Treponema putidum ATCC 700334 is an anaerobe, motile, coccus-shaped bacterium that was isolated from human - mouth.
motile coccus-shaped anaerobe genome sequence 16S sequence Bacteria| @ref 20215 |
|
|
| Domain Bacteria |
| Phylum Spirochaetota |
| Class Spirochaetia |
| Order Spirochaetales |
| Family Treponemataceae |
| Genus Treponema |
| Species Treponema putidum |
| Full scientific name Treponema putidum Wyss et al. 2004 |
| 29997 | Sample typehuman - mouth |
Global distribution of 16S sequence AJ543428 (>99% sequence identity) for Treponema putidum from Microbeatlas ![]()
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM75514v1 assembly for Treponema putidum OMZ 758 | complete | 221027 | 96.75 | ||||
| 66792 | ASM783059v1 assembly for Treponema putidum ATCC 700334 | scaffold | 221027 | 69.89 | ||||
| 66792 | Treponema putidum strain OMZ 758 (ATCC 700334) | complete | 221027 | 53.9 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 99.60 | no |
| 125439 | motility | BacteriaNetⓘ | no | 78.80 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.90 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 95.10 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 83.19 | no |
| 125438 | anaerobic | anaerobicⓘ | yes | 88.23 | yes |
| 125438 | spore-forming | spore-formingⓘ | no | 79.81 | no |
| 125438 | aerobic | aerobicⓘ | no | 98.38 | no |
| 125438 | thermophilic | thermophileⓘ | no | 91.49 | no |
| 125438 | flagellated | motile2+ⓘ | yes | 57.01 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Multilocus Sequence Analysis of Phylogroup 1 and 2 Oral Treponeme Strains. | Huo YB, Chan Y, Lacap-Bugler DC, Mo S, Woo PCY, Leung WK, Watt RM. | Appl Environ Microbiol | 10.1128/aem.02499-16 | 2017 | |
| Phylogeny | Targeting the treponemal microbiome of digital dermatitis infections by high-resolution phylogenetic analyses and comparison with fluorescent in situ hybridization. | Klitgaard K, Foix Breto A, Boye M, Jensen TK. | J Clin Microbiol | 10.1128/jcm.00320-13 | 2013 | |
| The occurrence of Treponema spp. in gingival plaque from dogs with varying degree of periodontal disease. | Nises J, Rosander A, Pettersson A, Backhans A. | PLoS One | 10.1371/journal.pone.0201888 | 2018 | ||
| Genetics | Complete Genome Sequence of the Oral Spirochete Bacterium Treponema putidum Strain OMZ 758T (ATCC 700334T). | Lacap-Bugler DC, Jiang J, Huo YB, Chan Y, Leung FC, Watt RM | Genome Announc | 10.1128/genomeA.01076-14 | 2014 | |
| Phylogeny | Treponema putidum sp. nov., a medium-sized proteolytic spirochaete isolated from lesions of human periodontitis and acute necrotizing ulcerative gingivitis. | Wyss C, Moter A, Choi BK, Dewhirst FE, Xue Y, Schupbach P, Gobel UB, Paster BJ, Guggenheim B | Int J Syst Evol Microbiol | 10.1099/ijs.0.02806-0 | 2004 |
| #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 ) |
| #26362 | IJSEM 1117 2004 ( DOI 10.1099/ijs.0.02806-0 , PubMed 15280279 ) |
| #29997 | 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 #26362 |
| #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) . |
| #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 . |
| #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 . |
| #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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