Chitinophaga niastensis JS16-4 is an aerobe, mesophilic, Gram-negative bacterium that was isolated from soil.
Gram-negative rod-shaped aerobe mesophilic genome sequence 16S sequence Bacteria|
|
| Domain Bacteria |
| Phylum Bacteroidota |
| Class Chitinophagia |
| Order Chitinophagales |
| Family Chitinophagaceae |
| Genus Chitinophaga |
| Species Chitinophaga niastensis |
| Full scientific name Chitinophaga niastensis Weon et al. 2009 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 17789 | R2A MEDIUM (DSMZ Medium 830) | Medium recipe at MediaDive | Name: R2A MEDIUM (DSMZ Medium 830) Composition: Agar 15.0 g/l Casamino acids 0.5 g/l Starch 0.5 g/l Glucose 0.5 g/l Proteose peptone 0.5 g/l Yeast extract 0.5 g/l K2HPO4 0.3 g/l Na-pyruvate 0.3 g/l MgSO4 x 7 H2O 0.05 g/l Distilled water |
| 67770 | Observationquinones: MK-7 |
| @ref | Spore formation | Confidence | |
|---|---|---|---|
| 125439 | 98.4 |
| @ref | pathway | enzyme coverage | annotated reactions | external links | |
|---|---|---|---|---|---|
| 66794 | cellulose degradation | 100 | 5 of 5 | ||
| 66794 | cis-vaccenate biosynthesis | 100 | 2 of 2 | ||
| 66794 | UDP-GlcNAc biosynthesis | 100 | 3 of 3 | ||
| 66794 | acetoin degradation | 100 | 3 of 3 | ||
| 66794 | CDP-diacylglycerol biosynthesis | 100 | 2 of 2 | ||
| 66794 | kanosamine biosynthesis II | 100 | 2 of 2 | ||
| 66794 | methylglyoxal degradation | 100 | 5 of 5 | ||
| 66794 | L-lactaldehyde degradation | 100 | 3 of 3 | ||
| 66794 | adipate degradation | 100 | 2 of 2 | ||
| 66794 | sulfopterin metabolism | 100 | 4 of 4 | ||
| 66794 | coenzyme A metabolism | 100 | 4 of 4 | ||
| 66794 | 1,4-dihydroxy-6-naphthoate biosynthesis | 100 | 6 of 6 | ||
| 66794 | gluconeogenesis | 100 | 8 of 8 | ||
| 66794 | folate polyglutamylation | 100 | 1 of 1 | ||
| 66794 | anapleurotic synthesis of oxalacetate | 100 | 1 of 1 | ||
| 66794 | ethanol fermentation | 100 | 2 of 2 | ||
| 66794 | palmitate biosynthesis | 100 | 22 of 22 | ||
| 66794 | ppGpp biosynthesis | 100 | 4 of 4 | ||
| 66794 | CMP-KDO biosynthesis | 100 | 4 of 4 | ||
| 66794 | suberin monomers biosynthesis | 100 | 2 of 2 | ||
| 66794 | biotin biosynthesis | 100 | 4 of 4 | ||
| 66794 | tetrahydrofolate metabolism | 92.86 | 13 of 14 | ||
| 66794 | phenylalanine metabolism | 92.31 | 12 of 13 | ||
| 66794 | pentose phosphate pathway | 90.91 | 10 of 11 | ||
| 66794 | Entner Doudoroff pathway | 90 | 9 of 10 | ||
| 66794 | threonine metabolism | 90 | 9 of 10 | ||
| 66794 | starch degradation | 90 | 9 of 10 | ||
| 66794 | lipid A biosynthesis | 88.89 | 8 of 9 | ||
| 66794 | d-mannose degradation | 88.89 | 8 of 9 | ||
| 66794 | valine metabolism | 88.89 | 8 of 9 | ||
| 66794 | C4 and CAM-carbon fixation | 87.5 | 7 of 8 | ||
| 66794 | ubiquinone biosynthesis | 85.71 | 6 of 7 | ||
| 66794 | reductive acetyl coenzyme A pathway | 85.71 | 6 of 7 | ||
| 66794 | photosynthesis | 85.71 | 12 of 14 | ||
| 66794 | heme metabolism | 85.71 | 12 of 14 | ||
| 66794 | vitamin B12 metabolism | 85.29 | 29 of 34 | ||
| 66794 | NAD metabolism | 83.33 | 15 of 18 | ||
| 66794 | glutamate and glutamine metabolism | 82.14 | 23 of 28 | ||
| 66794 | proline metabolism | 81.82 | 9 of 11 | ||
| 66794 | vitamin K metabolism | 80 | 4 of 5 | ||
| 66794 | glycogen metabolism | 80 | 4 of 5 | ||
| 66794 | metabolism of amino sugars and derivatives | 80 | 4 of 5 | ||
| 66794 | gallate degradation | 80 | 4 of 5 | ||
| 66794 | peptidoglycan biosynthesis | 80 | 12 of 15 | ||
| 66794 | tyrosine metabolism | 78.57 | 11 of 14 | ||
| 66794 | citric acid cycle | 78.57 | 11 of 14 | ||
| 66794 | aspartate and asparagine metabolism | 77.78 | 7 of 9 | ||
| 66794 | molybdenum cofactor biosynthesis | 77.78 | 7 of 9 | ||
| 66794 | chorismate metabolism | 77.78 | 7 of 9 | ||
| 66794 | serine metabolism | 77.78 | 7 of 9 | ||
| 66794 | leucine metabolism | 76.92 | 10 of 13 | ||
| 66794 | isoleucine metabolism | 75 | 6 of 8 | ||
| 66794 | acetate fermentation | 75 | 3 of 4 | ||
| 66794 | glycogen biosynthesis | 75 | 3 of 4 | ||
| 66794 | purine metabolism | 74.47 | 70 of 94 | ||
| 66794 | tryptophan metabolism | 73.68 | 28 of 38 | ||
| 66794 | flavin biosynthesis | 73.33 | 11 of 15 | ||
| 66794 | methionine metabolism | 73.08 | 19 of 26 | ||
| 66794 | vitamin B6 metabolism | 72.73 | 8 of 11 | ||
| 66794 | degradation of sugar acids | 72 | 18 of 25 | ||
| 66794 | propanol degradation | 71.43 | 5 of 7 | ||
| 66794 | cardiolipin biosynthesis | 71.43 | 5 of 7 | ||
| 66794 | lipid metabolism | 70.97 | 22 of 31 | ||
| 66794 | glycolysis | 70.59 | 12 of 17 | ||
| 66794 | propionate fermentation | 70 | 7 of 10 | ||
| 66794 | vitamin B1 metabolism | 69.23 | 9 of 13 | ||
| 66794 | lysine metabolism | 69.05 | 29 of 42 | ||
| 66794 | alanine metabolism | 68.97 | 20 of 29 | ||
| 66794 | formaldehyde oxidation | 66.67 | 2 of 3 | ||
| 66794 | acetyl CoA biosynthesis | 66.67 | 2 of 3 | ||
| 66794 | CO2 fixation in Crenarchaeota | 66.67 | 6 of 9 | ||
| 66794 | octane oxidation | 66.67 | 2 of 3 | ||
| 66794 | glycolate and glyoxylate degradation | 66.67 | 4 of 6 | ||
| 66794 | histidine metabolism | 65.52 | 19 of 29 | ||
| 66794 | pyrimidine metabolism | 64.44 | 29 of 45 | ||
| 66794 | d-xylose degradation | 63.64 | 7 of 11 | ||
| 66794 | ketogluconate metabolism | 62.5 | 5 of 8 | ||
| 66794 | 6-hydroxymethyl-dihydropterin diphosphate biosynthesis | 62.5 | 5 of 8 | ||
| 66794 | isoprenoid biosynthesis | 61.54 | 16 of 26 | ||
| 66794 | cysteine metabolism | 61.11 | 11 of 18 | ||
| 66794 | degradation of hexoses | 61.11 | 11 of 18 | ||
| 66794 | phenylacetate degradation (aerobic) | 60 | 3 of 5 | ||
| 66794 | coenzyme M biosynthesis | 60 | 6 of 10 | ||
| 66794 | arginine metabolism | 58.33 | 14 of 24 | ||
| 66794 | non-pathway related | 55.26 | 21 of 38 | ||
| 66794 | metabolism of disaccharids | 54.55 | 6 of 11 | ||
| 66794 | urea cycle | 53.85 | 7 of 13 | ||
| 66794 | degradation of pentoses | 53.57 | 15 of 28 | ||
| 66794 | 3-phenylpropionate degradation | 53.33 | 8 of 15 | ||
| 66794 | butanoate fermentation | 50 | 2 of 4 | ||
| 66794 | quinate degradation | 50 | 1 of 2 | ||
| 66794 | selenocysteine biosynthesis | 50 | 3 of 6 | ||
| 66794 | phenol degradation | 50 | 10 of 20 | ||
| 66794 | ribulose monophosphate pathway | 50 | 1 of 2 | ||
| 66794 | glycine metabolism | 50 | 5 of 10 | ||
| 66794 | pantothenate biosynthesis | 50 | 3 of 6 | ||
| 66794 | phenylmercury acetate degradation | 50 | 1 of 2 | ||
| 66794 | glutathione metabolism | 50 | 7 of 14 | ||
| 66794 | aminopropanol phosphate biosynthesis | 50 | 1 of 2 | ||
| 66794 | vitamin E metabolism | 50 | 2 of 4 | ||
| 66794 | degradation of aromatic, nitrogen containing compounds | 50 | 6 of 12 | ||
| 66794 | lactate fermentation | 50 | 2 of 4 | ||
| 66794 | dTDPLrhamnose biosynthesis | 50 | 4 of 8 | ||
| 66794 | cyclohexanol degradation | 50 | 2 of 4 | ||
| 66794 | polyamine pathway | 47.83 | 11 of 23 | ||
| 66794 | oxidative phosphorylation | 47.25 | 43 of 91 | ||
| 66794 | sulfate reduction | 46.15 | 6 of 13 | ||
| 66794 | phenylpropanoid biosynthesis | 46.15 | 6 of 13 | ||
| 66794 | arachidonic acid metabolism | 44.44 | 8 of 18 | ||
| 66794 | 4-hydroxymandelate degradation | 44.44 | 4 of 9 | ||
| 66794 | nitrate assimilation | 44.44 | 4 of 9 | ||
| 66794 | ascorbate metabolism | 40.91 | 9 of 22 | ||
| 66794 | myo-inositol biosynthesis | 40 | 4 of 10 | ||
| 66794 | arachidonate biosynthesis | 40 | 2 of 5 | ||
| 66794 | 3-chlorocatechol degradation | 40 | 2 of 5 | ||
| 66794 | lipoate biosynthesis | 40 | 2 of 5 | ||
| 66794 | androgen and estrogen metabolism | 37.5 | 6 of 16 | ||
| 66794 | carnitine metabolism | 37.5 | 3 of 8 | ||
| 66794 | cyanate degradation | 33.33 | 1 of 3 | ||
| 66794 | sulfoquinovose degradation | 33.33 | 1 of 3 | ||
| 66794 | (5R)-carbapenem carboxylate biosynthesis | 33.33 | 1 of 3 | ||
| 66794 | sphingosine metabolism | 33.33 | 2 of 6 | ||
| 66794 | IAA biosynthesis | 33.33 | 1 of 3 | ||
| 66794 | chlorophyll metabolism | 33.33 | 6 of 18 | ||
| 66794 | degradation of sugar alcohols | 31.25 | 5 of 16 | ||
| 66794 | phosphatidylethanolamine bioynthesis | 30.77 | 4 of 13 | ||
| 66794 | mevalonate metabolism | 28.57 | 2 of 7 | ||
| 66794 | aclacinomycin biosynthesis | 28.57 | 2 of 7 | ||
| 66794 | dolichyl-diphosphooligosaccharide biosynthesis | 27.27 | 3 of 11 | ||
| 66794 | catecholamine biosynthesis | 25 | 1 of 4 | ||
| 66794 | toluene degradation | 25 | 1 of 4 | ||
| 66794 | allantoin degradation | 22.22 | 2 of 9 |
Global distribution of 16S sequence EU714260 (>99% sequence identity) for Chitinophaga niastensis subclade from Microbeatlas ![]()
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 17789 | Chitinophaga niastensis strain JS16-4 16S ribosomal RNA gene, partial sequence | EU714260 | 1402 | 536980 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | no | 98.40 | no |
| 125439 | motility | BacteriaNetⓘ | no | 59.50 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 99.10 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 97.60 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | no | 96.01 | yes |
| 125438 | anaerobic | anaerobicⓘ | no | 97.82 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 77.46 | no |
| 125438 | aerobic | aerobicⓘ | yes | 88.29 | yes |
| 125438 | thermophilic | thermophileⓘ | no | 97.31 | no |
| 125438 | flagellated | motile2+ⓘ | no | 86.25 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Phylogeny | Chitinophaga solisilvae sp. nov., isolated from forest soil. | Ping W, Zhang Y, Pang H, Zhang J, Li D, Li Y, Zhang J | Int J Syst Evol Microbiol | 10.1099/ijsem.0.004350 | 2020 | |
| Phylogeny | Aurantisolimonas haloimpatiens gen. nov., sp. nov., a bacterium isolated from soil. | Liu MJ, Jin CZ, Asem MD, Ju YJ, Park DJ, Salam N, Xiao M, Li WJ, Kim CJ | Int J Syst Evol Microbiol | 10.1099/ijsem.0.002709 | 2018 | |
| Phylogeny | Chitinophaga taiwanensis sp. nov., isolated from the rhizosphere of Arabidopsis thaliana. | Lin SY, Hameed A, Liu YC, Hsu YH, Lai WA, Huang HI, Young CC | Int J Syst Evol Microbiol | 10.1099/ijs.0.054452-0 | 2013 | |
| Phylogeny | Chitinophaga niabensis sp. nov. and Chitinophaga niastensis sp. nov., isolated from soil. | Weon HY, Yoo SH, Kim YJ, Son JA, Kim BY, Kwon SW, Koo BS | Int J Syst Evol Microbiol | 10.1099/ijs.0.004804-0 | 2009 |
| #17789 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 24859 |
| #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 ) |
| #29045 | Barberan A, Caceres Velazquez H, Jones S, Fierer N.: Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information. mSphere 2: 2017 ( DOI 10.1128/mSphere.00237-17 , PubMed 28776041 ) - originally annotated from #25475 (see below) |
| #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 ) |
| #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 . |
| #86742 | Reimer, L.C., Lissin, A.,Schober, I., Witte,J.F., Podstawka, A., Lüken, H., Bunk, B.,Overmann, J.: StrainInfo: A central database for resolving microbial strain identifiers . ( DOI 10.60712/SI-ID403274.1 ) |
| #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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