Nannocystis pusilla (DSM 14622, CIP 109121, JCM 12635)

Name: Nannocystis pusilla (DSM 14622, CIP 109121, JCM 12635)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 10300

Type strain

Strain Designation Na p29

Culture col. no. DSM 14622 CIP 109121 JCM 12635 Na p29

NCBI tax ID(s) 889268

Special Collections DSMZ JCM CIP Reichenbach collection

History DSMZ <- H. Reichenbach; Na p29 JCM <-- DSM 14622 <-- H. Reichenbach Na p29.

Links

Nannocystis pusilla Na p29 is a bacterium that builds a fruiting body and was isolated from soil with decaying plant material.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 215409

DSM 14622,CIP 109121,JCM 12635

@ref 20215

Last LPSN update 2026-05-29 08:27:18

Domain Bacteria

Phylum Pseudomonadota

Class Deltaproteobacteria

Order Myxococcales

Family Nannocystaceae

Genus Nannocystis

Species Nannocystis pusilla

Full scientific name Nannocystis pusilla Reichenbach 2007

BacDive ID	Other strains from **Nannocystis pusilla** (20)	Type strain
10299	N. pusilla Na p23, DSM 14621
10301	N. pusilla Na p1, DSM 53154
10302	N. pusilla Na p3, DSM 53155
10303	N. pusilla Na p4, DSM 53156
10304	N. pusilla Na p5, DSM 53157
10305	N. pusilla Na p6, DSM 53158
10306	N. pusilla Na p7, DSM 53159
10307	N. pusilla Na p9, DSM 53160
10308	N. pusilla Na p10, DSM 53161
10309	N. pusilla Na p13, DSM 53162
10310	N. pusilla Na p16, DSM 53163
10311	N. pusilla Na p17, DSM 53164
10312	N. pusilla Na p20, DSM 53165
10313	N. pusilla Na p21, DSM 53166
10314	N. pusilla Na p24, DSM 53167
10315	N. pusilla Na p25, DSM 53168
10316	N. pusilla Na p26, DSM 53169
10317	N. pusilla Na p27, DSM 53170
10318	N. pusilla Na p28, DSM 53171
10319	N. pusilla Na p30, DSM 53172

Morphology

Multicellular morphology

@ref	Forms multicellular complex	Complex name
18281		fruiting body

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
5415	VY/2 AGAR (DSMZ Medium 9)		Medium recipe at MediaDive	Name: VY/2 AGAR (DSMZ Medium 9) Composition: Agar 15.0 g/l Baker's yeast 5.0 g/l CaCl2 x 2 H2O 1.36 g/l Vitamin B12 0.0005 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
5415	positive	growth	30
67770	positive	growth	30

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	98.958

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Soil
#Host	#Plants	#Decomposing plant

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
5415	soil with decaying plant material	California	USA	USA	North America
67770	Soil with plant residues		USA	USA	North America

Taxonmaps

69479

Global distribution of 16S sequence GU207878 (>99% sequence identity) for Nannocystis from Microbeatlas

Aquatic Samples	253
Soil Samples	589
Animal Samples	46
Plant Samples	82
Total Samples	970

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
5415	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM2662666v1 assembly for Nannocystis pusilla Na p29	contig	GCA_026626665	889268.8	8048784512	889268	65.13

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	Nannocystis pusilla partial 16S rRNA gene, type strain DSM 14622T	FR749907	1518		889268
20218	Nannocystis pusilla strain Na p29 16S ribosomal RNA gene, complete sequence	GU207878	1524		889268

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM2662666v1 assembly for Nannocystis pusilla Na p29
NCBI: GCA_026626665

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	98.96	no
125439	gram_stain	BacteriaNetⓘ	negative	56.26	no
125439	motility	BacteriaNetⓘ	yes	41.41	no
125439	spore_formation	BacteriaNetⓘ	yes	50.28	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Nannocystis pusilla Na p29
NCBI: GCA_026626665.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	81.25	no
125438	anaerobic	anaerobicⓘ	no	82.71	no
125438	aerobic	aerobicⓘ	yes	82.33	no
125438	spore-forming	spore-formingⓘ	no	80.54	no
125438	thermophilic	thermophileⓘ	no	91.24	yes
125438	flagellated	motile2+ⓘ	no	50.81	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Nannocystis konarekensis sp. nov., a novel myxobacterium from an Iranian desert.	Mohr KI, Moradi A, Glaeser SP, Kampfer P, Gemperlein K, Nubel U, Schumann P, Muller R, Wink J	Int J Syst Evol Microbiol	10.1099/ijsem.0.002569	2018

References

#5415	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 14622
#18281	Reichenbach, H.: Collection description and documentation of myxobacteria by H. Reichenbach, HZI (formerly GBF); Collection curr. located at the DSMZ . Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH:
#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 )
#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 .
#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 )

Content

About us

Nannocystis pusilla (DSM 14622, CIP 109121, JCM 12635)

Name and taxonomic classification

Morphology

Multicellular morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_026626665

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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