Ehrlichia muris CSUR E2 is a Gram-negative, coccus-shaped bacterium of the family Ehrlichiaceae.
Gram-negative coccus-shaped genome sequence 16S sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Pseudomonadota |
| Class Alphaproteobacteria |
| Order Rickettsiales |
| Family Ehrlichiaceae |
| Genus Ehrlichia |
| Species Ehrlichia muris |
| Full scientific name Ehrlichia muris Wen et al. 1995 |
| @ref | Name | Growth | |
|---|---|---|---|
| 43319 | DH82 canine macrophage-like cells |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM50822v1 assembly for Ehrlichia muris AS145 | complete | 1423892 | 97.48 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 124043 | Ehrlichia muris 16S ribosomal RNA gene, partial sequence. | U15527 | 1428 | 1423892 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | facultative anaerobe | 97.25 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.82 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 48.93 | no |
| 125439 | spore_formation | BacteriaNetⓘ | no | 99.99 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 84.23 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 81.18 | no |
| 125438 | aerobic | aerobicⓘ | no | 61.42 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 95.00 | no |
| 125438 | thermophilic | thermophileⓘ | no | 87.08 | no |
| 125438 | flagellated | motile2+ⓘ | no | 87.82 | yes |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Genetics | Complete Genome Sequence of Ehrlichia muris Strain AS145T, a Model Monocytotropic Ehrlichia Strain. | Thirumalapura NR, Qin X, Kuriakose JA, Walker DH | Genome Announc | 10.1128/genomeA.01234-13 | 2014 | |
| Phylogeny | Proposal to reclassify Ehrlichia muris as Ehrlichia muris subsp. muris subsp. nov. and description of Ehrlichia muris subsp. eauclairensis subsp. nov., a newly recognized tick-borne pathogen of humans. | Pritt BS, Allerdice MEJ, Sloan LM, Paddock CD, Munderloh UG, Rikihisa Y, Tajima T, Paskewitz SM, Neitzel DF, Hoang Johnson DK, Schiffman E, Davis JP, Goldsmith CS, Nelson CM, Karpathy SE | Int J Syst Evol Microbiol | 10.1099/ijsem.0.001896 | 2017 | |
| Phylogeny | Ehrlichia muris sp. nov., identified on the basis of 16S rRNA base sequences and serological, morphological, and biological characteristics. | Wen B, Rikihisa Y, Mott J, Fuerst PA, Kawahara M, Suto C | Int J Syst Bacteriol | 10.1099/00207713-45-2-250 | 1995 |
| #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 ) |
| #43319 | Bobbi S. Pritt, Michelle E. J. Allerdice, Lynne M. Sloan, Christopher D. Paddock, Ulrike G. Munderloh, Yasuko Rikihisa, Tomoko Tajima, Susan M. Paskewitz, David F. Neitzel, Diep K. Hoang Johnson, Elizabeth Schiffman, Jeffrey P. Davis, Cynthia S. Goldsmith, Curtis M. Nelson, Sandor E. Karpathy: Proposal to reclassify Ehrlichia muris as Ehrlichia muris subsp. muris subsp. nov. and description of Ehrlichia muris subsp. eauclairensis subsp. nov., a newly recognized tick-borne pathogen of humans. IJSEM 67: 2121 - 2126 2017 ( DOI 10.1099/ijsem.0.001896 , PubMed 28699575 ) |
| #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) . |
| #124043 | Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy . |
| #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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