Assessment of reproducibility in depletion and enrichment workflows for plasma proteomics using label‐free quantitative data‐independent LC‐MS

Abstract

Quantitation in plasma-based proteomics necessitates the reproducible removal of highly abundant proteins to enable the less abundant proteins to be visible to the mass spectrometer. We have evaluated immunodepletion (proteoprep20) and enrichment (Bio-Rad beads), as the current predominant approaches. Label-free analysis offers an opportunity to estimate the effectiveness of this approach without incorporating chemical labels. Human plasma samples were used to quantitatively assess the reproducibility of these two methods using nano-LC-data-independent acquisition MS. We have selected 18 candidate proteins and a comparison of both methodologies showed that both of the methods were reproducible and fell below 20% residual SD. With the same candidate proteins, individual inter-day variability for the samples was also processed, allowing us to monitor instrument reproducibility. Overall, a total of 131 proteins were identified by both methods with 272 proteins identified by enrichment and 200 identified by immunodepletion. Reproducibility of measurements of the amount of protein in the processed sample for individual proteins is within analytically acceptable standards for both methodologies. This enables both methods to be used for biomarker studies. However, when sample is limited, enrichment is not suitable as larger volumes (>1.0 mL) are required. In experiments where sample is not limited then a greater number of proteins can be reliably identified using enrichment.

Proteomic profiling of human plasma identifies apolipoprotein E as being associated with smoking and a marker for squamous metaplasia of the lung

“…A previous experiment by Bortner et al [19] performed by the same institutional Proteomic Mass Spectrometry core laboratory, which utilized a similar amount of starting material, prefractionization procedure and instruments, and the same mass spectrometer, verified two smoking-associated biomarker (ITI-HC3 and VDBP) in plasma of smokers after depletion of 20 highly abundant plasma proteins. In this study we implemented a proteins enrichment method, ProteoMiner (BioRad), which can enhance the depth of the proteomic analysis [35,36]. We were able to positively identify almost 2-fold more proteins than Bortner et al using the same quality control parameters (201 and 131, respectively), which suggested that protein enrichment may enhance the depth of proteomics analysis.…”

Evaluating the effects of preanalytical variables on the stability of the human plasma proteome

“…About 95% of the proteome is composed of 10–12 proteins, which can interfere with MS-based approaches for identifying and quantifying less abundant proteins. The removal of albumin and other highly abundant proteins via antibody depletion has become standard practice [3,25]. Recently the immunodepletion of abundant blood-derived proteins from solid tissue specimens has been recommended [29].…”

“…The challenges associated with plasma proteomics include the large dynamic range of protein concentrations [1,2], variability in preanalytic and analytic processes, and inherent biological variability. Detection of low abundance proteins is facilitated by depletion or enrichment of peptides or proteins prior to mass spectrometry (MS) analyses [3]. The use of sound study designs and system suitability protocols improves analytical reproducibility and statistical power [4–7].…”

Simultaneous Enrichment of Plasma Soluble and Extracellular Vesicular Glycoproteins Using Prolonged Ultracentrifugation-Electrostatic Repulsion-hydrophilic Interaction Chromatography (PUC-ERLIC) Approach*

“…To date, MS coupled with highresolution liquid chromatography (LC) has been the preferred tool for the identification of trypsin-digested N-glycopeptides and glycosylation sites (7,8). However, study of the human plasma glycoproteome remains challenging because of the vast dynamic range of protein abundance, which can span up to 12 orders of magnitude (8).…”

“…To date, MS coupled with highresolution liquid chromatography (LC) has been the preferred tool for the identification of trypsin-digested N-glycopeptides and glycosylation sites (7,8). However, study of the human plasma glycoproteome remains challenging because of the vast dynamic range of protein abundance, which can span up to 12 orders of magnitude (8). In addition, the low ionization efficiency of plasma glycopeptides, combined with the relatively high quantities of interfering nonglycosylated counterparts in the sample, can often result in signal suppression when subjected to MS analyses (7).…”