Acetoanaerobium sticklandii (DSM 519, ATCC 12662, CCUG 9281)

Name: Acetoanaerobium sticklandii (DSM 519, ATCC 12662, CCUG 9281)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 2717

Type strain

Strain Designation HF

Culture col. no. DSM 519 ATCC 12662 CCUG 9281 JCM 1433 NCIMB 10654 2 more

NCBI tax ID(s) 499177 1511

Special Collections DSMZ CCUG JCM Literature strains

History <- A. C. Schwartz, Univ. Bonn, Germany; HF <- T. C. Stadtman, National Institute of Health, Bethesda, Md., USA ATCC 12662 <-- A. C. Schwartz <-- T. C. Stadtman.

Links

Acetoanaerobium sticklandii HF is an anaerobe bacterium that was isolated from black mud.

anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 35630

ATCC 12662,CCUG 9281,DSM 519,NCIB 10654,JCM 1433,CCRC 14485,NCIMB 10654,BCRC 14485

@ref 20215

Last LPSN update 2026-02-09 11:18:20

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Peptostreptococcales

Family Peptostreptococcaceae

Genus Acetoanaerobium

Species Acetoanaerobium sticklandii

Full scientific name Acetoanaerobium sticklandii (Stadtman and McClung 1957) Galperin et al. 2016

Synonyms (1)

Clostridium sticklandii

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
263	ACETOANAEROBIUM MEDIUM (DSMZ Medium 38)		Medium recipe at MediaDive	Name: ACETOANAEROBIUM MEDIUM (DSMZ Medium 38) Composition: Tryptone 20.0 g/l Yeast extract 10.0 g/l K2HPO4 1.04 g/l KH2PO4 0.68 g/l Na2S x 9 H2O 0.15 g/l Sodium resazurin 0.0005 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
263	positive	growth	35
67770	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
263	anaerobe
125439	anaerobe	94.8

Compound production

263

Compoundglycine reductase

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	formaldehyde oxidation	100	3 of 3
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	kanosamine biosynthesis II	100	2 of 2
66794	C4 and CAM-carbon fixation	100	8 of 8
66794	aminopropanol phosphate biosynthesis	100	2 of 2
66794	reductive acetyl coenzyme A pathway	100	7 of 7
66794	adipate degradation	100	2 of 2
66794	coenzyme A metabolism	100	4 of 4
66794	suberin monomers biosynthesis	100	2 of 2
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	ppGpp biosynthesis	100	4 of 4
66794	aspartate and asparagine metabolism	100	9 of 9
66794	folate polyglutamylation	100	1 of 1
66794	palmitate biosynthesis	95.45	21 of 22
66794	vitamin B1 metabolism	92.31	12 of 13
66794	starch degradation	90	9 of 10
66794	threonine metabolism	90	9 of 10
66794	chorismate metabolism	88.89	8 of 9
66794	vitamin B12 metabolism	88.24	30 of 34
66794	isoleucine metabolism	87.5	7 of 8
66794	gluconeogenesis	87.5	7 of 8
66794	phenylalanine metabolism	84.62	11 of 13
66794	glycogen metabolism	80	4 of 5
66794	lipoate biosynthesis	80	4 of 5
66794	cellulose degradation	80	4 of 5
66794	peptidoglycan biosynthesis	80	12 of 15
66794	photosynthesis	78.57	11 of 14
66794	valine metabolism	77.78	7 of 9
66794	serine metabolism	77.78	7 of 9
66794	NAD metabolism	77.78	14 of 18
66794	butanoate fermentation	75	3 of 4
66794	acetate fermentation	75	3 of 4
66794	glycogen biosynthesis	75	3 of 4
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	75	6 of 8
66794	biotin biosynthesis	75	3 of 4
66794	sulfopterin metabolism	75	3 of 4
66794	flavin biosynthesis	73.33	11 of 15
66794	histidine metabolism	72.41	21 of 29
66794	purine metabolism	72.34	68 of 94
66794	propanol degradation	71.43	5 of 7
66794	glutamate and glutamine metabolism	71.43	20 of 28
66794	heme metabolism	71.43	10 of 14
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	glycolysis	70.59	12 of 17
66794	methionine metabolism	69.23	18 of 26
66794	urea cycle	69.23	9 of 13
66794	pyrimidine metabolism	68.89	31 of 45
66794	molybdenum cofactor biosynthesis	66.67	6 of 9
66794	CO2 fixation in Crenarchaeota	66.67	6 of 9
66794	cysteine metabolism	66.67	12 of 18
66794	L-lactaldehyde degradation	66.67	2 of 3
66794	d-mannose degradation	66.67	6 of 9
66794	selenocysteine biosynthesis	66.67	4 of 6
66794	acetoin degradation	66.67	2 of 3
66794	octane oxidation	66.67	2 of 3
66794	isoprenoid biosynthesis	65.38	17 of 26
66794	tetrahydrofolate metabolism	64.29	9 of 14
66794	oxidative phosphorylation	63.74	58 of 91
66794	degradation of sugar alcohols	62.5	10 of 16
66794	arginine metabolism	62.5	15 of 24
66794	alanine metabolism	62.07	18 of 29
66794	leucine metabolism	61.54	8 of 13
66794	tryptophan metabolism	60.53	23 of 38
66794	glycine betaine biosynthesis	60	3 of 5
66794	metabolism of amino sugars and derivatives	60	3 of 5
66794	hydrogen production	60	3 of 5
66794	methylglyoxal degradation	60	3 of 5
66794	propionate fermentation	60	6 of 10
66794	citric acid cycle	57.14	8 of 14
66794	ubiquinone biosynthesis	57.14	4 of 7
66794	lysine metabolism	54.76	23 of 42
66794	proline metabolism	54.55	6 of 11
66794	non-pathway related	52.63	20 of 38
66794	ribulose monophosphate pathway	50	1 of 2
66794	glycine metabolism	50	5 of 10
66794	ethanol fermentation	50	1 of 2
66794	cis-vaccenate biosynthesis	50	1 of 2
66794	ketogluconate metabolism	50	4 of 8
66794	myo-inositol biosynthesis	50	5 of 10
66794	phenylmercury acetate degradation	50	1 of 2
66794	lipid metabolism	48.39	15 of 31
66794	pentose phosphate pathway	45.45	5 of 11
66794	lipid A biosynthesis	44.44	4 of 9
66794	degradation of hexoses	44.44	8 of 18
66794	nitrate assimilation	44.44	4 of 9
66794	polyamine pathway	43.48	10 of 23
66794	tyrosine metabolism	42.86	6 of 14
66794	degradation of aromatic, nitrogen containing compounds	41.67	5 of 12
66794	Entner Doudoroff pathway	40	4 of 10
66794	sulfate reduction	38.46	5 of 13
66794	metabolism of disaccharids	36.36	4 of 11
66794	vitamin B6 metabolism	36.36	4 of 11
66794	degradation of pentoses	35.71	10 of 28
66794	IAA biosynthesis	33.33	1 of 3
66794	glycolate and glyoxylate degradation	33.33	2 of 6
66794	acetyl CoA biosynthesis	33.33	1 of 3
66794	coenzyme M biosynthesis	30	3 of 10
66794	glutathione metabolism	28.57	4 of 14
66794	benzoyl-CoA degradation	28.57	2 of 7
66794	ascorbate metabolism	27.27	6 of 22
66794	dTDPLrhamnose biosynthesis	25	2 of 8
66794	cyclohexanol degradation	25	1 of 4
66794	lactate fermentation	25	1 of 4
66794	vitamin E metabolism	25	1 of 4
66794	CMP-KDO biosynthesis	25	1 of 4
66794	toluene degradation	25	1 of 4
66794	4-hydroxymandelate degradation	22.22	2 of 9

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Mud (Sludge)

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
25060	black mud	east shore of San Francisco Bay	USA	USA	North America
263	mud water	east shore of San Francisco Bay	USA	USA	North America
67770	Mud water

Taxonmaps

69479

Global distribution of 16S sequence LC053841 (>99% sequence identity) for Acetoanaerobium sticklandii from Microbeatlas

Aquatic Samples	13161
Soil Samples	1323
Animal Samples	6000
Plant Samples	370
Total Samples	20854

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
263	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	ASM19645v1 assembly for Acetoanaerobium sticklandii DSM 519	complete	GCA_000196455	499177.3	649633033	1511	95.28

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	[Clostridium] sticklandii gene for 16S ribosomal RNA, partial sequence, strain: JCM 1433	LC053841	1388		1511
67770	C.sticklandii small subunit ribosomal RNA	M26494	1476		1511

GC content

@ref	GC-content (mol%)
25060	33.3
263	31.0
67770	31

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Clostridium sticklandii DSM 519
PATRIC: 499177.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	54.80	no
125439	motility	BacteriaNetⓘ	yes	66.80	no
125439	gram_stain	BacteriaNetⓘ	positive	74.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	94.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Clostridium sticklandii DSM 519
PATRIC: 499177.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	62.02	no
125438	anaerobic	anaerobicⓘ	yes	84.10	no
125438	spore-forming	spore-formingⓘ	yes	60.43	no
125438	aerobic	aerobicⓘ	no	92.27	no
125438	thermophilic	thermophileⓘ	no	88.24	yes
125438	flagellated	motile2+ⓘ	yes	80.81	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Identification of a novel 5-aminomethyl-2-thiouridine methyltransferase in tRNA modification.	Cho G, Lee J, Kim J.	Nucleic Acids Res	10.1093/nar/gkad048	2023
	Energy conservation under extreme energy limitation: the role of cytochromes and quinones in acetogenic bacteria.	Rosenbaum FP, Muller V.	Extremophiles	10.1007/s00792-021-01241-0	2021
Metabolism	The Sporomusa type Nfn is a novel type of electron-bifurcating transhydrogenase that links the redox pools in acetogenic bacteria.	Kremp F, Roth J, Muller V.	Sci Rep	10.1038/s41598-020-71038-2	2020
Metabolism	Distribution and preservation of the components of the engulfment. What is beyond representative genomes?	Soto-Avila L, Merce RC, Santos W, Castaneda N, Gutierrez-Rios RM.	PLoS One	10.1371/journal.pone.0246651	2021
Genetics	Comparative genomic analysis of hyper-ammonia producing Acetoanaerobium sticklandii DSM 519 with purinolytic Gottschalkia acidurici 9a and pathogenic Peptoclostridium difficile 630.	Sangavai C, Chellapandi P	Genomics	10.1016/j.ygeno.2021.11.010	2021
Metabolism	Growth-associated catabolic potential of Acetoanaerobium sticklandii DSM 519 on gelatin and amino acids.	Sangavai C, Chellapandi P	J Basic Microbiol	10.1002/jobm.202000292	2020
Metabolism	A metabolic study to decipher amino acid catabolism-directed biofuel synthesis in Acetoanaerobium sticklandii DSM 519.	Sangavai C, Chellapandi P	Amino Acids	10.1007/s00726-019-02777-4	2019
Genetics	Functional prediction, characterization, and categorization of operome from Acetoanaerobium sticklandii DSM 519.	Sangavai C, Prathiviraj R, Chellapandi P	Anaerobe	10.1016/j.anaerobe.2019.102088	2019
Phylogeny	Acetoanaerobium pronyense sp. nov., an anaerobic alkaliphilic bacterium isolated from a carbonate chimney of the Prony Hydrothermal Field (New Caledonia).	Bes M, Merrouch M, Joseph M, Quemeneur M, Payri C, Pelletier B, Ollivier B, Fardeau ML, Erauso G, Postec A	Int J Syst Evol Microbiol	10.1099/ijs.0.000307	2015

References

#263	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 519
#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 )
#25060	M. Y. B. Galperin, V.,Tolstoy, I.,Yutin, N.: Phylogenomic analysis of the family Peptostreptococcaceae (Clostridium cluster XI) and proposal for reclassification of Clostridium litorale (Fendrich et al. 1991) and Eubacterium acidaminophilum (Zindel et al. 1989) as Peptoclostridium litorale gen. nov. comb. nov. and Peptoclostridium acidaminophilum comb. nov. IJSEM 66: 5506 - 5513 2016 ( DOI 10.1099/ijsem.0.001548 , PubMed 27902180 )
#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) .
#66794	Antje Chang, Lisa Jeske, Sandra Ulbrich, Julia Hofmann, Julia Koblitz, Ida Schomburg, Meina Neumann-Schaal, Dieter Jahn, Dietmar Schomburg: BRENDA, the ELIXIR core data resource in 2021: new developments and updates. Nucleic Acids Res. 49: D498 - D508 2020 ( DOI 10.1093/nar/gkaa1025 , PubMed 33211880 )
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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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Acetoanaerobium sticklandii (DSM 519, ATCC 12662, CCUG 9281)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Compound production

Pathway annotation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_000196455

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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