Name: Legionella steigerwaltii SC-18-C9
Creator: BacDive
License: https://creativecommons.org/licenses/by/4.0/

Strain identifier

BacDive ID: 6753

Type strain:

Species: Legionella steigerwaltii

Strain Designation: SC-18-C9

Culture col. no.: DSM 23076, ATCC 35302, CCUG 29674, CCUG 56441, CIP 103851, JCM 7558, NCTC 11991

Strain history: CIP <- 1993, R.F. Benson, CDC, Atlanta, Georgia, USA: strain SC-18-C9

NCBI tax ID(s): 460 (species)

SI-ID 105415

ATCC 35302, NCTC 11991, CCUG 29674, CIP 103851, JCM 7558, CCUG 56441, DSM 23076

Special Collections

Section

When using BacDive for research please cite our paper

Legionella steigerwaltii SC-18-C9 is a microaerophile, mesophilic, Gram-negative bacterium that was isolated from tap water.

Gram-negative
rod-shaped
mesophilic
microaerophile
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	*Gammaproteobacteria*
	Order	*Legionellales*
	Family	*Legionellaceae*
	Genus	*Legionella*
	Species	**Legionella steigerwaltii**
	Full Scientific Name (LPSN)	Legionella steigerwaltii Brenner et al. 1985

Information on morphological and physiological properties Morphology

[Ref.: #123303]	Gram stain	negative
[Ref.: #125438]	Gram stain	negative Confidence in %99.479
[Ref.: #125439]	Gram stain	negative Confidence in %99.6

[Ref.: #123303]	Cell shape	rod-shaped

[Ref.: #123303]	Motility	no

Information on culture and growth conditions Culture and growth conditions

[Ref.: #16693]

Culture medium

BCYE-AGAR (DSMZ Medium 585)

[Ref.: #16693]

Culture medium growth

[Ref.: #16693]

Culture medium link

Medium recipe at MediaDive

[Ref.: #16693]

Culture medium composition

expand / minimize

[Ref.: #123303]

Culture medium

CIP Medium 23

[Ref.: #123303]

Culture medium growth

[Ref.: #123303]

Culture medium link

Medium recipe provided by DSMZ

	Temperatures	Kind of temperature		Temperature
[Ref.: #16693]			growth	30 °C

Information on physiology and metabolism Physiology and metabolism

[Ref.: #16693]	Oxygen tolerance	microaerophile
[Ref.: #125439]	Oxygen tolerance	obligate aerobe Confidence in %98.4

[Ref.: #125439]

Ability of spore formation

no Confidence in %99.4

	Enzymes	Enzyme	Enzyme activity	EC number
[Ref.: #16693]		catalase	+	1.11.1.6
[Ref.: #16693]		cytochrome-c oxidase	-	1.9.3.1

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

[Ref.: #16693]	Sample type/isolated from	tap water
[Ref.: #16693]	Geographic location (country and/or sea, region)	Saint-Croix
[Ref.: #16693]	Country	Virgin Islands (U.S.)
[Ref.: #16693]	Country ISO 3 Code	VIR
[Ref.: #16693]	Continent	Middle and South America

[Ref.: #60959]	Sample type/isolated from	Tap water
[Ref.: #60959]	Sampling date	1982
[Ref.: #60959]	Geographic location (country and/or sea, region)	Virgin Islands,Saint-Croix

[Ref.: #123303]	Sample type/isolated from	Other, Tap water
[Ref.: #123303]	Geographic location (country and/or sea, region)	Saint Croix, Virgin Islands
[Ref.: #123303]	Country	United States of America
[Ref.: #123303]	Country ISO 3 Code	USA
[Ref.: #123303]	Continent	North America
* marker position based on {}

Isolation sources categories

#Environmental	#Aquatic	#Freshwater
#Engineered	#Built environment	#Water reservoir (Aquarium/pool)
#Engineered	#Built environment	-

What are isolation sources categories?

[Ref.: #69479]

Global distribution of 16S sequence Z49737 (>99% sequence identity) for Legionella steigerwaltii subclade from Microbeatlas

Aquatic Samples	16
Soil Samples	14
Animal Samples	1
Plant Samples	2
Total Samples	33

Information on possible application of the strain and its possible interaction with e.g. potential hosts Safety information

[Ref.: #16693]	Pathogenicity (human)	yes, in single cases
[Ref.: #16693]	Biosafety level	1	Risk group (German classification) According to TRBA 466
[Ref.: #123303]	Biosafety level	2	Risk group (French classification)

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.: #16693]	L.steigerwaltii gene for ribosomal RNA, small subunit	Z49737	1435	GenBank ENA	460 tax ID
[Ref.: #20218]	L.steigerwaltii (ATCC 35302) gene for 16S rRNA	X73400	1467	GenBank ENA	460 tax ID	*
[Ref.: #20218]	Legionella steigerwaltii strain MDC1618 16S ribosomal RNA gene, partial sequence	JF720405	524	GenBank ENA	460 tax ID	*

Genome sequence information:

Only first 5 entries are displayed. Click here to see all.

	Sequence accession description	Seq. accession number	Assembly level	Sequence database	Associated NCBI tax ID
[Ref.: #66792]	Legionella steigerwaltii NCTC11991	GCA_900452835	contig	GenBank ENA	460 tax ID	*
[Ref.: #66792]	Legionella steigerwaltii SC-18-C9	GCA_001468065	scaffold	GenBank ENA	460 tax ID	*
[Ref.: #66792]	Legionella steigerwaltii SC-18-C9	GCA_900640025	contig	GenBank ENA	460 tax ID	*
[Ref.: #66792]	Legionella steigerwaltii strain NCTC11991	460.6	wgs	PATRIC	460 tax ID	*
[Ref.: #66792]	Legionella steigerwaltii strain SC-18-C9	460.5	wgs	PATRIC	460 tax ID	*
[Ref.: #66792]	Legionella steigerwaltii SC-18-C9	2660238143	draft	JGI IMG/M	460 tax ID	*

[Ref.: #16693]

GC-content

40.0 mol%

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: Legionella steigerwaltii SC-18-C9 NCBI: GCA_001468065.1
[Ref.: #125438]	gram-positive	gram-positiveⓘ	no	99.479	no
[Ref.: #125438]	anaerobic	anaerobicⓘ	no	95.489	yes
[Ref.: #125438]	aerobic	aerobicⓘ	no	71.089	no
[Ref.: #125438]	spore-forming	spore-formingⓘ	no	89.907	no
[Ref.: #125438]	thermophile	thermophilicⓘ	no	99	yes
[Ref.: #125438]	motile2+	flagellatedⓘ	yes	65.479	no

	Model	Trait	Prediction	Confidence in %
	Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Legionella steigerwaltii SC-18-C9 NCBI: GCA_001468065
[Ref.: #125439]	BacteriaNet	spore_formationⓘ	no	99.4
[Ref.: #125439]	BacteriaNet	motilityⓘ	yes	51.3
[Ref.: #125439]	BacteriaNet	gram_stainⓘ	negative	99.6
[Ref.: #125439]	BacteriaNet	oxygen_toleranceⓘ	obligate aerobe	98.4

Availability in culture collections External links

[Ref.: #16693]

Culture collection no.

DSM 23076, ATCC 35302, CCUG 29674, CCUG 56441, CIP 103851, JCM 7558, NCTC 11991

[Ref.: #76223]

SI-ID 105415

References

#16693

Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 23076

#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 )

#60959 Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 56441

#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 .

#76223

Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J.: StrainInfo: A central database for resolving microbial strain identifiers . ( DOI 10.60712/SI-ID105415.1 )

#123303 Collection of Institut Pasteur ; Curators of the CIP; CIP 103851

#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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