Automating Complex, Multistep Processes on a Single Robotic Platform to Generate Reproducible Phosphoproteomic Data.

Mass spectrometry-based phosphoproteomics holds promise for advancing drug treatment and disease diagnosis; however, its clinical translation has thus far been limited. This is in part due to an unstandardized and segmented sample preparation process that involves cell lysis, protein digestion, peptide desalting, and phosphopeptide enrichment. Automating this entire sample preparation process will be key in facilitating standardization and clinical translation of phosphoproteomics. While peptide desalting and phosphopeptide enrichment steps have been individually automated, integrating these two extractions and, further, the entire process requires more advanced robotic platforms as well as automation-friendly extraction tools. Here we describe a fully automated peptide desalting and phosphopeptide enrichment method using IMCStips on a Hamilton STAR. Using our established automated method, we identified more than 10,000 phosphopeptides from 200 µg of HCT116 cell lysate without fractionation with >85% phosphopeptide specificities. Compared with titania-based Spin Tip products, the automated IMCStips-based method gave 50% higher phosphopeptide identifications. The method reproducibility was further assessed using multiple reaction monitoring (MRM) to show >50% phosphopeptide recoveries after the automated phosphopeptide extraction with coefficients of variation (CVs) of <20% over a 3-week period. The established automated method is a step toward standardization of the sample preparation of phosphopeptide samples and could be further expanded upon to create a fully automated "cells to phosphopeptides" method.