Title |
PyroTRF-ID: a novel bioinformatics methodology for the affiliation of terminal-restriction fragments using 16S rRNA gene pyrosequencing data
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Published in |
BMC Microbiology, December 2012
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DOI | 10.1186/1471-2180-12-306 |
Pubmed ID | |
Authors |
David G Weissbrodt, Noam Shani, Lucas Sinclair, Grégory Lefebvre, Pierre Rossi, Julien Maillard, Jacques Rougemont, Christof Holliger |
Abstract |
In molecular microbial ecology, massive sequencing is gradually replacing classical fingerprinting techniques such as terminal-restriction fragment length polymorphism (T-RFLP) combined with cloning-sequencing for the characterization of microbiomes. Here, a bioinformatics methodology for pyrosequencing-based T-RF identification (PyroTRF-ID) was developed to combine pyrosequencing and T-RFLP approaches for the description of microbial communities. The strength of this methodology relies on the identification of T-RFs by comparison of experimental and digital T-RFLP profiles obtained from the same samples. DNA extracts were subjected to amplification of the 16S rRNA gene pool, T-RFLP with the HaeIII restriction enzyme, 454 tag encoded FLX amplicon pyrosequencing, and PyroTRF-ID analysis. Digital T-RFLP profiles were generated from the denoised full pyrosequencing datasets, and the sequences contributing to each digital T-RF were classified to taxonomic bins using the Greengenes reference database. The method was tested both on bacterial communities found in chloroethene-contaminated groundwater samples and in aerobic granular sludge biofilms originating from wastewater treatment systems. |
X Demographics
Geographical breakdown
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Japan | 2 | 3% |
United States | 2 | 3% |
Indonesia | 1 | 1% |
Brazil | 1 | 1% |
United Kingdom | 1 | 1% |
Portugal | 1 | 1% |
Finland | 1 | 1% |
Luxembourg | 1 | 1% |
Unknown | 59 | 86% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 21 | 30% |
Researcher | 13 | 19% |
Student > Master | 5 | 7% |
Student > Doctoral Student | 4 | 6% |
Professor | 4 | 6% |
Other | 14 | 20% |
Unknown | 8 | 12% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 32 | 46% |
Environmental Science | 10 | 14% |
Engineering | 5 | 7% |
Biochemistry, Genetics and Molecular Biology | 4 | 6% |
Chemical Engineering | 2 | 3% |
Other | 6 | 9% |
Unknown | 10 | 14% |