Lactococcus lactis (DSM 4366, Citrate plasmid, F7/2)

Name: Lactococcus lactis (DSM 4366, Citrate plasmid, F7/2)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 14694

Type strain

Strain Designation Citrate plasmid, F7/2

Culture col. no. DSM 4366 Citrate plasmid F7/2

NCBI tax ID(s) 1358

Special Collections DSMZ

History DSMZ <- H. Neve (Federal Dairy Research Center, Kiel)

Links

Lactococcus lactis Citrate plasmid is a bacterium of the family Streptococcaceae.

genome sequence Bacteria

Name and taxonomic classification

SI-ID 47837

DSM 4366

@ref 20215

Last LPSN update 2026-05-29 08:28:21

Domain Bacteria

Phylum Bacillota

Class Bacilli

Order Lactobacillales

Family Streptococcaceae

Genus Lactococcus

Species Lactococcus lactis

Full scientific name Lactococcus lactis (Lister 1873) Schleifer et al. 1986

Synonyms (4)

Lactobacillus xylosus
"Bacterium lactis"
Streptococcus lactis
Streptococcus lactis subsp. diacetilactis

BacDive ID	Other strains from **Lactococcus lactis** (42)	Type strain
14702	L. lactis OJ, N30, DSM 20481, ATCC 19435, CCM 1877, ... (type strain)
14699	L. lactis 117, DSM 20175, ATCC 15577, CCUG 21962, NRRL ...
14700	L. lactis 54296, DSM 20384
14701	L. lactis 5, DSM 20250
14703	L. lactis 2, DSM 20661, NCDO 176
14704	L. lactis Berridge X 13, DSM 20729, ATCC 11454, CCM ...
14705	L. lactis E9, DSM 30863
134825	L. lactis N34, RICE, CIP 70.57
134851	L. lactis CIP A216
135401	L. lactis H 214, N35, CIP 70.58
136206	L. lactis CIP 103449, JCM 7638
138955	L. lactis J4 conserves, CIP A217
138966	L. lactis J4 Alger, CIP A218
139482	L. lactis 129.86, CIP 102103
143933	L. lactis CCUG 21956, NCIMB 10493, ATCC 11007, LMG ...
145429	L. lactis CCUG 28474
146507	L. lactis CCUG 31342
146700	L. lactis CCUG 31972
146846	L. lactis CCUG 32225
148267	L. lactis CCUG 35127 B
149871	L. lactis CCUG 38585
150979	L. lactis CCUG 42927
151600	L. lactis CCUG 44423
152071	L. lactis CCUG 45692
152072	L. lactis CCUG 45693
152073	L. lactis CCUG 45695
152621	L. lactis CCUG 47216
152790	L. lactis CCUG 47618
154162	L. lactis CCUG 52621
154377	L. lactis CCUG 53296
155625	L. lactis CCUG 58504
155919	L. lactis CCUG 59643
156113	L. lactis CCUG 60423
156342	L. lactis CCUG 61221
160084	L. lactis SV21, DSM 27303
160085	L. lactis SB 17, DSM 111832
160086	L. lactis SB 352, DSM 111868
160087	L. lactis SB 150, DSM 111869
160088	L. lactis SB 261, DSM 111870
162165	L. lactis JCM 18008, FERM AP-21288
169254	L. lactis CLA-AV-14, DSM 110082
174486	L. lactis A537/21, DSM 117780

Morphology

Cell morphology

@ref	Motility	Confidence	Gram stain
125438		90.5
125438		93.026	positive

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
1547	M17 MEDIUM FOR LACTIC STREPTOCOCCI (DSMZ Medium 449)		Medium recipe at MediaDive	Name: M17 MEDIUM FOR LACTIC STREPTOCOCCI (DSMZ Medium 449) Composition: Sodium beta-glycerophosphate 19.0 g/l Bacto peptone 5.0 g/l Soy peptone 5.0 g/l Casein peptone 5.0 g/l Lactose 5.0 g/l Yeast extract 2.5 g/l Ascorbic acid 0.5 g/l MgSO4 x 7 H2O 0.25 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
1547	positive	growth	30

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	96.497

Isolation, sampling and environmental information

Interaction and safety

Risk assessment

@ref	Pathogenicity human	Biosafety level	Biosafety level comment
1547	yes, in single cases	1	Risk group (German classification) According to TRBA 466

Phages

@ref	Name	Strain number
124042	Lactococcus phage P001	DSM 4366
124042	Lactococcus phage P008	DSM 4366

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score
124043	ASM1602797v1 assembly for Lactococcus lactis FDAARGOS_887	complete	GCA_016027975	1358.1328	1358	97.8

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1602797v1 assembly for Lactococcus lactis FDAARGOS_887
BV-BRC: 1358.1328

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	96.50	no
125439	motility	BacteriaNetⓘ	no	74.95	no
125439	gram_stain	BacteriaNetⓘ	positive	49.44	no
125439	spore_formation	BacteriaNetⓘ	no	88.99	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Lactococcus lactis strain FDAARGOS_887 strain Not applicable
PATRIC: 1358.1328

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	93.03	no
125438	anaerobic	anaerobicⓘ	no	90.82	no
125438	spore-forming	spore-formingⓘ	no	81.64	no
125438	aerobic	aerobicⓘ	no	94.30	no
125438	thermophilic	thermophileⓘ	no	97.00	no
125438	flagellated	motile2+ⓘ	no	90.50	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Trends and challenges of fruit by-products utilization: insights into safety, sensory, and benefits of the use for the development of innovative healthy food: a review.	Hasan MM, Islam MR, Haque AR, Kabir MR, Khushe KJ, Hasan SMK.	Bioresour Bioprocess	10.1186/s40643-023-00722-8	2024
Phylogeny	A DNA microarray platform based on direct detection of rRNA for characterization of freshwater sediment-related prokaryotic communities.	Peplies J, Lachmund C, Glockner FO, Manz W.	Appl Environ Microbiol	10.1128/aem.02949-05	2006

References

#1547	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 4366
#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 )
#124042	Johannes Wittmann, Clara Rolland, Lorenz Reimer, Joaquim Sardà: PhageDive .
#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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Lactococcus lactis (DSM 4366, Citrate plasmid, F7/2)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Isolation, sampling and environmental information

Interaction and safety

Risk assessment

Phages

Sequence information

Genome sequences

Genome browser: GCA_016027975

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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