Name: Christiangramia salexigens LPB0144
Creator: BacDive
License: https://creativecommons.org/licenses/by/4.0/

Strain identifier

BacDive ID: 159710

Type strain:

Species: Christiangramia salexigens

Strain Designation: LPB0144

Culture col. no.: KACC 18894, JCM 31560

Strain history: H. Yi; Korea Univ., South Korea; LPB0144.

NCBI tax ID(s): 1913577 (species)

Special Collections

Section

When using BacDive for research please cite our paper

Christiangramia salexigens LPB0144 is an aerobe, mesophilic, Gram-negative bacterium that forms circular colonies and was isolated from seawater.

colony-forming
Gram-negative
motile
rod-shaped
aerobe
mesophilic
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	*Bacteroidota*
	Class	*Flavobacteriia*
	Order	*Flavobacteriales*
	Family	*Flavobacteriaceae*
	Genus	*Christiangramia*
	Species	**Christiangramia salexigens**
	Full Scientific Name (LPSN)	Christiangramia salexigens (Shin et al. 2018) Deshmukh and Oren 2023

Synonym

Gramella salexigens

Information on morphological and physiological properties Morphology

[Ref.: #66602]	Gram stain	negative
[Ref.: #125439]	Gram stain	negative Confidence in %98.8
[Ref.: #125438]	Gram stain	negative Confidence in %97.969

[Ref.: #66602]	Cell length	1.4-2.8 µm

[Ref.: #66602]	Cell width	0.4-0.6 µm

[Ref.: #66602]	Cell shape	rod-shaped

[Ref.: #66602]	Motility	yes
[Ref.: #125438]	Motility	no Confidence in %94.5

[Ref.: #66602]	Flagellum arrangement	gliding

[Ref.: #66602]	Colony color	yellow-orange
[Ref.: #66602]	Colony shape	circular
[Ref.: #66602]	Cultivation medium used	Marine agar (MA) 2216

[Ref.: #66602]	Pigment production	no
[Ref.: #66602]	Pigment name	flexirubin-type

Information on culture and growth conditions Culture and growth conditions

[Ref.: #66602]

Culture medium

Marine agar (MA) 2216

[Ref.: #66602]

Culture medium growth

		Temperature
[Ref.: #66602]	optimum	30 °C
[Ref.: #66602]	growth	4-40 °C
[Ref.: #67770]	growth	25 °C

	pH	Kind of pH		pH
[Ref.: #66602]			optimum	6.5-7
[Ref.: #66602]			growth	6.5-8.5

Information on physiology and metabolism Physiology and metabolism

[Ref.: #66602]

Oxygen tolerance

aerobe

[Ref.: #66602]	Ability of spore formation	no
[Ref.: #125439]	Ability of spore formation	no Confidence in %96.4
[Ref.: #125438]	Ability of spore formation	no Confidence in %90.691

	Halophily	Salt	Tested relation		Salt conc.
[Ref.: #66602]		NaCl		growth	2-14	%(w/v)
[Ref.: #66602]		NaCl		optimum	2	%(w/v)

[Ref.: #67770]

Observation

quinones: MK-6

	Metabolite	Utilization activity	Kind of utilization tested
[Ref.: #66602]	adipate ChEBI	-	carbon source
[Ref.: #66602]	agar ChEBI	-	hydrolysis
[Ref.: #66602]	alginate ChEBI	-	hydrolysis
[Ref.: #66602]	carboxymethylcellulose ChEBI	-	hydrolysis
[Ref.: #66602]	casein	-	hydrolysis
[Ref.: #66602]	chitin ChEBI	-	hydrolysis
[Ref.: #66602]	citric acid ChEBI	-	carbon source
[Ref.: #66602]	D-glucose ChEBI	-	carbon source
[Ref.: #66602]	D-mannitol ChEBI	-	carbon source
[Ref.: #66602]	D-mannose ChEBI	-	carbon source
[Ref.: #66602]	decanoate ChEBI	-	carbon source
[Ref.: #66602]	dna ChEBI	+	hydrolysis
[Ref.: #66602]	esculin ChEBI	+	hydrolysis
[Ref.: #66602]	gelatin ChEBI	+	hydrolysis
[Ref.: #66602]	gluconate ChEBI	-	carbon source
[Ref.: #66602]	glucose ChEBI	-	fermentation
[Ref.: #66602]	hypoxanthine ChEBI	-	hydrolysis
[Ref.: #66602]	L-arabinose ChEBI	-	carbon source
[Ref.: #66602]	L-tyrosine ChEBI	+	hydrolysis
[Ref.: #66602]	malate ChEBI	-	carbon source
[Ref.: #66602]	maltose ChEBI	-	carbon source
[Ref.: #66602]	N-acetylglucosamine ChEBI	-	carbon source
[Ref.: #66602]	nitrate ChEBI	-	reduction
[Ref.: #66602]	phenylacetate ChEBI	-	carbon source
[Ref.: #66602]	starch ChEBI	+	hydrolysis
[Ref.: #66602]	tween 20 ChEBI	+	hydrolysis
[Ref.: #66602]	tween 40 ChEBI	+	hydrolysis
[Ref.: #66602]	tween 60 ChEBI	+	hydrolysis
[Ref.: #66602]	tween 80 ChEBI	+	hydrolysis
[Ref.: #66602]	xanthine ChEBI	-	hydrolysis
	Only first 10 entries are displayed. Click here to see all.

	Metabolite	Antibiotic sensitivity	Concentration		Antibiotic resistance	Concentration
[Ref.: #66602]	ampicillin ChEBI	yes	50	µg (disc)
[Ref.: #66602]	chloramphenicol ChEBI	yes	50	µg (disc)
[Ref.: #66602]	kanamycin ChEBI				yes	50	µg (disc)
[Ref.: #66602]	streptomycin ChEBI				yes	50	µg (disc)

	Metabolite production	Metabolite	Production
[Ref.: #66602]		hydrogen sulfide ChEBI	no
[Ref.: #66602]		indole ChEBI	no

	Enzyme	Enzyme activity	EC number
[Ref.: #66602]	acid phosphatase	+	3.1.3.2
[Ref.: #66602]	alkaline phosphatase	+	3.1.3.1
[Ref.: #66602]	alpha-chymotrypsin	-	3.4.21.1
[Ref.: #66602]	alpha-fucosidase	-	3.2.1.51
[Ref.: #66602]	alpha-galactosidase	-	3.2.1.22
[Ref.: #66602]	alpha-glucosidase	+	3.2.1.20
[Ref.: #66602]	alpha-mannosidase	-	3.2.1.24
[Ref.: #66602]	beta-galactosidase	-	3.2.1.23
[Ref.: #66602]	beta-glucosidase	-	3.2.1.21
[Ref.: #66602]	beta-glucuronidase	-	3.2.1.31
[Ref.: #66602]	catalase	+	1.11.1.6
[Ref.: #66602]	cystine arylamidase	+	3.4.11.3
[Ref.: #66602]	cytochrome oxidase	+	1.9.3.1
[Ref.: #66602]	esterase (C 4)	+
[Ref.: #66602]	esterase Lipase (C 8)	+
[Ref.: #66602]	leucine arylamidase	+	3.4.11.1
[Ref.: #66602]	lipase (C 14)	-
[Ref.: #66602]	N-acetyl-beta-glucosaminidase	-	3.2.1.52
[Ref.: #66602]	naphthol-AS-BI-phosphohydrolase	+
[Ref.: #66602]	trypsin	+	3.4.21.4
[Ref.: #66602]	valine arylamidase	+
	Only first 10 entries are displayed. Click here to see all.

Fatty acid profile

Metadata FA analysis

Reference

[Ref.: #66602]

Fatty acid	Percentage
C15:0 anteiso	13.7
C15:0 iso	12.4
C16:0 iso	12.2
C17:0 iso 3OH	11
C17:0 2OH	7.5
C17:1 w6c	5.8
C16:1 w6c and/or C16:1 w7c	5.6
C16:0 iso 3OH	4.9
C17:1 iso w9c / C16:0 10-methyl	4.8
C17:1 anteiso w10c	4.2
C16:1 iso H	2.9
C15:0 2OH	2.8
C17:1 w8c	2.2
C15:1 w6c	1.9
C14:0 iso	1.2
C15:0 iso 3OH	1.2
C17:0 iso	0.7
C15:1 iso G	0.1

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

[Ref.: #66602]	Sample type/isolated from	seawater
[Ref.: #66602]	Geographic location (country and/or sea, region)	South Sea, Oryukdo Island, Busan
[Ref.: #66602]	Country	Republic of Korea
[Ref.: #66602]	Country ISO 3 Code	KOR
[Ref.: #66602]	Continent	Asia
[Ref.: #66602]	Geographic location	35.0911°/129.1270°
[Ref.: #66602]	Enrichment culture	marine agar
[Ref.: #66602]	Enrichment culture temperature	25, 30 ̊C
[Ref.: #66602]	Isolation/enrichment procedure	standard dilution plating technique at 25°C on marine agar and was cultivated routinely at 30°C on MA.

[Ref.: #67770]	Sample type/isolated from	Seawater of South Sea
[Ref.: #67770]	Country	Republic of Korea
[Ref.: #67770]	Country ISO 3 Code	KOR
[Ref.: #67770]	Continent	Asia
* marker position based on {}

Isolation sources categories

#Environmental

#Aquatic

#Marine

What are isolation sources categories?

[Ref.: #69479]

Global distribution of 16S sequence KX066854 (>99% sequence identity) for Gramella salexigens subclade from Microbeatlas

Aquatic Samples	162
Soil Samples	15
Animal Samples	60
Plant Samples
Total Samples	237

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.: #66602]	Christiangramia salexigens strain LPB0144 16S ribosomal RNA gene, partial sequence	KX066854	1488	GenBank ENA	1913577 tax ID

Genome sequence information:

	Sequence accession description	Seq. accession number	Assembly level	Sequence database	Associated NCBI tax ID
[Ref.: #66792]	Christiangramia salexigens LPB0144	GCA_001889005	complete	GenBank ENA	1913577 tax ID	*
[Ref.: #66792]	Gramella salexigens LPB0144	2718217989	complete	JGI IMG/M	1913577 tax ID	*

[Ref.: #66602]

GC-content

38.2 mol%

genome sequence analysis

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: Gramella salexigens LPB0144 NCBI: GCA_001889005.1
[Ref.: #125438]	gram-positive	gram-positiveⓘ	no	97.969	no
[Ref.: #125438]	anaerobic	anaerobicⓘ	no	95.762	yes
[Ref.: #125438]	aerobic	aerobicⓘ	yes	86.396	yes
[Ref.: #125438]	spore-forming	spore-formingⓘ	no	90.691	no
[Ref.: #125438]	thermophile	thermophilicⓘ	no	97.847	yes
[Ref.: #125438]	motile2+	flagellatedⓘ	no	94.5	no

	Model	Trait	Prediction	Confidence in %
	Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Gramella salexigens LPB0144 IMG: 2718217989
[Ref.: #125439]	BacteriaNet	spore_formationⓘ	no	96.4
[Ref.: #125439]	BacteriaNet	motilityⓘ	no	69.9
[Ref.: #125439]	BacteriaNet	gram_stainⓘ	negative	98.8
[Ref.: #125439]	BacteriaNet	oxygen_toleranceⓘ	facultative aerobe	77.1

Availability in culture collections External links

[Ref.: #66602]

Culture collection no.

KACC 18894, JCM 31560

Literature:

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Gramella salexigens sp. nov., isolated from seawater.	Shin SK, Kim E, Yi H	Int J Syst Evol Microbiol	10.1099/ijsem.0.002850	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 )

#66602

Su-Kyoung Shin, Eunji Kim, Hana Yi: Gramella salexigens sp. nov., isolated from seawater. IJSEM 68: 2381 - 2384 2018 ( DOI 10.1099/ijsem.0.002850 , PubMed 29851376 )

#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) .

#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 .

* These data were automatically processed and therefore are not curated

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