Development of high sensitivity and high specificity strategies for tissue microproteomics

Mass-spectrometry based proteomics has become an indispensable tool for molecular biology and clinical research because of its ability to identify and quantify thousands of proteins. When combined with laser capture microdissection (LCM), MS-based proteomics may be used to investigate disease-associated changes in the proteome of specific tissue regions or cell populations. Such specificity is essential because different anatomical regions often have distinct and diverse functions and may behave differently under pathological conditions. However, the number of proteins that may be identified and quantified decreases with smaller sample amounts. Strict anatomical/cellular specification usually yields micrograms or submicrograms of protein, and thus ultrasensitive microproteomics protocols are required to analyze these small sample amounts while maintaining high proteome coverage. Recent advances in liquid chromatography (LC) and MS equipment have improved the analysis of low sample amounts. The development of mass spectrometers with increased sequencing speed and ion transmission, have resulted in an increase in dynamic range and sensitivity. The advances in ultra high-pressure liquid chromatography (HPLC) has enabled the routine use of long columns (≥50 cm) with smaller internal diameter and smaller particle sized (< 5 μm) further increasing peptide separation resolution. However, the developments in LC-MS sensitivity have outpaced developments in sensitive sample preparation protocols. In this PhD thesis, I will present my 4-years research on the development of ultransensitive microproteomics strategies for the molecular characterization of tissues. During my PhD I developed and optimized an ultrasensitive proteomic workflow for the analysis of small sample amounts, and I applied it to biomedical case studies. First, I compared the digestion efficiency of the Filter-Aided Sample Preparation protocol (FASP) and the Single-Pot, Solid Phase-enhanced Sample Preparation protocol (SP3) with the conventional urea based in-solution digestion (ISD) method for different amounts of HeLa cells. The SP3 protocol, based on the use of carboxylate coated paramagnetic beads, outperformed the FASP and ISD protocols for the analysis of small sample amounts, providing the identification of about 3000 protein groups from 1 μg of HeLa lysate. As a proof of principle, I applied the optimized SP3 protocol to the characterization of the brain of a mouse model of glioblastoma. Laser capture microdissection provided the specificity required to isolate different anatomical regions of the brain (healthy, border and tumor regions), while the SP3 digestion protocol provided the sensitivity required for the analysis of heterogeneous and complex samples. To ensure accurate relative quantification and increase the proteome coverage I optimized in-solution and on-column Tandem Mass Tags (TMT) labeling and peptide fractionation of low sample amounts. Preliminary experiments revealed very low labeling efficiency when standard labeling conditions were applied to volume limited samples. Following an exhaustive optimized of in-solution and on-column TMT labeling the final conditions provided a TMT labeling efficiency (for 1 μg of HeLa digest) even greater than that obtained using standard methods on high sample amounts (25-50 μg of digest). Moreover, high-pH reversed phase fractionation increased proteome coverage by approximately 140% relative to single long gradient analyses. One of the challenges of working with microdissected tissues or other samples characterized by low total protein content, is the need to estimate total protein content (essential knowledge for accurate quantitation). Previously adjacent sections were used just for the protein content estimation, which is non-ideal because tissue histologies may differ (especially for small pathological features with a specific histology). To address this, I developed a colorimetric assay for protein content estimation. I modified the microBCA protein assay to be able to measure proteins in just 1 μL and in the presence of the reagents commonly used in lysis buffers (as SDS, EDTA, EGTA, etc.). This modified microBCA assay allowed a reproducible quantification of the protein content of each individual sample down to a concentration of 15 ng/μL. The final optimized quantitative workflow for the proteomic analysis of tissue samples comprised laser capture microdissection, protein content estimation with the modified MicroBCA assay, SP3 digestion, TMT labeling, high-pH reversed phase fractionation and injection in a nanoLC system coupled with an Orbitrap Fusion mass spectrometer. As a proof of principle, I applied the optimized workflow to the proteomic characterization of mouse kidney substructures. Finally, I applied the optimized workflow to the characterization of the central and peripheral nervous system of a mouse model of Krabbe disease (the Twitcher mouse). I compared the proteomes extracted from the corpus callosum, motor cortex and sciatic nerves of five Twitcher and five control wild type mice. The results on the proteome changes in the Twitcher mouse provided new insights into the molecular mechanisms of Krabbe disease showing neuroinflammation, activation of immune response, accumulation of lysosomal proteins, demyelination, membrane rafts disruption and reduced nervous system development. Altogether, the microproteomic protocol developed during my PhD represents a powerful tool for the proteomic characterization of pathological tissues. Moreover, the research study on Krabbe disease represents the first in-depth proteomic characterization of the Twitcher mouse and a starting point for future functional experiments to study the pathogenesis of Krabbe disease and new possible therapies.