15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A Review on the Applications of Next Generation Sequencing Technologies as Applied to Food-Related Microbiome Studies

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The development of next generation sequencing (NGS) techniques has enabled researchers to study and understand the world of microorganisms from broader and deeper perspectives. The contemporary advances in DNA sequencing technologies have not only enabled finer characterization of bacterial genomes but also provided deeper taxonomic identification of complex microbiomes which in its genomic essence is the combined genetic material of the microorganisms inhabiting an environment, whether the environment be a particular body econiche (e.g., human intestinal contents) or a food manufacturing facility econiche (e.g., floor drain). To date, 16S rDNA sequencing, metagenomics and metatranscriptomics are the three basic sequencing strategies used in the taxonomic identification and characterization of food-related microbiomes. These sequencing strategies have used different NGS platforms for DNA and RNA sequence identification. Traditionally, 16S rDNA sequencing has played a key role in understanding the taxonomic composition of a food-related microbiome. Recently, metagenomic approaches have resulted in improved understanding of a microbiome by providing a species-level/strain-level characterization. Further, metatranscriptomic approaches have contributed to the functional characterization of the complex interactions between different microbial communities within a single microbiome. Many studies have highlighted the use of NGS techniques in investigating the microbiome of fermented foods. However, the utilization of NGS techniques in studying the microbiome of non-fermented foods are limited. This review provides a brief overview of the advances in DNA sequencing chemistries as the technology progressed from first, next and third generations and highlights how NGS provided a deeper understanding of food-related microbiomes with special focus on non-fermented foods.

          Related collections

          Most cited references120

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            QIIME allows analysis of high-throughput community sequencing data.

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Search and clustering orders of magnitude faster than BLAST.

              Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                21 September 2017
                2017
                : 8
                : 1829
                Affiliations
                [1] 1UCD-Centre for Food Safety, Science Centre South, University College Dublin Dublin, Ireland
                [2] 2Food for Health Ireland, Science Centre South, University College Dublin Dublin, Ireland
                [3] 3Teagasc, Food Research Centre Fermoy, Ireland
                Author notes

                Edited by: Walid Alali, Hamad bin Khalifa University, Qatar

                Reviewed by: Biswapriya Biswavas Misra, Texas Biomedical Research Institute, United States; Vasiliki Chini, Qatar Foundation, Qatar

                *Correspondence: Shabarinath Srikumar srikumar.shabarinath@ 123456ucd.ie

                This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2017.01829
                5627019
                28144237
                558a6395-bec1-4cf1-b6d9-dcaa8d7fc7e8
                Copyright © 2017 Cao, Fanning, Proos, Jordan and Srikumar.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 April 2017
                : 06 September 2017
                Page count
                Figures: 1, Tables: 3, Equations: 0, References: 119, Pages: 16, Words: 13147
                Funding
                Funded by: Department of Agriculture, Food and the Marine 10.13039/501100001584
                Award ID: SMART-PIF; 13/F/423
                Funded by: Enterprise Ireland 10.13039/501100001588
                Award ID: IP 2015 0380
                Categories
                Microbiology
                Review

                Microbiology & Virology
                next generation sequencing,food microbiome,16s rdna,metagenomics,metatranscriptomics

                Comments

                Comment on this article