Mass spectrometry-based proteomics is well-known for its ability to quantify proteins with high accuracy and precision. External calibration curves and single-point calibration methods are often employed in targeted proteomics for protein quantification. These methods involve using external curves to determine the range of linearity, or adding isotopically labeled internal standards to samples to derive analyte concentration. However, they have limitations because the range of linearity is not directly determined within the sample. This issue is particularly significant when dealing with large patient cohorts. To address this challenge, a few years ago we developed the Isotopologue Multiple-point Calibration (ImCal) strategy. ImCal uses a mixture of isotopically labeled peptides at different concentrations to establish a multi-point internal calibration curve, ensuring precise and accurate quantification of specific peptides of interest in targeted proteomics applications. Unfortunately, the use of multiple isotopologue peptides in ImCal increases the cost of each targeted assay and limits the number of analytes measured due to cycle time constraints.

We extended the ImCal approach to the whole proteome by developing an inexpensive TMT-based multi-point internal calibration curve strategy (TMTCal) created from serial dilutions of total protein extracts. These dilutions are used to generate internal calibration curves within a single experiment for all peptides identified in a proteome.

For this purpose, human ovarian cancer cells (SK-OV-3) were cultured in triplicate, with and without cis-platinum, and subsequently digested with trypsin. Concurrently, a pooled sample was created to generate several dilutions and create an internal multi-point calibration curve. Tandem mass tags (TMT-11) were used to label the samples, which were then mixed. Following basic pH reversed-phase fractionation, samples were analyzed using a 90-min gradient in an Orbitrap Eclipse mass spectrometer and a Real-Time Search MS3 method (RTS-MS3). Acquired data were processed using Proteome Discoverer (v2.4).

Using the TMTCal, we observed that the majority of identified peptides demonstrated high quantitative response, with most exhibiting complete or nearly complete linear regression dilution curves (R²>0.95). Furthermore, we confirmed that the vast majority of peptides identified in the human ovarian cancer cell samples fell within the linear range of quantitation, ensuring accurate and precise relative quantification using either label-free direct comparison or by utilizing abundances derived from the individualized regression lines for each peptide. In conclusion, the TMTCal technique allows for a more comprehensive analysis of peptide quantitative behavior within the human proteome and, by extending the concept of multi-point internal calibration curves to the entire proteome, enables enhanced accuracy and precision in proteome-wide relative quantification.