Pseudomonas pyomelaninifaciens (KCTC 62307, JCM 32458)

Name: Pseudomonas pyomelaninifaciens (KCTC 62307, JCM 32458)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164261

Type strain

Culture col. no. KCTC 62307 JCM 32458

Special Collections JCM KCTC

History R. Chakraborty; Dept. of Biotechnol., Univ. of North Bengal, India; MR 02.

Pseudomonas pyomelaninifaciens JCM 32458 is a prokaryote that was isolated from Mahananda River at Siliguri.

genome sequence 16S sequence

Name and taxonomic classification

Culture Collection Numbers

KCTC 62307 JCM 32458

@ref 67770

Phylum Not assigned to order

Class Not assigned to order

Order Not assigned to order

Family Not assigned to family

Genus Pseudomonas

Species Pseudomonas pyomelaninifaciens

Full scientific name Pseudomonas pyomelaninifaciens

Type strain no

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	98.5
125438	negative	99

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	aerobe	93.875

Spore formation

@ref	Spore formation	Confidence
125439		99.2

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	Mahananda River at Siliguri	West Bengal	India	IND	Asia

Taxonmaps

69479

Global distribution of 16S sequence MF401548 (>99% sequence identity) for Pseudomonas from Microbeatlas

Aquatic Samples	543
Soil Samples	368
Animal Samples	799
Plant Samples	423
Total Samples	2133

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score
67770	ASM279747v1 assembly for Pseudomonas asiatica MR 02	scaffold	GCA_002797475	2048282.3	2048282	59.6

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Pseudomonas sp. MR 02 16S ribosomal RNA gene, partial sequence	MF401548	1501		2048282

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Pseudomonas sp. MR 02
NCBI: GCA_002797475

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.20	no
125439	motility	BacteriaNetⓘ	yes	89.20	no
125439	gram_stain	BacteriaNetⓘ	negative	98.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	83.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Pseudomonas sp. MR 02 MR 02
NCBI: GCA_002797475.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	99.00	no
125438	anaerobic	anaerobicⓘ	no	99.66	no
125438	aerobic	aerobicⓘ	yes	93.88	no
125438	spore-forming	spore-formingⓘ	no	86.59	no
125438	thermophilic	thermophileⓘ	no	98.99	no
125438	flagellated	motile2+ⓘ	yes	87.94	no

Literature

References

#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 .

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