Félix Elortza (Derio / ES), Javier Beaskoetxea (Derio / ES), Ibon Iloro (Derio / ES), Iraide Escobés (Derio / ES), Mikel Azkargorta (Derio / ES)
Blood is the most collected biofluid globally for clinical purposes and is used in approximately 40% of all completed tests. Consequently, plasma and serum are among the preferred sources for potential biomarker discovery and are of major interest in liquid biopsy research.
Identification of protein biomarkers in plasma has been limited, among others, because the 22 most abundant proteins in plasma account for 99% of all protein content, preventing the detection of less abundant proteins using discovery mass spectrometry (MS)–based proteomics. Therefore, depletion of the most abundant proteins is a common way to circumvent the dynamic range issue and different immunodepletion-based resins have been used for this purpose. Steen"s laboratory has recently published a method based on perchloric acid precipitation that is described to be fast-forward and cost-effective (1).
With the aim of sizing the overall performance of different depletion methods, we have accomplished a comparison among them: a) Immunodepletion by a commercial Top 14 protein depletion cartridge (Thermo Fischer); b) Perchloric acid depletion; c) Trichloro acetic acid (TCA) depletion. The depletions performance was checked by DDA and DIA in an EVOSEP + TimsTOF Pro system.
The overall results show that the three methods tested work in similar but complementary ways. The number of proteins identified by each approach is comparable, with some proteins being exclusive to each method. Precipitation-based approaches are methodologically easier to carry out in a high-throughput manner and are significantly cheaper. Consequently, we expect these methods to become routine in plasma-based biomarker discovery.
References
Viode A, van Zalm P, Smolen KK, Fatou B, Stevenson D, Jha M, Levy O, Steen J, Steen H; IMPACC Network. A simple, time- and cost-effective, high-throughput depletion strategy for deep plasma proteomics. Sci Adv. 2023 Mar 29;9(13)eadf9717.