Development of an Automated Multi-Dimensional Workflow and its Applications in Clinical Proteomics

• Main Author: Kullolli, Majlinda
• Format: Dissertation
• Language: English
• Published: ProQuest Dissertations & Theses 01-01-2011
• Subjects: Analytical chemistry; Biochemistry
• ISBN: 1124598685; 9781124598680

Plasma and/or serum are attractive biofluid specimens for the detection and identification of disease-specific biomarkers. Due to the complexity and wide dynamic range of protein concentrations in these samples, pre-fractionation is necessary in order to reduce the complexity of the sample prior to protein identification by mass spectrometry. Lectins are widely distributed in nature and have the ability to recognize carbohydrates structures. Thus, for several decades the specificity of lectincarbohydrate recognization has been explored in biology and medicine. The major application has been lectin affinity chromatography; where the unique specificity of a ligand-biomolecule interaction is considered to be one of the most specific separation methods to isolate glycoproteins. My thesis work focused on the development of high performance multi lectin affinity chromatography support (HP-M-LAC). The support was fully characterized to obtain a lectin affinity HPLC column designed for optimal capture of the plasma glycoproteome. For this purpose the ligand density, immobilization kinetics, and elution conditions were optimized. Due to the high flow rate/pressure properties of this HPLC support; the HP-M-LAC has been automated for high throughput sample fractionation in clinical proteomics. This platform has been applied to a number of clinical proteomics studies, such as colon cancer, multiple sclerosis, obesity and type 2 diabetes after gastric bypass surgery. As part of a biomarker discovery program, we have studied well-defined clinical specimens and have found that with specific disease mechanisms, proteins that are up or down-regulated can be identified and verified by ELISA and Western blotting.