Mass spectrometric comparison of blood matrices and sample preparation techniques. Benchmarking clinical sample SOPs and different proteolysis methods for plasma and serum by LC-MSMS in DIA mode

While plasma and serum are the most frequently studied sample types in clinical research, the susceptibility to minor changes during clinical sample collection and preparation such as centrifugation, type of collection tubes and sample temperature during handling remains understudied. The high dynamic range of plasma proteins further impairs the analytical depths and coverage when time and costs are critical.

Here, we systematically explored the LC-MS/MS proteomic profiles of pooled blood samples from three healthy probands sampled by EDTA-, citrate- and heparin-anticoagulated blood as well as serum generated with and without separation gel. In addition, proteolysis prior to LC-MS/MS analysis was conducted with five different methods. We evaluated the commercially available iST and ENRICH-iST kits from Preomics as well as strong-anion exchange (SAX) beads from MagReSyn, the TFA-based approach SPEED and a depletion-based method which uses perchloric acid (perCA) for precipitation of large proteins. Mass-spectrometric measurements were performed on a QExactive HF-X and a timsTOF HT in DIA mode. Identification and quantification analysis of recorded spectra was performed with DIA-NN v1.8.1. The total dataset comprises 250 raw files (5 different blood matrices, proteolyzed with 5 different methods and measured in 5 replicates on two LC-MSMS set-ups).

Over all possible combinations of matrices and proteolysis methods, the QExactive HF-X MS instrument achieved identifications between 250 and 600 protein groups whereas the timsTOF HT identifies between 275 and 1100 protein groups. Large differences on protein group ID level in the applied proteolysis techniques are evident. Workflows using SAX-beads, ENRICH-iST and the perCA precipitation showed highest identification rates but also highest variability between the different blood matrices. Here, EDTA-plasma and serum exhibited the highest ID numbers while citrated plasma showed the lowest. 116 protein groups overlap between all 25 sample sets for QExactive HF-X and 182 protein groups for timsTOF HT. Moreover, subsets of protein groups are uniquely identified in specific combinations of proteolysis method and blood matrix indicating important implications for clinical studies.

In conclusion, this study represents a systematic approach to determine suitable sample preparation and matrix parameters for the robust identification of individual body fluid marker proteins by mass spectrometry.