Quantification of surfactant protein D (SPD) in human serum by liquid chromatography-mass spectrometry (LC-MS)

2019 
Abstract Quantification of intact proteins in complex biological matrices by liquid chromatography-mass spectrometry (LC-MS) is a promising analytical strategy but is technically challenging, notably for concentrations at or below the ng/mL level. Therefore, MS-based protein quantification is mostly based on measuring protein-specific peptides, so-called ‘surrogate peptides’, that are released through proteolysis. While quantitative protein bioanalysis based on peptide LC-MS is much more sensitive, not every peptide is suitable in this respect. For example, some peptides are too small to be unique for a protein while others are too large to be measured with sufficient sensitivity, so careful selection of appropriate peptides is essential. Here we present a validated LC-MS method for quantification of surfactant protein D (SPD) at clinically relevant levels between 5 and 500 ng/mL using 50 μL of serum. This method targets two SPD-specific peptides in the C-type lectin, ligand binding domain of the SPD protein. One of these peptides contains a methionine residue which would typically be avoided because of its unstable nature. Some quantitative methods do target methionine-containing peptides, and corresponding workflows feature an oxidation step at the peptide level using hydrogen peroxide (H 2 O 2 ) to convert all methionine residues to more stable methionine sulfoxides. For our method, such a procedure was associated with peptide loss, hence we developed an oxidation procedure at the protein level using H 2 O 2 to oxidize methionine residues and the enzyme catalase to quench excess H 2 O 2 . This procedure may be applicable to other quantitative methods based on a surrogate peptide-based approach and may potentially also be useful for MS-based workflows targeting intact proteins.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    34
    References
    6
    Citations
    NaN
    KQI
    []