Ultrasensitive and robust quntification of proteins

We devised a new pipeline to facilitate a high-throughput and accurate method development for targeted protein quantification. Instead of using an in silico method to predict the best SP and optimal SRM conditions, we employed an experimental strategy to discover and optimize many SP candidates, and then evaluate these candidates in target matrices prior to SP selection. Briefly, the pool of SP candidates was generated by a data-dependent LC/MS experiment following a stringent filtering step to remove peptides that are not unique to the target, containing labile amino acid (cysteine residues were not excluded as a number of studies showed cysteine-containing peptides may be used in a reliable quantification), known modification or miss cleavage. To evaluate these candidates, the target protein was spiked into the blank matrices (e.g., plasma or tissue extract) and then prepared and digested. The optimal LC/MS conditions of all SP candidates were accurately obtained by a high-throughput and on-the-fly orthogonal array optimization (OAO) procedure, which has the capacity to develop the SRM conditions for .100 candidates within one single LC/MS run with high accuracy and reproducibility. Using the developed LC/MS conditions, all candidates were thoroughly assessed for stability and signal-to-noise ratios (S/N) in the matrix digest. Among the stable peptides, two peptides with the highest S/N were selected as the SPs. The use of two SP from different domains of the same protein provides a versatile gauge for the reliability of quantitative methods and results. Details can be found in the following references. 


Update date: May, 2017