title: The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies.
abstract: BACKGROUND
  Characterizing microbial communities via next-generation sequencing is subject to a number of pitfalls involving sample processing. The observed community composition can be a severe distortion of the quantities of bacteria actually present in the microbiome, hampering analysis and threatening the validity of conclusions from metagenomic studies. We introduce an experimental protocol using mock communities for quantifying and characterizing bias introduced in the sample processing pipeline. We used 80 bacterial mock communities comprised of prescribed proportions of cells from seven vaginally-relevant bacterial strains to assess the bias introduced in the sample processing pipeline. We created two additional sets of 80 mock communities by mixing prescribed quantities of DNA and PCR product to quantify the relative contribution to bias of (1) DNA extraction, (2) PCR amplification, and (3) sequencing and taxonomic classification for particular choices of protocols for each step. We developed models to predict the "true" composition of environmental samples based on the observed proportions, and applied them to a set of clinical vaginal samples from a single subject during four visits.
  
  
  RESULTS
  We observed that using different DNA extraction kits can produce dramatically different results but bias is introduced regardless of the choice of kit. We observed error rates from bias of over 85% in some samples, while technical variation was very low at less than 5% for most bacteria. The effects of DNA extraction and PCR amplification for our protocols were much larger than those due to sequencing and classification. The processing steps affected different bacteria in different ways, resulting in amplified and suppressed observed proportions of a community. When predictive models were applied to clinical samples from a subject, the predicted microbiome profiles were better reflections of the physiology and diagnosis of the subject at the visits than the observed community compositions.
  
  
  CONCLUSIONS
  Bias in 16S studies due to DNA extraction and PCR amplification will continue to require attention despite further advances in sequencing technology. Analysis of mock communities can help assess bias and facilitate the interpretation of results from environmental samples.
authors.affiliation: Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, 23284-3083, Richmond, VA, USA. jpbrooks@vcu.edu.|Center for the Study of Biological Complexity, Virginia Commonwealth University, 23284, Richmond, VA, USA. jpbrooks@vcu.edu.
authors.forename: J Paul
authors.initials: JP
authors.lastname: Brooks
authors.affiliation: Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, 23284-3083, Richmond, VA, USA. dedwards7@vcu.edu.
authors.forename: David J
authors.initials: DJ
authors.lastname: Edwards
authors.affiliation: Department of Microbiology and Immunology, Virginia Commonwealth University, 23284, Richmond, VA, USA. harwichmd@gmail.com.
authors.forename: Michael D
authors.initials: MD
authors.lastname: Harwich
authors.affiliation: Department of Biology, Virginia Commonwealth University, 23284, Richmond, VA, USA. mcrivera@vcu.edu.
authors.forename: Maria C
authors.initials: MC
authors.lastname: Rivera
authors.affiliation: Department of Microbiology and Immunology, Virginia Commonwealth University, 23284, Richmond, VA, USA. fettweisjm@vcu.edu.
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Fettweis
authors.affiliation: Center for the Study of Biological Complexity, Virginia Commonwealth University, 23284, Richmond, VA, USA. mgserrano@vcu.edu.|Department of Microbiology and Immunology, Virginia Commonwealth University, 23284, Richmond, VA, USA. mgserrano@vcu.edu.
authors.forename: Myrna G
authors.initials: MG
authors.lastname: Serrano
authors.affiliation: Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, 23284-3083, Richmond, VA, USA. rerisra@vcu.edu.
authors.forename: Robert A
authors.initials: RA
authors.lastname: Reris
authors.affiliation: Center for the Study of Biological Complexity, Virginia Commonwealth University, 23284, Richmond, VA, USA. nsheth@vcu.edu.
authors.forename: Nihar U
authors.initials: NU
authors.lastname: Sheth
authors.affiliation: Department of Microbiology and Immunology, Virginia Commonwealth University, 23284, Richmond, VA, USA. huangb2@vcu.edu.
authors.forename: Bernice
authors.initials: B
authors.lastname: Huang
authors.affiliation: Department of Obstetrics and Gynecology, Virginia Commonwealth University, 23284, Richmond, VA, USA. pgirerd@vcu.edu.
authors.forename: Philippe
authors.initials: P
authors.lastname: Girerd
authors.affiliation: Department of Obstetrics and Gynecology, Virginia Commonwealth University, 23284, Richmond, VA, USA. jfstrauss@vcu.edu.
authors.forename: Jerome F
authors.initials: JF
authors.lastname: Strauss
authors.affiliation: Center for the Study of Biological Complexity, Virginia Commonwealth University, 23284, Richmond, VA, USA. kkjefferson@vcu.edu.|Department of Microbiology and Immunology, Virginia Commonwealth University, 23284, Richmond, VA, USA. kkjefferson@vcu.edu.
authors.forename: Kimberly K
authors.initials: KK
authors.lastname: Jefferson
authors.affiliation: Center for the Study of Biological Complexity, Virginia Commonwealth University, 23284, Richmond, VA, USA. gabuck@vcu.edu.|Department of Microbiology and Immunology, Virginia Commonwealth University, 23284, Richmond, VA, USA. gabuck@vcu.edu.
authors.forename: Gregory A
authors.initials: GA
authors.lastname: Buck
mesh_terms: D016477:Artifacts; D001419:Bacteria / Q000145:classification / Q000235:genetics* / Q000302:isolation & purification; D015982:Bias; D004269:DNA, Bacterial / Q000235:genetics* / Q000302:isolation & purification; D005260:Female; D020459:Genes, rRNA; D059014:High-Throughput Nucleotide Sequencing / Q000592:standards; D006801:Humans; D056186:Metagenomics / Q000295:instrumentation / Q000379:methods / Q000592:standards; D059013:Microbial Consortia / Q000235:genetics; D064307:Microbiota / Q000235:genetics; D008954:Models, Biological; D010802:Phylogeny; D016133:Polymerase Chain Reaction / Q000592:standards; D012336:RNA, Ribosomal, 16S / Q000235:genetics* / Q000302:isolation & purification; D013048:Specimen Handling / Q000592:standards*; D014621:Vagina / Q000382:microbiology
chemical_list: D004269:DNA, Bacterial; D012336:RNA, Ribosomal, 16S