Acinetobacter radioresistens (DSM 108293, 108293)

Name: Acinetobacter radioresistens (DSM 108293, 108293)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 169353

Type strain

Strain Designation 108293

Culture col. no. DSM 108293 108293

NCBI tax ID(s) 40216

Special Collections DSMZ DZIF

History DSMZ <- P. Schröttner, Institut für Medizinische Mikrobiologie und Hygiene. Technische Universität Dresden.; 77614 (2)

Links

Acinetobacter radioresistens 108293 is a bacterium that was isolated from swab.

genome sequence Bacteria

Name and taxonomic classification

SI-ID 407551

DSM 108293

@ref 20215

Last LPSN update 2026-05-29 08:46:35

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Pseudomonadales

Family Moraxellaceae

Genus Acinetobacter

Species Acinetobacter radioresistens

Full scientific name Acinetobacter radioresistens Nishimura et al. 1988

BacDive ID	Other strains from **Acinetobacter radioresistens** (34)	Type strain
8096	A. radioresistens FO-1, DSM 6976, ATCC 43998, IAM 13186, CCUG ... (type strain)
127845	A. radioresistens ST027624,
136812	A. radioresistens SEIP 12.81, CIP 110469, NIPH 2130, BOUVET ...
147887	A. radioresistens CCUG 34434
155470	A. radioresistens CCUG 57822
155574	A. radioresistens CCUG 58199
155608	A. radioresistens CCUG 58362
155713	A. radioresistens CCUG 59117
155833	A. radioresistens CCUG 59434
155952	A. radioresistens CCUG 59753
156455	A. radioresistens CCUG 61887
166022	A. radioresistens JCM 9327, ATCC 43999, IAM 13187
166023	A. radioresistens JCM 9328, ATCC 49000, IAM 13188
169349	A. radioresistens 108289, DSM 108289
169350	A. radioresistens 108290, DSM 108290
169351	A. radioresistens 108291, DSM 108291
169352	A. radioresistens 108292, DSM 108292
169354	A. radioresistens 108294, DSM 108294
169355	A. radioresistens 108295, DSM 108295
169356	A. radioresistens 108296, DSM 108296
169357	A. radioresistens 22290, 108297, DSM 108297
169358	A. radioresistens 108349, DSM 108349
169359	A. radioresistens 108719, DSM 108719
169360	A. radioresistens 108820, DSM 108820
169361	A. radioresistens 109999, DSM 109999
169362	A. radioresistens 112286, DSM 112286
169363	A. radioresistens 112285, DSM 112285
173525	A. radioresistens CM38.2, CIP 111668
173526	A. radioresistens CM38.1, CIP 111749
174835	A. radioresistens 115027, DSM 115027
174836	A. radioresistens Dres_AcRes_20, DSM 113703
174837	A. radioresistens Dres_AcRes_18, DSM 110647
174838	A. radioresistens Dres_AcRes_19, DSM 110746
174839	A. radioresistens 115092, DSM 115092

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	98.667

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
68624	TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92)		Medium recipe at MediaDive	Name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Yeast extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
68624	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	97.882

Spore formation

@ref	Spore formation	Confidence
125438		95.293
125439		97.78

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
68624	swab	Dresden	Germany	DEU	Europe

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
68624	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score
66792	ASM2313055v1 assembly for Acinetobacter radioresistens DSM 108293	contig	GCA_023130555	40216.128	40216	59.31

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM2313055v1 assembly for Acinetobacter radioresistens DSM 108293
NCBI: GCA_023130555

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	97.78	no
125439	motility	BacteriaNetⓘ	no	60.81	no
125439	gram_stain	BacteriaNetⓘ	negative	86.85	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	97.88	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Acinetobacter radioresistens DSM 108293
NCBI: GCA_023130555.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.67	no
125438	anaerobic	anaerobicⓘ	no	95.70	no
125438	aerobic	aerobicⓘ	yes	88.09	no
125438	spore-forming	spore-formingⓘ	no	95.29	no
125438	thermophilic	thermophileⓘ	no	98.48	no
125438	flagellated	motile2+ⓘ	no	79.75	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Comparative Study of Different Diagnostic Routine Methods for the Identification of Acinetobacter radioresistens.	Bigge R, Bunk B, Rudolph WW, Gunzer F, Coldewey SM, Riedel T, Schrottner P.	Microorganisms	10.3390/microorganisms10091767	2022

References

#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) .
#68624	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 108293
#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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Acinetobacter radioresistens (DSM 108293, 108293)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Isolation, sampling and environmental information

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_023130555

Genome-based predictions

Predictions

Literature

Literature

References

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