Name: Paraburkholderia fynbosensis LMG 27177
Creator: BacDive
License: https://creativecommons.org/licenses/by/4.0/

Strain identifier

BacDive ID: 159875

Type strain:

Species: Paraburkholderia fynbosensis

Culture col. no.: LMG 27177, HAMBI 3356, WSM 4178

NCBI tax ID(s): 1200993 (species)

Special Collections

Literature strains

Section

When using BacDive for research please cite our paper

Paraburkholderia fynbosensis LMG 27177 is a Gram-negative, motile, rod-shaped bacterium that forms circular colonies and was isolated from root nodules of Lebeckia ambigua.

colony-forming
Gram-negative
motile
rod-shaped
16S sequence
Bacteria
genome sequence

Information on the name and the taxonomic classification. Name and taxonomic classification

	Last LPSN update	09-12-2024 (DD-MM-YYYY)
	Domain	*Bacteria*
	Phylum	*Pseudomonadota*
	Class	*Betaproteobacteria*
	Order	*Burkholderiales*
	Family	*Burkholderiaceae*
	Genus	*Paraburkholderia*
	Species	**Paraburkholderia fynbosensis**
	Full Scientific Name (LPSN)	Paraburkholderia fynbosensis De Meyer et al. 2018

Information on morphological and physiological properties Morphology

[Ref.: #66624]	Gram stain	negative
[Ref.: #125438]	Gram stain	negative Confidence in %98.5

[Ref.: #66624]	Cell length	2.0-2.5 µm

[Ref.: #66624]	Cell width	0.9 µm

[Ref.: #66624]	Cell shape	rod-shaped

[Ref.: #66624]	Motility	yes

[Ref.: #66624]	Colony size	2.2-4 mm
[Ref.: #66624]	Colony color	white
[Ref.: #66624]	Colony shape	circular
[Ref.: #66624]	Cultivation medium used	1/2 lupin agar medium

Information on culture and growth conditions Culture and growth conditions

[Ref.: #66624]

Culture medium

1/2 lupin agar medium

[Ref.: #66624]

Culture medium growth

	Kind of temperature		Temperature
[Ref.: #66624]	negative	growth	4 °C
[Ref.: #66624]	negative	growth	40 °C
[Ref.: #66624]		growth	10-37 °C

	pH	Kind of pH		pH
[Ref.: #66624]			growth	5-9

Information on physiology and metabolism Physiology and metabolism

[Ref.: #125438]	Oxygen tolerance	aerobe Confidence in %91.155
[Ref.: #125439]	Oxygen tolerance	obligate aerobe Confidence in %99

	Halophily	Salt	Tested relation		Salt conc.
[Ref.: #66624]		NaCl		growth	0-10	%

	Metabolite	Utilization activity	Kind of utilization tested
[Ref.: #66624]	adipate ChEBI	+	assimilation
[Ref.: #66624]	amygdalin ChEBI	-	oxidation
[Ref.: #66624]	citric acid ChEBI	+	assimilation
[Ref.: #66624]	D-glucose ChEBI	+	assimilation
[Ref.: #66624]	D-glucose ChEBI	-	oxidation
[Ref.: #66624]	D-mannitol ChEBI	+	assimilation
[Ref.: #66624]	D-mannitol ChEBI	-	oxidation
[Ref.: #66624]	D-mannose ChEBI	+	assimilation
[Ref.: #66624]	D-sorbitol ChEBI	-	oxidation
[Ref.: #66624]	L-arabinose ChEBI	+	assimilation
[Ref.: #66624]	L-arabinose ChEBI	-	oxidation
[Ref.: #66624]	L-rhamnose ChEBI	+	oxidation
[Ref.: #66624]	malate ChEBI	+	assimilation
[Ref.: #66624]	maltose ChEBI	-	assimilation
[Ref.: #66624]	melibiose ChEBI	-	oxidation
[Ref.: #66624]	myo-inositol ChEBI	-	oxidation
[Ref.: #66624]	N-acetylglucosamine ChEBI	+	assimilation
[Ref.: #66624]	nitrate ChEBI	-	reduction
[Ref.: #66624]	phenylacetate ChEBI	+	assimilation
[Ref.: #66624]	potassium gluconate ChEBI	+	assimilation
[Ref.: #66624]	sucrose ChEBI	-	oxidation
	Only first 10 entries are displayed. Click here to see all.

	Metabolite	Antibiotic sensitivity	Concentration		Antibiotic resistance	Concentration
[Ref.: #66624]	ampicillin ChEBI				yes	10	µg (disc)
[Ref.: #66624]	chloramphenicol ChEBI	yes	30	µg (disc)
[Ref.: #66624]	gentamicin ChEBI				yes	10	µg (disc)
[Ref.: #66624]	kanamycin ChEBI				yes	30	µg (disc)
[Ref.: #66624]	penicillin g ChEBI	yes	10	µg (disc)
[Ref.: #66624]	streptomycin ChEBI				yes	10	µg (disc)
[Ref.: #66624]	tetracycline ChEBI				yes	30	µg (disc)

	Metabolite	Production
[Ref.: #66624]	acetoin ChEBI	yes
[Ref.: #66624]	hydrogen sulfide ChEBI	no
[Ref.: #66624]	indole ChEBI	no

	Enzyme	Enzyme activity	EC number
[Ref.: #66624]	arginine dihydrolase	+	3.5.3.6
[Ref.: #66624]	beta-galactosidase	+	3.2.1.23
[Ref.: #66624]	beta-glucosidase	+	3.2.1.21
[Ref.: #66624]	catalase	+	1.11.1.6
[Ref.: #66624]	cytochrome oxidase	+	1.9.3.1
[Ref.: #66624]	gelatinase	-
[Ref.: #66624]	lysine decarboxylase	-	4.1.1.18
[Ref.: #66624]	ornithine decarboxylase	-	4.1.1.17
[Ref.: #66624]	protease	-
[Ref.: #66624]	tryptophan deaminase	+/-	4.1.99.1
[Ref.: #66624]	urease	-	3.5.1.5
	Only first 10 entries are displayed. Click here to see all.

Information on isolation source, the sampling and environmental conditions Isolation, sampling and environmental information

[Ref.: #66624]	Sample type/isolated from	root nodules of Lebeckia ambigua
[Ref.: #66624]	Host species	Lebeckia ambigua
[Ref.: #66624]	Sampling date	2002-2007
[Ref.: #66624]	Geographic location (country and/or sea, region)	Western Cape
[Ref.: #66624]	Country	South Africa
[Ref.: #66624]	Country ISO 3 Code	ZAF
[Ref.: #66624]	Continent	Africa
[Ref.: #66624]	Geographic location	-31.4464°/19.1447°
* marker position based on {}

Isolation sources categories

#Host	#Plants	#Herbaceous plants (Grass,Crops)
#Host Body-Site	#Plant	#Root nodule

What are isolation sources categories?

Information on genomic background e.g. entries in nucleic sequence databass Sequence information

16S Sequence information:

	Sequence accession description	Seq. accession number	Sequence length (bp)	Sequence database	Associated NCBI tax ID
[Ref.: #66624]	Burkholderia sp. WSM4178 16S rRNA gene, strain WSM4178	HE862279	1495	GenBank ENA	1200993 tax ID

Genome sequence information:

	Sequence accession description	Seq. accession number	Assembly level	Sequence database	Associated NCBI tax ID
[Ref.: #66792]	Paraburkholderia fynbosensis LMG 27177	GCA_902859935	contig	GenBank ENA	1200993 tax ID	*
[Ref.: #66792]	Paraburkholderia fynbosensis strain LMG 27177	1200993.3	wgs	PATRIC	1200993 tax ID	*
[Ref.: #66792]	Paraburkholderia fynbosensis LMG 27177	2921684003	draft	JGI IMG/M	1200993 tax ID	*

[Ref.: #66624]

GC-content

62.40 mol%

high performance liquid chromatography (HPLC)

Data predicted using genome information as a basis Genome-based predictions

	Model	Trait	Prediction	Confidence in %	In training data
	Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Paraburkholderia fynbosensis strain LMG 27177 PATRIC: 1200993.3
[Ref.: #125438]	gram-positive	gram-positiveⓘ	no	98.5	yes
[Ref.: #125438]	anaerobic	anaerobicⓘ	no	96.084	no
[Ref.: #125438]	spore-forming	spore-formingⓘ	no	84.979	no
[Ref.: #125438]	aerobic	aerobicⓘ	yes	91.155	no
[Ref.: #125438]	thermophile	thermophilicⓘ	no	98	no
[Ref.: #125438]	motile2+	flagellatedⓘ	yes	87.578	no

	Model	Trait	Prediction	Confidence in %
	Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Paraburkholderia fynbosensis LMG 27177 NCBI: GCA_902859935
[Ref.: #125439]	BacteriaNet	spore_formationⓘ	no	87.1
[Ref.: #125439]	BacteriaNet	motilityⓘ	yes	61.6
[Ref.: #125439]	BacteriaNet	gram_stainⓘ	negative	83.3
[Ref.: #125439]	BacteriaNet	oxygen_toleranceⓘ	obligate aerobe	99

Availability in culture collections External links

[Ref.: #66624]

Culture collection no.

LMG 27177, HAMBI 3356, WSM 4178

Literature:

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Symbiotic and non-symbiotic Paraburkholderia isolated from South African Lebeckia ambigua root nodules and the description of Paraburkholderia fynbosensis sp. nov.	De Meyer SE, Cnockaert M, Moulin L, Howieson JG, Vandamme P	Int J Syst Evol Microbiol	10.1099/ijsem.0.002884	2018	*

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 )

#66624

Sofie E. De Meyer, Margo Cnockaert, Lionel Moulin, John G. Howieson and Peter Vandamme: Symbiotic and non-symbiotic Paraburkholderia isolated from South African Lebeckia ambigua root nodules and the description of Paraburkholderia fynbosensis sp. nov.. IJSEM 68: 2607 - 2614 2018 ( DOI 10.1099/ijsem.0.002884 , PubMed 29957169 )

#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) .

#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 .

* These data were automatically processed and therefore are not curated

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Paraburkholderia fynbosensis strain LMG 27177

Paraburkholderia fynbosensis LMG 27177

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