In recent years, the biological sciences have seen a surge in the development of methods, including high-throughput global methods, for the quantitative measurement of biomolecule levels (i.e., RNA, proteins, metabolites) from cells and tissues. Just as important as quantitation of biomolecules has been the creation of approaches that uncover the regulatory and signaling connections between biomolecules. Our specific interest is in understanding peptide metabolism in a physiological setting, and this has led us to develop a multidisciplinary approach that integrates genetics, analytical chemistry, synthetic chemistry, biochemistry, and chemical biology to identify the substrates of peptidases in vivo. To accomplish this we utilize a liquid chromatography-mass spectrometry (LC-MS)-based peptidomics platform to measure changes in the peptidome as a function of peptidase activity. Previous analysis of mice lacking the enzyme dipeptidyl peptidase 4 (DPP4(-/-) mice), a biomedically relevant peptidase, using this approach identified a handful of novel endogenous DPP4 substrates. Here, we utilize these substrates and tissues from DPP4(-/-) mice to improve the coverage of the peptidomics platform by optimizing the key steps in the workflow, and in doing so, discover over 70 renal DPP4 substrates (up from 7 at the beginning of our optimization), a 10-fold improvement in our coverage. The sequences of these DPP4 peptide substrates support a broad role for DPP4 in proline-containing peptide catabolism and strengthen a biochemical model that interlinks aminopeptidase and DPP4 activities. Moreover, the improved peptidome coverage also led to the detection of greater numbers of known bioactive peptides (e.g., peptide hormones) during the analysis of gut samples, suggesting additional uses for this optimized workflow. Together these results strengthen our ability to identify endogenous peptide substrates through improved peptidome coverage and demonstrate a broader potential of this peptidomics platform.