Purpose – Variability and dynamic range of protein abundance substantially influence the human plasma proteome analysis. To develop novel markers indicative of diseases using proteomics-based approaches, the plasma workflow has to be high-throughput and robust for hundreds of runs to make a reliable conclusion out of a clinical study. In this study, we developed a standardized high throughput (HT) plasma proteomics analysis workflow focusing on balancing the depth identification and scalability for sampling large population cohorts. The workflow consists of an automated sample preparation method and an Evosep LC system coupled to an Q Exactive HF-X platform. This poster presents a high throughput serum and plasma proteomics analysis workflow for large population cohorts.
Methods – To reduce analytical variability of plasma sample preparation for LC-MS/MS analysis, we automated Thermo Scientific™ EasyPep™ Mini MS Sample Prep Kit using the Hamilton Microlab STARlet liquid handling system with [MPE]2 positive pressure and evaporation modules. The Evosep LC system was used to run high throughput and automated LC methods. Thermo Scientific™ Q Exactive™ HF-X MS and data-dependent acquisition (DDA) were used to generate quantitative LFQ plasma proteome data. Skyline was used for retention time analysis and Thermo Scientific™ Proteome Discoverer™ 2.3 software was used for database search and post-data analysis.
Results – The automated sample preparation can process 96 samples within 4 hours with ~80% recovery. The throughput of LC analysis for the standardized workflow is > 50 samples per day with 10% overhead to minimize sample carrying over. Around 150 and 200 core proteins (high confident) could be reproducibly identified and quantified for the undepleted serum and the depleted plasma samples, respectively. An example of this workflow applied to small scale depleted plasma lung cancer samples is presented in this poster as well.