Cite this strain

Micromonospora trujilloniae (DSM 45674, CCTCC AA 2011018, JCM 31041)

Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 8034

Type strain

Strain Designation 234402

Culture col. no. DSM 45674 CCTCC AA 2011018 JCM 31041 NBRC 110790 234402

NCBI tax ID(s) 1287068

Special Collections DSMZ JCM

Links

Name and taxonomic classification

Micromonospora trujilloniae 234402 is an aerobe, spore-forming, mesophilic bacterium that was isolated from mangrove soil.

spore-forming Gram-positive aerobe mesophilic genome sequence 16S sequence Bacteria

SI-ID 403745

DSM 45674

Last LPSN update 2024-12-09 10:44:00

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Micromonosporales

Family Micromonosporaceae

Genus Micromonospora

Species Micromonospora trujilloniae

Full scientific name Micromonospora trujilloniae Nouioui et al. 2018

Synonyms (1)

Verrucosispora wenchangensis

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	positive	99.8
125439		91.1
125438		90
125438	positive	90.93

Multimedia

@ref:	18037
manual_annotation:	1
multimedia content:	DSM_45674.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_45674.jpg
caption:	Medium 65 28°C
intellectual property rights:	© Leibniz-Institut DSMZ

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
18037	GYM STREPTOMYCES MEDIUM (DSMZ Medium 65)		Medium recipe at MediaDive	Name: GYM STREPTOMYCES MEDIUM (DSMZ Medium 65) Composition: Agar 18.0 g/l Malt extract 10.0 g/l Yeast extract 4.0 g/l Glucose 4.0 g/l CaCO3 2.0 g/l Distilled water
18037	GPHF-MEDIUM (DSMZ Medium 553)		Medium recipe at MediaDive	Name: GPHF-MEDIUM (DSMZ Medium 553) Composition: Agar 20.0 g/l Glucose 10.0 g/l Beef extract 5.0 g/l Yeast extract 5.0 g/l Casein peptone 5.0 g/l CaCl2 x 2 H2O 0.74 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
18037	positive	growth	28	mesophilic
67770	positive	growth	28	mesophilic

Physiology and metabolism

Observation

67770

Observationquinones: MK-9(H₄), MK-9(H₆), MK-9(H₈)

Spore formation

@ref	Spore formation	Confidence
125438		90.402

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	aerobe	90.973
125439	obligate aerobe	99.3

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Mangrove
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
18037	mangrove soil	Hainan, Wenchang (N19°36.506', E110°47.746')	China	CHN	Asia	19.6084	110.796 19.6084/110.796
67770	Mangrove soil in Wenchang	Hainan Province	China	CHN	Asia

Taxonmaps

69479

Global distribution of 16S sequence HQ123435 (>99% sequence identity) for Micromonospora from Microbeatlas

Aquatic Samples	47
Soil Samples	308
Animal Samples	71
Plant Samples	23
Total Samples	449

Safety information

Risk assessment

@ref	Biosafety level	Biosafety level comment
18037	1	Risk group (German classification) According to TRBA 466

Sequence information

GC content

@ref	GC-content (mol%)	Method
18037	69.2	high performance liquid chromatography (HPLC)

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
18037	Verrucosispora wenchangensis strain 234402 16S ribosomal RNA gene, partial sequence	HQ123435	1475		879618

Genome sequences

@ref	Description	Accession	Assembly level	Database	NCBI tax ID
66792	Micromonospora andamanensis NBRC 110790	GCA_016863595	contig		1287068
66792	Micromonospora trujilloniae strain NBRC 110790	879618.3	wgs	PATRIC	879618

Genome-based predictions

Predictions

Predictions from Diaspora project based on:
Micromonospora andamanensis NBRC 110790
NCBI: GCA_016863595

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	89.60	no
125439	motility	BacteriaNetⓘ	no	91.10	no
125439	gram_stain	BacteriaNetⓘ	positive	99.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.30	no

Predictions from Diaspora project based on:
Micromonospora trujilloniae strain NBRC 110790
PATRIC: 879618.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	90.93	no
125438	anaerobic	anaerobicⓘ	no	95.32	no
125438	aerobic	aerobicⓘ	yes	90.97	no
125438	spore-forming	spore-formingⓘ	yes	90.40	no
125438	thermophilic	thermophileⓘ	no	91.48	no
125438	flagellated	motile2+ⓘ	no	90.00	no

External links

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Verrucosispora wenchangensis sp. nov., isolated from mangrove soil.	Xie QY, Lin HP, Li L, Brown R, Goodfellow M, Deng Z, Hong K	Antonie Van Leeuwenhoek	10.1007/s10482-012-9707-1	2012

Straininfo Link

@ref	Straininfo	Culture collections
77464	403745	DSM 45674

Culture collection no.

Culture collection no.
DSM 45674
CCTCC AA 2011018
JCM 31041
NBRC 110790
234402

References

#18037	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 45674
#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 )
#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) .
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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 .
#77464	Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J.: StrainInfo: A central database for resolving microbial strain identifiers . ( DOI 10.60712/SI-ID403745.1 )
#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 .

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