Clostridium thermautotrophicum CIP 108447 is an anaerobe, Gram-positive, rod-shaped bacterium of the family Clostridiaceae.
Gram-positive rod-shaped anaerobe genome sequence 16S sequence Bacteria| @ref 20215 |
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| Domain Bacteria |
| Phylum Bacillota |
| Class Clostridia |
| Order Eubacteriales |
| Family Clostridiaceae |
| Genus Clostridium |
| Species Clostridium thermautotrophicum |
| Full scientific name Clostridium thermautotrophicum corrig. Wiegel et al. 1982 |
| Synonyms (6) |
| @ref | Gram stain | Cell shape | Motility | |
|---|---|---|---|---|
| 36735 | positive | rod-shaped |
| @ref | Name | Growth | Composition | Medium link | |
|---|---|---|---|---|---|
| 36735 | MEDIUM 224 - for anaerobic bacteria TGV | Distilled water make up to (1000.000 ml);Glucose (10.000 g);Yeast extract (20.000 g);Resazurin (2.000 mg);Trypto casein soy broth (30.000 g);L-Cysteine (0.500 g);Hemin solution - M00149 (25.000 ml);Vitamins solution - M00850 (10.000 ml) | |||
| 36735 | CIP Medium 20 | Medium recipe at CIP |
| @ref | Growth | Type | Temperature (°C) | |
|---|---|---|---|---|
| 36735 | positive | growth | 55 |
| @ref | Spore formation | Confidence | |
|---|---|---|---|
| 125439 | 95.275 |
Global distribution of 16S sequence L09168 (>99% sequence identity) for Moorella thermoacetica from Microbeatlas ![]()
| @ref | Biosafety level | Biosafety level comment | |
|---|---|---|---|
| 36735 | 1 | Risk group (French classification) |
| @ref | Description | Assembly level | INSDC accession | BV-BRC accession | NCBI tax ID | Score | |
|---|---|---|---|---|---|---|---|
| 66792 | ASM812189v1 assembly for Neomoorella thermoacetica ATCC 33924 | contig | 1525 | 64.03 |
| @ref | Description | Accession | Length | Database | NCBI tax ID | |
|---|---|---|---|---|---|---|
| 36735 | Clostridium thermoautotrophicum (DSM 1974) 16S ribosomal RNA (16S rRNA) gene | L09168 | 1553 | 1560 | ||
| 124043 | Moorella thermoautotrophica strain DSM 1974 16S-23S ribosomal RNA intergenic spacer and 23S ribosomal RNA gene, partial sequence. | DQ192549 | 278 | 1525 | ||
| 124043 | Moorella thermoautotrophica 16S rRNA gene, strain DSM 1974 | X77849 | 1523 | 1525 |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125439 | oxygen_tolerance | BacteriaNetⓘ | anaerobe | 99.87 | no |
| 125439 | gram_stain | BacteriaNetⓘ | negative | 66.75 | no |
| 125439 | spore_formation | BacteriaNetⓘ | no | 95.28 | no |
| 125439 | motility | BacteriaNetⓘ | no | 65.72 | no |
| @ref | Trait | Model | Prediction | Confidence in % | In training data |
|---|---|---|---|---|---|
| 125438 | gram-positive | gram-positiveⓘ | yes | 53.59 | no |
| 125438 | anaerobic | anaerobicⓘ | yes | 90.38 | yes |
| 125438 | spore-forming | spore-formingⓘ | yes | 74.54 | no |
| 125438 | aerobic | aerobicⓘ | no | 92.53 | yes |
| 125438 | thermophilic | thermophileⓘ | yes | 77.23 | yes |
| 125438 | flagellated | motile2+ⓘ | yes | 66.54 | no |
| Topic | Title | Authors | Journal | DOI | Year | |
|---|---|---|---|---|---|---|
| Acetate Production from Syngas Produced from Lignocellulosic Biomass Materials along with Gaseous Fermentation of the Syngas: A Review. | Harahap BM, Ahring BK. | Microorganisms | 10.3390/microorganisms11040995 | 2023 | ||
| Metabolism | Using gas mixtures of CO, CO2 and H2 as microbial substrates: the do's and don'ts of successful technology transfer from laboratory to production scale. | Takors R, Kopf M, Mampel J, Bluemke W, Blombach B, Eikmanns B, Bengelsdorf FR, Weuster-Botz D, Durre P. | Microb Biotechnol | 10.1111/1751-7915.13270 | 2018 | |
| Metabolism | Tolerance and metabolic response of acetogenic bacteria toward oxygen. | Karnholz A, Kusel K, Gossner A, Schramm A, Drake HL. | Appl Environ Microbiol | 10.1128/aem.68.2.1005-1009.2002 | 2002 | |
| Enzymology | Carbonic anhydrase in Acetobacterium woodii and other acetogenic bacteria. | Braus-Stromeyer SA, Schnappauf G, Braus GH, Gossner AS, Drake HL. | J Bacteriol | 10.1128/jb.179.22.7197-7200.1997 | 1997 | |
| Metabolism | Degradation of glyoxylate and glycolate with ATP synthesis by a thermophilic anaerobic bacterium, Moorella sp. strain HUC22-1. | Sakai S, Inokuma K, Nakashimada Y, Nishio N. | Appl Environ Microbiol | 10.1128/aem.01421-07 | 2008 | |
| Metabolism | Thermophilic Moorella thermoacetica as a platform microorganism for C1 gas utilization: physiology, engineering, and applications. | Jia D, Deng W, Hu P, Jiang W, Gu Y. | Bioresour Bioprocess | 10.1186/s40643-023-00682-z | 2023 | |
| Enzymology | Direct quantification of the enteric bacterium Oxalobacter formigenes in human fecal samples by quantitative competitive-template PCR. | Sidhu H, Holmes RP, Allison MJ, Peck AB. | J Clin Microbiol | 10.1128/jcm.37.5.1503-1509.1999 | 1999 | |
| Genome-Based Comparison of All Species of the Genus Moorella, and Status of the Species Moorella thermoacetica and Moorella thermoautotrophica. | Redl S, Poehlein A, Esser C, Bengelsdorf FR, Jensen TO, Jendresen CB, Tindall BJ, Daniel R, Durre P, Nielsen AT | Front Microbiol | 10.3389/fmicb.2019.03070 | 2020 |
| #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 ) |
| #36735 | Collection of Institut Pasteur ; Curators of the CIP; CIP 108447 |
| #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) . |
| #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 . |
| #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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