Matched Matrix Calibration Curves

2024-03-29

In this project, we propose a framework for discriminating between detected and quantitative peptides in proteomics experiments. We introduce an alternative to stable isotope label calibration curves called "matched matrix calibration curves, and we demonstrate the method using yeast as a model system. We additionally apply the proposed framework for cerebrospinal fluid (CSF) proteomics and formalin-fixed paraffin-embedded (FFPE) renal biopsies. We find that, regardless of the sample type, the framework shows that not all detected peptides are quantitative, and that peptide LOQs range orders of magnitude even within the same protein. This illustrates the need for additional criteria to ensure that detected peptides are also quantitative. We thus demonstrate that proteomics experiments employing matched matrix calibration curves can produce truly quantitative measurements of peptides and proteins at the scale of an entire proteome.