Magnetospirillum molischianum S is an anaerobe, mesophilic, spiral-shaped prokaryote that was isolated from mud from a ditch.
spiral-shaped anaerobe mesophilic genome sequence 16S sequence| @ref 20215 |
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| Domain Pseudomonadati |
| Phylum Pseudomonadota |
| Class Alphaproteobacteria |
| Order Rhodospirillales |
| Family Rhodospirillaceae |
| Genus Magnetospirillum |
| Species Magnetospirillum molischianum |
| Full scientific name Magnetospirillum molischianum (Giesberger 1947) Hördt et al. 2020 |
| Synonyms (2) |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 2105 | RHODOSPIRILLACEAE MEDIUM (modified) (DSMZ Medium 27) | Medium recipe at MediaDive | Name: RHODOSPIRILLACEAE MEDIUM (modified) (DSMZ Medium 27) Composition: Disodium succinate 1.0 g/l KH2PO4 0.5 g/l Ammonium acetate 0.5 g/l NaCl 0.4 g/l NH4Cl 0.4 g/l MgSO4 x 7 H2O 0.4 g/l Yeast extract 0.3 g/l L-Cysteine HCl 0.3 g/l CaCl2 x 2 H2O 0.05 g/l Fe(III) citrate 0.005 g/l Resazurin 0.005 g/l H3BO3 0.0003 g/l CoCl2 x 6 H2O 0.0002 g/l ZnSO4 x 7 H2O 0.0001 g/l MnCl2 x 4 H2O 3e-05 g/l Na2MoO4 x 2 H2O 3e-05 g/l NiCl2 x 6 H2O 2e-05 g/l CuCl2 x 2 H2O 1e-05 g/l Vitamin B12 Distilled water |
| @ref | Spore formation | Confidence | |
|---|---|---|---|
| 125439 | 99.4 |
| 67771 | Observationquinones: Q-9, MK-9 |
| @ref | pathway | enzyme coverage | annotated reactions | external links | |
|---|---|---|---|---|---|
| 66794 | ppGpp biosynthesis | 100 | 4 of 4 | ||
| 66794 | propionate fermentation | 100 | 10 of 10 | ||
| 66794 | cis-vaccenate biosynthesis | 100 | 2 of 2 | ||
| 66794 | acetoin degradation | 100 | 3 of 3 | ||
| 66794 | C4 and CAM-carbon fixation | 100 | 8 of 8 | ||
| 66794 | methylglyoxal degradation | 100 | 5 of 5 | ||
| 66794 | enterobactin biosynthesis | 100 | 3 of 3 | ||
| 66794 | acetate fermentation | 100 | 4 of 4 | ||
| 66794 | palmitate biosynthesis | 100 | 22 of 22 | ||
| 66794 | biotin biosynthesis | 100 | 4 of 4 | ||
| 66794 | L-lactaldehyde degradation | 100 | 3 of 3 | ||
| 66794 | adipate degradation | 100 | 2 of 2 | ||
| 66794 | anapleurotic synthesis of oxalacetate | 100 | 1 of 1 | ||
| 66794 | ceramide biosynthesis | 100 | 1 of 1 | ||
| 66794 | hydrogen production | 100 | 5 of 5 | ||
| 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 | coenzyme A metabolism | 100 | 4 of 4 | ||
| 66794 | photosynthesis | 92.86 | 13 of 14 | ||
| 66794 | phenylalanine metabolism | 92.31 | 12 of 13 | ||
| 66794 | lipid A biosynthesis | 88.89 | 8 of 9 | ||
| 66794 | aspartate and asparagine metabolism | 88.89 | 8 of 9 | ||
| 66794 | gluconeogenesis | 87.5 | 7 of 8 | ||
| 66794 | tetrahydrofolate metabolism | 85.71 | 12 of 14 | ||
| 66794 | ubiquinone biosynthesis | 85.71 | 6 of 7 | ||
| 66794 | propanol degradation | 85.71 | 6 of 7 | ||
| 66794 | vitamin B1 metabolism | 84.62 | 11 of 13 | ||
| 66794 | phenylacetate degradation (aerobic) | 80 | 4 of 5 | ||
| 66794 | ethylmalonyl-CoA pathway | 80 | 4 of 5 | ||
| 66794 | threonine metabolism | 80 | 8 of 10 | ||
| 66794 | vitamin K metabolism | 80 | 4 of 5 | ||
| 66794 | peptidoglycan biosynthesis | 80 | 12 of 15 | ||
| 66794 | cellulose degradation | 80 | 4 of 5 | ||
| 66794 | alanine metabolism | 79.31 | 23 of 29 | ||
| 66794 | citric acid cycle | 78.57 | 11 of 14 | ||
| 66794 | heme metabolism | 78.57 | 11 of 14 | ||
| 66794 | chorismate metabolism | 77.78 | 7 of 9 | ||
| 66794 | CO2 fixation in Crenarchaeota | 77.78 | 7 of 9 | ||
| 66794 | NAD metabolism | 77.78 | 14 of 18 | ||
| 66794 | valine metabolism | 77.78 | 7 of 9 | ||
| 66794 | d-mannose degradation | 77.78 | 7 of 9 | ||
| 66794 | serine metabolism | 77.78 | 7 of 9 | ||
| 66794 | leucine metabolism | 76.92 | 10 of 13 | ||
| 66794 | vitamin B12 metabolism | 76.47 | 26 of 34 | ||
| 66794 | glutamate and glutamine metabolism | 75 | 21 of 28 | ||
| 66794 | glycogen biosynthesis | 75 | 3 of 4 | ||
| 66794 | CMP-KDO biosynthesis | 75 | 3 of 4 | ||
| 66794 | butanoate fermentation | 75 | 3 of 4 | ||
| 66794 | isoleucine metabolism | 75 | 6 of 8 | ||
| 66794 | vitamin B6 metabolism | 72.73 | 8 of 11 | ||
| 66794 | cardiolipin biosynthesis | 71.43 | 5 of 7 | ||
| 66794 | glutathione metabolism | 71.43 | 10 of 14 | ||
| 66794 | reductive acetyl coenzyme A pathway | 71.43 | 5 of 7 | ||
| 66794 | purine metabolism | 68.09 | 64 of 94 | ||
| 66794 | octane oxidation | 66.67 | 2 of 3 | ||
| 66794 | acetyl CoA biosynthesis | 66.67 | 2 of 3 | ||
| 66794 | formaldehyde oxidation | 66.67 | 2 of 3 | ||
| 66794 | non-pathway related | 65.79 | 25 of 38 | ||
| 66794 | methionine metabolism | 65.38 | 17 of 26 | ||
| 66794 | isoprenoid biosynthesis | 65.38 | 17 of 26 | ||
| 66794 | glycolysis | 64.71 | 11 of 17 | ||
| 66794 | 6-hydroxymethyl-dihydropterin diphosphate biosynthesis | 62.5 | 5 of 8 | ||
| 66794 | degradation of sugar alcohols | 62.5 | 10 of 16 | ||
| 66794 | pyrimidine metabolism | 62.22 | 28 of 45 | ||
| 66794 | chlorophyll metabolism | 61.11 | 11 of 18 | ||
| 66794 | oxidative phosphorylation | 60.44 | 55 of 91 | ||
| 66794 | glycogen metabolism | 60 | 3 of 5 | ||
| 66794 | flavin biosynthesis | 60 | 9 of 15 | ||
| 66794 | lipid metabolism | 58.06 | 18 of 31 | ||
| 66794 | cysteine metabolism | 55.56 | 10 of 18 | ||
| 66794 | tryptophan metabolism | 55.26 | 21 of 38 | ||
| 66794 | histidine metabolism | 55.17 | 16 of 29 | ||
| 66794 | arginine metabolism | 54.17 | 13 of 24 | ||
| 66794 | sulfate reduction | 53.85 | 7 of 13 | ||
| 66794 | urea cycle | 53.85 | 7 of 13 | ||
| 66794 | sulfopterin metabolism | 50 | 2 of 4 | ||
| 66794 | 4-hydroxyphenylacetate degradation | 50 | 5 of 10 | ||
| 66794 | dTDPLrhamnose biosynthesis | 50 | 4 of 8 | ||
| 66794 | alginate biosynthesis | 50 | 2 of 4 | ||
| 66794 | starch degradation | 50 | 5 of 10 | ||
| 66794 | glycolate and glyoxylate degradation | 50 | 3 of 6 | ||
| 66794 | ethanol fermentation | 50 | 1 of 2 | ||
| 66794 | tyrosine metabolism | 50 | 7 of 14 | ||
| 66794 | glycine metabolism | 50 | 5 of 10 | ||
| 66794 | quinate degradation | 50 | 1 of 2 | ||
| 66794 | lysine metabolism | 50 | 21 of 42 | ||
| 66794 | aminopropanol phosphate biosynthesis | 50 | 1 of 2 | ||
| 66794 | phosphatidylethanolamine bioynthesis | 46.15 | 6 of 13 | ||
| 66794 | metabolism of disaccharids | 45.45 | 5 of 11 | ||
| 66794 | proline metabolism | 45.45 | 5 of 11 | ||
| 66794 | nitrate assimilation | 44.44 | 4 of 9 | ||
| 66794 | degradation of aromatic, nitrogen containing compounds | 41.67 | 5 of 12 | ||
| 66794 | carotenoid biosynthesis | 40.91 | 9 of 22 | ||
| 66794 | ascorbate metabolism | 40.91 | 9 of 22 | ||
| 66794 | arachidonate biosynthesis | 40 | 2 of 5 | ||
| 66794 | glycine betaine biosynthesis | 40 | 2 of 5 | ||
| 66794 | lipoate biosynthesis | 40 | 2 of 5 | ||
| 66794 | ketogluconate metabolism | 37.5 | 3 of 8 | ||
| 66794 | cholesterol biosynthesis | 36.36 | 4 of 11 | ||
| 66794 | pentose phosphate pathway | 36.36 | 4 of 11 | ||
| 66794 | cyanate degradation | 33.33 | 1 of 3 | ||
| 66794 | molybdenum cofactor biosynthesis | 33.33 | 3 of 9 | ||
| 66794 | sphingosine metabolism | 33.33 | 2 of 6 | ||
| 66794 | IAA biosynthesis | 33.33 | 1 of 3 | ||
| 66794 | pantothenate biosynthesis | 33.33 | 2 of 6 | ||
| 66794 | selenocysteine biosynthesis | 33.33 | 2 of 6 | ||
| 66794 | androgen and estrogen metabolism | 31.25 | 5 of 16 | ||
| 66794 | coenzyme M biosynthesis | 30 | 3 of 10 | ||
| 66794 | myo-inositol biosynthesis | 30 | 3 of 10 | ||
| 66794 | Entner Doudoroff pathway | 30 | 3 of 10 | ||
| 66794 | arachidonic acid metabolism | 27.78 | 5 of 18 | ||
| 66794 | degradation of hexoses | 27.78 | 5 of 18 | ||
| 66794 | polyamine pathway | 26.09 | 6 of 23 | ||
| 66794 | carnitine metabolism | 25 | 2 of 8 | ||
| 66794 | lactate fermentation | 25 | 1 of 4 | ||
| 66794 | cyclohexanol degradation | 25 | 1 of 4 | ||
| 66794 | toluene degradation | 25 | 1 of 4 | ||
| 66794 | methanogenesis from CO2 | 25 | 3 of 12 | ||
| 66794 | phenylpropanoid biosynthesis | 23.08 | 3 of 13 | ||
| 66794 | degradation of pentoses | 21.43 | 6 of 28 |
Global distribution of 16S sequence FR733695 (>99% sequence identity) for Magnetospirillum from Microbeatlas ![]()
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 78.70 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.70 | no |
| 125439 | motility | BacteriaNetⓘ | yes | 77.50 | no |
| 125439 | spore_formation | BacteriaNetⓘ | no | 99.40 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 98.07 | yes |
| 125438 | anaerobic | anaerobicⓘ | yes | 61.21 | yes |
| 125438 | spore-forming | spore-formingⓘ | no | 89.67 | no |
| 125438 | aerobic | aerobicⓘ | no | 78.04 | yes |
| 125438 | thermophilic | thermophileⓘ | no | 93.78 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 76.55 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Genetics | Analysis of 1,000+ Type-Strain Genomes Substantially Improves Taxonomic Classification of Alphaproteobacteria. | Hordt A, Lopez MG, Meier-Kolthoff JP, Schleuning M, Weinhold LM, Tindall BJ, Gronow S, Kyrpides NC, Woyke T, Goker M. | Front Microbiol | 10.3389/fmicb.2020.00468 | 2020 | |
| Metabolism | Stark absorption spectroscopy on the carotenoids bound to B800-820 and B800-850 type LH2 complexes from a purple photosynthetic bacterium, Phaeospirillum molischianum strain DSM120. | Horibe T, Qian P, Hunter CN, Hashimoto H | Arch Biochem Biophys | 10.1016/j.abb.2014.12.015 | 2014 | |
| Genetics | Draft genome sequence of the purple photosynthetic bacterium Phaeospirillum molischianum DSM120, a particularly versatile bacterium. | Duquesne K, Prima V, Ji B, Rouy Z, Medigue C, Talla E, Sturgis JN | J Bacteriol | 10.1128/JB.00605-12 | 2012 | |
| Metabolism | Antenna mixing in photosynthetic membranes from Phaeospirillum molischianum. | Mascle-Allemand C, Duquesne K, Lebrun R, Scheuring S, Sturgis JN | Proc Natl Acad Sci U S A | 10.1073/pnas.0914854107 | 2010 | |
| Enzymology | Electron paramagnetic resonance studies of ferric cytochrome c' from photosynthetic bacteria. | Fujii S, Yoshimura T, Kamada H, Yamaguchi K, Suzuki S, Shidara S, Takakuwa S | Biochim Biophys Acta | 10.1016/0167-4838(95)00092-9 | 1995 | |
| Phylogeny | Phaeospirillum tilakii sp. nov., a phototrophic alphaproteobacterium isolated from aquatic sediments. | Raj PS, Chakravarthy SK, Ramaprasad EVV, Sasikala C, Ramana CV | Int J Syst Evol Microbiol | 10.1099/ijs.0.032250-0 | 2011 |
| #2105 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 120 |
| #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) . |
| #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 ) |
| #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 . |
| #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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