Design and expression of a QconCAT protein to validate Hi3 protein quantification of influenza vaccine antigens.

UNLABELLED: Quantification of the antigens hemagglutinin and neuraminidase in influenza vaccines has been reported using an antibody-free liquid chromatography-mass spectrometry (LC-MS) based method known as MS(E) "Hi3". This approach is based on the average signal intensity of the three most intense tryptic peptides relative to a primary standard. This strategy assumes that the Hi3 signal responses are consistent for all proteins, and therefore comparable to a spiked reference for absolute quantification. This method is much faster than the current standard methods; however, the results can vary significantly which brought the method's accuracy into question. To address this question we generated synthetic proteins comprising a concatenation of the peptides used to quantify the proteins of interest (QconCAT). Complete tryptic digestion of a QconCAT protein produces equal molar peptide amounts, allowing verification of equal signal response of Hi3 peptides for the proteins of interest. The generation of an intact, stable, QconCAT protein that digest completely is challenging. We have designed and analyzed five QconCAT proteins with unique design elements to address these challenges. We conclude that a suitable QconCAT protein can be produced and that the results obtained reinforce the validity of the Hi3 approach for quantifying proteins in annual influenza vaccine formulations. SIGNIFICANCE: The advances in quantitative proteomics have allowed the adaptation and application of these methods to numerous fields. In this paper we have validated a Hi3 approach to augment the antigen quantification for influenza vaccines injected into many millions annually. This methodology allows analysis of multiple antigens simultaneously without the need to generate antibodies. Key circumstances where this is advantageous are for quantitation of very similar antigens, such as the new quadravalent products and when time is critical such as in a flu pandemic.