Needles in a haystack of protein diversity: Interrogation of complex biological samples through specialized strategies in bottom-up proteomics uncover peptides of interest for diverse applications

Peptide identification is at the core of bottom-up proteomics measurements. However, even with state-of the-art mass spectrometric instrumentation, peptide level information is still lost or missing in these types of experiments. Reasons behind missing peptide identifications in bottom-up proteomics include variable peptide ionization efficiencies, ion suppression effects, as well as the occurrence of chimeric spectra that can lower the efficacy of database search strategies. Peptides derived from naturally abundant proteins in a biological system also have better chances of being identified in comparison to the ones produced from less abundant proteins, at least in regular discovery-based proteomics experiments. This dissertation focused on the recovery of the “missing or hidden proteome” information in complex biological matrices by approaching this challenge under a peptide-centric view and implementing different liquid chromatography tandem mass spectrometry (LC-MS/MS) experimental workflows. In particular, the projects presented here covered: (1) The feasibility of applying a liquid chromatography-multiple reaction monitoring MS methodology for the targeted identification of peptides serving as surrogates of protein biomarkers in environmental matrices with unknown microbial diversities; (2) the evaluation of selecting unique tryptic peptides in-silico that can distinguish groups of proteins, instead of individual proteins, for targeted proteomics workflows; (3) maximizing peptide identification in spectral data collected from different LC-MS/MS setups by applying a multi-peptide-spectrum-match algorithm, and (4) showing that LC-MS/MS combined with de novo assisted-database searches is a feasible strategy for the comprehensive identification of peptides derived from native proteolytic mechanisms in biological systems