Title |
Enhanced whole genome sequence and annotation of Clostridium stercorarium DSM8532T using RNA-seq transcriptomics and high-throughput proteomics
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Published in |
BMC Genomics, July 2014
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DOI | 10.1186/1471-2164-15-567 |
Pubmed ID | |
Authors |
John J Schellenberg, Tobin J Verbeke, Peter McQueen, Oleg V Krokhin, Xiangli Zhang, Graham Alvare, Brian Fristensky, Gerhard G Thallinger, Bernard Henrissat, John A Wilkins, David B Levin, Richard Sparling |
Abstract |
Growing interest in cellulolytic clostridia with potential for consolidated biofuels production is mitigated by low conversion of raw substrates to desired end products. Strategies to improve conversion are likely to benefit from emerging techniques to define molecular systems biology of these organisms. Clostridium stercorarium DSM8532T is an anaerobic thermophile with demonstrated high ethanol production on cellulose and hemicellulose. Although several lignocellulolytic enzymes in this organism have been well-characterized, details concerning carbohydrate transporters and central metabolism have not been described. Therefore, the goal of this study is to define an improved whole genome sequence (WGS) for this organism using in-depth molecular profiling by RNA-seq transcriptomics and tandem mass spectrometry-based proteomics. |
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Geographical breakdown
Country | Count | As % |
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United States | 1 | 25% |
France | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 50% |
Scientists | 2 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Brazil | 2 | 3% |
United States | 1 | 1% |
Unknown | 64 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 20 | 30% |
Researcher | 10 | 15% |
Student > Master | 8 | 12% |
Student > Doctoral Student | 7 | 10% |
Other | 5 | 7% |
Other | 11 | 16% |
Unknown | 6 | 9% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 24 | 36% |
Biochemistry, Genetics and Molecular Biology | 12 | 18% |
Immunology and Microbiology | 6 | 9% |
Engineering | 5 | 7% |
Computer Science | 3 | 4% |
Other | 13 | 19% |
Unknown | 4 | 6% |