Assay for Characterizing Adsorption‐Properties of Surfaces (APS)

Analytes, from sample preparation, until entering an analytical instrument, are prone to adsorb to surfaces, driven by the chemical properties of the surface and the liquids they are dissolved in. This problem can be addressed with internal standards when a single or few known analytes are quantified that are usually not available in omics. However, minimal to no loss of analytes is the aim. Here, we present a novel assay for qualifying and quantifying interactions responsible for adsorption of molecules to surfaces (APS) by using LC–MS/MS‐based differential quantitative analysis. To reflect a broad range of chemical interactions with surfaces, a reference mixture of thousands of tryptic peptides, with known compositions was selected, representing a variety of different chemical characteristics. The assay was tested by investigating the adsorption properties of several different vials with different surface chemistries. A significant number of hydrophobic peptides adsorbed to conventional polypropylene vials. In contrast, only few peptides adsorbed to polypropylene vials, assigned as low‐protein‐binding. The highest number of peptides adsorbed to glass vials driven by electrostatic interactions. In summary, the new assay is suitable to characterize adsorption properties of different surfaces and to approximate the loss of analytes during sample preparation. With APS the types of interactions can be determined causing adsorption of analytes to surfaces, driven by partition of analytes between the sample liquid and the solid surface having contact with the sample liquid. This is especially helpful for estimation of analyte loss occurring by their binding to surfaces during sample preparation and analysis and for developing measures for minimizing loss of analytes. The test is based on the quantification of probes consisting of thousands of defined peptides spanning a broad range of chemical properties. Interpretation of APS results is facilitated by an automated script‐based analysis.