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      Strategies and Methodologies for Developing Microbial Detoxification Systems to Mitigate Mycotoxins

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          Abstract

          Mycotoxins, the secondary metabolites of mycotoxigenic fungi, have been found in almost all agricultural commodities worldwide, causing enormous economic losses in livestock production and severe human health problems. Compared to traditional physical adsorption and chemical reactions, interest in biological detoxification methods that are environmentally sound, safe and highly efficient has seen a significant increase in recent years. However, researchers in this field have been facing tremendous unexpected challenges and are eager to find solutions. This review summarizes and assesses the research strategies and methodologies in each phase of the development of microbiological solutions for mycotoxin mitigation. These include screening of functional microbial consortia from natural samples, isolation and identification of single colonies with biotransformation activity, investigation of the physiological characteristics of isolated strains, identification and assessment of the toxicities of biotransformation products, purification of functional enzymes and the application of mycotoxin decontamination to feed/food production. A full understanding and appropriate application of this tool box should be helpful towards the development of novel microbiological solutions on mycotoxin detoxification.

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          Most cited references153

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          Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses.

          Although the applicability of small subunit ribosomal RNA (16S rRNA) sequences for bacterial classification is now well accepted, the general use of these molecules has been hindered by the technical difficulty of obtaining their sequences. A protocol is described for rapidly generating large blocks of 16S rRNA sequence data without isolation of the 16S rRNA or cloning of its gene. The 16S rRNA in bulk cellular RNA preparations is selectively targeted for dideoxynucleotide-terminated sequencing by using reverse transcriptase and synthetic oligodeoxynucleotide primers complementary to universally conserved 16S rRNA sequences. Three particularly useful priming sites, which provide access to the three major 16S rRNA structural domains, routinely yield 800-1000 nucleotides of 16S rRNA sequence. The method is evaluated with respect to accuracy, sensitivity to modified nucleotides in the template RNA, and phylogenetic usefulness, by examination of several 16S rRNAs whose gene sequences are known. The relative simplicity of this approach should facilitate a rapid expansion of the 16S rRNA sequence collection available for phylogenetic analyses.
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            Advancing our understanding of the human microbiome using QIIME.

            High-throughput DNA sequencing technologies, coupled with advanced bioinformatics tools, have enabled rapid advances in microbial ecology and our understanding of the human microbiome. QIIME (Quantitative Insights Into Microbial Ecology) is an open-source bioinformatics software package designed for microbial community analysis based on DNA sequence data, which provides a single analysis framework for analysis of raw sequence data through publication-quality statistical analyses and interactive visualizations. In this chapter, we demonstrate the use of the QIIME pipeline to analyze microbial communities obtained from several sites on the bodies of transgenic and wild-type mice, as assessed using 16S rRNA gene sequences generated on the Illumina MiSeq platform. We present our recommended pipeline for performing microbial community analysis and provide guidelines for making critical choices in the process. We present examples of some of the types of analyses that are enabled by QIIME and discuss how other tools, such as phyloseq and R, can be applied to expand upon these analyses. © 2013 Elsevier Inc. All rights reserved.
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              Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers

              The recent introduction of massively parallel pyrosequencers allows rapid, inexpensive analysis of microbial community composition using 16S ribosomal RNA (rRNA) sequences. However, a major challenge is to design a workflow so that taxonomic information can be accurately and rapidly assigned to each read, so that the composition of each community can be linked back to likely ecological roles played by members of each species, genus, family or phylum. Here, we use three large 16S rRNA datasets to test whether taxonomic information based on the full-length sequences can be recaptured by short reads that simulate the pyrosequencer outputs. We find that different taxonomic assignment methods vary radically in their ability to recapture the taxonomic information in full-length 16S rRNA sequences: most methods are sensitive to the region of the 16S rRNA gene that is targeted for sequencing, but many combinations of methods and rRNA regions produce consistent and accurate results. To process large datasets of partial 16S rRNA sequences obtained from surveys of various microbial communities, including those from human body habitats, we recommend the use of Greengenes or RDP classifier with fragments of at least 250 bases, starting from one of the primers R357, R534, R798, F343 or F517.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Toxins (Basel)
                Toxins (Basel)
                toxins
                Toxins
                MDPI
                2072-6651
                07 April 2017
                April 2017
                : 9
                : 4
                : 130
                Affiliations
                Guelph Research and Development Centre, Agriculture and Agri-Food Canada, Guelph, ON N1G5C9, Canada; yan.zhu@ 123456agr.gc.ca (Y.Z.); yousef.hassan@ 123456agr.gc.ca (Y.I.H.); dion.lepp@ 123456agr.gc.ca (D.L.); Suqin.Shao@ 123456agr.gc.ca (S.S.)
                Author notes
                [* ]Correspondence: ting.zhou@ 123456agr.gc.ca ; Tel.: +1-226-217-8084; Fax: +1-519-829-2600
                Article
                toxins-09-00130
                10.3390/toxins9040130
                5408204
                28387743
                eae4b2f7-da52-4f45-9bd0-591781f91b6e
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 13 February 2017
                : 04 April 2017
                Categories
                Review

                Molecular medicine
                mycotoxin,detoxification,biodegradation,biotransformation,enzyme,microorganism identification

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