Analytical Chemistry

Does Filter Aided Sample Preparation (FASP) Provide Sufficient Method Linearity for Quantitative Plant Shotgun Proteomics?

Andrej Frolov Leibniz Institute of Plant Biochemistry


Gel-free LC-based shotgun proteomics represents the current gold standard of proteome analysis due to its outstanding throughput, analytical resolution and reproducibility. Thereby, the efficiency of sample preparation, i.e., protein isolation, solubilization and proteolysis, directly affects the correctness and reliability of quantification, being therefore the bottle neck of shotgun proteomics. The desired performance of the sample preparation protocols can be achieved by application of detergents. However, these ultimately compromise reverse phase chromatographic separation and disrupt electrospray ionization. Filter aided sample preparation (FASP) represents an elegant approach to overcome these limitations. Although this method is comprehensively validated for cell proteomics, its applicability to plants and compatibility with plant-specific protein isolation protocols is still unknown, i.e., no data on linearity of underlying protein quantification methods for plant matrices is available. To fill this gap, we address here the potential of FASP in combination with two protein isolation protocols for quantitative analysis of pea (Pisum sativum) seed and Arabidopsis thaliana leaf proteomes by the shotgun approach. For this, in comprehensive spiking experiments with bovine serum albumin (BSA), we evaluated the linear dynamic range (LDR) of protein quantification in the presence of plant matrices. Further, we addressed the interference of two different plant matrices in quantitative experiments, accomplished with two alternative sample preparation workflows in comparison to conventional FASP-based digestion of cell lysates, considered here as a reference. Our results indicate very good applicability of FASP to quantitative plant proteomics with an only limited impact of the protein isolation technique on the methods overall performance.


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Supplementary material

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210510 Leonova et al Supplementary information JPR