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Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Medical Biophysics

Supervisor

Siqueira, Walter L.

Affiliation

University of Saskatchewan

2nd Supervisor

Vieira, Liliani A. C.

Joint Supervisor

3rd Supervisor

McKenzie, Charles A.

Joint Supervisor

Abstract

Saliva’s clinical application for disease diagnosis and monitoring is limited by incomplete knowledge of salivary protein interactions, the effect of stimulation on the salivary proteome, and if these factors impact protein identification. This thesis expands knowledge of the salivary interactome and effects of stimulation intensity and duration on parotid saliva’s proteome. First, previous in vitro studies identified 43 proteins in the histatin 1-protein network and demonstrated histatin 1’s increased stability in whole saliva when interacting with amylase. We hypothesized that protein-protein-interaction databases could enlarge the histatin 1-protein network. A comprehensive histatin 1-protein network was created using STRING database, merging previous in vitro complex partners with in-silico interactors. Thirty-seven novel histatin 1 interactors were identified, demonstrating STRING’s utility for studying protein-protein networks. Second, heterotypic complexes between amylase and MUC 5B, MUC 7, histatin 1 and histatin 5 have been described. Given amylase’s biochemical characteristics and abundance in saliva, we theorized that amylase interacted with other proteins. Affinity chromatography, gel electrophoresis, tryptic in-gel and in-solution digestion, and mass spectrometry were used. Sixty-six proteins were identified in whole saliva’s amylase-protein network. Acidic, low molecular weight proteins involved in host protection had preference in amylase’s complex formation. An inclusive amylase-protein network was constructed using STRING database, opening avenue for further studies about the amylase interactome. Third, stimulation intensity and duration affect the composition of salivary gland secretions. We questioned if the proteome of the parotid gland’s secretion was also affected by stimulation intensity and duration. Continuous parotid saliva secretion (0.25 and 1.00 ml/min) for 30 consecutive minutes was achieved. After in-solution digestion and mass spectrometry, five time points were used for proteome identification. Combining both flows, 169 proteins were identified. Stimulation intensity strongly affected 119 proteins, 44 were affected by both factors, and 4 by neither, suggesting possible protein-specific secretory mechanisms. This thesis demonstrates that salivary proteins participate in large complexes, that can be represented and expanded with aid of protein-protein-interaction databases. It also provides insights into the complexity of factors affecting saliva composition, such as stimulation, and highlights the importance of developing standardized protocols for salivary biomarker research.

Summary for Lay Audience

Saliva is formed mainly by the secretion from salivary glands. However, it also contains elements from the blood, so it might be used to diagnose oral and systemic diseases. Many studies have investigated molecules in saliva that can be used to determine the onset of diseases like tooth decay and cancer. Changes in some salivary proteins may indicate the presence of disease. There is little information about how the interactions among proteins in saliva and the stimulation of saliva production interfere with saliva’s protein composition (salivary proteome). This thesis expands the knowledge of interactions between salivary proteins in the formation of complexes and the effects of intensity and duration of stimulation on the proteome of the secretion from salivary glands. The mouth’s harsh environment can break proteins into small pieces. The interaction of salivary proteins can protect some proteins from degradation and improve their clinical detection. First, the STRING protein-protein-interactions database was used to construct a comprehensive representation of the proteins that interact with histatin 1. Thirty-seven novel proteins were identified in the novel histatin 1-protein network. Second, our laboratory developed an approach to identify 66 proteins that interact with amylase, the most abundant protein in saliva. A novel inclusive amylase-protein network was created using the STRING database, combining the 66 partners with additional database interactors. Third, variations in the saliva secreted by salivary glands depending on stimulation can impact the composition and diagnostic application of saliva. Differences in the proteins secreted by the parotid glands, the largest human salivary glands, due to stimulation intensity (given by two flow rates) and duration (given by 30 minutes) were demonstrated, suggesting critical implications for the development of protocols for the discovery of biological markers (biomarkers) for diseases in saliva. This thesis shows that salivary proteins participate in large complexes, that can be visualized and enlarged with assistance of protein-protein-interaction databases, like STRING. It also provides an indication of the complexity of factors affecting saliva’s composition, such as stimulation, and emphasizes the importance of developing consistent procedures to investigate disease biomarkers in saliva.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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