Achromobacter deleyi (LMG 3458, CCUG 62433)

Name: Achromobacter deleyi (LMG 3458, CCUG 62433)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 140506

Type strain

Culture col. no. LMG 3458 CCUG 62433

NCBI tax ID(s) 1353891

Special Collections CCUG Literature strains

Links

Achromobacter deleyi LMG 3458 is an aerobe, mesophilic, Gram-negative prokaryote that was isolated from lung autopsy sample from mouse.

Gram-negative motile rod-shaped aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 823

LMG 3458,CCUG 62433

@ref 20215

Last LPSN update 2025-12-16 10:03:36

Domain Pseudomonadati

Phylum Pseudomonadota

Class Betaproteobacteria

Order Burkholderiales

Family Alcaligenaceae

Genus Achromobacter

Species Achromobacter deleyi

Full scientific name Achromobacter deleyi Vandamme et al. 2016

BacDive ID	Other strains from **Achromobacter deleyi** (1)	Type strain
303	A. deleyi DSM 26072, CCUG 48135

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Motility	Confidence
43168	negative	0.9-2.0 µm	0.4-0.7 µm	rod-shaped
125438	negative					97.55

Colony morphology

@ref	Colony size	Colony color	Incubation period	Medium used
43168	1-1.5 mm	non-pigmented	2 days	trypticase soy agar (TSA)
62841			1 day

Culture and growth conditions

Culture medium

@ref	Name	Growth
43168	trypticase soy agar (TSA)
43168	Drigalsky agar
43168	blood agar
43168	cetrimide agar

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
43168	positive	growth	37	mesophilic
43168	positive	growth	30	mesophilic
62841	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance
43168	aerobe
62841	aerobe

Halophily

@ref	Salt	Growth	Tested relation	Concentration
43168	NaCl	positive	growth	3 %
43168	NaCl	positive	growth	4.5 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
43168	16004 ChEBI	(R)-lactate	+	assimilation
43168	27856 ChEBI	acetamide	+	growth
43168	17128 ChEBI	adipate	+	assimilation
43168	16947 ChEBI	citrate	+	assimilation
43168	8391 ChEBI	D-gluconate	+	assimilation
43168	16899 ChEBI	D-mannitol	-	assimilation
43168	16024 ChEBI	D-mannose	-	assimilation
43168	27689 ChEBI	decanoate	+	assimilation
43168	4853 ChEBI	esculin	-	hydrolysis
43168	5291 ChEBI	gelatin	-	hydrolysis
43168	17234 ChEBI	glucose	-	assimilation
43168	30849 ChEBI	L-arabinose	-	assimilation
43168	16467 ChEBI	L-arginine	-	assimilation
43168	15589 ChEBI	L-malate	+	assimilation
43168	17306 ChEBI	maltose	-	assimilation
43168	506227 ChEBI	N-acetylglucosamine	-	assimilation
43168	17632 ChEBI	nitrate	+	reduction
43168	16301 ChEBI	nitrite	-	reduction
43168	36405 ChEBI	norleucine	-	assimilation
43168	18401 ChEBI	phenylacetate	+	assimilation
43168	17992 ChEBI	sucrose	-	assimilation
43168	27082 ChEBI	trehalose	-	assimilation
43168	53426 ChEBI	tween 80	-	hydrolysis

Metabolite production

@ref	Chebi-ID	Metabolite	Production
43168	16136 ChEBI	hydrogen sulfide
43168	35581 ChEBI	indole

Enzymes

@ref	Value	Activity	Ec
43168	acid phosphatase	+	3.1.3.2
43168	alkaline phosphatase	+	3.1.3.1
43168	alpha-fucosidase	-	3.2.1.51
43168	alpha-galactosidase	-	3.2.1.22
43168	alpha-glucosidase	-	3.2.1.20
43168	alpha-mannosidase	-	3.2.1.24
43168	amylase	-
43168	arginine dihydrolase	-	3.5.3.6
43168	beta-galactosidase	-	3.2.1.23
43168	beta-glucosidase	-	3.2.1.21
43168	beta-glucuronidase	-	3.2.1.31
43168	catalase	+	1.11.1.6
43168	chymotrypsin	-	3.4.4.5
43168	cystine arylamidase	-	3.4.11.3
43168	cytochrome oxidase	+	1.9.3.1
43168	DNase	-
43168	esterase (C 4)	+
43168	esterase Lipase (C 8)	-
43168	leucine arylamidase	+	3.4.11.1
43168	lipase (C 14)	-
43168	lysine decarboxylase	-	4.1.1.18
43168	N-acetyl-beta-glucosaminidase	-	3.2.1.52
43168	ornithine decarboxylase	-	4.1.1.17
43168	phosphoamidase	+	3.9.1.1
43168	trypsin	-	3.4.21.4
43168	tryptophanase	-	4.1.99.1
43168	urease	-	3.5.1.5
43168	valine arylamidase	-

Fatty acid profile

Metadata FA analysis

@ref

43168

Fatty acid	Percentage	SD
C16:0	31.74	2.1
C15:0 iso 2OH / C16:1ω7c	23.97	4.58
C17:0 cyclo	12.4	4.52
C16:1 iso I / C14:0 3OH	11.43	2.5
C18:1ω7c	7.33	1.56
C12:0 2OH	4.09	0.97
C14:0 2OH	2.76	1.53
C14:0	2.53	1.21
C18:0	1.48	0.13

Metadata FA analysis

@ref

62841

Fatty acid	Percentage	ECL
C16:0	29.9	16
C17:0 CYCLO	24.9	16.888
C16:1 ω7c	15.5	15.819
C14:0 3OH/C16:1 ISO I	10.4	15.485
C14:0 2OH	5.1	15.205
C12:0 2OH	4.5	13.178
C18:1 ω7c /12t/9t	4.4	17.824
C14:0	1.5	14
C18:1 DMA 17.252	1.4	17.252
Unidentified	1.4	16.298
C18:0	0.6	18
C12:0	0.5	12

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Mammals	#Muridae (Mouse/Rat)
#Host Body-Site	#Oral cavity and airways	#Lung

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
43168	lung autopsy sample from mouse	Denmark	DNK	Europe
62841	Mouse, lung autopsy sample	Denmark	DNK	Europe

Taxonmaps

69479

Global distribution of 16S sequence HG324053 (>99% sequence identity) for Achromobacter from Microbeatlas

Aquatic Samples	1212
Soil Samples	1429
Animal Samples	2896
Plant Samples	1751
Total Samples	7288

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	LMG 3458 assembly for Achromobacter deleyi LMG 3458	contig	GCA_902859705	1353891.6	8112221806	1353891	64.08

16S sequences

@ref	Description	Accession	Length	NCBI tax ID
43168	Achromobacter deleyi partial 16S rRNA gene, strain LMG 3458	HG324053	1483	1353891
124043	Achromobacter deleyi strain LMG 3458 16S ribosomal RNA gene, partial sequence.	MT974313	643	1353891
124043	Achromobacter deleyi strain LMG 3458 16S ribosomal RNA gene, partial sequence.	PV263177	1329	1353891

GC content

@ref	GC-content (mol%)	Method
43168	66.8	high performance liquid chromatography (HPLC)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Achromobacter deleyi LMG 3458
NCBI: GCA_902859705

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	74.40	no
125439	motility	BacteriaNetⓘ	no	59.60	no
125439	gram_stain	BacteriaNetⓘ	positive	85.00	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	88.40	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Achromobacter deleyi strain LMG 3458
PATRIC: 1353891.6

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.55	yes
125438	anaerobic	anaerobicⓘ	no	98.24	no
125438	spore-forming	spore-formingⓘ	no	89.09	no
125438	aerobic	aerobicⓘ	yes	89.90	yes
125438	thermophilic	thermophileⓘ	no	98.96	yes
125438	flagellated	motile2+ⓘ	yes	83.60	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Functional Characterization of Culturable Rhizobacteria From Mexican Maize Landrace Palomero Toluqueño (Zea mays var. Everta).	Salcedo-Vite K, Ferrera-Cerrato R, Cortes-Perez S, Cardenas-Marcelo AL, Maurice-Lira JV, Alarcon A.	J Basic Microbiol	10.1002/jobm.70119	2025
	The Interaction between Intratumoral Microbiome and Immunity Is Related to the Prognosis of Ovarian Cancer.	Sheng D, Yue K, Li H, Zhao L, Zhao G, Jin C, Zhang L.	Microbiol Spectr	10.1128/spectrum.03549-22	2023
	Pneumocystis jirovecii associated with Lung Virome in patients with severe pneumonia.	Huang Y, Wei X, Huang X, Peng C, Lin B, Ren X, He G, Zhang X, Jiang C, Huang L, Gu S.	iScience	10.1016/j.isci.2025.113710	2025
	Identification of a MarR Subfamily That Regulates Arsenic Resistance Genes.	Yu Y, Chen J, Li Y, Liang J, Xie Z, Feng R, Alwathnani HA, Rosen BP, Grove A, Chen J, Rensing C.	Appl Environ Microbiol	10.1128/aem.01588-21	2021
	Maternal gastrointestinal microbiome shapes gut microbial function and resistome of newborns in a cow-to-calf model.	Zhuang Y, Liu S, Gao D, Xu Y, Jiang W, Hou G, Li S, Zhao X, Chen T, Li S, Zhang S, Huang Y, Wang J, Xiao J, Li M, Wang W, Li S, Cao Z.	Microbiome	10.1186/s40168-024-01943-5	2024
Phylogeny	Individuality and generality of intratumoral microbiome in the three most prevalent gynecological malignancies: an observational study.	Xiao Q, Chen W-j, Wu F, Zhang X-y, Li X, Wei J, Chen T-t, Liu Z-x.	Microbiol Spectr	10.1128/spectrum.01004-24	2024
Phylogeny	Microbiota analysis of perimenopausal women experiencing recurrent vaginitis in conjunction with urinary tract infection.	Bi Y, Wang Y, Li W, Chen Y, Qin J, Zheng H.	BMC Microbiol	10.1186/s12866-024-03709-3	2025
	Leveraging the intratumoral microbiota to treat human cancer: are engineered exosomes an effective strategy?	Qiu J, Jiang Y, Ye N, Jin G, Shi H, Qian D.	J Transl Med	10.1186/s12967-024-05531-x	2024
	Emerging crops and plant growth-promoting bacteria (PGPB): a synergistic approach to climate-resilient agriculture.	Perez-Montano F, Aparicio N, Arenas F, Arjona JM, Camacho M, Fernandez-Garcia N, Garcia-Fraile P, Goicoechea N, Macias-Naranjo S, Matias J, Montero-Calasanz MDC, Morte A, Olmos E, Pueyo JJ, Quinones MA, Rey L, Reguera M.	Microbiome	10.1186/s40168-025-02225-4	2025
	Diversity and Biocontrol Potential of Cultivable Endophytic Bacteria Associated with Halophytes from the West Aral Sea Basin.	Gao L, Ma J, Liu Y, Huang Y, Mohamad OAA, Jiang H, Egamberdieva D, Li W, Li L.	Microorganisms	10.3390/microorganisms9071448	2021
	The car tank lid bacteriome: a reservoir of bacteria with potential in bioremediation of fuel.	Vidal-Verdu A, Gomez-Martinez D, Latorre-Perez A, Pereto J, Porcar M.	NPJ Biofilms Microbiomes	10.1038/s41522-022-00299-8	2022
Metabolism	Pesticide-tolerant bacteria isolated from a biopurification system to remove commonly used pesticides to protect water resources.	Briceno G, Lamilla C, Leiva B, Levio M, Donoso-Pinol P, Schalchli H, Gallardo F, Diez MC.	PLoS One	10.1371/journal.pone.0234865	2020
Phylogeny	Genomic characterization of Achromobacter species isolates from chronic and occasional lung infection in cystic fibrosis patients.	Veschetti L, Sandri A, Patuzzo C, Melotti P, Malerba G, Lleo MM.	Microb Genom	10.1099/mgen.0.000606	2021
	Polymyxin Resistance and Heteroresistance Are Common in Clinical Isolates of Achromobacter Species and Correlate with Modifications of the Lipid A Moiety of Lipopolysaccharide.	MacDonald L, Keenan S, Di Lorenzo F, Adade NE, Kenna DTD, Millar BC, Moore JE, Ramos Vivas J, Molinaro A, Valvano MA.	Microbiol Spectr	10.1128/spectrum.03729-22	2023
	Microbiota in mesenteric adipose tissue from Crohn's disease promote colitis in mice.	He Z, Wu J, Gong J, Ke J, Ding T, Zhao W, Cheng WM, Luo Z, He Q, Zeng W, Yu J, Jiao N, Liu Y, Zheng B, Dai L, Zhi M, Wu X, Jobin C, Lan P.	Microbiome	10.1186/s40168-021-01178-8	2021
Metabolism	Intratumoral Microbiome: Foe or Friend in Reshaping the Tumor Microenvironment Landscape?	Kyriazi AA, Karaglani M, Agelaki S, Baritaki S.	Cells	10.3390/cells13151279	2024
	Achromobacter xylosoxidans infection in cystic fibrosis siblings with different outcomes: Case reports.	Firmida MC, Marques EA, Leao RS, Pereira RH, Rodrigues ER, Albano RM, Folescu TW, Bernardo V, Daltro P, Capone D, Lopes AJ.	Respir Med Case Rep	10.1016/j.rmcr.2017.01.005	2017
	Achromobacter Infections and Treatment Options.	Isler B, Kidd TJ, Stewart AG, Harris P, Paterson DL.	Antimicrob Agents Chemother	10.1128/aac.01025-20	2020
	Assessing hydrocarbon degradation capacity of Isoptericola peretonis sp. nov. and related species: a comparative study.	Vidal-Verdu A, Latorre-Perez A, Pascual J, Manes-Collado R, Nevot-Terraes A, Porcar M.	Front Microbiol	10.3389/fmicb.2025.1471121	2025
Phylogeny	Taxonomic dissection of Achromobacter denitrificans Coenye et al. 2003 and proposal of Achromobacter agilis sp. nov., nom. rev., Achromobacter pestifer sp. nov., nom. rev., Achromobacter kerstersii sp. nov. and Achromobacter deleyi sp. nov.	Vandamme PA, Peeters C, Inganas E, Cnockaert M, Houf K, Spilker T, Moore ERB, LiPuma JJ	Int J Syst Evol Microbiol	10.1099/ijsem.0.001254	2016

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 )
#43168	Peter A. Vandamme, Charlotte Peeters, Elisabeth Inganäs, Margo Cnockaert, Kurt Houf, Theodore Spilker, Edward R. B. Moore, John J. LiPuma: Taxonomic dissection of Achromobacter denitrificans Coenye et al. 2003 and proposal of Achromobacter agilis sp. nov., nom. rev., Achromobacter pestifer sp. nov., nom. rev., Achromobacter kerstersii sp. nov. and Achromobacter deleyi sp. nov.. IJSEM 66: 3708 - 3717 2016 ( DOI 10.1099/ijsem.0.001254 , PubMed 27373279 )
#62841	Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 62433
#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 .
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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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Achromobacter deleyi (LMG 3458, CCUG 62433)

Name and taxonomic classification