Xanthomonas hyacinthi DSM 19077 is a plant pathogen that was isolated from Hyacinthus orientalis.
plant pathogen genome sequence 16S sequence Bacteria| @ref 20215 |
|
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| Domain Bacteria |
| Phylum Pseudomonadota |
| Class Gammaproteobacteria |
| Order Lysobacterales |
| Family Lysobacteraceae |
| Genus Xanthomonas |
| Species Xanthomonas hyacinthi |
| Full scientific name Xanthomonas hyacinthi (ex Wakker 1883) Vauterin et al. 1995 |
| BacDive ID | Other strains from Xanthomonas hyacinthi (2) | Type strain |
|---|---|---|
| 17590 | X. hyacinthi DSM 50855, ICPB XH 110, LMG 742 | |
| 141435 | X. hyacinthi CCUG 1830, CCM 1896 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 7869 | NUTRIENT AGAR (DSMZ Medium 1) | Medium recipe at MediaDive | Name: NUTRIENT AGAR (DSMZ Medium 1) Composition: Agar 15.0 g/l Peptone 5.0 g/l Meat extract 3.0 g/l Distilled water |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 7869 | positive | growth | 30 |
| @ref | Sample type | Country | Country ISO 3 Code | Continent | |
|---|---|---|---|---|---|
| 7869 | Hyacinthus orientalis | Netherlands | NLD | Europe |
Global distribution of 16S sequence Y10754 (>99% sequence identity) for Xanthomonas from Microbeatlas ![]()
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 124043 | ASM4264802v1 assembly for Xanthomonas hyacinthi ICMP 189 | contig | 56455 | 70.27 | ||||
| 66792 | ASM101043v1 assembly for Xanthomonas hyacinthi DSM 19077 | contig | 1440765 | 0 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 7869 | X.hyacinthi 16S rRNA gene | Y10754 | 1500 | 56455 | ||
| 124043 | Xanthomonas hyacinthi strain LMG739 16S-23S ribosomal RNA intergenic spacer, complete sequence. | AF209759 | 493 | 56455 | ||
| 124043 | Xanthomonas hyacinthi strain ICMP 189 16S ribosomal RNA gene, partial sequence. | MT760330 | 1379 | 56455 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 98.92 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 85.59 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 96.10 | no |
| 125439 | spore_formation | BacteriaNetⓘ | no | 99.74 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 97.99 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 95.96 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 86.44 | no |
| 125438 | aerobic | aerobicⓘ | yes | 88.12 | no |
| 125438 | thermophilic | thermophileⓘ | no | 97.50 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 76.84 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogenetic Distribution and Evolution of Type VI Secretion System in the Genus Xanthomonas. | Liyanapathiranage P, Wagner N, Avram O, Pupko T, Potnis N. | Front Microbiol | 10.3389/fmicb.2022.840308 | 2022 | ||
| Enzymology | Differences in hyporheic-zone microbial community structure along a heavy-metal contamination gradient. | Feris K, Ramsey P, Frazar C, Moore JN, Gannon JE, Holben WE. | Appl Environ Microbiol | 10.1128/aem.69.9.5563-5573.2003 | 2003 |
| #7869 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 19077 |
| #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 ) |
| #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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https://doi.org/10.13145/bacdive17589.20260601.11
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