidase	-	3.2.1.22	from API rID32A
68380	alpha-glucosidase	-	3.2.1.20	from API rID32A
68380	arginine dihydrolase	-	3.5.3.6	from API rID32A
68380	beta-galactosidase	-	3.2.1.23	from API rID32A
68380	beta-Galactosidase 6-phosphate	-		from API rID32A
68380	beta-glucosidase	-	3.2.1.21	from API rID32A
68380	beta-glucuronidase	-	3.2.1.31	from API rID32A
68380	glutamyl-glutamate arylamidase	-		from API rID32A
68380	glycin arylamidase	-		from API rID32A
68380	histidine arylamidase	-		from API rID32A
68380	L-arginine arylamidase	-		from API rID32A
68380	leucine arylamidase	-	3.4.11.1	from API rID32A
68380	leucyl glycin arylamidase	-	3.4.11.1	from API rID32A
68380	N-acetyl-beta-glucosaminidase	-	3.2.1.52	from API rID32A
68380	phenylalanine arylamidase	-		from API rID32A
68380	proline-arylamidase	-	3.4.11.5	from API rID32A
68380	pyrrolidonyl arylamidase	-	3.4.19.3	from API rID32A
68380	serine arylamidase	-		from API rID32A
68380	tryptophan deaminase	+	4.1.99.1	from API rID32A
68380	tyrosine arylamidase	-		from API rID32A
68380	urease	-	3.5.1.5	from API rID32A

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	C4 and CAM-carbon fixation	100	8 of 8
66794	L-lactaldehyde degradation	100	3 of 3
66794	biotin biosynthesis	100	4 of 4
66794	ppGpp biosynthesis	100	4 of 4
66794	adipate degradation	100	2 of 2
66794	coenzyme A metabolism	100	4 of 4
66794	folate polyglutamylation	100	1 of 1
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	chorismate metabolism	88.89	8 of 9
66794	gluconeogenesis	87.5	7 of 8
66794	palmitate biosynthesis	86.36	19 of 22
66794	propanol degradation	85.71	6 of 7
66794	phenylalanine metabolism	84.62	11 of 13
66794	vitamin B12 metabolism	82.35	28 of 34
66794	flavin biosynthesis	80	12 of 15
66794	peptidoglycan biosynthesis	80	12 of 15
66794	citric acid cycle	78.57	11 of 14
66794	photosynthesis	78.57	11 of 14
66794	serine metabolism	77.78	7 of 9
66794	aspartate and asparagine metabolism	77.78	7 of 9
66794	NAD metabolism	77.78	14 of 18
66794	lipid A biosynthesis	77.78	7 of 9
66794	CO2 fixation in Crenarchaeota	77.78	7 of 9
66794	vitamin B1 metabolism	76.92	10 of 13
66794	alanine metabolism	75.86	22 of 29
66794	isoleucine metabolism	75	6 of 8
66794	glycogen biosynthesis	75	3 of 4
66794	butanoate fermentation	75	3 of 4
66794	CMP-KDO biosynthesis	75	3 of 4
66794	acetate fermentation	75	3 of 4
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	tetrahydrofolate metabolism	71.43	10 of 14
66794	glycolysis	70.59	12 of 17
66794	purine metabolism	69.15	65 of 94
66794	glutamate and glutamine metabolism	67.86	19 of 28
66794	valine metabolism	66.67	6 of 9
66794	acetoin degradation	66.67	2 of 3
66794	formaldehyde oxidation	66.67	2 of 3
66794	d-mannose degradation	66.67	6 of 9
66794	methionine metabolism	65.38	17 of 26
66794	pyrimidine metabolism	64.44	29 of 45
66794	heme metabolism	64.29	9 of 14
66794	oxidative phosphorylation	63.74	58 of 91
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	62.5	5 of 8
66794	urea cycle	61.54	8 of 13
66794	methylglyoxal degradation	60	3 of 5
66794	glycogen metabolism	60	3 of 5
66794	metabolism of amino sugars and derivatives	60	3 of 5
66794	glycine betaine biosynthesis	60	3 of 5
66794	propionate fermentation	60	6 of 10
66794	lipid metabolism	58.06	18 of 31
66794	tryptophan metabolism	55.26	21 of 38
66794	vitamin B6 metabolism	54.55	6 of 11
66794	dTDPLrhamnose biosynthesis	50	4 of 8
66794	suberin monomers biosynthesis	50	1 of 2
66794	threonine metabolism	50	5 of 10
66794	glycolate and glyoxylate degradation	50	3 of 6
66794	cysteine metabolism	50	9 of 18
66794	sulfopterin metabolism	50	2 of 4
66794	aminopropanol phosphate biosynthesis	50	1 of 2
66794	cis-vaccenate biosynthesis	50	1 of 2
66794	phenylmercury acetate degradation	50	1 of 2
66794	glycine metabolism	50	5 of 10
66794	quinate degradation	50	1 of 2
66794	ethanol fermentation	50	1 of 2
66794	ketogluconate metabolism	50	4 of 8
66794	histidine metabolism	48.28	14 of 29
66794	non-pathway related	47.37	18 of 38
66794	leucine metabolism	46.15	6 of 13
66794	isoprenoid biosynthesis	46.15	12 of 26
66794	pentose phosphate pathway	45.45	5 of 11
66794	nitrate assimilation	44.44	4 of 9
66794	degradation of hexoses	44.44	8 of 18
66794	ubiquinone biosynthesis	42.86	3 of 7
66794	reductive acetyl coenzyme A pathway	42.86	3 of 7
66794	glutathione metabolism	42.86	6 of 14
66794	tyrosine metabolism	42.86	6 of 14
66794	degradation of sugar acids	40	10 of 25
66794	ethylmalonyl-CoA pathway	40	2 of 5
66794	Entner Doudoroff pathway	40	4 of 10
66794	hydrogen production	40	2 of 5
66794	starch degradation	40	4 of 10
66794	phosphatidylethanolamine bioynthesis	38.46	5 of 13
66794	sulfate reduction	38.46	5 of 13
66794	lysine metabolism	38.1	16 of 42
66794	arginine metabolism	37.5	9 of 24
66794	molybdenum cofactor biosynthesis	33.33	3 of 9
66794	acetyl CoA biosynthesis	33.33	1 of 3
66794	degradation of aromatic, nitrogen containing compounds	33.33	4 of 12
66794	octane oxidation	33.33	1 of 3
66794	sulfoquinovose degradation	33.33	1 of 3
66794	selenocysteine biosynthesis	33.33	2 of 6
66794	IAA biosynthesis	33.33	1 of 3
66794	degradation of pentoses	32.14	9 of 28
66794	phenylpropanoid biosynthesis	30.77	4 of 13
66794	polyamine pathway	30.43	7 of 23
66794	benzoyl-CoA degradation	28.57	2 of 7
66794	d-xylose degradation	27.27	3 of 11
66794	dolichyl-diphosphooligosaccharide biosynthesis	27.27	3 of 11
66794	ascorbate metabolism	27.27	6 of 22
66794	proline metabolism	27.27	3 of 11
66794	toluene degradation	25	1 of 4
66794	cyclohexanol degradation	25	1 of 4
66794	lactate fermentation	25	1 of 4
66794	degradation of sugar alcohols	25	4 of 16

API rID32A

@ref	URE	ADH (Arg)	alpha GAL	beta GAL	beta-Galactosidase 6-phosphatebeta GP	alpha GLU	beta GLU	alpha ARA	beta GUR	beta-N-Acetyl-beta-glucosaminidasebeta NAG	MNE	RAF	GDC	alpha FUC	Reduction of nitrateNIT	IND	PAL	L-arginine arylamidaseArgA	ProA	LGA	Phenylalanine arylamidasePheA	Leucine arylamidaseLeuA	PyrA	Tyrosine arylamidaseTyrA	Alanine arylamidaseAlaA	Glycin arylamidaseGlyA	Histidine arylamidaseHisA	Glutamyl-glutamate arylamidaseGGA	Serine arylamidaseSerA
8250	-	-	-	-	-	-	-	-	-	-	-	-	+	-	-	+	-	-	-	-	-	-	-	-	-	-	-	-	-
51232	-	-	-	-	-	-	-	-	-	-	-	-	+	-	-	+	-	-	-	-	-	-	-	-	-	-	-	-	-
8250	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	+	-	-	-	-	-	-	-	-	-	-	-	-	-
8250	-	-	-	-	-	-	-	-	-	-	-	-	+	-	-	+	-	-	-	-	-	-	-	-	-	-	-	-	-
8250	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	+	-	-	-	-	-	-	-	-	-	-	-	-	-

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	-	-
#Host Body-Site	#Gastrointestinal tract	#Large intestine

Isolation

@ref	Sample type	Sampling date	Geographic location	Country	Country ISO 3 Code	Continent	Isolation date
8250	animal colon			United Kingdom	GBR	Europe
51232	Animal colon	1989	London	United Kingdom	GBR	Europe
121369	Animal, Colon		London	United Kingdom	GBR	Europe	1989

Taxonmaps

69479

Global distribution of 16S sequence GQ301042 (>99% sequence identity) for Fusobacterium from Microbeatlas

Aquatic Samples	111
Soil Samples	83
Animal Samples	11007
Plant Samples	35
Total Samples	11236

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
8250	2	Risk group (German classification) According to TRBA 466
121369	1	Risk group (French classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
67770	ASM22082v1 assembly for Fusobacterium animalis ATCC 51191	scaffold	GCA_000220825	997347.4	2540341044	997347

16S sequences

@ref	Description	Accession	Length	NCBI tax ID
20218	Fusobacterium nucleatum subsp. animalis gene for 16S ribosomal RNA, partial sequence, strain: JCM 11025	AB639143	1480	76859
20218	Fusobacterium nucleatum subsp. animalis strain ATCC 51191 16S ribosomal RNA gene, partial sequence; internal transcribed spacer 1, complete sequence; and 23S ribosomal RNA gene, partial sequence	AF342835	740	997347
20218	Fusobacterium nucleatum subsp. animalis strain ATCC 51191 16S ribosomal RNA gene, partial sequence	GQ301042	1441	997347
20218	Fusobacterium nucleatum subsp. animalis strain ATCC 51191 16S ribosomal RNA gene, partial sequence	HM347083	1331	997347
20218	Fusobacterium nucleatum subsp. animalis small subunit ribosomal RNA	X55404	1331	997347
124043	Fusobacterium nucleatum subsp. animalis strain ATCC 51191 16S ribosomal RNA gene, partial sequence.	HM347054	1386	76859
124043	Fusobacterium nucleatum subsp. animalis strain ATCC 51191 16S ribosomal RNA gene, partial sequence.	HM347065	1382	76859
124043	Fusobacterium nucleatum subsp. animalis strain ATCC 51191 16S ribosomal RNA gene, partial sequence.	HM347076	1396	76859
124043	Fusobacterium nucleatum subsp. animalis JCM 11025 gene for 16S rRNA, partial sequence.	LC752386	562	76859

GC content

@ref	GC-content (mol%)	Method
22916	26-28	thermal denaturation, midpoint method (Tm)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Fusobacterium animalis ATCC 51191
NCBI: GCA_000220825

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	55.80	no
125439	motility	BacteriaNetⓘ	yes	68.40	no
125439	gram_stain	BacteriaNetⓘ	positive	76.10	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	96.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Fusobacterium nucleatum subsp. animalis ATCC 51191
PATRIC: 997347.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	87.91	yes
125438	anaerobic	anaerobicⓘ	yes	90.38	yes
125438	aerobic	aerobicⓘ	no	96.13	no
125438	spore-forming	spore-formingⓘ	no	82.36	no
125438	thermophilic	thermophileⓘ	no	92.82	yes
125438	flagellated	motile2+ⓘ	no	86.50	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	New Insights into Mucosa-Associated Microbiota in Paired Tumor and Non-Tumor Adjacent Mucosal Tissues in Colorectal Cancer Patients.	Gonzalez A, Fullaondo A, Navarro D, Rodriguez J, Tirnauca C, Odriozola A.	Cancers (Basel)	10.3390/cancers16234008	2024
Phylogeny	The rise and evolving role of Fusobacterium nucleatum subspecies.	Wolf M, Steinberg T, Scholz KJ, Kruse A, Rezasoltani S, Conrads G, Al-Ahmad A, Cieplik F.	Curr Res Microb Sci	10.1016/j.crmicr.2025.100414	2025
	Clostridium butyricum-altered lung microbiome is associated with enhanced anti-influenza effects via G-protein-coupled receptor120.	Hagihara M, Yamashita M, Ariyoshi T, Minemura A, Yoshida C, Higashi S, Oka K, Takahashi M, Ota A, Maenaka A, Iwasaki K, Hirai J, Shibata Y, Umemura T, Mori T, Kato H, Asai N, Mikamo H.	iScience	10.1016/j.isci.2025.113502	2025
	Positive selection at core genes may underlie niche adaptation in Fusobacterium animalis.	Forni D, Sivertsen A, Cagliani R, Mozzi A, Molteni C, Kommedal O, Sironi M.	Gut Pathog	10.1186/s13099-025-00740-1	2025
	Microbial interactions induce the mutational signature of mismatch repair deficiency in colorectal cancer and associated with EPPK1 mutations.	Hu D, Zhao J, Wu M, Zhou Y, Lyu B, Xu C, Huang C, Su Z, Zhang H, Guo J, Tang W, Chen G, Li Q.	Cancer Lett	10.1016/j.canlet.2025.217807	2025
Genetics	Limitations of MALDI-TOF MS in identifying anaerobic bacteremia: challenges in polymicrobial infections and the role of whole-genome sequencing.	Hosoda T, Suzuki M, Matsuno T, Matsui K, Ohyama K, Doi Y.	Microbiol Spectr	10.1128/spectrum.01014-25	2025
	Conjugation-based genetic manipulation of Fusobacterium animalis.	Ko D, Garrett WS.	mBio	10.1128/mbio.01714-25	2025
	Virulence factor discovery identifies associations between the Fic gene family and Fap2⁺ fusobacteria in colorectal cancer microbiomes.	Nakatsu G, Ko D, Michaud M, Franzosa EA, Morgan XC, Huttenhower C, Garrett WS.	mBio	10.1128/mbio.03732-24	2025
	Esophageal cancer and precancerous lesions: focus on resident bacteria and fungi.	Yuan L, Zhang Y, Wen C, Liu S, Zhang Q, Yin W, Jia Q, Chen M, Luo G, Deng M, Lv M, Xiao W.	Microbiol Spectr	10.1128/spectrum.03137-24	2025
	Positive selection at core genes may underlie niche adaptation in Fusobacterium animalis	Forni D, Sivertsen A, Cagliani R, Mozzi A, Molteni C, Kommedal O, Sironi M.	Gut Pathog		2025
	Causal relationship between oral/gut microbiota and lung cancer: a two-sample Mendelian randomization study.	Huang ZJ, Wu L, Peng YL, Chen ZH, Xu CR, Deng Y, Yan HH, Lu C, Zhou Q.	Discov Oncol	10.1007/s12672-025-03853-w	2025
	Fusobacterium nucleatum in Colorectal Cancer: Ally Mechanism and Targeted Therapy Strategies.	Lu J, Wei W, Zheng D.	Research (Wash D C)	10.34133/research.0640	2025
	Association between root canals and gingival sulci microbiota in secondary and persistent endodontic infections.	Park DH, Tak EJ, Park OJ, Perinpanayagam H, Yoo YJ, Lee HJ, Jeong YS, Lee JY, Kim HS, Bae JW, Kum KY, Han SH.	Sci Rep	10.1038/s41598-025-95522-9	2025
	Characterization of diet-linked amino acid pool influence on Fusobacterium spp. growth and metabolism.	Robinson AV, Vancuren SJ, Marcone M, Allen-Vercoe E.	mSphere	10.1128/msphere.00789-24	2025
	Gut microbiome compositional and functional features associate with Alzheimer's disease pathology.	Kang JW, Khatib LA, Heston MB, Dilmore AH, Labus JS, Deming Y, Schimmel L, Blach C, McDonald D, Gonzalez A, Bryant M, Ulland TK, Johnson SC, Asthana S, Carlsson CM, Chin NA, Blennow K, Zetterberg H, Rey FE, Alzheimer Gut Microbiome Project Consortium, Kaddurah-Daouk R, Knight R, Bendlin BB.	Alzheimers Dement	10.1002/alz.70417	2025
	Appendectomy and Long-term Colorectal Cancer Incidence, Overall and by Tumor Fusobacterium nucleatum Status.	Kawamura H, Ugai T, Takashima Y, Okadome K, Shimizu T, Mima K, Akimoto N, Haruki K, Arima K, Zhao M, Vayrynen JP, Wu K, Zhang X, Ng K, Nowak JA, Meyerhardt JA, Giovannucci EL, Giannakis M, Chan AT, Huttenhower C, Garrett WS, Song M, Ogino S.	Ann Surg	10.1097/sla.0000000000006315	2025
	Fusobacterium-associated molecular and immunological alterations in colorectal cancer: Insights from a Norwegian cohort.	Omran TA, Subirats Camacho JL, Senthakumaran T, Gundersen G, Alte AK, Randen U, Tunsjo HS, Saether PC, Bemanian V.	Front Immunol	10.3389/fimmu.2025.1601423	2025
	Valid and accepted novel bacterial taxa derived from human clinical specimens and taxonomic revisions published in 2022.	Munson E, Carella A, Carroll KC.	J Clin Microbiol	10.1128/jcm.00838-23	2023
	Fusobacterium Species in Osteoarticular Infections in Childhood-A Systematic Review with Data Synthesis and a Case Series in the Acetabular and Hip Joint Regions.	Delbruck H, Schroder S, Stapper T, Schacht S, Pappa A, Hildebrand F, Hertwig MK.	Infect Dis Rep	10.3390/idr17020030	2025
	Salivary biomarkers present in patients with periodontitis without clinical distinction: findings from a meta-analysis.	Gomes PR, Rocha MD, Lira JA, Coelho FA, Alves EH, Nascimento HM, Oliveira SM, Carmo RR, Araujo HT, Silva FR, Vasconcelos DF.	Med Oral Patol Oral Cir Bucal	10.4317/medoral.25876	2023
	Intratumoral microbiota in colorectal cancer: focus on specific distribution and potential mechanisms.	Long J, Wang J, Xiao C, You F, Jiang Y, Li X.	Cell Commun Signal	10.1186/s12964-024-01831-3	2024
	Vaginal and rectal microbiome contribute to genital inflammation in chronic pelvic pain.	Jimenez N, Norton T, Diadala G, Bell E, Valenti M, Farland LV, Mahnert N, Herbst-Kralovetz MM.	BMC Med	10.1186/s12916-024-03500-1	2024
Pathogenicity	Dual oxic-anoxic co-culture enables direct study of anaerobe-host interactions at the airway epithelial interface.	Moore PJ, Hoffman K, Ahmed S, Fletcher JR, Wiggen TD, Lucas SK, Arif SJ, Gilbertsen AJ, Kent LA, Fiege JK, Langlois RA, O'Grady SM, Hunter RC.	mBio	10.1128/mbio.01338-24	2025
	Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases.	Jin D-M, Morton JT, Bonneau R.	mSystems	10.1128/msystems.00295-24	2024
Genetics	Microbial Identification Using rRNA Operon Region: Database and Tool for Metataxonomics with Long-Read Sequence.	Seol D, Lim JS, Sung S, Lee YH, Jeong M, Cho S, Kwak W, Kim H.	Microbiol Spectr	10.1128/spectrum.02017-21	2022
Genetics	Enrichment of oral-derived bacteria in inflamed colorectal tumors and distinct associations of Fusobacterium in the mesenchymal subtype.	Younginger BS, Mayba O, Reeder J, Nagarkar DR, Modrusan Z, Albert ML, Byrd AL.	Cell Rep Med	10.1016/j.xcrm.2023.100920	2023
	Interspecies metabolite transfer fuels the methionine metabolism of Fusobacterium nucleatum to stimulate volatile methyl mercaptan production.	Hara T, Sakanaka A, Lamont RJ, Amano A, Kuboniwa M.	mSystems	10.1128/msystems.00764-23	2024
	Consistent signatures in the human gut microbiome of old- and young-onset colorectal cancer.	Qin Y, Tong X, Mei WJ, Cheng Y, Zou Y, Han K, Yu J, Jie Z, Zhang T, Zhu S, Jin X, Wang J, Yang H, Xu X, Zhong H, Xiao L, Ding PR.	Nat Commun	10.1038/s41467-024-47523-x	2024
Genetics	Using Decision Tree Aggregation with Random Forest Model to Identify Gut Microbes Associated with Colorectal Cancer.	Ai D, Pan H, Han R, Li X, Liu G, Xia LC.	Genes (Basel)	10.3390/genes10020112	2019
Metabolism	Intratumor microbiota in cancer pathogenesis and immunity: from mechanisms of action to therapeutic opportunities.	Wang M, Yu F, Li P.	Front Immunol	10.3389/fimmu.2023.1269054	2023
Metabolism	Intratumoral Microbiome: Foe or Friend in Reshaping the Tumor Microenvironment Landscape?	Kyriazi AA, Karaglani M, Agelaki S, Baritaki S.	Cells	10.3390/cells13151279	2024
Phylogeny	Bacterial diversity in human subgingival plaque.	Paster BJ, Boches SK, Galvin JL, Ericson RE, Lau CN, Levanos VA, Sahasrabudhe A, Dewhirst FE.	J Bacteriol	10.1128/jb.183.12.3770-3783.2001	2001
Enzymology	Molecular analysis of bacterial species associated with childhood caries.	Becker MR, Paster BJ, Leys EJ, Moeschberger ML, Kenyon SG, Galvin JL, Boches SK, Dewhirst FE, Griffen AL.	J Clin Microbiol	10.1128/jcm.40.3.1001-1009.2002	2002
Phylogeny	Reassessing taxonomy and virulence in the Fusobacterium nucleatum group-rebuttal of Fusobacterium animalis clades "Fna C1" and "Fna C2," genome announcement for Fusobacterium watanabei, and description of Fusobacterium paranimalis sp. nov.	Sivertsen A, Forni D, Molteni C, Bivand J, Dimmen G, Bruvold TS, Sironi M, Kommedal O.	mBio	10.1128/mbio.00941-25	2025
Phylogeny	Fusobacterium nucleatum subsp. fusiforme subsp. nov. and Fusobacterium nucleatum subsp. animalis subsp. nov. as additional subspecies within Fusobacterium nucleatum.	Gharbia SE, Shah HN	Int J Syst Bacteriol	10.1099/00207713-42-2-296	1992

References

#8250	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 19679
#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 )
#22916	Saheer E. Gharbia, Haroun N. Shah: Fusobacterium nucleatum subsp. fusiforme subsp. nov. and Fusobacterium nucleatum subsp. animalis subsp. nov. as Additional Subspecies within Fusobacterium nucleatum. IJSEM 42: 296 - 298 1992 ( DOI 10.1099/00207713-42-2-296 , PubMed 1581188 )
#41358	; Curators of the CIP;
#51232	Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 32879
#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;
#68380	Automatically annotated from API rID32A .
#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 .
#121369	Collection of Institut Pasteur ; Curators of the CIP; CIP 104879
#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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Fusobacterium nucleatum (CCUG 32879, DSM 19679, ATCC 51191)

Name and taxonomic classification

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