Quantitative Proteomics for Marker Peptide Discovery: Simultaneous Quantification of All Regulatory Allergenic Foods and Application of Plasma Phosphopeptide for Alzheimer's Disease Staging

Abstract

Quantitative proteomics became a robust analytical approach that has revolutionized field of biology and biochemistry. Especially, LC-MS technique facilitates the identification and quantification of a wide range of biomolecules, from proteins to post-translational modifications. Also, this methodology enables the high-throughput measurement and simultaneous comparison of proteins in complex biological samples, offering valuable insights into disease mechanisms, and biomarker discovery. In recent times, there has been a notable upswing in biomarker research, with a primary emphasis on tackling a wide spectrum of diseases. The validation of biomarkers, crucial in understanding disease mechanisms and developing diagnostic tools, places a premium on quantitative precision. In response to this need, mass spectrometry technologies, specifically Multiple Reaction Monitoring (MRM) and Parallel Reaction Monitoring (PRM), have gained prominence. Each of these methods offers distinct advantages, making them indispensable tools in the quest for effective biomarker validation. This study encompasses two distinctive yet interconnected research directions, where the groundbreaking novelty of marker exploration with LC-MS takes center stage: (1) Simultaneous Quantification of South Korea All Regulatory Allergenic Foods and (2) Discovery and Application of Plasma Phosphopeptide Markers for Alzheimer’s Disease Staging. In part Ⅰ, the prevalence of food allergies is on the rise, yet a definitive treatment remains elusive. Given that strict allergen avoidance is often the primary management strategy, clear food labeling of major allergens is imperative. To achieve this, precise detection methods capable of identifying allergenic ingredients in trace amounts are essential. In this study, I discovered 62 marker peptides including 29 newly-found marker peptides and selected a total of 42 highly sensitive marker peptides for 21 distinct types of allergen-inducing foods, as ii designated in Korea using multi-stage protein marker peptide selection strategy. These food types encompassed egg, milk, chicken, cow, pig, abalone, oyster, mussel, bivalvia, pine nut, shrimp, mackerel, peach, tomato, crab, soy, wheat, walnut, peanut, squid, and buckwheat. I optimized the dynamic Multiple Reaction Monitoring (dyMRM) method for single quantitative analysis, enabling us to perform quantitative analyses on eight different processed foods in just 25 minutes, using only 10 micrograms of analytes. As a result of this research, I have developed a method that can confirm the accurate labeling status of processed foods with a single analysis, allowing for the detection of allergenic ingredients at concentrations as low as parts per million (ppm). This advancement is a significant step towards improving food safety and supporting individuals with food allergies. In part Ⅱ, in this study, I conducted a comprehensive analysis of plasma samples from individuals at various stages of Alzheimer's disease (AD) and healthy controls. Specifically, I have focused on phosphopeptides associated with Tau, a key protein in AD pathology, and brain tissue-specific proteins such as GSK3β. Utilizing LC-MS/MS PRM analysis, I identified 11 phosphopeptides that showed distinct patterns corresponding to AD progression in pooled plasma samples. Notably, there were a total of 7 phosphopeptides corresponding to pTau, and the remaining 4 were phosphopeptides related to GSK3β, NEFM, DPYSL2, and MAP1B. Six phosphopeptides that showed differences between the normal-negative and normal-positive groups can be classified as potential markers for the early stages of AD. The phosphopeptides corresponding to NEFM and MAP1B showed significant changes in the MCI-positive or AD-positive groups, suggesting that they can be classified as marker peptide candidates for the late stages of AD. To enable precise quantification, I synthesized and labeled these phosphopeptides with isotopes. In the validation cohort, I employed a quantitative approach to assess the significance of these biomarkers, measuring phosphopeptide levels in both plasma and CSF by determining the total peak area ratio of analytes and standards. Through an optimized scheduled PRM method, I detected 3 phosphopeptides, revealing significant differences between AD stages. This research underscores the potential for stage-specific classification of Alzheimer's disease using LCMS/MS, shedding light on the utility of these phosphopeptides as valuable tools for early diagnosis and monitoring of AD progression.