Methylomonas sp. (DSM 24493, LW13)

Name: Methylomonas sp. (DSM 24493, LW13)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 158224

Type strain

Strain Designation LW13

Culture col. no. DSM 24493 LW13

NCBI tax ID(s) 418

Special Collections DSMZ

History <- A. Vorobev, Univ. of Washington, Seattle, USA; LW13 <- M. G. Kalyuzhnaya <- A. J. Auman

Links

LW13 is a mesophilic prokaryote that was isolated from Sediment.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 400878

DSM 24493

@ref 20215

Last LPSN update 2026-02-09 11:38:15

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Methylococcales

Family Methylococcaceae

Genus Methylomonas

Full scientific name Methylomonas (ex Leadbetter 1974) Whittenbury and Krieg 1984

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	99
125439	negative	99

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
64844	MINERAL MEDIUM (DSMZ Medium 1007)		Medium recipe at MediaDive	Name: MINERAL MEDIUM (DSMZ Medium 1007) Composition: KNO3 0.25 g/l KH2PO4 0.1 g/l MgSO4 x 7 H2O 0.05 g/l CaCl2 x 2 H2O 0.01 g/l EDTA 0.005 g/l FeSO4 x 7 H2O 0.002 g/l CoCl2 x 6 H2O 0.0002 g/l CuCl2 x 5 H2O 0.0001 g/l ZnSO4 x 7 H2O 0.0001 g/l Na2MoO4 3e-05 g/l MnCl2 x 4 H2O 3e-05 g/l NiCl2 x 6 H2O 2e-05 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
64844	positive	growth	25	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	aerobe	94.8

Spore formation

@ref	Spore formation	Confidence
125438		90.271
125439		98.3

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Sediment
#Environmental	#Terrestrial	#Sediment

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
64844	Sediment	Lake Washington	USA	USA	North America

Taxonmaps

69479

Global distribution of 16S sequence AF150792 (>99% sequence identity) for Methylomonas from Microbeatlas

Aquatic Samples	7580
Soil Samples	1556
Animal Samples	1076
Plant Samples	914
Total Samples	11126

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1686525v1 assembly for Methylomonas sp. LW13	complete	GCA_016865255		2923715482	107637	98.33
66792	ASM70292v1 assembly for Methylomonas sp. LW13	contig	GCA_000702925	107637.3	2561511042	107637	12.13

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
64844	Methylomonas sp. LW13 16S ribosomal RNA gene, partial sequence	AF150792	1498		107637

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Methylomonas sp. LW13
NCBI: GCA_016865255

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	94.80	no
125439	gram_stain	BacteriaNetⓘ	negative	99.00	no
125439	motility	BacteriaNetⓘ	yes	82.90	no
125439	spore_formation	BacteriaNetⓘ	no	98.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methylomonas sp. LW13 LW13
NCBI: GCA_016865255.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	99.00	no
125438	anaerobic	anaerobicⓘ	no	83.85	no
125438	aerobic	aerobicⓘ	yes	70.09	no
125438	spore-forming	spore-formingⓘ	no	90.27	no
125438	thermophilic	thermophileⓘ	no	94.42	no
125438	flagellated	motile2+ⓘ	yes	68.05	no

Literature

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 )
#64844	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 24493
#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) .
#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 )

Rate our new design

Content

About us