Acidianus brierleyi (DSM 1651, IFO 15269, NBRC 15269)

Name: Acidianus brierleyi (DSM 1651, IFO 15269, NBRC 15269)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 16640

Type strain

Culture col. no. DSM 1651 IFO 15269 NBRC 15269

NCBI tax ID(s) 41673

Special Collections DSMZ

Links

Acidianus brierleyi DSM 1651 is a thermophilic prokaryote that was isolated from thermal spring drainage.

thermophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 47466

DSM 1651,IFO 15269,JCM 8954,NBRC 15269

@ref 20215

Last LPSN update 2025-12-16 09:50:53

Domain Thermoproteati

Phylum Thermoproteota

Class Thermoprotei

Order Sulfolobales

Family Sulfolobaceae

Genus Acidianus

Species Acidianus brierleyi

Full scientific name Acidianus brierleyi (Zillig et al. 1980) Segerer et al. 1986

Synonyms (1)

Sulfolobus brierleyi

BacDive ID	Other strains from **Acidianus brierleyi** (1)	Type strain
16641	A. brierleyi Sp3a/1, DSM 6334

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	96.4

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
614	ACIDIANUS BRIERLEYI MEDIUM (DSMZ Medium 150)		Medium recipe at MediaDive	Name: ACIDIANUS BRIERLEYI MEDIUM (DSMZ Medium 150) Composition: Sulfur 10.0 g/l (NH4)2SO4 3.0 g/l MgSO4 x 7 H2O 0.5 g/l K2HPO4 x 3 H2O 0.5 g/l Yeast extract 0.2 g/l KCl 0.1 g/l Ca(NO3)2 x 4 H2O 0.02 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
614	positive	growth	70	thermophilic

Physiology and metabolism

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	ribulose monophosphate pathway	100	2 of 2
66794	acetate fermentation	100	4 of 4
66794	starch degradation	100	10 of 10
66794	adipate degradation	100	2 of 2
66794	ethanol fermentation	100	2 of 2
66794	valine metabolism	100	9 of 9
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	suberin monomers biosynthesis	100	2 of 2
66794	flavin biosynthesis	93.33	14 of 15
66794	Entner Doudoroff pathway	90	9 of 10
66794	molybdenum cofactor biosynthesis	88.89	8 of 9
66794	CO2 fixation in Crenarchaeota	88.89	8 of 9
66794	chorismate metabolism	88.89	8 of 9
66794	palmitate biosynthesis	86.36	19 of 22
66794	propanol degradation	85.71	6 of 7
66794	citric acid cycle	85.71	12 of 14
66794	ubiquinone biosynthesis	85.71	6 of 7
66794	leucine metabolism	84.62	11 of 13
66794	vitamin B1 metabolism	84.62	11 of 13
66794	pyrimidine metabolism	82.22	37 of 45
66794	cellulose degradation	80	4 of 5
66794	threonine metabolism	80	8 of 10
66794	methylglyoxal degradation	80	4 of 5
66794	ethylmalonyl-CoA pathway	80	4 of 5
66794	propionate fermentation	80	8 of 10
66794	phenylacetate degradation (aerobic)	80	4 of 5
66794	vitamin B12 metabolism	79.41	27 of 34
66794	alanine metabolism	79.31	23 of 29
66794	photosynthesis	78.57	11 of 14
66794	glutamate and glutamine metabolism	78.57	22 of 28
66794	serine metabolism	77.78	7 of 9
66794	phenylalanine metabolism	76.92	10 of 13
66794	glycogen biosynthesis	75	3 of 4
66794	C4 and CAM-carbon fixation	75	6 of 8
66794	coenzyme A metabolism	75	3 of 4
66794	CMP-KDO biosynthesis	75	3 of 4
66794	butanoate fermentation	75	3 of 4
66794	pentose phosphate pathway	72.73	8 of 11
66794	purine metabolism	71.28	67 of 94
66794	methionine metabolism	69.23	18 of 26
66794	L-lactaldehyde degradation	66.67	2 of 3
66794	NAD metabolism	66.67	12 of 18
66794	formaldehyde oxidation	66.67	2 of 3
66794	cyanate degradation	66.67	2 of 3
66794	d-mannose degradation	66.67	6 of 9
66794	enterobactin biosynthesis	66.67	2 of 3
66794	aspartate and asparagine metabolism	66.67	6 of 9
66794	octane oxidation	66.67	2 of 3
66794	acetoin degradation	66.67	2 of 3
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	62.5	5 of 8
66794	isoleucine metabolism	62.5	5 of 8
66794	gluconeogenesis	62.5	5 of 8
66794	lipid metabolism	61.29	19 of 31
66794	polyamine pathway	60.87	14 of 23
66794	lipoate biosynthesis	60	3 of 5
66794	creatinine degradation	60	3 of 5
66794	hydrogen production	60	3 of 5
66794	glycogen metabolism	60	3 of 5
66794	glycolysis	58.82	10 of 17
66794	degradation of aromatic, nitrogen containing compounds	58.33	7 of 12
66794	arginine metabolism	58.33	14 of 24
66794	non-pathway related	57.89	22 of 38
66794	tryptophan metabolism	57.89	22 of 38
66794	isoprenoid biosynthesis	57.69	15 of 26
66794	heme metabolism	57.14	8 of 14
66794	mevalonate metabolism	57.14	4 of 7
66794	reductive acetyl coenzyme A pathway	57.14	4 of 7
66794	glutathione metabolism	57.14	8 of 14
66794	oxidative phosphorylation	54.95	50 of 91
66794	lysine metabolism	54.76	23 of 42
66794	proline metabolism	54.55	6 of 11
66794	carotenoid biosynthesis	54.55	12 of 22
66794	d-xylose degradation	54.55	6 of 11
66794	sulfate reduction	53.85	7 of 13
66794	urea cycle	53.85	7 of 13
66794	degradation of sugar acids	52	13 of 25
66794	resorcinol degradation	50	1 of 2
66794	dolichol and dolichyl phosphate biosynthesis	50	1 of 2
66794	CDP-diacylglycerol biosynthesis	50	1 of 2
66794	coenzyme M biosynthesis	50	5 of 10
66794	cis-vaccenate biosynthesis	50	1 of 2
66794	sulfopterin metabolism	50	2 of 4
66794	pantothenate biosynthesis	50	3 of 6
66794	selenocysteine biosynthesis	50	3 of 6
66794	aminopropanol phosphate biosynthesis	50	1 of 2
66794	ketogluconate metabolism	50	4 of 8
66794	glycolate and glyoxylate degradation	50	3 of 6
66794	phenylmercury acetate degradation	50	1 of 2
66794	cysteine metabolism	50	9 of 18
66794	dTDPLrhamnose biosynthesis	50	4 of 8
66794	biotin biosynthesis	50	2 of 4
66794	glycine metabolism	50	5 of 10
66794	histidine metabolism	48.28	14 of 29
66794	degradation of pentoses	46.43	13 of 28
66794	metabolism of disaccharids	45.45	5 of 11
66794	dolichyl-diphosphooligosaccharide biosynthesis	45.45	5 of 11
66794	nitrate assimilation	44.44	4 of 9
66794	degradation of sugar alcohols	43.75	7 of 16
66794	tyrosine metabolism	42.86	6 of 14
66794	tetrahydrofolate metabolism	42.86	6 of 14
66794	3-phenylpropionate degradation	40	6 of 15
66794	peptidoglycan biosynthesis	40	6 of 15
66794	gallate degradation	40	2 of 5
66794	3-chlorocatechol degradation	40	2 of 5
66794	degradation of hexoses	38.89	7 of 18
66794	vitamin B6 metabolism	36.36	4 of 11
66794	acetyl CoA biosynthesis	33.33	1 of 3
66794	lipid A biosynthesis	33.33	3 of 9
66794	IAA biosynthesis	33.33	1 of 3
66794	methanogenesis from CO2	33.33	4 of 12
66794	4-hydroxymandelate degradation	33.33	3 of 9
66794	ascorbate metabolism	31.82	7 of 22
66794	4-hydroxyphenylacetate degradation	30	3 of 10
66794	phenol degradation	30	6 of 20
66794	myo-inositol biosynthesis	30	3 of 10
66794	cardiolipin biosynthesis	28.57	2 of 7
66794	vitamin E metabolism	25	1 of 4
66794	lactate fermentation	25	1 of 4
66794	toluene degradation	25	1 of 4
66794	ppGpp biosynthesis	25	1 of 4
66794	cyclohexanol degradation	25	1 of 4

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Thermal spring

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
614	thermal spring drainage	Wyoming, Yellowstone Natl. Park	USA	USA	North America

Taxonmaps

69479

Global distribution of 16S sequence X90477 (>99% sequence identity) for Acidianus brierleyi subclade from Microbeatlas

Aquatic Samples	12
Soil Samples
Animal Samples
Plant Samples
Total Samples	12

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
614	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	BV-BRC accession	NCBI tax ID	Score
66792	Acidianus brierleyi strain DSM 1651	complete	41673.4	41673	97.8
66792	ASM320183v2 assembly for Acidianus brierleyi DSM 1651	complete	41673.10	41673	93.13

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	A.brierleyi DNA for 16S ribosomal RNA gene	X90477	1460		41673
614	Acidianus brierleyi 16S rRNA gene complete sequence and 23S rRNA gene 5' region	D26489	2582		41673

GC content

614

GC-content (mol%)31.0

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Acidianus brierleyi strain DSM 1651
PATRIC: 41673.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	74.10	no
125439	motility	BacteriaNetⓘ	no	60.30	no
125439	gram_stain	BacteriaNetⓘ	negative	96.40	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	69.10	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Acidianus brierleyi DSM 1651
NCBI: GCA_003201835.2

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	74.55	no
125438	anaerobic	anaerobicⓘ	yes	68.02	no
125438	aerobic	aerobicⓘ	no	68.66	no
125438	spore-forming	spore-formingⓘ	no	85.14	no
125438	thermophilic	thermophileⓘ	yes	79.79	no
125438	flagellated	motile2+ⓘ	no	89.00	no

Literature

Title	Authors	Journal	DOI	Year
Complete Genome Sequences of Extremely Thermoacidophilic Metal-Mobilizing Type Strain Members of the Archaeal Family Sulfolobaceae, Acidianus brierleyi DSM-1651, Acidianus sulfidivorans DSM-18786, and Metallosphaera hakonensis DSM-7519.	Counts JA, Vitko NP, Kelly RM.	Microbiol Resour Announc	10.1128/mra.00831-18	2018
Phenotype-driven assessment of the ancestral trajectory of sulfur biooxidation in the thermoacidophilic archaea Sulfolobaceae.	Willard DJ, H Manesh MJ, Bing RG, Alexander BH, Kelly RM.	mBio	10.1128/mbio.01033-24	2024
New virus isolates from Italian hydrothermal environments underscore the biogeographic pattern in archaeal virus communities.	Baquero DP, Contursi P, Piochi M, Bartolucci S, Liu Y, Cvirkaite-Krupovic V, Prangishvili D, Krupovic M.	ISME J	10.1038/s41396-020-0653-z	2020
Enzymes Catalyzing Crotonyl-CoA Conversion to Acetoacetyl-CoA During the Autotrophic CO₂ Fixation in Metallosphaera sedula.	Liu L, Huber H, Berg IA.	Front Microbiol	10.3389/fmicb.2020.00354	2020
Ca²⁺ in Hybridization Solutions for Fluorescence in situ Hybridization Facilitates the Detection of Enterobacteriaceae.	Haruta S, Iino T, Ohkuma M, Suzuki KI, Igarashi Y.	Microbes Environ	10.1264/jsme2.me16186	2017
Isolation and Characterization of Metallosphaera Turreted Icosahedral Virus, a Founding Member of a New Family of Archaeal Viruses.	Wagner C, Reddy V, Asturias F, Khoshouei M, Johnson JE, Manrique P, Munson-McGee J, Baumeister W, Lawrence CM, Young MJ.	J Virol	10.1128/jvi.00925-17	2017
Pyrite oxidation by thermophilic archaebacteria.	Larsson L, Olsson G, Holst O, Karlsson HT.	Appl Environ Microbiol	10.1128/aem.56.3.697-701.1990	1990
Characterization of a bifunctional archaeal acyl coenzyme A carboxylase.	Chuakrut S, Arai H, Ishii M, Igarashi Y.	J Bacteriol	10.1128/jb.185.3.938-947.2003	2003
New insight into RNase P RNA structure from comparative analysis of the archaeal RNA.	Harris JK, Haas ES, Williams D, Frank DN, Brown JW.	RNA	10.1017/s1355838201001777	2001

References

#614	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 1651
#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 )
#20218	Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.: StrainInfo introduces electronic passports for microorganisms.. Syst Appl Microbiol. 37: 42 - 50 2014 ( DOI 10.1016/j.syapm.2013.11.002 , PubMed 24321274 )
#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 )
#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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Acidianus brierleyi (DSM 1651, IFO 15269, NBRC 15269)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Pathway annotation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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