Marinobacter psychrophilus 20041 is an aerobe, psychrophilic, Gram-negative bacterium that was isolated from seawater.
Gram-negative motile rod-shaped aerobe psychrophilic genome sequence 16S sequence Bacteria|
|
| Domain Bacteria |
| Phylum Pseudomonadota |
| Class Gammaproteobacteria |
| Order Alteromonadales |
| Family Alteromonadaceae |
| Genus Marinobacter |
| Species Marinobacter psychrophilus |
| Full scientific name Marinobacter psychrophilus Zhang et al. 2008 |
Global distribution of 16S sequence DQ060402 (>99% sequence identity) for Marinobacter psychrophilus subclade from Microbeatlas ![]()
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 32559 | Marinobacter psychrophilus strain 20041 16S ribosomal RNA gene, partial sequence | DQ060402 | 1506 | 330734 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 98.50 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 84.40 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.20 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 97.20 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 99.50 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 97.78 | yes |
| 125438 | aerobic | aerobicⓘ | yes | 84.35 | yes |
| 125438 | spore-forming | spore-formingⓘ | no | 86.62 | no |
| 125438 | thermophilic | thermophileⓘ | no | 97.82 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 85.73 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Complete genome of Marinobacter psychrophilus strain 20041(T) isolated from sea-ice of the Canadian Basin. | Song L, Ren L, Wang L, Yu Y, Wang X, Liu G | Mar Genomics | 10.1016/j.margen.2016.02.001 | 2016 | |
| Phylogeny | Marinobacter psychrophilus sp. nov., a psychrophilic bacterium isolated from the Arctic. | Zhang DC, Li HR, Xin YH, Chi ZM, Zhou PJ, Yu Y | Int J Syst Evol Microbiol | 10.1099/ijs.0.65690-0 | 2008 |
| Culture collection no. | |
|---|---|
| CGMCC 1.6499 | |
| JCM 14643 | |
| 20041 | |
| BCRC 80070 |
| #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 ) |
| #32559 | Barberan A, Caceres Velazquez H, Jones S, Fierer N.: Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information. mSphere 2: 2017 ( DOI 10.1128/mSphere.00237-17 , PubMed 28776041 ) - originally annotated from #28777 (see below) |
| #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 . |
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