Bacillus paramycoides (MCCC 1A04098, KCTC 33709, LMG 28876)

Name: Bacillus paramycoides (MCCC 1A04098, KCTC 33709, LMG 28876)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 140968

Type strain

Strain Designation NH24A2

Culture col. no. MCCC 1A04098 KCTC 33709 LMG 28876 NH24A2 NBRC 113922 1 more

NCBI tax ID(s) 2026194

Special Collections KCTC Literature strains CIP

Links

Bacillus paramycoides NH24A2 is a facultative anaerobe, Gram-positive, rod-shaped prokaryote that forms circular colonies and was isolated from sediment of the South China Sea.

Gram-positive rod-shaped colony-forming facultative anaerobe genome sequence 16S sequence

Name and taxonomic classification

SI-ID 413866

LMG 28876,KCTC 33709,CIP 111461

@ref 20215

Last LPSN update 2025-12-16 10:03:44

Domain Bacillati

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Bacillaceae

Genus Bacillus

Species Bacillus paramycoides

Full scientific name Bacillus paramycoides Liu et al. 2017

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape
43860	positive	1.8-2.2 µm	0.8-1.2 µm	rod-shaped
67771				rod-shaped
67771	positive
121570	positive			rod-shaped

Colony morphology

@ref	Colony size	Colony shape	Incubation period	Medium used
43860	2-3 mm	circular	2 days	Luria-Bertani agar

Culture and growth conditions

Culture medium

@ref	Name	Growth
43860	LB (Luria-Bertani) MEDIUM
43860	Trypticase soy agar
121570	CIP Medium 72

Culture temp

@ref	Growth	Type	Temperature (°C)
43860	positive	growth	15-39
43860	positive	optimum	30
67771	positive	growth	28

Culture pH

@ref	Ability	Type	PH
43860	positive	optimum	7
43860	positive	growth	5.0-9.0

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance
43860	facultative anaerobe
67771	facultative anaerobe

Spore formation

@ref	Spore formation
43860
67771

Halophily

@ref	Salt	Growth	Tested relation	Concentration
43860	NaCl	positive	growth	0-5 %(w/v)
43860	NaCl	positive	optimum	0.5 %(w/v)

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
43860	16808 ChEBI	2-dehydro-D-gluconate	-	builds acid from
43860	58143 ChEBI	5-dehydro-D-gluconate	-	builds acid from
43860	27613 ChEBI	amygdalin	-	builds acid from
43860	27613 ChEBI	amygdalin	+	builds acid from
43860	22599 ChEBI	arabinose	-	builds acid from
43860	18305 ChEBI	arbutin	+	builds acid from
43860		casein	+	hydrolysis
43860	17057 ChEBI	cellobiose	+	builds acid from
43860	16947 ChEBI	citrate	+	carbon source
43860	17108 ChEBI	D-arabinose	-	builds acid from
43860	18333 ChEBI	D-arabitol	-	builds acid from
43860	15824 ChEBI	D-fructose	+	builds acid from
43860	28847 ChEBI	D-fucose	-	builds acid from
43860	12936 ChEBI	D-galactose	+	builds acid from
43860	17634 ChEBI	D-glucose	+	builds acid from
43860	62318 ChEBI	D-lyxose	-	builds acid from
43860	16899 ChEBI	D-mannitol	-	builds acid from
43860	16024 ChEBI	D-mannose	+	builds acid from
43860	16988 ChEBI	D-ribose	+	builds acid from
43860	17924 ChEBI	D-sorbitol	-	builds acid from
43860	16443 ChEBI	D-tagatose	-	builds acid from
43860	65327 ChEBI	D-xylose	-	builds acid from
43860	17113 ChEBI	erythritol	-	builds acid from
43860		esculin ferric citrate	+	builds acid from
43860	16813 ChEBI	galactitol	-	builds acid from
43860	28066 ChEBI	gentiobiose	-	builds acid from
43860	17234 ChEBI	glucose	+	builds acid from
43860	17754 ChEBI	glycerol	-	builds acid from
43860	28087 ChEBI	glycogen	+	builds acid from
43860	15443 ChEBI	inulin	-	builds acid from
43860	30849 ChEBI	L-arabinose	-	builds acid from
43860	18403 ChEBI	L-arabitol	-	builds acid from
43860	18287 ChEBI	L-fucose	-	builds acid from
43860	62345 ChEBI	L-rhamnose	-	builds acid from
43860	17266 ChEBI	L-sorbose	-	builds acid from
43860	65328 ChEBI	L-xylose	-	builds acid from
43860	17716 ChEBI	lactose	-	builds acid from
43860	17306 ChEBI	maltose	+	builds acid from
43860	29864 ChEBI	mannitol	-	builds acid from
43860	6731 ChEBI	melezitose	-	builds acid from
43860	28053 ChEBI	melibiose	-	builds acid from
43860	320061 ChEBI	methyl alpha-D-glucopyranoside	-	builds acid from
43860	43943 ChEBI	methyl alpha-D-mannoside	-	builds acid from
43860	74863 ChEBI	methyl beta-D-xylopyranoside	-	builds acid from
43860	17268 ChEBI	myo-inositol	-	builds acid from
43860	506227 ChEBI	N-acetylglucosamine	+	builds acid from
43860	32032 ChEBI	potassium gluconate	-	builds acid from
43860	16634 ChEBI	raffinose	-	builds acid from
43860	26546 ChEBI	rhamnose	-	builds acid from
43860	15963 ChEBI	ribitol	-	builds acid from
43860	17814 ChEBI	salicin	+	builds acid from
43860		skimmed milk	+	hydrolysis
43860	30911 ChEBI	sorbitol	-	builds acid from
43860	28017 ChEBI	starch	+	builds acid from
43860	28017 ChEBI	starch	+	hydrolysis
43860	17992 ChEBI	sucrose	-	builds acid from
43860	17992 ChEBI	sucrose	+	builds acid from
43860	27082 ChEBI	trehalose	+	builds acid from
43860	32528 ChEBI	turanose	-	builds acid from
43860	17151 ChEBI	xylitol	-	builds acid from

Metabolite production

@ref	Chebi-ID	Metabolite
43860	15688 ChEBI	acetoin
43860	16136 ChEBI	hydrogen sulfide
43860	35581 ChEBI	indole

Metabolite tests

@ref	Chebi-ID	Metabolite	Voges-proskauer-test
43860	15688 ChEBI	acetoin	+

Enzymes

@ref	Value	Activity	Ec
43860	arginine dihydrolase	-	3.5.3.6
43860	beta-galactosidase	-	3.2.1.23
43860	catalase	+	1.11.1.6
43860	cytochrome oxidase	+	1.9.3.1
43860	gelatinase	+
43860	lysine decarboxylase	-	4.1.1.18
43860	ornithine decarboxylase	-	4.1.1.17
43860	tryptophan deaminase	-	4.1.99.1
43860	urease	-	3.5.1.5

Fatty acid profile

Metadata FA analysis

@ref

43860

Fatty acid	Percentage
C16:0	33
C15:0 iso	9
C17:0 iso	8.5
C13:0 iso	7.9
C16:1ω7c / C15:0 iso 2OH	6.7
C18:0	5.5
C15:0 anteiso	4.2
C14:0	3.9
C16:0 iso	3.6
C13:0 anteiso	2.5
C17:0 anteiso	2
C14:0 iso	1.9
C17:1 iso I /C17:1 anteiso B	1.8
C12:0 iso	1.5
C12:0	1.5
C16:1ω11c	1.2
C17:1 iso ω10c	1.1

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Marine
#Environmental	#Aquatic	#Sediment

Isolation

@ref	Sample type
43860	sediment of the South China Sea
67771	From sediments
121570	Environment, Sediments

Taxonmaps

69479

Global distribution of 16S sequence KJ812444 (>99% sequence identity) for Bacillus from Microbeatlas

Aquatic Samples	446
Soil Samples	1920
Animal Samples	1524
Plant Samples	1079
Total Samples	4969

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
121570	1	Risk group (French classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	IMG accession	NCBI tax ID	Score
66792	ASM188423v1 assembly for Bacillus paramycoides NH24A2	contig	GCA_001884235	8023021088	2026194	50.19

Genome browser: GCA_001884235

16S sequences

@ref	Description	Accession
43860	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence	KJ812444
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MT508531
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MN339968
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MT159579
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	OQ366607
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	OQ331049
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MT539292
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MW228432
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	PV628405
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MT176483
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MK782791
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MK779773
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	PV528907
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MK183820
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MK182806
124043	Bacillus paramycoides strain MCCC 1A04098 16S ribosomal RNA gene, partial sequence.	MW065486

GC content

@ref	GC-content (mol%)	Method
43860	35.2	genome sequence analysis
67771	35.2

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Bacillus paramycoides NH24A2
NCBI: GCA_001884235

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	84.80	no
125439	motility	BacteriaNetⓘ	yes	74.90	no
125439	gram_stain	BacteriaNetⓘ	variable	75.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	87.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Bacillus paramycoides NH24A2
NCBI: GCA_001884235.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	76.51	no
125438	anaerobic	anaerobicⓘ	no	94.33	yes
125438	aerobic	aerobicⓘ	no	57.46	yes
125438	spore-forming	spore-formingⓘ	yes	69.48	yes
125438	thermophilic	thermophileⓘ	no	94.82	yes
125438	flagellated	motile2+ⓘ	yes	83.03	no

Literature

Title	Authors	Journal	DOI	Year
Potential antimicrobial and fruit juice clarification activity of amylase enzyme from Bacillus strains.	Hossain KM, Khan U, Mahbubur Rahman SM, Khan MS.	Biotechnol Rep (Amst)	10.1016/j.btre.2024.e00861	2024
Molecular Characterization and Antibiogram Profiling of Bacteria Isolated From Sewage and Surface Water in Bangladesh.	Polash MA, Islam MS, Zahan N, Sarker S, Haque MH.	Scientifica (Cairo)	10.1155/sci5/1848058	2025
Biosynthesis of Zinc Oxide Nanoparticles Using Bacillus paramycoides for In Vitro Biological Activities and In Vivo Assessment Against Hepatorenal Injury Induced by CCl₄ in Rats.	El-Refai HA, Saleh AM, Mohamed SIA, Aboul Naser AF, Zaki RA, Gomaa SK, Hamed MA.	Appl Biochem Biotechnol	10.1007/s12010-023-04817-y	2024
Potential use of Bacillus paramycoides for the production of the biopolymer polyhydroxybutyrate from leftover carob fruit agro-waste.	Djerrab L, Chekroud Z, Rouabhia A, Dems MA, Attailia I, Garcia LIR, Smadi MA.	AIMS Microbiol	10.3934/microbiol.2022023	2022
Volatile Organic Compounds Produced by Bacillus sp. Strain R2 Inhibit Aspergillus flavus Growth In Vitro and in Unhulled Rice.	Wang Q, Zhang K, Yu L, Lin Q, Zhou W.	Foods	10.3390/foods13182898	2024
Study on biodegradation of used engine oil in a stirred batch bioreactor by ochrobactrum intermedium and Bacillus paramycoides isolates.	Elhamrouni I, Alhammadi E, Ishak MY.	Sci Rep	10.1038/s41598-025-20748-6	2025
Characterization of plant growth promoting activities of indigenous bacteria of phosphate mine wastes, a first step toward revegetation.	Mghazli N, Bruneel O, Zouagui R, Hakkou R, Sbabou L.	Front Microbiol	10.3389/fmicb.2022.1026991	2022
Proteomic and metabolomic approach to rationalize the differential mosquito larvicidal toxicity in Bacillus sp. isolated from the mid-gut of Culex quinquefasciatus mosquito larvae.	Colvin D, Dhuri V, Samant M, Verma H, Lokhande R, Kale A.	Anal Sci Adv	10.1002/ansa.202000081	2021
Identification and characterization of thermophilic amylase producing bacterial isolates from the brick kiln soil.	Ullah I, Khan MS, Khan SS, Ahmad W, Zheng L, Shah SUA, Ullah M, Iqbal A.	Saudi J Biol Sci	10.1016/j.sjbs.2020.11.017	2021
Diversity and Phosphate Solubilizing Characteristics of Cultivable Organophosphorus-Mineralizing Bacteria in the Sediments of Sancha Lake.	Li Y, Yu X, Zheng J, Gong Z, Xu W.	Int J Environ Res Public Health	10.3390/ijerph19042320	2022
Bio-Based and Biodegradable Polymeric Materials for a Circular Economy.	Oliver-Cuenca V, Salaris V, Munoz-Gimena PF, Aguero A, Peltzer MA, Montero VA, Arrieta MP, Sempere-Torregrosa J, Pavon C, Samper MD, Crespo GR, Kenny JM, Lopez D, Peponi L.	Polymers (Basel)	10.3390/polym16213015	2024
Biosynthesis of Poly-ss-Hydroxybutyrate (PHB) from Different Bacterial Strains Grown on Alternative Cheap Carbon Sources.	El-Kadi SM, Elbagory M, El-Zawawy HAH, El-Shaer HFA, Shoukry AA, El-Nahrawy S, Omara AE, Ali DFI	Polymers (Basel)	10.3390/polym13213801	2021
Groundwater hydro-geochemistry, quality, microbiology and human health risk assessment in semi-arid area of Rajasthan, India: a chemometric approach.	Khan N, Malik A, Nehra K	Environ Monit Assess	10.1007/s10661-021-08979-2	2021
Novel Effective Bacillus cereus Group Species "Bacillus clarus" Is Represented by Antibiotic-Producing Strain ATCC 21929 Isolated from Soil.	Mendez Acevedo M, Carroll LM, Mukherjee M, Mills E, Xiaoli L, Dudley EG, Kovac J	mSphere	10.1128/mSphere.00882-20	2020
Proposal of nine novel species of the Bacillus cereus group.	Liu Y, Du J, Lai Q, Zeng R, Ye D, Xu J, Shao Z	Int J Syst Evol Microbiol	10.1099/ijsem.0.001821	2017

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 )
#43860	Yang Liu, Juan Du, Qiliang Lai, Runying Zeng, Dezan Ye, Jun Xu, Zongze Shao: Proposal of nine novel species of the Bacillus cereus group. IJSEM 67: 2499 - 2508 2017 ( DOI 10.1099/ijsem.0.001821 , PubMed 28792367 )
#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) .
#67771	Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC;
#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 .
#121570	Collection of Institut Pasteur ; Curators of the CIP; CIP 111461
#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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Bacillus paramycoides (MCCC 1A04098, KCTC 33709, LMG 28876)

Name and taxonomic classification