Comamonas granuli Ko03 is an aerobe, mesophilic, Gram-negative prokaryote that was isolated from granular sludge in industrial wastewater treatment plant.
Gram-negative aerobe mesophilic genome sequence 16S sequence| @ref 20215 |
|
|
| Domain Pseudomonadati |
| Phylum Pseudomonadota |
| Class Betaproteobacteria |
| Order Burkholderiales |
| Family Comamonadaceae |
| Genus Comamonas |
| Species Comamonas granuli |
| Full scientific name Comamonas granuli Kim et al. 2011 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 7544 | REACTIVATION WITH LIQUID MEDIUM 830 (DSMZ Medium 830c) | Medium recipe at MediaDive | Name: REACTIVATION WITH LIQUID MEDIUM 830 (DSMZ Medium 830c) Composition: Agar 15.0 g/l Yeast extract 0.5 g/l Proteose peptone 0.5 g/l Casamino acids 0.5 g/l Glucose 0.5 g/l Starch 0.5 g/l K2HPO4 0.3 g/l Na-pyruvate 0.3 g/l MgSO4 x 7 H2O 0.05 g/l Distilled water |
| Cat1 | Cat2 | Cat3 | |
|---|---|---|---|
| #Engineered | #Waste | #Industrial wastewater | |
| #Engineered | #Waste | #Activated sludge | |
| #Engineered | #Waste | #Water treatment plant |
Global distribution of 16S sequence AB681516 (>99% sequence identity) for Comamonas granuli subclade from Microbeatlas ![]()
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM73999v1 assembly for Comamonas granuli NBRC 101663 | contig | 1223521 | 68.66 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 94.80 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.50 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 85.10 | no |
| 125439 | spore_formation | BacteriaNetⓘ | no | 99.00 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 97.99 | yes |
| 125438 | anaerobic | anaerobicⓘ | no | 90.67 | yes |
| 125438 | spore-forming | spore-formingⓘ | no | 89.75 | no |
| 125438 | aerobic | aerobicⓘ | yes | 70.76 | yes |
| 125438 | thermophilic | thermophileⓘ | no | 92.57 | no |
| 125438 | flagellated | motile2+ⓘ | yes | 87.28 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Nanopore Long-Read Guided Complete Genome Assembly of Hydrogenophaga intermedia, and Genomic Insights into 4-Aminobenzenesulfonate, p-Aminobenzoic Acid and Hydrogen Metabolism in the Genus Hydrogenophaga. | Gan HM, Lee YP, Austin CM. | Front Microbiol | 10.3389/fmicb.2017.01880 | 2017 | |
| Phylogeny | Comamonas granuli sp. nov., isolated from granules used in a wastewater treatment plant. | Kim KH, Ten LN, Liu QM, Im WT, Lee ST | J Microbiol | 10.1007/s12275-008-0019-0 | 2008 |
| #7544 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 18411 |
| #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 ) |
| #20218 | Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.: StrainInfo introduces electronic passports for microorganisms.. Syst Appl Microbiol. 37: 42 - 50 2014 ( DOI 10.1016/j.syapm.2013.11.002 , PubMed 24321274 ) |
| #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) . |
| #67771 | Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC; |
| #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 . |
| #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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