Proteomic analysis of human immunodeficiency virus and periodontitis

Periodontal disease is a chronic oral infection that results from prolonged and persistent irritation of the supragingival tissue by dental biofilm buildup and can result in the destruction of connective tissue, cementum, the periodontal ligament, and the alveolar bone [1–3]. The findings of several studies have indicated a relationship between periodontitis and systemic and major lifestyle-related diseases, inasmuch as periodontitis is considered to be triggered by certain types of bacteria, poor dietary habits, and smoking [4–7]. Ahmad et al. reported that the majority of topics covered by the top 100 most widely read publications concerned the associations of periodontal disease with cardiovascular diseases (8598 citations) and with diabetes mellitus (7660 citations), followed by the systemic complications of periodontitis (mixed manifestations; 3918 citations), pregnancy-related manifestations (10,909 citations), rheumatic manifestations (1955 citations), pulmonary manifestations (399 citations), cerebrovascular diseases (478 citations), and cancer (169 citations) [8]. However, the mechanisms underlying periodontitis are unclear. Bacterial pathogens are associated with the onset and progression of periodontal disease [9,10]. Consideration of some of the more general aspects of microbial dental biofilm, including the development, heterogeneity, microbial succession, composition, structure, and mechanisms of dental biofilm formation, should precede the discussion of the microbial composition of the gingival crevice (subgingival dental biofilm).

Dental biofilm is a collection of heterogeneous, dense, and non-calcified bacterial masses intimately associated with the tooth surface, and their firm adherence to the surface is usually considered to prevent their dislodgement with the salivary flow. Subgingival biofilms are nonadherent and comprise a large number of motile organisms. However, the detailed mechanism by which systemic disease is related to periodontal disease remains unclear. MS-based approaches can quantify enzyme levels in biological fluids, but they lack the capacity to measure their enzymatic activity [11]. The mechanistic aspects underlying the disease state are unknown, although the onset of periodontal disease is reportedly triggered by bacterial periodontal infection. Viruses may participate in the pathogenesis of periodontitis by altering immunological defenses or inducing destructive host reactions, or through direct lytic effects on periodontal tissue [12,13].

Proteome, which defines the entire set of proteins that can be expressed by an organism, tissue, or cell, has attracted considerable attention because it can directly lead to the development of targeted therapeutics and identification of disease markers. In recent years, proteomic technology has been used to identify periodontitis biomarkers, with the discovery of several promising candidates as a result of exhaustive studies [14–17]. To determine the identity of biomarkers, extracted proteins are separated by one- and two-dimensional gel electrophoresis and their mass-to-charge ratios are measured with matrix-assisted laser desorption/ionization–time-of-flight (MALDI–TOF) mass spectrometry (MS). Liquid chromatography (LC)–MS, another tool used for protein identification, is particularly indispensable for screening proteins involved in inborn metabolism errors, toxicological analyses, and determining the efficacy of drugs. In addition, various immunoassays are frequently used to detect or measure steroid and peptide hormone concentrations.

Historically, protein detection approaches have served as the basis to define a number of pathways regulated during the course of periodontal disease. The early techniques available had a very limited ability to identify a restricted number of the potentially involved factors; therefore, a significantly large number of samples were needed for broader analysis. The more recent approaches, including high-throughput sequencing, allow for a more complete understanding of the whole process because they enable the identification of an unlimited number of factors (including unknown factors).

Gingival crevicular fluid (GCF) is the so-called proximal fluid that best reflects the condition of periodontal tissues and is close to the lesion site. GCF has been used widely as a sample. The gingival sulcus, a V-shaped space that surrounds the tooth, exudes the GCF. This fluid contains a large number of enzymes and proteins related to the metabolism of periodontal tissues, and these amounts are said to be very important indicators for understanding the progression of periodontitis and evaluating its pathological processes. However, the level of each enzyme and protein in GCFs is very small, and mass spectrometry can be used to analyze the trace amounts of proteins in periodontal tissues and GCF [18–20]. The gingival sulcus exudate contains various proteins involved in the progression of periodontal diseases and destruction of periodontal tissues; for example, proteins specific to each pathological condition of periodontal diseases are expressed or increased, and enzymes are produced by the destruction of cells. It is expected that some of these proteins are candidate markers for periodontal diseases.

Until recently, proteomic analyses have relied on several methods, including integrative MS, antibody-based affinity purification of protein complexes, cross-linking, and protein microarray to characterize the interplay between host proteins and RNA and DNA viruses after infection. Moreover, MALDI–TOF MS and LC–MS/MS have been widely used to analyze purified virions, which led to the discovery of previously unidentified viral components [21]. Recently, investigators have attempted to simultaneously decipher the microbiome and proteomes of diseased periodontal tissues [22]. The increased prevalence and severity of chronic periodontitis in patients with human immunodeficiency virus (HIV) suggest that HIV infection might predispose patients to this oral condition.

A meta-analysis by Gao et al. revealed that multiple approaches are used for the statistical analyses of proteomic data [23]. The authors examined 21 studies that included a total of 995 patients with periodontitis and 564 individuals with clinically healthy gingival tissue and found that the Epstein–Barr virus (EBV) was associated with chronic and aggressive periodontitis. This relationship was present predominantly in Asian, European, and American study populations in whom EBV was most easily detected in the subgingival biofilm and gingival tissue rather than in crevicular fluid. The authors concluded that periodontal pockets ≥5 mm in length were superior to those ≤3 mm in length for EBV detection.

Phelan et al. hypothesized that significant differences in crosstalk exist between the proteome, microbiome, and innate immune systems between antiretroviral-naive subjects with HIV infection and uninfected individuals and that clinical findings would reflect such differences [24]. The clinical core formed the infrastructure of this study.

In a study by Schulte et al., targeted and discovery-based LC–MS/MS workflows were used to determine changes in the levels of salivary metabolites in 20 children with perinatally acquired HIV and 20 uninfected children with and without moderate periodontitis [25]. The evaluation of the main effects associated with perinatally acquired HIV and periodontitis, and their interaction showed that the metabolism of oral bacteria may be influenced by HIV and highly active antiretroviral therapy.

Proteomic approaches using MS can quantify post-translational modifications of host and viral proteins during the course of infection. The clinical applications of MS can be broadly classified into two categories as follows: search for new diagnostic biomarkers based on comprehensive proteomic and metabolomic analyses, and use in clinical laboratories (mainly bacteriological tests).

With the increasing commercialization of MALDI–TOF MS, the combination of electrospray ionization and LC–MS/MS has rapidly become a popular method for the quantitative determination of low-molecular-weight compounds, and LC–MS has become an essential tool in forensic toxicology. The number of studies on bacterial identification using MS is increasing every year. Although rapid microbial identification by MALDI–TOF MS has become an essential method in clinical laboratories, LC–MS/MS is expected to play an increasing role in the future.

It is done. Most studies of virus-mediated post-translational modifications use either stable isotope labeling with amino acids in cell culture or isobaric labeling; however, label-free quantitative proteomics is increasingly preferred owing to its improved instrumental sensitivity. Not only periodontal disease but also numerous other diseases in humans alter the expression levels of proteins in cells, which greatly impact normal metabolic activities. Therefore, detection and detailed analysis of proteins are necessary to understand disease progression, elucidate the causes, and develop new treatment methods. Specifically, in periodontal disease, the information transmitted from periodontal tissue lesions must be accurately determined.

For protein identification, proteins extracted from cells, tissues, and body fluids are expanded in one- and two-dimensional electrophoresis gels, and samples cut from the gels are identified using MALDI–TOF MS. After the digestion of biological samples with trypsin and other enzymes, the mass of the cleaved peptides is measured with LC–MS; this approach allows the analysis and identification of various proteins in tissues and organs. Currently, only a few applications of proteomic analysis using MS are available for the investigation of the association of HIV with periodontitis, and more applications are expected in the future.

In conclusion, proteomic analysis has become the leading approach with increasing significance in clinical applications that is associated with the development of high-performance instruments that allow for the identification of disease-specific biomarkers and rapid protein profiling of the analyzed samples for large-scale analysis of complex biological samples. The creation of bioinformatic tools for proteomic analyses will be necessary to advance our understanding of how HIV infection moderates the risk and development of periodontitis.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

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Funding

This work was supported by Grant-in-Aid for Scientific Research (grant no. 18K09593).