Introduction
Mass spectrometry-based plasma proteomics remains the promising method of understanding human molecular pathophysiology and the discovery of disease biomarkers. However, it has been a challenging workflow for many years due to a large dynamic range in protein expression and the current capabilities of analytical methods, especially with regards to the throughput and depth of proteome coverage. Here we present a label-free plasma proteomics workflow using an Orbitrap Astral MS as a robust analytical setup for in-depth analysis of plasma proteins. Two different types of samples were used, a neat plasma and a plasma prepared with Seer’s Proteograph Product Suite, utilizing a multi-nanoparticle-based approach.
Methods
The neat plasma sample was prepared using Accelerome and the enriched plasma sample was prepared on Seer’s Proteograph Product Suite. Both were analyzed using two different workflows:(1) a Max-ID method using a 75cm EasySpray column on a 60min gradient for deep proteome coverage (14 SPD) and (2) a short, 5.5min gradient method using a 15cm EasySpray column for high-throughput (180 SPD for the neat and 36 SPD for the enriched samples). A Vanquish Neo UHPLC system was used at 250nl/min for the Max-ID and 1.3ul/min for the high-throughput method. Orbitrap Astral MS was used with a DIA method. Data analysis was done using a beta version of Proteome Discoverer 3.1.
Preliminary data
To tackle the plasma dynamic range issue, an Orbitrap Astral MS utilizing a label-free proteomics workflow in DIA mode was used as a robust analytical setup for both high-throughput and in-depth analysis of plasma samples. Analysis of 500 ng of the neat plasma sample using the 15cm EasySpray column on a 5.5min active gradient resulted in 762 protein groups and 6342 unique peptides. Analysis of the plasma sample enriched using Seer’s Proteograph Product Suite resulted in ~3000 protein groups and ~2500 unique peptides, when the high-throughput method was used with 500 ng peptide loaded on the column for each nanoparticle fraction (5 individual injections of the 5 different nanoparticles separately). Similar to the neat plasma results, when the Max-ID method was used with a longer gradient, a significant improvement in the number of proteins and peptides was observed with a total of 6034 protein groups and 54393 unique peptides from 2 ug sample load of a pool of all 5 nanoparticle fractions.