Acceleration of Purine Degradation by Periodontal Diseases

Abstract

Periodontal diseases, such as gingivitis and periodontitis, are characterized by bacterial plaque accumulation around the gingival crevice and the subsequent inflammation and destruction of host tissues. To test the hypothesis that cellular metabolism is altered as a result of host-bacteria interaction, we performed an unbiased metabolomic profiling of gingival crevicular fluid (GCF) collected from healthy, gingivitis, and periodontitis sites in humans, by liquid and gas chromatography mass spectrometry. The purine degradation pathway, a major biochemical source for reactive oxygen species (ROS) production, was significantly accelerated at the disease sites. This suggests that periodontal-disease-induced oxidative stress and inflammation are mediated through this pathway. The complex host-bacterial interaction was further highlighted by depletion of anti-oxidants, degradation of host cellular components, and accumulation of bacterial products in GCF. These findings provide new mechanistic insights and a panel of comprehensive biomarkers for periodontal disease progression.

INTRODUCTION

Periodontal diseases are among the most common infectious diseases in humans (Pihlstrom et al., 2005). Gingivitis, the mild form of the diseases, is characterized by host tissue inflammation and bacterial plaque accumulation around the gingival margin. Treatment of gingivitis by improved oral hygiene practices can significantly reverse the disease condition. However, left untreated, gingivitis can lead to the more serious and irreversible disease, periodontitis. Aside from affecting oral tissues, periodontal diseases have been associated with various systemic diseases (Seymour et al., 2007).

The majority of the complex interactions between host tissues and bacteria in periodontal diseases occur at the junctional and crevicular epithelia. Many substances released by bacteria, such as endotoxins, proteases, lipases, and sialidases, have been demonstrated to play significant roles in host tissue damage (Smalley, 1994). However, increasing evidence suggests that the diseases are also mediated by the host’s inflammatory responses to bacteria (Van Dyke and Serhan, 2003). Under activation of various chemical signals, the host tissues orchestrate a range of complex responses to combat bacteria. Polymorphonuclear leukocytes produce increasing levels of reactive oxygen species (ROS) and proteolytic enzymes. Hyperactivity of this response can inadvertently contribute to host tissue damage.

At the interface of the epithelia and bacterial plaque is plasma-derived gingival crevicular fluid (GCF). Because GCF can be collected non-invasively and is site-specific, it is an ideal substrate for the study of host-bacteria interactions (Embery and Waddington, 1994). In a variety of targeted biochemical analyses, many potential GCF biomarkers for periodontal disease have been proposed. These include host and bacterial enzymes, endotoxins, nucleic acids, proteins, carbohydrates and lipids, degradation products from collagens and bones, immunoglobulins, cytokines, and hormones (Embery and Waddington, 1994; Akalin et al., 2007; Karthikeyan and Pradeep, 2007; Pradeep et al., 2007; Prapulla et al., 2007). However, despite the wealth of information published, the broad extent of host-bacteria interaction and the mechanistic details of disease progression on cellular biochemical metabolism still lack clarity.

Metabolomic profiling is a rapidly evolving technology that has been increasingly used in disease characterization and drug development. Hence, we attempted to gain further understanding of the biochemical basis of periodontal disease progression by analyzing GCF from healthy, gingivitis, and periodontitis sites using an unbiased metabolomic profiling approach based on liquid and gas chromatography/mass spectrometry (LC/MS and GC/MS).

MATERIALS, PARTICIPANTS, & METHODS

Experimental Design and Participants

Twenty-two persons with chronic periodontitis (41% males), 33 to 67 yrs of age (53 ± 11), were selected from among research volunteers at The Forsyth Institute Dental Clinic. These individuals had at least 20 natural uncrowned teeth, ≥ 8 sites with pocket depth ≥ 5 mm, and clinical attachment level (CAL) ≥ 3 mm. The participants had no known history of allergy to the dentifrice for the washout period (see below). Exclusion criteria included: presence of orthodontic appliances, abnormal salivary function, use of prescription drugs, use of antibiotics 1 mo prior to or during the study, use of any over-the-counter medications other than analgesics, daily use of vitamin supplements, presence of 5 or more decayed dental sites, diseases of the soft or hard oral tissues, and other systemic conditions. The study protocol was approved by The Forsyth Institute’s Institutional Review Board, and all study participants signed an informed consent form prior to enrollment. At their first visit, participants received a tube of Colgate Regular dentifrice (Colgate-Palmolive, Piscataway, NJ, USA) and a toothbrush and were instructed to use the product for a minimum of 1 wk (washout period) prior to their sampling visit. Other mechanical oral hygiene devices were allowed during this washout period, but no other oral care products.

GCF Sample Collection

Following isolation of sites with cotton rolls to prevent contamination with saliva, supragingival plaque was removed with a curette, sites were gently air-dried, and GCF samples were obtained from 3 different site categories. For each participant, 6 healthy (H; PD ≤ 3 mm and no bleeding on probing [BOP]), 6 gingivitis (G; PD ≤ 3 mm and BOP), and 3 periodontitis (P; PD ≥ 5 mm and BOP) sites were sampled. GCF samples were collected from each site by means of filter strips (Periopaper^®, Interstate Drug Exchange, Amityville, NY, USA) gently inserted into the orifice of the periodontal pocket. Periopaper strips were kept in place for 30 sec, and the GCF volume collected was determined with a pre-calibrated Periotron 8000^® (Oraflow Inc., Plainview, NY, USA). Samples from each participant were pooled into different site categories, placed in separate Eppendorf tubes, and stored at −80^oC until assay.

Metabolomic Profiling Technology

Metabolomic profiling was performed as described previously (Lawton et al., 2008). In summary, after the extraction of metabolites from the GCF collection strips, the extracts were analyzed by GC/MS and LC/MS. We carried out chromatographic separation, followed by full-scan mass spectroscopy, to record and quantify all detectable ions presented in the samples. We identified metabolites with known chemical structure by matching the ions’ chromatographic retention index and mass spectral fragmentation signatures with reference library entries created from authentic standard metabolites under the identical analytical procedure as the experimental samples. For ions that were not covered by the standards, additional library entries were added based on their unique ion signatures (chromatographic and mass spectral). After this, these ions could be routinely detected and quantified. The detailed procedure is described in Appendix A.

Statistical Analysis

After normalization and imputation (see the Appendices), the data were log-transformed. We then performed ANOVA and t tests to compare data obtained from the healthy, gingivitis, and periodontitis sites. Multiple comparisons were accounted for with the false discovery (FDR) rate method, and each FDR was estimated by q-values.

RESULTS

Metabolomic Profiles of GCF Samples and Statistical Analysis

In total, 330 individual GCF samples were collected, resulting in 66 pooled samples. The GCF samples ranged from 0.01 μL to 1.15 μL. The mean volumes in μL (± SD) for the healthy, gingivitis, and periodontitis site categories were: 0.18 ± 0.10, 0.25 ± 0.13, and 0.42 ± 0.19, respectively.

With the metabolomic profiling method, 228 metabolites were detected, of which 103 matched known chemical structures in our chemical reference library. We used matched-pairs t tests to analyze the differences among the healthy, gingivitis, and periodontitis sites. Approximately 50% of the detected metabolites showed altered levels among the 3 sites (p < 0.05). The metabolites matched with known chemical structures and their statistical comparisons among the healthy, gingivitis, and periodontal sites by t test are listed in Appendix B. A summary of the biochemical pathways and compound classes altered by the periodontal diseases is presented in the Table. ANOVA analysis did not produce a list of metabolites different from the t tests (data not shown). For the majority of metabolites with altered concentrations, the levels at gingivitis sites resided between the levels at healthy and periodontitis sites (Appendix B). This suggests that the metabolic changes induced by gingivitis are a continuum of those of periodontitis.

Up-regulation of the Purine Degradation Pathway

One of the most striking results was the up-regulation of inosine, hypoxanthine, xanthine, guanosine, and guanine at the disease sites (Fig. 1 ), which indicated accelerated metabolic flux of the purine degradation pathway. The consecutive steps of conversion of hypo xanthine to xanthine and then to uric acid are both catalyzed by xanthine oxidase. The reactions are coupled with a reduction of oxygen to generate superoxides in the form of O₂ ⁻ and H₂O₂ (Fig. 1 ). In contrast, the level of uric acid, the end-product of this pathway, was decreased at the disease sites (Fig. 1 ). Uric acid is a known cellular anti-oxidant. As described in the next section, the change in uric acid was consistent with that in other anti-oxidants.

Oxidative Stress

The levels of both reduced and oxidized glutathione were decreased at the disease sites (Fig. 2 ). Glutathione plays a central role in cellular defense against free radicals and xenobiotics. Two other major cellular anti-oxidants, ascorbic acid (Fig. 2 ) and uric acid (Fig. 1 ), were also decreased at the disease sites.

Metabolites of Host Tissue and Bacteria Interaction

The changes in many metabolites may further illustrate the host-bacteria interactions (Appendix B). The levels of many free amino acids and amino acid metabolites were increased by the diseases. The only exception was glutamine, which exhibited a clear decrease.

Putrescine and cadaverine, two polyamines and the end-products of amino acid degradation, were found to be up- regulated by the diseases. While putrescine can be produced by both the mammalian and bacterial pathways, cadaverine is almost exclusively of bacterial origin (Fothergill and Guest, 1977).

Choline and glycerol-3-phosphate, two lipid metabolites, were increased by the diseases. Alteration of several sugars (maltotriose, maltose, and glucose) by the diseases was also evident. In addition, N-acetylneuraminic acid, a major sialic acid presented in glycoproteins, was increased at the disease sites.

DISCUSSION

In this study, we successfully used biochemical profiling technology to analyze GCF samples from healthy, gingivitis, and periodontitis sites. The impact of periodontal diseases on this panel of metabolites produced a broad overview of the effects of complex host-bacteria interactions on biochemical metabolism. In addition to recapitulating some of the previously published observations, we have identified metabolic changes associated with periodontal disease progression that were previously unknown or unclear.

The most significant results in this study pertained to pathways and metabolites associated with cellular oxidative stress. Redox balance is vital for the maintenance of normal cellular function and health. Overproduction of ROS and/or decreased cellular anti-oxidant capabilities can lead to tissue damage and disease (Bergamini et al., 2004; Valko et al., 2007). The reductions of anti-oxidants by periodontal diseases have been well-documented in the literature (Embery and Waddington, 1994; Chapple et al., 2002). The decreased levels of glutathione and ascorbate and uric acid at the disease sites observed in this study provided further confirmation of these findings. However, the biochemical origin of ROS production in periodontal diseases has not been well-understood. In muscular and venous tissues, the main enzymatic sources for ROS are the mitochondrial respiratory chain, NADPH oxidase, xanthine oxidase, and nitric oxide synthase (Jackson et al., 2007). It has been proposed that the NAD(P)H oxidase shunt and mitochondrial dysfunction could be involved in periodontal diseases (Szasz et al., 2007). While this hypothesis needs to be further explored, analysis of the data generated in this study argues that xanthine oxidase plays a significant role in ROS generation in periodontal diseases.

Inosine, hypoxanthine and xanthine, guanosine, and guanine were among the most dramatically elevated metabolites observed in this study. This suggests that the purine degradation pathway and ROS generated by xanthine oxidase are significantly accelerated under the disease conditions. Xanthine oxidase and its associated ROS production have been shown to be involved in the pathogenesis of various diseases, such as cardiovascular diseases, ischemia- reperfusion injury, diabetes, hypertension, and inflammatory diseases (Harrison, 2004; Pacher et al., 2006). Our results provide evidence, for the first time, that the progression of periodontal diseases could also be attributed, at least in part, to the purine degradation pathway and xanthine oxidase. While it is plausible that the increased purine degradation could result from the breakdown of DNA molecules related to tissue damage, the most likely cause is that host tissues up-regulate this pathway as a defense mechanism against bacterial pathogens. It has been shown that one of the functions of xanthine oxidase is antimicrobial activity and host defense through ROS generation against oxidant-sensitive organisms (Segal et al., 2000; Stevens et al., 2000). Interestingly, several known factors that stimulate xanthine oxidase expression, such as lipopolysaccharide, inter-leukin-1, interleukin-3, and tumor necrosis factor α (Berry and Hare, 2004), are also shown to be elevated by periodontal diseases (Van Dyke and Serhan, 2003). Perhaps their mode of action could be mediated through xanthine oxidase. It is likely that, in periodontal diseases, hyperactivity of the purine degradation pathway in host connective tissue results in excess ROS production beyond its own anti-oxidative capacities. With the growing understanding of the biological and pathological function of xanthine oxidase, therapeutic intervention for cardiovascular and inflammatory diseases with xanthine oxidase inhibitors has attracted great interest (Pacher et al., 2006). Similar strategies may hold promise for managing periodontal diseases as well.

Analysis of the data generated in this study provides a broad picture of the interaction between host and bacteria (Table). For example, the increase of many amino acids, choline, and glycerol-3-phosphate at the disease sites was likely the result of host tissue degradation. Glutamine was the only amino acid that showed a significant decrease, probably due to its consumption as a nitrogen source by the bacteria. The sialic acid N-acetylneuraminic acid was increased at the disease sites. It is known that bacteria associated with periodontitis express sialidase as a virulence factor [presumably to cleave sialic acids from host glycoproteins to prevent host defense and degrade host cellular proteins (Ishikura et al., 2003)].

The current diagnosis of periodontal diseases is based on visual and radiographic examinations, which often indicate only the consequences of past diseases. Early prediction of risk and accurate diagnosis of current disease activity are needed for effective prevention and treatment. Many potential biomarkers have been proposed as diagnostic candidates for periodontal diseases, especially enzymes of host or bacterial origin and prostaglandin E₂ (Lamster, 1997; Pihlstrom et al., 2005). However, because of concerns with specificity and sensitivity, the utility of these markers is uncertain. In this study, the simultaneous measurement of approximately 200 metabolites in GCF provided a more comprehensive picture of the complex host-bacteria interaction than previous targeted analyses. By monitoring selected metabolites representing the diverse biochemical pathways, it is therefore possible to get an accurate assessment of healthy/disease states, current stages of diseases, and the effectiveness of therapeutic interventions.

In conclusion, this study demonstrated that biochemical profiling technology is a powerful tool for periodontal disease research. The results provide new mechanistic insights, bio-markers, and treatment strategies for periodontal diseases.

Table.

Summary of the Biochemical Pathways and Compounds Altered at the Gingivitis and Periodontitis Sites in Comparison with the Healthy Sites

Biochemical Pathway and Compound Classes	Changes at the Disease Sites
The detailed list of the metabolites and the statistical values by matched-pair t tests are listed in Appendix B. Up: The pathway or metabolites were up-regulated by the diseases. Down: The pathway or metabolites were down-regulated by the diseases.
Anti-oxidants (glutathione, ascorbic acid, uric acid)	down
Glutamine	down
Tri- and di- saccharides	down
Amino acids (except glutamine)	up
Choline, glycerol phosphate	up
Glucose, α-ketoglutarate	up
Polyamines: putrescine and cadaverine	up
Purine degradation	up
Urea cycle	up

Figure 1.

Illustration of purine degradation pathway and the levels of inosine, hypoxanthine, xanthine, uric acid, guanosine, and guanine by box plot for site categories (data distribution of the 22 participants in this study) and scatter plot for each individual in the GCF samples. The metabolites that were up-regulated and down-regulated by the diseases are indicated by up and down block arrows, respectively. For the box plots, the top and bottom of the box represent the 75th and 25th percentiles, respectively. The top and bottom bars (“whiskers”) represent the entire spread of the datapoints for the participants, excluding “extreme” points, which are indicated with squares. The filled triangle indicates the mean value, and the open triangle indicates the median value. The p-values for all comparisons are referenced in Appendix B, and if < 0.05, are marked with an asterisk. H, healthy sites; G, gingivitis sites; P, periodontitis sites. The analytical variations for the compounds measured were below 15%.

Figure 2.

The levels of reduced glutathione (A), oxidized glutathione (B), and ascorbic acid (C) by box plot for site categories (data distribution for the 22 participants in this study) and scatter plot for each individual in the GCF samples. The explanation for box plots can be found in the legend of Fig. 1. H, healthy sites; G, gingivitis sites; P, periodontitis sites. The analytical variations for the compounds measured were below 15%.

Footnotes

Notes

A supplemental appendix to this article is published electronically only at .

Acknowledgements

The authors thank Drs. Danny Alexander, Kirk Beebe, and Allen Phillips for helpful discussions. This investigation was supported by a research grant from Colgate-Palmolive Company to The Forsyth Institute and Metabolon Inc. Virginia Barnes, Harsh Trivedi, William Devizio, and Tao Xu are employees of Colgate-Palmolive Company. Ricardo Teles is an employee of The Forsyth Institute. Matthew Mitchell, Michael Milburn, and Lining Guo are employees of Metabolon.

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