Mucilaginibacter gotjawali (DSM 29289, CECT 8628, KCTC 32515)

Name: Mucilaginibacter gotjawali (DSM 29289, CECT 8628, KCTC 32515)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131323

Type strain

Strain Designation SA3-7

Culture col. no. DSM 29289 CECT 8628 KCTC 32515 SA3-7 JCM 32202

NCBI tax ID(s) 1550579

Special Collections DSMZ JCM KCTC

Links

Mucilaginibacter gotjawali SA3-7 is an aerobe, mesophilic prokaryote that was isolated from soil of forest on lava.

aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 399496

KCTC 32515,CECT 8628,DSM 29289

@ref 20215

Last LPSN update 2025-12-16 10:01:13

Domain Pseudomonadati

Phylum Bacteroidota

Class Sphingobacteriia

Order Sphingobacteriales

Family Sphingobacteriaceae

Genus Mucilaginibacter

Species Mucilaginibacter gotjawali

Full scientific name Mucilaginibacter gotjawali Lee et al. 2015

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	99.8
125438	negative	94.16

Colony morphology

22550

Incubation period3-7 days

Multimedia

@ref:	22550
multimedia content:	DSM_29289.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_29289.jpg
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
22550	R2A MEDIUM (DSMZ Medium 830)		Medium recipe at MediaDive	Name: R2A MEDIUM (DSMZ Medium 830) Composition: Agar 15.0 g/l Casamino acids 0.5 g/l Starch 0.5 g/l Glucose 0.5 g/l Proteose peptone 0.5 g/l Yeast extract 0.5 g/l K2HPO4 0.3 g/l Na-pyruvate 0.3 g/l MgSO4 x 7 H2O 0.05 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
22550	positive	growth	28	mesophilic
67770	positive	growth	30	mesophilic
67771	positive	growth	30	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance
67771	aerobe
125439	obligate aerobe

Spore formation

@ref	Spore formation	Confidence
125439		98.9

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Forest
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
22550	soil of forest on lava	Jeju, Gotjawal forest	Republic of Korea	KOR	Asia
67770	Soil of a lava forest	Gotjawal, Jeju	Republic of Korea	KOR	Asia
67771	From soil (Habitat Jeju)		Republic of Korea	KOR	Asia

Taxonmaps

69479

Global distribution of 16S sequence KM588182 (>99% sequence identity) for Mucilaginibacter gotjawali subclade from Microbeatlas

Aquatic Samples	101
Soil Samples	679
Animal Samples	42
Plant Samples	146
Total Samples	968

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
22550	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	ASM235543v1 assembly for Mucilaginibacter gotjawali SA3-7	complete	GCA_002355435	1550579.3	2775506936	1550579	96.08
66792	ASM1419163v1 assembly for Mucilaginibacter gotjawali CECT 8628	scaffold	GCA_014191635	1550579.5	2824259966	1550579	66.96

Genome browser: GCA_002355435

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
22550	Mucilaginibacter gotjawali strain SA3-7 16S ribosomal RNA gene, partial sequence	KM588182	1451		1550579

GC content

@ref	GC-content (mol%)	Method
22550	43.1	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: Mucilaginibacter gotjawali SA3-7
NCBI: GCA_002355435

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	98.90	no
125439	motility	BacteriaNetⓘ	no	80.90	no
125439	gram_stain	BacteriaNetⓘ	negative	99.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	97.00	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Mucilaginibacter gotjawali SA3-7
NCBI: GCA_002355435.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.16	no
125438	anaerobic	anaerobicⓘ	no	96.05	yes
125438	aerobic	aerobicⓘ	yes	76.87	yes
125438	spore-forming	spore-formingⓘ	no	84.70	no
125438	thermophilic	thermophileⓘ	no	96.24	yes
125438	flagellated	motile2+ⓘ	no	86.00	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Mucilaginibacter xinganensis sp. nov., a phenanthrene-degrading bacterium isolated from wetland soil.	Jiang MZ, Qiu ZJ, Zhang GW, Gao SY, You XY, Ma YF	Antonie Van Leeuwenhoek	10.1007/s10482-018-1194-6	2018
Phylogeny	Mucilaginibacter ginsenosidivorans sp. nov., Isolated from Soil of Ginseng Field.	Kim MM, Siddiqi MZ, Im WT	Curr Microbiol	10.1007/s00284-017-1329-4	2017
Phylogeny	Mucilaginibacter hankyongensis sp. nov., isolated from soil of ginseng field Baekdu Mountain.	Liu Q, Siddiqi MZ, Kim MS, Kim SY, Im WT	J Microbiol	10.1007/s12275-017-7180-2	2017
Phylogeny	Mucilaginibacter gotjawali sp. nov., isolated from soil of a lava forest.	Lee KC, Kim KK, Eom MK, Kim JS, Kim DS, Ko SH, Lee JS	Int J Syst Evol Microbiol	10.1099/ijs.0.000044	2015
Phylogeny	Mucilaginibacter Phenanthrenivorans sp. nov., a Novel Phenanthrene Degradation Bacterium Isolated from Wetland Soil.	You XY, Liu JH, Tian H, Ding Y, Bu QY, Zhang KX, Ren GY, Duan X	Curr Microbiol	10.1007/s00284-022-03085-z	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 )
#22550	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 29289
#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;
#67771	Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC;
#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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Mucilaginibacter gotjawali (DSM 29289, CECT 8628, KCTC 32515)

Name and taxonomic classification

Morphology

Cell morphology

Colony morphology

Multimedia

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_002355435

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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