Development of amyloidosis typing method and data acquisition strategies using tandem mass spectrometry

Abstract

A variety of mass spectrometry acquisition methods are designed to maximize multiplexing capacity, quantification accuracy, or detection sensitivity of peptide ions in complex biological matrices. Data-independent acquisition (DIA) is an emerging method that aims to quantify proteins with high accuracy embracing the proteome complexity. With DIA, a novel strategy was proposed to predict amyloidosis types with a majority vote rule. Informative amyloid peptides were selected to cast the vote for specific amyloidosis types based on intensity distributions in disease populations. In contrast to DIA, the goal of data dependent acquisition (DDA) is to maximize the multiplexing capacity of peptide identification. Although DDA is a powerful data collection strategy, the majority of peptide ions in a complex mixture remain unanalyzed by tandem mass spectrometry (MS/MS). In this thesis, a novel acquisition approach, data dependent acquisition plus (DDA+), is proposed to improve sampling coverage by combing the characteristics of existing DDA and DIA methods.