Introduction

Blood plasma represents an invaluable source for proteomic biomarker discovery as it is easily accessible and provides comprehensive information about an individual´s health status. However, the high dynamic range as well as sample heterogeneity and complexity pose significant challenges for LC-MS-based proteomics, limiting access to the entire proteome. Moreover, common plasma workflows require tedious manual processing and are often incompatible with automation or the analysis of large cohorts. With ENRICHplus, we present a fully automatable plasma workflow that allows parallel processing of 96 samples in 5 hrs and enhances proteome coverage for human plasma by up to 7-fold compared to neat sample preparation. Combined with state-of-the-art data acquisition and analysis, it provides a high-throughput plasma platform for the analysis of large-scale proteomic studies.

Methods

The ENRICHplus workflow utilizes a proprietary single particle solution for dynamic range compression by enriching low-abundance proteins from 20-80 µL of plasma onto paramagnetic beads. Upon enrichment, proteins were further processed according to the iST-BCT protocol. The full sample preparation workflow was done manually or fully automated in 96well format. Peptides were analyzed by a nanoLC coupled to a timsTOF HT instrument using diaPASEF® acquisition mode. Data processing was done with Spectronaut®.

Preliminary results

For a human EDTA plasma pool, almost 4,700 protein groups were identified in a short 17-min LC-gradient, which corresponds to a 6.8-fold increase compared to neat samples and provides access to low-abundance proteins by covering a protein concentration range of 10 orders of magnitude. Moreover, superb precision was achieved with a CV of 11%. To further enhance the throughput of ENRICHplus, the sample preparation workflow was successfully automated and combined with 5-mins gradients, allowing rapid analysis of large sample cohorts. Preliminary results revealed over 2,100 protein groups identified and no decrease in precision compared to long gradients of 35-mins.

To assess its potential for biomarker discovery, the ENRICHplus kit was applied to a small cohort of colorectal cancer patients (n=6) and matched healthy donors (n=6), resulting in more than 5,800 protein group identifications. Statistical analysis showed a clear stratification between healthy and sick donors, and the 13 proteins that showed substantial regulation are all known to be associated with cancer, including the serum amyloid A1 (SAA1), which is a hallmark of malignant disease progression in colorectal cancer.

Conclusion

The presented plasma platform with the ENRICHplus technology enables rapid and deep analysis of large plasma sample cohorts, opening up new possibilities for high-throughput biomarker discovery.