Immune responses are characterized by specific shared immunoglobulin peptides that can be detected by proteomic techniques.

In the adaptive immune response, immunoglobulins develop that bind specifically to the antigens to which the organism was exposed. Immunoglobulins may bind to known or unknown antigens in a variety of diseases and have been used in the past to identify novel antigens for use as a biomarker. We propose that the immunoglobulins themselves could also be used as biomarkers in antibody-mediated disease. In this proteomic study, rats were immunized with one of two purified antigens, and immunoglobulins from pre- and postimmune sera were analyzed with nano-LC coupled mass spectrometry. It was found that the two treatment groups could be distinguished based on cluster analysis of the immunoglobulin peptides from the immune sera. In addition, we identified 684 specific peptides that were differentially present in one of the two treated groups. We could find an amino acid sequence for 44% of the features in the mass spectra by combining database-driven and de novo sequencing techniques. The latter were essential for sequence identification, as the more common database-driven approach suffers from a poor representation of immunoglobulins in the available databases. Our data show that the development of immunoglobulins during an immune response is not a fully random process, but that instead selection pressures exist that favor the best binding amino acid sequences, and that this selection is shared between different animals. This finding implies that immunoglobulin peptides could indeed be a powerful and easily accessible class of biomarkers.