Transcriptomic and taxonomic profiling of periodontitis by massively parallel sequencing

Periodontitis is a microbial-induced, chronic inflammatory disease that affects tissue and bone anchoring the teeth, and can ultimately lead to tooth loss. In addition, periodontitis may contribute to systemic diseases, such as cardiovascular disease (CVD), diabetes, rheumatoid arthritis (RA), and inflammatory bowel diseases. The pathogenesis of periodontitis is complex and involves bacterial products and host-immune response, as well as genetic and environmental factors. Despite extensive studies, the specific genes and mechanisms contributing to disease initiation and progression are poorly understood. The main aim of this thesis was to add to current knowledge of the disease; for this, we generated the transcriptomic and taxonomic profiles from gingival tissue and saliva samples collected from patients with periodontitis and from healthy controls. Study I explored the gene expression profile of periodontitis compared to the healthy state. Using RNA sequencing (RNA-seq) we characterized the gene expression of gingival biopsies from 62 patients with periodontitis and 62 healthy controls. In patients with periodontitis, RNA-seq showed that genes related to inflammation, the wounding and defence responses, apoptosis, and cell death were up-regulated compared with the controls while genes related to extracellular matrix organization and structural support were down-regulated. The two most highly up-regulated genes in periodontitis were mucin 4 (MUC4) and matrix metalloproteinase 7 (MMP7). Comparisons of the gene expression profiles of periodontitis, CVD, RA, and the inflammatory bowel disease ulcerative colitis (UC) identified only one gene that was commonly up-regulated in all four inflammatory conditions: pleckstrin (PLEK). Study II investigated the protein products of MUC4 and MMP7 in saliva and gingival crevicular fluid (GCF) samples from patients with periodontitis and from healthy controls. MUC4 levels were significantly lower in the saliva and GCF samples of patients with periodontitis compared to the controls, whereas MMP7 levels were significantly higher. Controlling for age and smoking, analyses revealed a significant association between MUC4 levels and periodontitis. Analysis that controlled for total protein levels, age, and smoking also found a significant association between the ratio of MUC4 to MMP7 levels and periodontitis, suggesting that this combination of MUC4 and MMP7 could possibly be used as a diagnostic marker for periodontitis. Study III used 16S ribosomal RNA gene sequencing to characterize the taxonomic composition in saliva and investigate the correlation between presence of microorganisms and levels of host inflammatory mediators in samples from 46 patients with periodontitis and 47 healthy controls. The composition of the microbial community differed significantly between these two groups. The microbes Prevotella sp., Phocaeicola sp., Fretibacterium sp., Streptococcus mitis/parasanguinis, Eubacterium saphenum, Tannerella forsythia, Filifactor alocis, and Parvimonas micra were elevated in the patients with periodontitis, as was the inflammatory mediator glycoprotein 130 (gp130). This mediator, as well as soluble tumour necrosis factor receptor 1 (sTNF-R1), sTNF-R2, soluble interleukin-6 receptor α (sIL-6Rα), pentraxin 3, and chitinase-3-like 1, were identified as positively correlated with the microbes Streptococcus sp., Selenomonas sp., Treponema sp., and Selenomonas sputigena. In contrast, we found the anti-inflammatory mediator IL-10 to be negatively correlated with Streptococcus sp., Eubacterium nodatum, and Filifactor alocis, and positively correlated with Granulicatella elegans. The final two studies of this thesis investigated the patterns of local gene expression in tissue sections. Study IV developed a technique for RNA-seq analysis within tissue sections, which Study V then used in periodontitis-affected gingival tissue. Differential expression analysis between inflamed compared with non-inflamed areas in the gingival tissue revealed 442 up-regulated genes in the inflamed domain. The three most highly up-regulated genes in the inflamed domain were immunoglobulin lambda like polypeptide 5 (IGLL5), signal sequence receptor subunit 4 (SSR4), and marginal zone B and B1 cell specific protein (MZB1). In contrast, we identified no down-regulated genes in the inflamed area when compared to the non-inflamed area. In summary, the studies in this thesis have used massively parallel sequencing to generate transcriptomic and taxonomic characterizations of gingival tissue and saliva samples from patients with periodontitis and healthy individuals in an attempt to identify specific genes involved in the pathogenesis of periodontitis. The thesis also identifies candidate biomarker proteins and microbes for future diagnostic assessment of the chronic inflammatory disease periodontitis