knowledge on the ecology of fungal – bacterial interactions in search for potential targets for a guided ecological balance towards a healthy oral ecosystem. The specific aim of this study was to assess the relationship between the load of oral Candida and the diversity and composition of the oral bacterial microbiome. For this we obtained oral bacterial pyrosequencing profiles of healthy Dutch older adults with various levels of oral Candida carriage and established that there is a relationship between the oral Candida load and the bacterial microbiome. Results Overall Sequencing Output Of all reads (available at SRA of NCBI as SRA050301), 90% passed the quality control, 73% passed denoising and 59% reads (805413 reads; average length 419 nt) remained after removing the reads with chimeric sequences. The 601 unique sequences clustered into 425 OTUs of which 334 OTUs contained at least 5 reads. On average, a sample contained 87 (SD 39; min 21, max 222) OTUs. In order to avoid the effect of variable sample size on the diversity analyses, a randomly picked subset of 800 reads per sample was created and used for all subsequent analyses. After random picking of the subset of 800 reads per sample, 300 OTUs remained in the dataset with an average 43 (SD 13; min 11, max 73) OTUs per sample (Dataset S1). The subsampled reads were classified into 12 phyla (Table S1), with Firmicutes dominating the dataset (57% of reads), followed by Actinobacteria (20%), Bacteroidetes (14%) and Proteobacteria (7%). The predominant genera were Streptococcus (34% of reads), Rothia (12%), Veillonella (11%), Prevotella (10.5%), Gemella (6.9%), Actinomyces (6.7%), Neisseria (4.5%), Porphyromonas (2.6%), Haemophilus (1.8%), Lactobacillus (1.2%) and Leptotrichia (1% of reads) (Dataset S2). Individual Microbiomes by Candida Load Saliva of Dutch older adults contained between 0 and 14.5% Candida as a proportion of Candida specific ITS gene over bacterial DNA (16S rRNA gene), with a median Candida load of 0.06% (Table S2). The exception was a single sample (LASA181) where Candida genes dominated over bacterial 16S gene at more than three orders of magnitude (ITS/16S = 1440%). The microbial profiles of these samples showed a high interindividual variation already at the bacterial class level (Figure 1). Increase in Candida load correlated positively with reads classified as Bacilli (p = 0.013; Spearman’s rho 0.274), while class Bacteroidia (p = 0.001; Spear- man’s rho 20.360), Flavobacteria (p = 0.003; Spearman’s rho 20.322) and Fusobacteria (p = 0.012; Spearman’s rho 20.275) correlated negatively with the Candida load (Figure S1). Sample LASA181 differed in the microbial composition from the rest of the samples by dominance of genus Lactobacillus (81% of reads) and Streptococcus (16% of reads). This particular sample was the abovementioned outlier also regarding the Candida load. Diversity statistics showed that the Candida load correlated positively with the Dominance Index (p,0.001; Spearman’s rho 0.388) and negatively with the Shannon Diversity Index (p,0.001; Spearman’s rho 20.403) (Figure 2) and the number of OTUs per sample (p = 0.003; Spearman’s rho 20.321). To assess the relation of the Candida load with the individual microbiome, the samples were divided into three categories - low (,0.01% Candida), medium (0.01–0.1%) and high Candida load (.0.1%) groups. The samples with a high Candida load were less diverse than samples with low Candida (p,0.005) (Figure S2C). The multidimensionality of the data was first reduced by an OTU-based method – Principal Component Analysis (PCA). Oral Candida and Salivary Microbiome There was no clear separation into sample clusters by the Candida load. Rather than that, a continuous gradient from low to high Candida load samples was observed (Figure 3A, arrow). Next, we applied the phylogeny-based method UniFrac to the data. UniFrac accounts for the phylogenetic divergence between the OTUs. No separation of samples was obtained in principal coordinate analysis (PCoA) on unweighted (qualitative) UniFrac distances (Figure S3A), while weighted (quantitative) UniFrac distances (Figure S3B) showed a gradient from low to high Candida load samples similar to the PCA plot. Based on the loadings of the PCA, the OTUs that contributed most towards the low Candida load sample direction in the PC1 were classified as Prevotella (4 OTUs), Actinomyces, Veillonella, Megasphaera, Leptotrichia (2 OTUs) and in the PC2– Porphyromonas, Neisseria, Haemophilus and Prevotella. The OTUs that contributed towards high Candida load sample direction were classified as Streptococcus (2 OTUs), Lactobacillus (2 OTUs), Rothia and Gemella. Prevalence of OTUs classified as Lactobacillus (2 OTUs) and Scardovia were associated with the high Candida load (p,0.005, G- test, NS after Bonferroni correction). Abundance of OTUs classified as candidate division TM7, Leptotrichia (2 OTUs), Prevotella (3 OTUs), Peptostreptococcus, Capnocytophaga and Johnsonella were associated with the low Candida load (p,0.005, ANOVA, NS after Bonferroni correction). Individual Microbiomes by the Presence of Teeth versus Full Dentures From the information obtained by the questionnaire we could split the subjects into a dentate (N = 34) and an edentate (N = 20) group (Table S2). The edentate subjects reported regular use of full upper and lower dentures. The dentate subjects did not report wearing any prosthesis. The remaining subjects were either partially dentate and wore partial prosthesis (N = 20) or did not fill the questionnaire completely and were classified as ‘‘Not reported’’ (NR) (N = 8). Diversity statistics showed that samples from dentate subjects had significantly more OTUs per sample (mean 47, SD 11) than samples from the edentate group (mean 34, SD 14) (p = 0.001, Mann-Whitney test) and had higher sample diversity (Shannon Diversity Index 2.4, SD 0.3) than subjects with full dentures (2.1, SD 0.5) (p = 0.021) (Figure S2 D–F). Although dentate subjects showed a trend for a lower Candida load (median 0.04%, mean 0.32%, SD 0.6) than edentate subjects (median 0.16%, mean 72.6%, SD 322), there was no statistically significant difference in the Candida load between these groups (p = 0.311, Mann-Whitney test). The three data reduction approaches - the OTU-based PCA and the PCoA of the unweighted and the weighted UniFrac distances (Figure S4) - all stratified samples into the dentate and the edentate groups. The loadings of the PCA showed that Prevotella (4 OTUs), Actinomyces, Leptotrichia and Neisseria contributed towards the dentate group, while Rothia, Lactobacillus (3 OTUs) and Streptococcus (3 OTUs) contributed to the edentate group. Subjects with a dentition had a higher prevalence of OTUs classified as genus Parvimonas, Peptostreptococcus, unclassified Micro- coccales, Prevotella, Solobacterium, Neisseria and Abiotropia (p,0.05; G- test; NS after Bonferroni correction) and a higher abundance of OTUs belonging to genus Prevotella, Leptotrichia, Peptostreptococcus, Parvimonas, Solobacterium, Dialister and Porphyromonas (p,0.05; ANOVA; not significant (NS) after Bonferroni correction). Edentate subjects had a higher prevalence of Lactobacillus (p,0.05; G-test; NS after Bonferroni correction) and a higher abundance of an OTU classified as Rothia (p,0.05; ANOVA; NS after Bonferroni correction). PLOS ONE | www.plosone.org 2 August 2012 | Volume 7 | Issue 8 | e42770