title: Optimisation of methods for bacterial skin microbiome investigation: primer selection and comparison of the 454 versus MiSeq platform.
abstract: BACKGROUND
  The composition of the skin microbiome is predicted to play a role in the development of conditions such as atopic eczema and psoriasis. 16S rRNA gene sequencing allows the investigation of bacterial microbiota. A significant challenge in this field is development of cost effective high throughput methodologies for the robust interrogation of the skin microbiota, where biomass is low. Here we describe validation of methodologies for 16S rRNA (ribosomal ribonucleic acid) gene sequencing from the skin microbiome, using the Illumina MiSeq platform, the selection of primer to amplify regions for sequencing and we compare results with the current standard protocols..
  
  
  METHODS
  DNA was obtained from two low density mock communities of 11 diverse bacterial strains (with and without human DNA supplementation) and from swabs taken from the skin of healthy volunteers. This was amplified using primer pairs covering hypervariable regions of the 16S rRNA gene: primers 63F and 519R (V1-V3); and 347F and 803R (V3-V4). The resultant libraries were indexed for the MiSeq and Roche454 and sequenced. Both data sets were denoised, cleaned of chimeras and analysed using QIIME.
  
  
  RESULTS
  There was no significant difference in the diversity indices at the phylum and the genus level observed between the platforms. The capture of diversity using the low density mock community samples demonstrated that the primer pair spanning the V3-V4 hypervariable region had better capture when compared to the primer pair for the V1-V3 region and was robust to spiking with human DNA. The pilot data generated using the V3-V4 region from the skin of healthy volunteers was consistent with these results, even at the genus level (Staphylococcus, Propionibacterium, Corynebacterium, Paracoccus, Micrococcus, Enhydrobacter and Deinococcus identified at similar abundances on both platforms).
  
  
  CONCLUSIONS
  The results suggest that the bacterial community diversity captured using the V3-V4 16S rRNA hypervariable region from sequencing using the MiSeq platform is comparable to the Roche454 GS Junior platform. These findings provide evidence that the optimised method can be used in human clinical samples of low bacterial biomass such as the investigation of the skin microbiota.
authors.affiliation: NIHR Manchester Musculoskeletal Biomedical research Unit, Central Manchester Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, England.
authors.forename: Madhura
authors.identifier: http://orcid.org/0000-0002-2724-0122
authors.initials: M
authors.lastname: Castelino
authors.affiliation: Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.
authors.forename: Stephen
authors.initials: S
authors.lastname: Eyre
authors.affiliation: Microbiology and Virology Unit, Institute of Inflammation and Repair, The University of Manchester, Stopford Building, Oxford Road, Manchester, UK.
authors.forename: John
authors.initials: J
authors.lastname: Moat
authors.affiliation: DNA Sequencing Facility, Faculty of Medical & Human Sciences, The University of Manchester, Stopford Building, Oxford Road, Manchester, UK.
authors.forename: Graeme
authors.initials: G
authors.lastname: Fox
authors.affiliation: Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.
authors.forename: Paul
authors.initials: P
authors.lastname: Martin
authors.affiliation: NIHR Manchester Musculoskeletal Biomedical research Unit, Central Manchester Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, England.
authors.forename: Pauline
authors.initials: P
authors.lastname: Ho
authors.affiliation: School of Biomedical and Healthcare Sciences, Plymouth University Peninsular Schools of Medicine and Dentistry, Plymouth, UK.
authors.forename: Mathew
authors.initials: M
authors.lastname: Upton
authors.affiliation: NIHR Manchester Musculoskeletal Biomedical research Unit, Central Manchester Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, England. anne.barton@manchester.ac.uk.|Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK. anne.barton@manchester.ac.uk.
authors.forename: Anne
authors.initials: A
authors.lastname: Barton
mesh_terms: D000328:Adult; D001419:Bacteria / Q000145:classification / Q000235:genetics* / Q000302:isolation & purification*; D015373:Bacterial Typing Techniques / Q000379:methods*; D001483:Base Sequence; D018533:Biomass; D019295:Computational Biology / Q000379:methods; D059018:DNA Contamination; D017931:DNA Primers / Q000235:genetics; D004269:DNA, Bacterial / Q000235:genetics / Q000302:isolation & purification; D005798:Genes, Bacterial; D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing / Q000295:instrumentation / Q000379:methods*; D006801:Humans / Q000382:microbiology; D064307:Microbiota / Q000235:genetics*; D008875:Middle Aged; D010802:Phylogeny; D016133:Polymerase Chain Reaction / Q000379:methods; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D017422:Sequence Analysis, DNA / Q000379:methods; D012867:Skin / Q000382:microbiology*
chemical_list: D017931:DNA Primers; D004269:DNA, Bacterial; D012336:RNA, Ribosomal, 16S
keywords: 16s rRNA gene; Bacterial microbiome; Low biomass; Methods; Miseq platform; Next generation sequencing; Optimisation; Primer selection; Skin microbiome