Mycobacterium shinjukuense DSM 45663 is an aerobe, mesophilic prokaryote that was isolated from sputum.
aerobe mesophilic genome sequence 16S sequence| @ref 20215 |
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| Domain Bacillati |
| Phylum Actinomycetota |
| Class Actinomycetes |
| Order Mycobacteriales |
| Family Mycobacteriaceae |
| Genus Mycobacterium |
| Species Mycobacterium shinjukuense |
| Full scientific name Mycobacterium shinjukuense Saito et al. 2011 |
| 59937 | Incubation period7-10 days |
| @ref: | 18021 |
| multimedia content: | DSM_45663.jpg |
| multimedia.multimedia content: | https://www.dsmz.de/microorganisms/photos/DSM_45663.jpg |
| caption: | Medium 645 37°C |
| intellectual property rights: | © Leibniz-Institut DSMZ |
| manual_annotation: | 1 |
| @ref | Name | Growth | Medium link | Composition | |
|---|---|---|---|---|---|
| 18021 | MIDDLEBROOK MEDIUM (DSMZ Medium 645) | Medium recipe at MediaDive | Name: MIDDLEBROOK MEDIUM (DSMZ Medium 645) Composition: Bacto Middlebrook 7H10 agar 20.9945 g/l Glycerol Distilled water |
| @ref | pathway | enzyme coverage | annotated reactions | external links | |
|---|---|---|---|---|---|
| 66794 | adipate degradation | 100 | 2 of 2 | ||
| 66794 | methylglyoxal degradation | 100 | 5 of 5 | ||
| 66794 | butanoate fermentation | 100 | 4 of 4 | ||
| 66794 | vitamin K metabolism | 100 | 5 of 5 | ||
| 66794 | valine metabolism | 100 | 9 of 9 | ||
| 66794 | cis-vaccenate biosynthesis | 100 | 2 of 2 | ||
| 66794 | formaldehyde oxidation | 100 | 3 of 3 | ||
| 66794 | phenylmercury acetate degradation | 100 | 2 of 2 | ||
| 66794 | UDP-GlcNAc biosynthesis | 100 | 3 of 3 | ||
| 66794 | glycolate and glyoxylate degradation | 100 | 6 of 6 | ||
| 66794 | CDP-diacylglycerol biosynthesis | 100 | 2 of 2 | ||
| 66794 | biotin biosynthesis | 100 | 4 of 4 | ||
| 66794 | cardiolipin biosynthesis | 100 | 7 of 7 | ||
| 66794 | suberin monomers biosynthesis | 100 | 2 of 2 | ||
| 66794 | coenzyme A metabolism | 100 | 4 of 4 | ||
| 66794 | octane oxidation | 100 | 3 of 3 | ||
| 66794 | ethanol fermentation | 100 | 2 of 2 | ||
| 66794 | folate polyglutamylation | 100 | 1 of 1 | ||
| 66794 | anapleurotic synthesis of oxalacetate | 100 | 1 of 1 | ||
| 66794 | palmitate biosynthesis | 100 | 22 of 22 | ||
| 66794 | aerobactin biosynthesis | 100 | 1 of 1 | ||
| 66794 | ppGpp biosynthesis | 100 | 4 of 4 | ||
| 66794 | IAA biosynthesis | 100 | 3 of 3 | ||
| 66794 | taurine degradation | 100 | 1 of 1 | ||
| 66794 | cyanate degradation | 100 | 3 of 3 | ||
| 66794 | phenylalanine metabolism | 92.31 | 12 of 13 | ||
| 66794 | threonine metabolism | 90 | 9 of 10 | ||
| 66794 | starch degradation | 90 | 9 of 10 | ||
| 66794 | propionate fermentation | 90 | 9 of 10 | ||
| 66794 | chorismate metabolism | 88.89 | 8 of 9 | ||
| 66794 | CO2 fixation in Crenarchaeota | 88.89 | 8 of 9 | ||
| 66794 | aspartate and asparagine metabolism | 88.89 | 8 of 9 | ||
| 66794 | molybdenum cofactor biosynthesis | 88.89 | 8 of 9 | ||
| 66794 | peptidoglycan biosynthesis | 86.67 | 13 of 15 | ||
| 66794 | propanol degradation | 85.71 | 6 of 7 | ||
| 66794 | glutamate and glutamine metabolism | 85.71 | 24 of 28 | ||
| 66794 | citric acid cycle | 85.71 | 12 of 14 | ||
| 66794 | leucine metabolism | 84.62 | 11 of 13 | ||
| 66794 | pentose phosphate pathway | 81.82 | 9 of 11 | ||
| 66794 | ethylmalonyl-CoA pathway | 80 | 4 of 5 | ||
| 66794 | glycogen metabolism | 80 | 4 of 5 | ||
| 66794 | factor 420 biosynthesis | 80 | 4 of 5 | ||
| 66794 | cellulose degradation | 80 | 4 of 5 | ||
| 66794 | flavin biosynthesis | 80 | 12 of 15 | ||
| 66794 | phenylacetate degradation (aerobic) | 80 | 4 of 5 | ||
| 66794 | hydrogen production | 80 | 4 of 5 | ||
| 66794 | photosynthesis | 78.57 | 11 of 14 | ||
| 66794 | heme metabolism | 78.57 | 11 of 14 | ||
| 66794 | serine metabolism | 77.78 | 7 of 9 | ||
| 66794 | NAD metabolism | 77.78 | 14 of 18 | ||
| 66794 | d-mannose degradation | 77.78 | 7 of 9 | ||
| 66794 | lipid metabolism | 77.42 | 24 of 31 | ||
| 66794 | vitamin B1 metabolism | 76.92 | 10 of 13 | ||
| 66794 | purine metabolism | 76.6 | 72 of 94 | ||
| 66794 | lactate fermentation | 75 | 3 of 4 | ||
| 66794 | C4 and CAM-carbon fixation | 75 | 6 of 8 | ||
| 66794 | isoleucine metabolism | 75 | 6 of 8 | ||
| 66794 | dTDPLrhamnose biosynthesis | 75 | 6 of 8 | ||
| 66794 | glycogen biosynthesis | 75 | 3 of 4 | ||
| 66794 | acetate fermentation | 75 | 3 of 4 | ||
| 66794 | cyclohexanol degradation | 75 | 3 of 4 | ||
| 66794 | toluene degradation | 75 | 3 of 4 | ||
| 66794 | sulfopterin metabolism | 75 | 3 of 4 | ||
| 66794 | metabolism of disaccharids | 72.73 | 8 of 11 | ||
| 66794 | alanine metabolism | 72.41 | 21 of 29 | ||
| 66794 | reductive acetyl coenzyme A pathway | 71.43 | 5 of 7 | ||
| 66794 | ubiquinone biosynthesis | 71.43 | 5 of 7 | ||
| 66794 | glycolysis | 70.59 | 12 of 17 | ||
| 66794 | urea cycle | 69.23 | 9 of 13 | ||
| 66794 | androgen and estrogen metabolism | 68.75 | 11 of 16 | ||
| 66794 | degradation of sugar alcohols | 68.75 | 11 of 16 | ||
| 66794 | L-lactaldehyde degradation | 66.67 | 2 of 3 | ||
| 66794 | acetyl CoA biosynthesis | 66.67 | 2 of 3 | ||
| 66794 | cysteine metabolism | 66.67 | 12 of 18 | ||
| 66794 | acetoin degradation | 66.67 | 2 of 3 | ||
| 66794 | degradation of aromatic, nitrogen containing compounds | 66.67 | 8 of 12 | ||
| 66794 | enterobactin biosynthesis | 66.67 | 2 of 3 | ||
| 66794 | tryptophan metabolism | 65.79 | 25 of 38 | ||
| 66794 | pyrimidine metabolism | 64.44 | 29 of 45 | ||
| 66794 | tetrahydrofolate metabolism | 64.29 | 9 of 14 | ||
| 66794 | glutathione metabolism | 64.29 | 9 of 14 | ||
| 66794 | proline metabolism | 63.64 | 7 of 11 | ||
| 66794 | 6-hydroxymethyl-dihydropterin diphosphate biosynthesis | 62.5 | 5 of 8 | ||
| 66794 | gluconeogenesis | 62.5 | 5 of 8 | ||
| 66794 | lysine metabolism | 61.9 | 26 of 42 | ||
| 66794 | isoprenoid biosynthesis | 61.54 | 16 of 26 | ||
| 66794 | non-pathway related | 60.53 | 23 of 38 | ||
| 66794 | glycine betaine biosynthesis | 60 | 3 of 5 | ||
| 66794 | 4-hydroxyphenylacetate degradation | 60 | 6 of 10 | ||
| 66794 | gallate degradation | 60 | 3 of 5 | ||
| 66794 | 3-chlorocatechol degradation | 60 | 3 of 5 | ||
| 66794 | 3-phenylpropionate degradation | 60 | 9 of 15 | ||
| 66794 | arachidonate biosynthesis | 60 | 3 of 5 | ||
| 66794 | methionine metabolism | 57.69 | 15 of 26 | ||
| 66794 | 4-hydroxymandelate degradation | 55.56 | 5 of 9 | ||
| 66794 | histidine metabolism | 55.17 | 16 of 29 | ||
| 66794 | oxidative phosphorylation | 54.95 | 50 of 91 | ||
| 66794 | cholesterol biosynthesis | 54.55 | 6 of 11 | ||
| 66794 | sphingosine metabolism | 50 | 3 of 6 | ||
| 66794 | pantothenate biosynthesis | 50 | 3 of 6 | ||
| 66794 | arginine metabolism | 50 | 12 of 24 | ||
| 66794 | Entner Doudoroff pathway | 50 | 5 of 10 | ||
| 66794 | ketogluconate metabolism | 50 | 4 of 8 | ||
| 66794 | degradation of pentoses | 50 | 14 of 28 | ||
| 66794 | mannosylglycerate biosynthesis | 50 | 1 of 2 | ||
| 66794 | bile acid biosynthesis, neutral pathway | 47.06 | 8 of 17 | ||
| 66794 | phenol degradation | 45 | 9 of 20 | ||
| 66794 | nitrate assimilation | 44.44 | 4 of 9 | ||
| 66794 | lipid A biosynthesis | 44.44 | 4 of 9 | ||
| 66794 | degradation of hexoses | 44.44 | 8 of 18 | ||
| 66794 | benzoyl-CoA degradation | 42.86 | 3 of 7 | ||
| 66794 | ascorbate metabolism | 40.91 | 9 of 22 | ||
| 66794 | coenzyme M biosynthesis | 40 | 4 of 10 | ||
| 66794 | D-cycloserine biosynthesis | 40 | 2 of 5 | ||
| 66794 | bacilysin biosynthesis | 40 | 2 of 5 | ||
| 66794 | glycine metabolism | 40 | 4 of 10 | ||
| 66794 | lipoate biosynthesis | 40 | 2 of 5 | ||
| 66794 | sulfate reduction | 38.46 | 5 of 13 | ||
| 66794 | carnitine metabolism | 37.5 | 3 of 8 | ||
| 66794 | d-xylose degradation | 36.36 | 4 of 11 | ||
| 66794 | vitamin B6 metabolism | 36.36 | 4 of 11 | ||
| 66794 | tyrosine metabolism | 35.71 | 5 of 14 | ||
| 66794 | vitamin B12 metabolism | 35.29 | 12 of 34 | ||
| 66794 | polyamine pathway | 34.78 | 8 of 23 | ||
| 66794 | (5R)-carbapenem carboxylate biosynthesis | 33.33 | 1 of 3 | ||
| 66794 | methane metabolism | 33.33 | 1 of 3 | ||
| 66794 | selenocysteine biosynthesis | 33.33 | 2 of 6 | ||
| 66794 | phenylpropanoid biosynthesis | 30.77 | 4 of 13 | ||
| 66794 | phosphatidylethanolamine bioynthesis | 30.77 | 4 of 13 | ||
| 66794 | dolichyl-diphosphooligosaccharide biosynthesis | 27.27 | 3 of 11 | ||
| 66794 | CMP-KDO biosynthesis | 25 | 1 of 4 | ||
| 66794 | vitamin E metabolism | 25 | 1 of 4 | ||
| 66794 | methanogenesis from CO2 | 25 | 3 of 12 | ||
| 66794 | chlorophyll metabolism | 22.22 | 4 of 18 |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | IMG accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|---|
| 66792 | ASM1073005v1 assembly for Mycobacterium shinjukuense JCM 14233 | complete | 398694 | 95.99 | ||||
| 124043 | MshiDSM45663v1 assembly for Mycobacterium shinjukuense DSM 45663 | complete | 398694 | 90.12 | ||||
| 66792 | ASM2582228v1 assembly for Mycobacterium shinjukuense DSM 45663 | scaffold | 398694 | 58.92 | ||||
| 67770 | ASM208675v1 assembly for Mycobacterium shinjukuense CCUG 53584 | contig | 398694 | 42.05 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 18021 | Mycobacterium shinjukuense gene for 16S rRNA, partial sequence, strain: GTC 2738 | AB268503 | 1505 | 398694 |
| @ref | GC-content (mol%) | Method | |
|---|---|---|---|
| 67770 | 67.8 | genome sequence analysis |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | spore_formation | BacteriaNetⓘ | yes | 56.90 | no |
| 125439 | motility | BacteriaNetⓘ | no | 79.80 | no |
| 125439 | gram_stain | BacteriaNetⓘ | positive | 91.00 | no |
| 125439 | oxygen_tolerance | BacteriaNetⓘ | obligate aerobe | 98.40 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 89.56 | no |
| 125438 | anaerobic | anaerobicⓘ | no | 95.19 | yes |
| 125438 | aerobic | aerobicⓘ | yes | 74.88 | no |
| 125438 | spore-forming | spore-formingⓘ | no | 65.14 | no |
| 125438 | thermophilic | thermophileⓘ | no | 93.95 | no |
| 125438 | flagellated | motile2+ⓘ | no | 91.88 | no |
| Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|
| Genomic and phenotypic characterization of Mycobacterium tuberculosis' closest-related non-tuberculous mycobacteria. | Sous C, Frigui W, Pawlik A, Sayes F, Ma L, Cokelaer T, Brosch R. | Microbiol Spectr | 10.1128/spectrum.04126-23 | 2024 | |
| Evolution and emergence of Mycobacterium tuberculosis. | Orgeur M, Sous C, Madacki J, Brosch R. | FEMS Microbiol Rev | 10.1093/femsre/fuae006 | 2024 | |
| Shared Pathogenomic Patterns Characterize a New Phylotype, Revealing Transition toward Host-Adaptation Long before Speciation of Mycobacterium tuberculosis. | Sapriel G, Brosch R. | Genome Biol Evol | 10.1093/gbe/evz162 | 2019 | |
| Microbiological features and clinical relevance of new species of the genus Mycobacterium. | Tortoli E. | Clin Microbiol Rev | 10.1128/cmr.00035-14 | 2014 | |
| The Presence of esat-6 and cfp10 and Other Gene Orthologs of the RD 1 Region in Non-Tuberculous Mycobacteria, Mycolicibacteria, Mycobacteroides and Mycolicibacter as Possible Impediments for the Diagnosis of (Animal) Tuberculosis | Gcebe N, Hlokwe T, Bouw A, Michel A, Rutten V. | Microorganisms | 2024 | ||
| Cold Cas: reevaluating the occurrence of CRISPR/Cas systems in Mycobacteriaceae. | Brenner E, Sreevatsan S. | Front Microbiol | 10.3389/fmicb.2023.1204838 | 2023 | |
| Rifampicin-Induced Lung Injury in Mycobacterium shinjukuense Infection: A Case Report. | Hachisu Y, Hanawa M, Hosino Y, Uno S, Onuki Y, Ezawa K, Horie T. | Respirol Case Rep | 10.1002/rcr2.70208 | 2025 | |
| Pulmonary Mycobacterium shinjukuense infection with cavitary lesion. | Sueda Y, Tokuyasu H, Sakai H, Yamasaki A. | Respirol Case Rep | 10.1002/rcr2.1399 | 2024 | |
| Mycobacterium shinjukuense infection successfully treated with clarithromycin, rifampicin, and ethambutol. | Nakamura K, Murakami E, Kishino D, Mashimo S, Kurioka Y, Shibata Y, Taniguchi A, Higo H, Hiramatsu Y, Maeda Y, Miyahara N. | Respir Med Case Rep | 10.1016/j.rmcr.2023.101894 | 2023 | |
| Two Cases of Mycobacterium shinjukuense Pulmonary Disease With a Long-Term Response to Treatment With Clarithromycin, Rifampicin, and Ethambutol. | Imakura T, Kakiuchi S, Kagawa H, Murakami N, Haku T. | Cureus | 10.7759/cureus.52888 | 2024 | |
| A universal, high-quality, and high-yield DNA purification method for mycobacteria, including Mycobacterium tuberculosis: large-scale assessment of the chloroform-bead method. | Murase Y, Hosoya M, Morishige Y, Shimomura Y, Nagai M, Tamaru A, Takaki A, Mitarai S, Japan Tuberculosis Genotyping Group (2023), Japan Tuberculosis Genotyping Group. | Microbiol Spectr | 10.1128/spectrum.00765-25 | 2025 | |
| Mycobacterium Shinjukuense Pulmonary Disease Progressed to Pleuritis after Iatrogenic Pneumothorax: A Case Report. | Taoka T, Shinohara T, Hatakeyama N, Iwamura S, Murase Y, Mitarai S, Ogushi F. | J Clin Tuberc Other Mycobact Dis | 10.1016/j.jctube.2020.100160 | 2020 | |
| Nontuberculous Mycobacterial Lung Disease Caused by Mycobacterium shinjukuense: The First Reported Case in Korea. | Moon SM, Kim SY, Chung MJ, Lee SH, Shin SJ, Koh WJ. | Tuberc Respir Dis (Seoul) | 10.4046/trd.2015.78.4.416 | 2015 | |
| Mono- and multidomain defense toxins of the RelE/ParE superfamily. | Gerdes K. | mBio | 10.1128/mbio.00258-25 | 2025 | |
| Mycobacterium shinjukuense lung disease that was successfully treated with antituberculous drugs. | Watanabe K, Shinkai M, Yamaguchi N, Shinoda M, Hara Y, Ishigatsubo Y, Kaneko T. | Intern Med | 10.2169/internalmedicine.52.1116 | 2013 | |
| Diagnostic Utility of a Mycobacterium Multiplex PCR Detection Panel for Tuberculosis and Nontuberculous Mycobacterial Infections. | Uwamino Y, Aono A, Tomita Y, Morimoto K, Kawashima M, Kamata H, Sasaki Y, Nagai H, Hasegawa N, Mitarai S. | Microbiol Spectr | 10.1128/spectrum.05162-22 | 2023 | |
| Clinical Efficacy and Diagnostic Value of Metagenomic Next-Generation Sequencing for Pathogen Detection in Patients with Suspected Infectious Diseases: A Retrospective Study from a Large Tertiary Hospital. | Xiao YH, Liu MF, Wu H, Xu DR, Zhao R. | Infect Drug Resist | 10.2147/idr.s401707 | 2023 | |
| Pangenome databases improve host removal and mycobacteria classification from clinical metagenomic data. | Hall MB, Coin LJM. | Gigascience | 10.1093/gigascience/giae010 | 2024 | |
| Comparative Genomic and Transcriptomic Analyses of Mycobacterium kansasii Subtypes Provide New Insights Into Their Pathogenicity and Taxonomy. | Guan Q, Ummels R, Ben-Rached F, Alzahid Y, Amini MS, Adroub SA, van Ingen J, Bitter W, Abdallah AM, Pain A. | Front Cell Infect Microbiol | 10.3389/fcimb.2020.00122 | 2020 | |
| Insights into the ancestry evolution of the Mycobacterium tuberculosis complex from analysis of Mycobacterium riyadhense. | Guan Q, Garbati M, Mfarrej S, AlMutairi T, Laval T, Singh A, Fagbo S, Smyth A, Browne JA, urRahman MA, Alruwaili A, Hoosen A, Meehan CJ, Nakajima C, Suzuki Y, Demangel C, Bhatt A, Gordon SV, AlAsmari F, Pain A. | NAR Genom Bioinform | 10.1093/nargab/lqab070 | 2021 | |
| Impact of Genomics on Clarifying the Evolutionary Relationships amongst Mycobacteria: Identification of Molecular Signatures Specific for the Tuberculosis-Complex of Bacteria with Potential Applications for Novel Diagnostics and Therapeutics. | Gupta RS. | High Throughput | 10.3390/ht7040031 | 2018 | |
| Cell-wall synthesis and ribosome maturation are co-regulated by an RNA switch in Mycobacterium tuberculosis. | Schwenk S, Moores A, Nobeli I, McHugh TD, Arnvig KB. | Nucleic Acids Res | 10.1093/nar/gky226 | 2018 | |
| Genome-Based Taxonomic Classification of the Phylum Actinobacteria. | Nouioui I, Carro L, Garcia-Lopez M, Meier-Kolthoff JP, Woyke T, Kyrpides NC, Pukall R, Klenk HP, Goodfellow M, Goker M. | Front Microbiol | 10.3389/fmicb.2018.02007 | 2018 | |
| Mycobacterium shinjukuense sp. nov., a slowly growing, non-chromogenic species isolated from human clinical specimens. | Saito H, Iwamoto T, Ohkusu K, Otsuka Y, Akiyama Y, Sato S, Taguchi O, Sueyasu Y, Kawabe Y, Fujimoto H, Ezaki T, Butler R | Int J Syst Evol Microbiol | 10.1099/ijs.0.025478-0 | 2010 |
| #18021 | Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 45663 |
| #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 ) |
| #59937 | Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 53584 |
| #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; |
| #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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