Abstract

Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample.

Highlights

  • Proteomics is an important tool to identify relevant biomarkers for prognosis or diagnosis of various diseases

  • About 95% of the plasma proteome is accounted by only 10–12 highly abundant proteins; the remaining 5% being in extremely low abundance

  • All targeted proteins, keratins and immunoglobulins were removed from the protein groups

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Summary

Introduction

Proteomics is an important tool to identify relevant biomarkers for prognosis or diagnosis of various diseases. Plasma is the most preferred diagnostic material for disease proteomic studies due to its non-invasive nature It is a heterogeneous collection of proteins secreted or leaked from all types of tissues revealing the cellular state due to spatio-temporal differences in protein expression. Being a direct reflection of the patho-physiological condition of a patient, it is considered to be a diagnostic goldmine for biomarkers[1] It is one of the most difficult body fluids to work with because of the sample complexity and wide dynamic range of abundance spanning .12 orders of magnitude[2]. Accurate profiling of changes in protein expression patterns could give critical insights into the development of a potential biomarker for clinical diagnostics It is a non-trivial task to identify and validate them due to the abundance complexity as they get masked by large and abundant proteins. There are various methods used for depletion of one or more of the abundant proteins in the plasma, immunoaffinity based method, which allows simultaneous depletion of multiple high abundant proteins is widely used[10,11]

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