Bioanalyser with the DNA 1000 Chip kit (Agilent Technologies, Santa Clara, CA, USA). The amplicon libraries were pooled in equimolar amounts and sequenced unidirectionally in the reverse direction (B-adaptor) by means of the Genome Sequencer FLX Titanium system (Roche, Basel, Switzerland). Sequencing Data Analysis The sequencing data were processed using QIIME (Quantita- tive Insights Into Microbial Ecology) [44] version 1.4.0. For further downstream analyses, barcodes and primer sequences were trimmed and low quality reads (reads containing ambiguous base calls, .1 error in the primer, .1 error in the barcode, .5 nt homopolymer sequence, the average quality score below 25, or a length ,150 bp or .1000 bp) were removed from the analyses. Sliding window test (50 nt) of quality scores was enabled and sequences of low quality were truncated at the beginning of the poor quality window. The reads were denoised using Denoiser version 1.3.0 [45]. The denoised reads were checked for chimeric sequences using UCHIME version 4.2.40 [46]. The results of the de novo and the reference-based approach were combined and reads marked as chimeric were removed. The cleaned reads were clustered into Operational Taxonomic Units (OTUs) at a minimal sequence similarity of 97% using UCLUST Reference Optimal [47]. The representative sequence of each cluster was assigned a taxonomy using the Ribosomal Database Project (RDP) classifier [48]. The minimum confidence was set at 0.8. For taxonomy assignment the SILVA rRNA database [49] was trimmed to span the targeted hypervariable regions V5– V7 as described by Brandt et al. [50]. The taxonomy assigned OTUs were aligned using PyNAST [51]. For the alignment, the minimum aligned sequence length was set at 150 nt and the minimum percent identity at 75%. FastTree [52] was used to build a phylogenetic tree of the representative sequences. To allow comparisons among different samples, a randomly subsampled dataset of 800 reads per sample (the minimum nr of reads per sample was 881) was created. Data reduction by principal component analysis (PCA) on log2 transformed OTU data and the diversity statistics (Shannon Diversity Index, Dominance Index) was performed using PAST software [53]. Shannon Diversity index takes into account the number of taxa (OTUs) and the relative contribution of each OTU to the whole dataset. Dominance Index measures the ‘dominance’ of the community and ranges from 0 (all taxa equally present) to 1 (one taxon dominates the community completely). For phylogenetic measures of community ß diversity, unweighted UniFrac (a qualitative measure) and weighted UniFrac (a quantitative measure) [54] were used in QIIME. Principal coordinates analysis (PCoA), in which a distance matrix is used to plot the n samples in (n – 1)-dimensional space, was used to compare groups of samples based on unweighted and weighted UniFrac distance metrics. PCoA is analogous to a PCA. The distinction is that PCA begins with a table of the number of times each OTU was observed in each environment, whereas PCoA begins with a table of distances between each pair of environments [54]. Spearman’s correlation was performed to assess the correlation between the proportion of Candida (% ITS/16S) in saliva and the abundance of individual bacterial classes, the Mann-Whitney test was used to compare diversity statistics between sample groups (high vs. low Candida load, dentate vs. edentate subjects) using SPSS version 17.0. A G-test of Independence and ANOVA (implemented in QIIME 1.4.0.) were used to identify OTUs that are differentially represented among the groups of samples. The G-test of indepen- dence determines whether presence/absence of an OTU is associated with a category. ANOVA determines whether the relative Oral Candida and Salivary Microbiome abundance of an OTU is different between categories. The categorical variables used were: high versus low Candida load; dentate versus edentate subjects; and within the dentate group – high and low Candida load. The medium Candida load was arbitrarily set at an ITS/ 16S gene proportion between 0.01% and 0.1%. All values below 0.01% were considered low, values above 0.1% – high Candida load. The probability after multiple comparisons was corrected using Bonferroni correction. In this correction the p value is multiplied by the number of comparisons (the number of OTUs remaining after applying the filter). The filter that was applied required that a minimum of 10 samples contained the OTU for the OTU to be included in the analysis. Supporting Information Figure S1 Relative abundance of four bacterial classes that showed correlation with Candida load plotted against the Candida load. The abundance (nr of reads/ sample) of (A) Bacilli, (B) Bacteroidia, (C) Fusobacteria and (D) Flavobacteria by Candida load. Candida load was measured as the proportion of ITS gene over 16S gene abundance by qPCR. The values were normalized by log10 transformation. (TIF) Figure S2 Diversity statistics of salivary microbiomes by Candida load. Diversity statistics of salivary microbiomes by Candida load (A–C) in saliva and by Dentition of the subjects (D–F) as boxplots of (A, D) OTUs per sample, (B, E) Dominance Index and (C, F) Shannon Diversity Index. Each box shows the median, quartiles, and outliers (circles). Connector connects statistically significantly different groups (p,0.05; Mann-Whitney test). (TIF) Figure S3 Salivary microbiome UniFrac distance data by Candida load. Salivary microbiome UniFrac distance data plotted by Candida load in all individuals (A, B) and in dentate individuals only (C, D) as unweighted (A, C) and weighted (B, D) UniFrac distance PCoA plots. Samples are colored by Candida load: green - low, blue - medium and red - high Candida load. (TIF) Figure S4 Salivary microbiome data plotted by denti- tion. Salivary microbiome data plotted by dentition of the subjects: A) PCA of OTU-based distances, B) PCoA of unweighted (qualitative) UniFrac distances and C) PCoA of weighted (quantitative) UniFrac distances. Samples are color-coded by the dentition status of the subjects: dentate (N = 34) – blue, edentate (N = 20) – red. (TIF) Table S1 Relative abundance of reads and number of OTUs per phylum. (DOCX) Table S2 Relative and absolute abundance of Candida (ITS gene) in saliva samples. (DOCX) OTU-table of salivary microbiome data. Dataset S1 (XLSX) Dataset S2 Distribution of higher taxa (genus or higher taxon) in saliva samples. (XLSX) Author Contributions Conceived and designed the experiments: EAK MV BJFK WC EZ. Performed the experiments: EAK M. J. Buijis. Analyzed the data: EAK M. PLOS ONE | www.plosone.org 7 August 2012 | Volume 7 | Issue 8 | e42770