The Methodological Proteome: Developing Novel Methods for Bottom-Up Proteomics

Shotgun or ‘bottom-up’ proteomics is a common technique used to characterize proteins from biological samples. In this technique, proteins are enzymatically digested into peptides, which are then separated and analyzed via liquid chromatography tandem mass spectrometry (LC-MS/MS). By comparing the masses of tandem spectra with those predicted from a sequence database or a peptide spectral library, peptides can be identified and assembled into a protein identification. Over the years, proteomics has seen significant technological advancements, allowing for deeper detection of proteome complexity. There are now mass spectrometers with shorter cycle times and higher resolving power as well as statistical methods and search engine software capable of identifying and quantifying thousands of proteins and peptides from a single sample. These advances have made bottom-up proteomics an indispensable tool for a wide variety of researchers motivated by fast and effective sample preparations.

While the technology for mass spectrometry has been evolving, so too are the methods for preparing protein samples prior to MS analysis. In particular, protein filter-based preparations, such as Filter Aided Sample Preparation (FASP) and Suspension Traps (S-Traps), have improved bottom-up sample preparations. Filter-based preparations have made it possible to isolate and process proteins from complex mixtures. This allows the use of reagents that are beneficial to proteomic preparations (e.g. detergents), but otherwise impede instrument performance. However, these improvements are often attached to time-consuming or expensive protocols, and many proteins evade detection via ‘traditional’ bottom-up approaches. In this thesis, I highlight how protein filters for bottom-up proteomics studies have greatly advanced the field and describe novel approaches and design new methods for protein preparation, isolation, long-term storage, and modify existing protocols to detect novel ‘dark proteome’ proteins.