title: An accurate and efficient experimental approach for characterization of the complex oral microbiota.
abstract: BACKGROUND
  Currently, taxonomic interrogation of microbiota is based on amplification of 16S rRNA gene sequences in clinical and scientific settings. Accurate evaluation of the microbiota depends heavily on the primers used, and genus/species resolution bias can arise with amplification of non-representative genomic regions. The latest Illumina MiSeq sequencing chemistry has extended the read length to 300 bp, enabling deep profiling of large number of samples in a single paired-end reaction at a fraction of the cost. An increasingly large number of researchers have adopted this technology for various microbiome studies targeting the 16S rRNA V3-V4 hypervariable region.
  
  
  RESULTS
  To expand the applicability of this powerful platform for further descriptive and functional microbiome studies, we standardized and tested an efficient, reliable, and straightforward workflow for the amplification, library construction, and sequencing of the 16S V1-V3 hypervariable region using the new 2 × 300 MiSeq platform. Our analysis involved 11 subgingival plaque samples from diabetic and non-diabetic human subjects suffering from periodontitis. The efficiency and reliability of our experimental protocol was compared to 16S V3-V4 sequencing data from the same samples. Comparisons were based on measures of observed taxonomic richness and species evenness, along with Procrustes analyses using beta(β)-diversity distance metrics. As an experimental control, we also analyzed a total of eight technical replicates for the V1-V3 and V3-V4 regions from a synthetic community with known bacterial species operon counts. We show that our experimental protocol accurately measures true bacterial community composition. Procrustes analyses based on unweighted UniFrac β-diversity metrics depicted significant correlation between oral bacterial composition for the V1-V3 and V3-V4 regions. However, measures of phylotype richness were higher for the V1-V3 region, suggesting that V1-V3 offers a deeper assessment of population diversity and community ecology for the complex oral microbiota.
  
  
  CONCLUSIONS
  This study provides researchers with valuable experimental evidence for the selection of appropriate 16S amplicons for future human oral microbiome studies. We expect that the tested 16S V1-V3 framework will be widely applicable to other types of microbiota, allowing robust, time-efficient, and inexpensive examination of thousands of samples for population, phylogenetic, and functional crossectional and longitutidal studies.
authors.affiliation: Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, NY, 14203, USA. wzheng4@buffalo.edu.
authors.forename: Wei
authors.initials: W
authors.lastname: Zheng
authors.affiliation: Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY, 14203, USA. tsompana@buffalo.edu.|Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY, 14203, USA. tsompana@buffalo.edu.
authors.forename: Maria
authors.initials: M
authors.lastname: Tsompana
authors.affiliation: Department of Oral Biology, State University of New York at Buffalo, Buffalo, NY, 14203, USA. aruscitt@buffalo.edu.
authors.forename: Angela
authors.initials: A
authors.lastname: Ruscitto
authors.affiliation: Department of Oral Biology, State University of New York at Buffalo, Buffalo, NY, 14203, USA. sharmaa@buffalo.edu.
authors.forename: Ashu
authors.initials: A
authors.lastname: Sharma
authors.affiliation: Department of Oral Biology, State University of New York at Buffalo, Buffalo, NY, 14203, USA. rjgenco@buffalo.edu.|Department of Microbiology and Immunology, State University of New York at Buffalo, Buffalo, NY, 14203, USA. rjgenco@buffalo.edu.
authors.forename: Robert
authors.initials: R
authors.lastname: Genco
authors.affiliation: Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, NY, 14203, USA. yijunsun@buffalo.edu.|Department of Microbiology and Immunology, State University of New York at Buffalo, Buffalo, NY, 14203, USA. yijunsun@buffalo.edu.
authors.forename: Yijun
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY, 14203, USA. mjbuck@buffalo.edu.|Department of Biochemistry, State University of New York at Buffalo, Buffalo, NY, 14203, USA. mjbuck@buffalo.edu.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Buck
mesh_terms: D001419:Bacteria / Q000145:classification / Q000235:genetics; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D054892:Metagenome; D064307:Microbiota; D009055:Mouth / Q000382:microbiology*; D010802:Phylogeny; D012336:RNA, Ribosomal, 16S / Q000235:genetics
chemical_list: D012336:RNA, Ribosomal, 16S