Mass spectrometry based targeted proteomics is the most sensitive approach to answer and address specific biological questions in an accurate and quantitative fashion. However, the data analysis design used for such quantification varies in the field leading to discrepancies in the reported values. In this study, different quantification strategies based on calibration curves were evaluated and compared. The best linearity was achieved when creating a calibration curve using the intensity to amount method. However, the best accuracy and coefficient of variation was achieved by ratio to ratio calibration curves. In addition, we also demonstrated how a LLOQ estimation in combination with one-point calibration can be utilized to conduct a less laborious strategy for absolute quantification. Finally, we applied the most accurate method ratio to ratio quantification to analyze very low abundant insulin signaling proteins such as PIK3 (0.34-0.9 fmol/mg), AKT1 (0.33-0.54 fmol/mg) and the Insulin receptor (0.34 -3.98 fmol/mg) and demonstrated that upon pathway perturbation the concentration of key proteins is dynamically adapted.

This study investigated calibration curve designs and different methods for calculation following different analytical aspects. Ultimately, the aim is to work out which of the above-mentioned calibration curves provides the most robust results in terms of linear range, recovery factor, reproducibility and limit of quantification.

In the experiment, cells treated under four different conditions – 0.1% dimethyl sulfoxide (DMSO) as control, Rosiglitazone (Rosi), TNFα, and Rosiglitazone followed with TNFα (RT) representing the four states of ISP-baseline, insulin sensitization, insulin resistance, and relapse.