Paenibacillus ihumii AT5 is a mesophilic prokaryote that was isolated from human stool specimen, 33-year-old woman with morbid obesity.
mesophilic genome sequence 16S sequence| @ref 20215 |
|
|
| Domain Bacillati |
| Phylum Bacillota |
| Class Bacilli |
| Order Caryophanales |
| Family Paenibacillaceae |
| Genus Paenibacillus |
| Species Paenibacillus ihumii |
| Full scientific name Paenibacillus ihumii Togo et al. 2017 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 24290 | CASO AGAR (MERCK 105458) (DSMZ Medium 220) | Medium recipe at MediaDive | Name: CASO AGAR (Merck 105458) (DSMZ Medium 220) Composition: Agar 15.0 g/l Casein peptone 15.0 g/l NaCl 5.0 g/l Soy peptone 5.0 g/l Distilled water |
| @ref | Growth | Type | Temperature (°C) | Range | |
|---|---|---|---|---|---|
| 24290 | positive | growth | 30 | mesophilic |
| Cat1 | Cat2 | Cat3 | |
|---|---|---|---|
| #Infection | #Patient | #Specimen | |
| #Host | #Human | #Female | |
| #Host Body Product | #Gastrointestinal tract | #Feces (Stool) |
| @ref | Sample type | Geographic location | Country | Country ISO 3 Code | Continent | |
|---|---|---|---|---|---|---|
| 24290 | human stool specimen, 33-year-old woman with morbid obesity | Marseille | France | FRA | Europe |
Global distribution of 16S sequence LN881615 (>99% sequence identity) for Paenibacillus ihumii from Microbeatlas ![]()
| @ref | Biosafety level | Biosafety level comment | |
|---|---|---|---|
| 24290 | 1 | Risk group (German classification) |
| @ref | Description | Assembly level | INSDC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|
| 66792 | Paenibacillus ihumii assembly for Paenibacillus ihumii AT5 | scaffold | 687436 | 75.45 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 24290 | Paenibacillus sp. AT5 partial 16S rRNA gene, strain AT5 | LN881615 | 1518 | 687436 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 24290 | 50 | sequence analysis |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | yes | 93.00 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 89.00 | no |
| 125439 | gram_stain | BacteriaNetⓘ | variable | 86.10 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | facultative anaerobe | 88.80 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 58.54 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 96.23 | no |
| 125438 | aerobic | aerobicⓘ | no | 52.73 | no |
| 125438 | spore-forming | spore-formingⓘ | yes | 92.73 | no |
| 125438 | thermophilic | thermophileⓘ | no | 90.20 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 81.18 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Genetics | Systematically investigating and identifying bacteriocins in the human gut microbiome. | Zhang D, Zou Y, Shi Y, Zhang J, Liu J, Wu G, Zhang J, Gao Y, Chen M, Li YX. | Cell Genom | 10.1016/j.xgen.2025.100983 | 2025 | |
| Genetics | Noncontiguous finished genome sequence and description of Paenibacillus ihumii sp. nov. strain AT5. | Togo AH, Khelaifia S, Lagier JC, Caputo A, Robert C, Fournier PE, Maraninchi M, Valero R, Raoult D, Million M | New Microbes New Infect | 10.1016/j.nmni.2016.01.013 | 2016 |
| #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 ) |
| #24290 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 100664 |
| #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 . |
| #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/bacdive132501.20251217.10
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BacDive in 2025: the core database for prokaryotic strain data