Acetivibrio alkalicellulosi (DSM 17461, VKM B-2349, Z-7026)

Name: Acetivibrio alkalicellulosi (DSM 17461, VKM B-2349, Z-7026)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 2838

Type strain

Strain Designation Z-7026

Culture col. no. DSM 17461 VKM B-2349 Z-7026

NCBI tax ID(s) 1002220 320502

Special Collections DSMZ

History <- T. N. Zhilina, Winogradsky Inst. Microbiol., RAS, Moscow, Russia; Z-7026 (Clostridium alkalicellum)

Links

Acetivibrio alkalicellulosi Z-7026 is an anaerobe bacterium that was isolated from deposits of soda lake.

anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 291125

DSM 17461,VKM B-2349

@ref 20215

Last LPSN update 2026-02-09 11:18:22

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Oscillospiraceae

Genus Acetivibrio

Species Acetivibrio alkalicellulosi

Full scientific name Acetivibrio alkalicellulosi (Zhilina et al. 2006) Tindall 2019

Synonyms (3)

Clostridium alkalicellulosi
Clostridium alkalicellum
Hungateiclostridium alkalicellulosi

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
7000	ACETIVIBRIO ALKALICELLULOSI MEDIUM (DSMZ Medium 1036)		Medium recipe at MediaDive	Name: ACETIVIBRIO ALKALICELLULOSI MEDIUM (DSMZ Medium 1036) Composition: NaCl 9.98004 g/l NaHCO3 7.58483 g/l Cellobiose 2.99401 g/l Na2CO3 0.998004 g/l Na2S x 9 H2O 0.499002 g/l NH4Cl 0.499002 g/l KH2PO4 0.199601 g/l KCl 0.199601 g/l Yeast extract 0.199601 g/l MgCl2 x 6 H2O 0.0998004 g/l HCl 0.00249501 g/l FeCl2 x 4 H2O 0.00149701 g/l NaOH 0.000499002 g/l CoCl2 x 6 H2O 0.000189621 g/l MnCl2 x 4 H2O 9.98004e-05 g/l ZnCl2 6.98603e-05 g/l Na2MoO4 x 2 H2O 3.59281e-05 g/l NiCl2 x 6 H2O 2.39521e-05 g/l H3BO3 5.98802e-06 g/l Na2WO4 x 2 H2O 3.99202e-06 g/l Na2SeO3 x 5 H2O 2.99401e-06 g/l CuCl2 x 2 H2O 1.99601e-06 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
7000	positive	growth	35

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
7000	anaerobe
125438	anaerobe	93.702
125439	anaerobe	92.1

Compound production

7000

Compoundcellulase

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Waste	#Solid waste
#Environmental	#Aquatic	#Lake (large)
#Condition	#Alkaline	-

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
7000	deposits of soda lake	Buryatiya, Beloe soda lake	Russia	RUS	Asia

Taxonmaps

69479

Global distribution of 16S sequence AY959944 (>99% sequence identity) for Acetivibrio alkalicellulosi subclade from Microbeatlas

Aquatic Samples	34
Soil Samples	31
Animal Samples	21
Plant Samples	6
Total Samples	92

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
7000	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM812507v1 assembly for Acetivibrio alkalicellulosi DSM 17461	scaffold	GCA_008125075	320502.3	2509887034	320502	37.3

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
7000	Clostridium alkalicellum 16S ribosomal RNA gene, partial sequence	AY959944	1489		320502

GC content

@ref	GC-content (mol%)	Method
7000	30	thermal denaturation, midpoint method (Tm)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Acetivibrio alkalicellulosi DSM 17461
NCBI: GCA_008125075

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	73.70	no
125439	motility	BacteriaNetⓘ	yes	63.10	no
125439	gram_stain	BacteriaNetⓘ	positive	84.60	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	92.10	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Acetivibrio alkalicellulosi DSM 17461
NCBI: GCA_008125075.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	58.33	no
125438	anaerobic	anaerobicⓘ	yes	93.70	yes
125438	aerobic	aerobicⓘ	no	96.96	no
125438	spore-forming	spore-formingⓘ	yes	75.83	no
125438	thermophilic	thermophileⓘ	no	75.20	no
125438	flagellated	motile2+ⓘ	yes	83.95	no

Literature

References

#7000	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 17461
#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 .
#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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