Unidentified bacterium (JCM 14676)

Name: Unidentified bacterium (JCM 14676)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 161515

Type strain

Culture col. no. JCM 14676

NCBI tax ID(s) 1869227

Special Collections JCM

Unidentified bacterium JCM 14676 is a mesophilic prokaryote that was isolated from Stem of cultivated rice, Oryza sativa Bu-24.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

Culture Collection Numbers

JCM 14676

@ref 67770

Phylum Not assigned to order

Class Not assigned to order

Order Not assigned to order

Family Not assigned to family

Genus Not assigned to family

Species Unidentified bacterium

Full scientific name Unidentified bacterium

Type strain no

BacDive ID	Other strains from Unidentified bacterium (32)	Type strain
161399	U. bacterium JCM 13814, KCCM 42310
161840	U. bacterium JCM 16616
161841	U. bacterium JCM 16617
161842	U. bacterium JCM 16618
161887	U. bacterium JCM 16863
161892	U. bacterium JCM 16992
162014	U. bacterium JCM 17375
162200	U. bacterium JCM 18222
162201	U. bacterium JCM 18223
162454	U. bacterium JCM 19270
162455	U. bacterium JCM 19271
162456	U. bacterium JCM 19272
162457	U. bacterium JCM 19273
162460	U. bacterium JCM 19276
162464	U. bacterium JCM 19292
162465	U. bacterium JCM 19293
162467	U. bacterium JCM 19295
162474	U. bacterium JCM 19303
163446	U. bacterium JCM 28254
163447	U. bacterium JCM 28255
163463	U. bacterium JCM 28272
163467	U. bacterium JCM 28276
163468	U. bacterium JCM 28277
163469	U. bacterium JCM 28278
163477	U. bacterium JCM 28286
163481	U. bacterium JCM 28292
163490	U. bacterium JCM 28301
163985	U. bacterium JCM 31257
164107	U. bacterium JCM 31632
164108	U. bacterium JCM 31633
164109	U. bacterium JCM 31639
164319	U. bacterium JCM 32665, DSM 108248

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	99.8
125438	negative	94.597

Culture and growth conditions

Culture temp

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

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	97.1

Spore formation

@ref	Spore formation	Confidence
125439		98.9

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Host species
67770	Stem of cultivated rice, Oryza sativa Bu-24	Oryza sativa

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
67770	ASM33329v1 assembly for Cytophagales bacterium B6	scaffold	GCA_000333295	100480.3	2590828101	100480

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Cytophagales str. B6 gene for 16S rRNA, partial sequence	AB029902	483		100480

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Cytophagales bacterium B6
NCBI: GCA_000333295

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	98.90	no
125439	motility	BacteriaNetⓘ	no	71.30	no
125439	gram_stain	BacteriaNetⓘ	negative	99.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	97.10	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Cytophagales bacterium B6 B6
NCBI: GCA_000333295.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.60	no
125438	anaerobic	anaerobicⓘ	no	97.25	no
125438	aerobic	aerobicⓘ	yes	83.38	no
125438	spore-forming	spore-formingⓘ	no	85.54	no
125438	thermophilic	thermophileⓘ	no	95.20	yes
125438	flagellated	motile2+ⓘ	no	86.50	no

Literature

References

#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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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