Sporosarcina jiandibaonis (LAM9210, GGMCC 1.18607, JCM 32514)

Name: Sporosarcina jiandibaonis (LAM9210, GGMCC 1.18607, JCM 32514)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 168279

Type strain

Strain Designation LAM9210, GGMCC 1.18607

Culture col. no. LAM9210 GGMCC 1.18607 JCM 32514 GDMCC 1.2002

NCBI tax ID(s) 2715535

Special Collections JCM

Links

Sporosarcina jiandibaonis LAM9210 is a prokaryote of the family Caryophanaceae.

genome sequence 16S sequence

Name and taxonomic classification

SI-ID 133631

JCM 32514

@ref 20215

Last LPSN update 2025-12-16 10:10:18

Domain Bacillati

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Caryophanaceae

Genus Sporosarcina

Species Sporosarcina jiandibaonis

Full scientific name Sporosarcina jiandibaonis Kong et al. 2022

Morphology

Culture and growth conditions

Physiology and metabolism

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1318449v1 assembly for Sporosarcina jiandibaonis LAM9210	contig	GCA_013184495	2715535.3	2915350061	2715535	67.36

Genome browser: GCA_013184495

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20215	Sporosarcina jiandibaonis strain LAM9210 16S ribosomal RNA gene, partial sequence	MG645384	1516		2715535

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Sporosarcina jiandibaonis LAM9210
NCBI: GCA_013184495

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	60.60	no
125439	motility	BacteriaNetⓘ	yes	54.30	no
125439	gram_stain	BacteriaNetⓘ	variable	73.40	no
125439	oxygen_tolerance	BacteriaNetⓘ	microaerophile	81.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Sporosarcina jiandibaonis LAM9210
NCBI: GCA_013184495.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	74.52	no
125438	anaerobic	anaerobicⓘ	no	96.23	no
125438	aerobic	aerobicⓘ	yes	76.56	no
125438	spore-forming	spore-formingⓘ	yes	83.48	no
125438	thermophilic	thermophileⓘ	no	87.90	no
125438	flagellated	motile2+ⓘ	yes	56.44	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Sporosarcina jiandibaonis sp. nov., isolated from saline soil.	Kong D, Xia Z, Gao Y, Zhou Y, Jiang X, Xu P, Guo W, Ruan Z	Int J Syst Evol Microbiol	10.1099/ijsem.0.005244	2022

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 )
#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) .
#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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Sporosarcina jiandibaonis (LAM9210, GGMCC 1.18607, JCM 32514)

Name and taxonomic classification

Morphology

Culture and growth conditions

Physiology and metabolism

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_013184495

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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