Sinomonas susongensis (DSM 28245, CCTCC AB 2014068, A31)

Name: Sinomonas susongensis (DSM 28245, CCTCC AB 2014068, A31)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 130438

Type strain

Strain Designation A31

Culture col. no. DSM 28245 CCTCC AB 2014068 A31 JCM 31752

NCBI tax ID(s) 1324851

Special Collections DSMZ JCM

History <- Z. Huang, Nanjing Agric. Univ., China; A31 <- R. Yuan CCTCC AB 2014068 <-- Z. Huang; Nanjing Agric. Univ., China; A31.

Links

Sinomonas susongensis A31 is a bacterium that was isolated from surface of weathered biotite.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 404603

DSM 28245

@ref 20215

Last LPSN update 2026-02-09 11:31:13

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Micrococcales

Family Micrococcaceae

Genus Sinomonas

Species Sinomonas susongensis

Full scientific name Sinomonas susongensis Bao et al. 2015

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	positive	98

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
22069	TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92)		Medium recipe at MediaDive	Name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Yeast extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
22069	positive	growth	28
67770	positive	growth	28

Physiology and metabolism

Observation

67770

Observationquinones: MK-9(H₂), MK-10(H₂)

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Geologic

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
22069	surface of weathered biotite	Anhui Province, Susong	China	CHN	Asia
67770	Surface of weathered biotite	Susong, Anhui Province	China	CHN	Asia

Taxonmaps

69479

Global distribution of 16S sequence KC841860 (>99% sequence identity) for Sinomonas susongensis from Microbeatlas

Aquatic Samples	12
Soil Samples	255
Animal Samples	15
Plant Samples	9
Total Samples	291

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
22069	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM587700v1 assembly for Sinomonas susongensis A31	scaffold	GCA_005877005	1324851.3	2890423931	1324851	70.8

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
22069	Sinomonas susongensis strain A31 16S ribosomal RNA gene, partial sequence	KC841860	1447		1324851

GC content

@ref	GC-content (mol%)	Method
22069	70.8	high performance liquid chromatography (HPLC)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Sinomonas susongensis A31
NCBI: GCA_005877005

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	66.50	no
125439	motility	BacteriaNetⓘ	no	78.20	no
125439	gram_stain	BacteriaNetⓘ	positive	98.00	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	73.60	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Sinomonas susongensis A31
NCBI: GCA_005877005.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	87.49	no
125438	anaerobic	anaerobicⓘ	no	96.91	no
125438	aerobic	aerobicⓘ	yes	86.47	no
125438	spore-forming	spore-formingⓘ	no	74.27	no
125438	thermophilic	thermophileⓘ	no	97.00	yes
125438	flagellated	motile2+ⓘ	no	73.50	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Sinomonas susongensis sp. nov., isolated from the surface of weathered biotite.	Bao YY, Huang Z, Mao DM, Sheng XF, He LY	Int J Syst Evol Microbiol	10.1099/ijs.0.000064	2015

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 )
#22069	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 28245
#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 .
#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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Sinomonas susongensis (DSM 28245, CCTCC AB 2014068, A31)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Observation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_005877005

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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