Strain identifier
version 9.3 (current version)
General
@ref: 58581
BacDive-ID: 153408
keywords: genome sequence, Bacteria
description: Aggregatibacter aphrophilus CCUG 49494 is a bacterium of the family Pasteurellaceae.
NCBI tax id
- NCBI tax id: 732
- Matching level: species
doi: 10.13145/bacdive153408.20250331.9.3
Name and taxonomic classification
LPSN
- @ref: 20215
- description: domain/bacteria
- keyword: phylum/pseudomonadota
- domain: Bacteria
- phylum: Pseudomonadota
- class: Gammaproteobacteria
- order: Pasteurellales
- family: Pasteurellaceae
- genus: Aggregatibacter
- species: Aggregatibacter aphrophilus
- full scientific name: Aggregatibacter aphrophilus (Khairat 1940) Nørskov-Lauritsen and Kilian 2006
synonyms
@ref synonym 20215 Haemophilus paraphrophilus 20215 Haemophilus aphrophilus
@ref: 58581
domain: Bacteria
phylum: Proteobacteria
class: Gammaproteobacteria
order: Pasteurellales
family: Pasteurellaceae
genus: Aggregatibacter
species: Aggregatibacter aphrophilus
type strain: no
Morphology
cell morphology
| @ref | motility | confidence | gram stain |
|---|---|---|---|
| 125438 | no | 91.2 | |
| 125438 | 97.438 | negative | |
| 125439 | 97.5 | negative |
Physiology and metabolism
oxygen tolerance
- @ref: 125439
- oxygen tolerance: obligate aerobe
- confidence: 98.7
spore formation
| @ref | spore formation | confidence |
|---|---|---|
| 125438 | no | 90.617 |
| 125439 | no | 99.5 |
Sequence information
Genome sequences
- @ref: 66792
- description: Aggregatibacter aphrophilus strain HK83
- accession: 732.170
- assembly level: wgs
- database: patric
- NCBI tax ID: 732
Genome-based predictions
predictions
| @ref | model | trait | description | prediction | confidence | training_data |
|---|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positive | Positive reaction to Gram-staining | no | 97.438 | no |
| 125438 | anaerobic | anaerobic | Ability to grow under anoxygenic conditions (including facultative anaerobes) | no | 92.459 | no |
| 125438 | spore-forming | spore-forming | Ability to form endo- or exospores | no | 90.617 | no |
| 125438 | aerobic | aerobic | Ability to grow under oxygenic conditions (including facultative aerobes) | no | 84.533 | no |
| 125438 | thermophile | thermophilic | Ability to grow at temperatures above or equal to 45°C | no | 97.5 | no |
| 125438 | motile2+ | flagellated | Ability to perform flagellated movement | no | 91.2 | no |
| 125439 | BacteriaNet | spore_formation | Ability to form endo- or exospores | no | 99.5 | |
| 125439 | BacteriaNet | motility | Ability to perform movement | yes | 56.1 | |
| 125439 | BacteriaNet | gram_stain | Reaction to gram-staining | negative | 97.5 | |
| 125439 | BacteriaNet | oxygen_tolerance | Oxygenic conditions needed for growth | obligate aerobe | 98.7 |
External links
@ref: 58581
culture collection no.: CCUG 49494
straininfo link
- @ref: 107215
- straininfo: 214661
Reference
| @id | authors | title | doi/url | catalogue |
|---|---|---|---|---|
| 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 | 10.1099/ijsem.0.004332 | |
| 58581 | Curators of the CCUG | https://www.ccug.se/strain?id=49494 | Culture Collection University of Gothenburg (CCUG) (CCUG 49494) | |
| 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) | https://diaspora-project.de/progress.html#genomes | |
| 107215 | Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J. | StrainInfo: A central database for resolving microbial strain identifiers | 10.60712/SI-ID214661.1 | |
| 125438 | Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann | Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets | 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 | https://github.com/GenomeNet/deepG |