Mesobacillus campisalis (DSM 28801, MTCC 11848, SA2-6)

Name: Mesobacillus campisalis (DSM 28801, MTCC 11848, SA2-6)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131455

Type strain

Strain Designation SA2-6

Culture col. no. DSM 28801 MTCC 11848 SA2-6

NCBI tax ID(s) 1408103

Special Collections DSMZ

Mesobacillus campisalis SA2-6 is a prokaryote that was isolated from solar saltern.

genome sequence 16S sequence

Name and taxonomic classification

Culture Collection Numbers

DSM 28801 MTCC 11848 SA2-6

@ref 20215

Last LPSN update 2025-12-16 10:01:15

Domain Bacillati

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Cytobacillaceae

Genus Mesobacillus

Species Mesobacillus campisalis

Full scientific name Mesobacillus campisalis (Kumar et al. 2015) Patel and Gupta 2020

Synonyms (1)

Bacillus campisalis

Morphology

Culture and growth conditions

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125438		90.74

Pathway annotation

Computationally determined by

@ref	pathway	enzyme coverage	annotated reactions
66794	cellulose degradation	100	5 of 5
66794	C4 and CAM-carbon fixation	100	8 of 8
66794	ribulose monophosphate pathway	100	2 of 2
66794	pentose phosphate pathway	100	11 of 11
66794	cis-vaccenate biosynthesis	100	2 of 2
66794	threonine metabolism	100	10 of 10
66794	aspartate and asparagine metabolism	100	9 of 9
66794	enterobactin biosynthesis	100	3 of 3
66794	palmitate biosynthesis	100	22 of 22
66794	ppGpp biosynthesis	100	4 of 4
66794	methylglyoxal degradation	100	5 of 5
66794	valine metabolism	100	9 of 9
66794	lipoate biosynthesis	100	5 of 5
66794	L-lactaldehyde degradation	100	3 of 3
66794	gluconeogenesis	100	8 of 8
66794	vitamin K metabolism	100	5 of 5
66794	anapleurotic synthesis of oxalacetate	100	1 of 1
66794	ceramide biosynthesis	100	1 of 1
66794	tetrahydrofolate metabolism	100	14 of 14
66794	folate polyglutamylation	100	1 of 1
66794	suberin monomers biosynthesis	100	2 of 2
66794	UDP-GlcNAc biosynthesis	100	3 of 3
66794	CDP-diacylglycerol biosynthesis	100	2 of 2
66794	denitrification	100	2 of 2
66794	adipate degradation	100	2 of 2
66794	teichoic acid biosynthesis	100	1 of 1
66794	formaldehyde oxidation	100	3 of 3
66794	propionate fermentation	100	10 of 10
66794	sulfopterin metabolism	100	4 of 4
66794	coenzyme A metabolism	100	4 of 4
66794	glutamate and glutamine metabolism	92.86	26 of 28
66794	heme metabolism	92.86	13 of 14
66794	vitamin B1 metabolism	92.31	12 of 13
66794	starch degradation	90	9 of 10
66794	Entner Doudoroff pathway	90	9 of 10
66794	4-hydroxyphenylacetate degradation	90	9 of 10
66794	molybdenum cofactor biosynthesis	88.89	8 of 9
66794	chorismate metabolism	88.89	8 of 9
66794	CO2 fixation in Crenarchaeota	88.89	8 of 9
66794	serine metabolism	88.89	8 of 9
66794	reductive acetyl coenzyme A pathway	85.71	6 of 7
66794	propanol degradation	85.71	6 of 7
66794	photosynthesis	85.71	12 of 14
66794	leucine metabolism	84.62	11 of 13
66794	purine metabolism	84.04	79 of 94
66794	glycolysis	82.35	14 of 17
66794	pyrimidine metabolism	82.22	37 of 45
66794	glycogen metabolism	80	4 of 5
66794	degradation of sugar acids	80	20 of 25
66794	metabolism of amino sugars and derivatives	80	4 of 5
66794	gallate degradation	80	4 of 5
66794	3-chlorocatechol degradation	80	4 of 5
66794	peptidoglycan biosynthesis	80	12 of 15
66794	alanine metabolism	79.31	23 of 29
66794	citric acid cycle	78.57	11 of 14
66794	NAD metabolism	77.78	14 of 18
66794	methionine metabolism	76.92	20 of 26
66794	phenylalanine metabolism	76.92	10 of 13
66794	isoleucine metabolism	75	6 of 8
66794	6-hydroxymethyl-dihydropterin diphosphate biosynthesis	75	6 of 8
66794	acetate fermentation	75	3 of 4
66794	biotin biosynthesis	75	3 of 4
66794	CMP-KDO biosynthesis	75	3 of 4
66794	glycogen biosynthesis	75	3 of 4
66794	butanoate fermentation	75	3 of 4
66794	non-pathway related	73.68	28 of 38
66794	flavin biosynthesis	73.33	11 of 15
66794	vitamin B6 metabolism	72.73	8 of 11
66794	glutathione metabolism	71.43	10 of 14
66794	cardiolipin biosynthesis	71.43	5 of 7
66794	histidine metabolism	68.97	20 of 29
66794	degradation of sugar alcohols	68.75	11 of 16
66794	androgen and estrogen metabolism	68.75	11 of 16
66794	cyanate degradation	66.67	2 of 3
66794	octane oxidation	66.67	2 of 3
66794	glycolate and glyoxylate degradation	66.67	4 of 6
66794	arginine metabolism	66.67	16 of 24
66794	acetyl CoA biosynthesis	66.67	2 of 3
66794	acetoin degradation	66.67	2 of 3
66794	selenocysteine biosynthesis	66.67	4 of 6
66794	oxidative phosphorylation	65.93	60 of 91
66794	degradation of pentoses	64.29	18 of 28
66794	proline metabolism	63.64	7 of 11
66794	d-xylose degradation	63.64	7 of 11
66794	tryptophan metabolism	63.16	24 of 38
66794	ketogluconate metabolism	62.5	5 of 8
66794	urea cycle	61.54	8 of 13
66794	cysteine metabolism	61.11	11 of 18
66794	glycine betaine biosynthesis	60	3 of 5
66794	phenol degradation	60	12 of 20
66794	arachidonate biosynthesis	60	3 of 5
66794	creatinine degradation	60	3 of 5
66794	isoprenoid biosynthesis	57.69	15 of 26
66794	lysine metabolism	57.14	24 of 42
66794	d-mannose degradation	55.56	5 of 9
66794	nitrate assimilation	55.56	5 of 9
66794	lipid metabolism	54.84	17 of 31
66794	phenylpropanoid biosynthesis	53.85	7 of 13
66794	phosphatidylethanolamine bioynthesis	53.85	7 of 13
66794	3-phenylpropionate degradation	53.33	8 of 15
66794	bile acid biosynthesis, neutral pathway	52.94	9 of 17
66794	aminopropanol phosphate biosynthesis	50	1 of 2
66794	glycine metabolism	50	5 of 10
66794	lactate fermentation	50	2 of 4
66794	cyclohexanol degradation	50	2 of 4
66794	pantothenate biosynthesis	50	3 of 6
66794	toluene degradation	50	2 of 4
66794	quinate degradation	50	1 of 2
66794	ethanol fermentation	50	1 of 2
66794	coenzyme M biosynthesis	50	5 of 10
66794	dTDPLrhamnose biosynthesis	50	4 of 8
66794	degradation of aromatic, nitrogen containing compounds	50	6 of 12
66794	sulfate reduction	46.15	6 of 13
66794	metabolism of disaccharids	45.45	5 of 11
66794	cholesterol biosynthesis	45.45	5 of 11
66794	degradation of hexoses	44.44	8 of 18
66794	4-hydroxymandelate degradation	44.44	4 of 9
66794	ubiquinone biosynthesis	42.86	3 of 7
66794	benzoyl-CoA degradation	42.86	3 of 7
66794	ascorbate metabolism	40.91	9 of 22
66794	phenylacetate degradation (aerobic)	40	2 of 5
66794	myo-inositol biosynthesis	40	4 of 10
66794	O-antigen biosynthesis	40	2 of 5
66794	arachidonic acid metabolism	38.89	7 of 18
66794	tyrosine metabolism	35.71	5 of 14
66794	polyamine pathway	34.78	8 of 23
66794	IAA biosynthesis	33.33	1 of 3
66794	lipid A biosynthesis	33.33	3 of 9
66794	allantoin degradation	33.33	3 of 9
66794	(5R)-carbapenem carboxylate biosynthesis	33.33	1 of 3
66794	vitamin B12 metabolism	29.41	10 of 34
66794	chlorophyll metabolism	27.78	5 of 18
66794	carotenoid biosynthesis	27.27	6 of 22
66794	alginate biosynthesis	25	1 of 4
66794	carnitine metabolism	25	2 of 8

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2
#Condition	#Saline

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
22682	solar saltern	Kanyakumari coast of the Bay of Bengal, Thamaraikulam (8° 07' 07.30'' N 77° 29' 13.76'' E)	India	IND	Asia	8.1187	77.4872 8.1187/77.4872

Taxonmaps

69479

Global distribution of 16S sequence AB859673 (>99% sequence identity) for Mesobacillus from Microbeatlas

Aquatic Samples	44
Soil Samples	154
Animal Samples	24
Plant Samples	5
Total Samples	227

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	IMG accession	NCBI tax ID	Score
66792	ASM98678v1 assembly for Mesobacillus campisalis SA2-6	scaffold	GCA_000986785	2630968476	1408103	55.4

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
22682	Bacillus campisalis gene for 16S ribosomal RNA, partial sequence	AB859673	1493		1408103

GC content

@ref	GC-content (mol%)	Method
22682	45.44	sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Mesobacillus campisalis SA2-6
NCBI: GCA_000986785

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	86.20	no
125439	motility	BacteriaNetⓘ	yes	78.30	no
125439	gram_stain	BacteriaNetⓘ	variable	89.30	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	72.20	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Mesobacillus campisalis SA2-6
NCBI: GCA_000986785.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	75.40	no
125438	anaerobic	anaerobicⓘ	no	97.32	no
125438	aerobic	aerobicⓘ	yes	71.20	no
125438	spore-forming	spore-formingⓘ	yes	90.74	no
125438	thermophilic	thermophileⓘ	no	93.55	no
125438	flagellated	motile2+ⓘ	yes	69.30	no

Literature

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 )
#22682	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 28801
#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 .

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