Abstract: The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility.
Keywords: automation; mass spectrometry; plasma; proteomics
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Guryča, V.; Roeder, D.; Piraino, P.; Lamerz, J.; Ducret, A.; Langen, H.; Cutler, P. Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery. Biology 2014, 3, 205-219.
Guryča V, Roeder D, Piraino P, Lamerz J, Ducret A, Langen H, Cutler P. Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery. Biology. 2014; 3(1):205-219.
Guryča, Vilém; Roeder, Daniel; Piraino, Paolo; Lamerz, Jens; Ducret, Axel; Langen, Hanno; Cutler, Paul. 2014. "Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery." Biology 3, no. 1: 205-219.