Serum-antibody Profiling of H3N2-infected Ferrets Using a Combinatorial Phage-display Random Peptide Library

Area of Science:

• Immunology
• Computational Biology
• Infectious Disease Diagnostics

Background:

• The serum antibody repertoire (IgOme) is diverse and individual-specific, reflecting pathogen exposure history.
• Profiling the IgOme holds potential for diagnosing human viral infections.
• The Motifier computational pipeline was previously developed to identify antibody-binding peptide markers.

Purpose of the Study:

• To evaluate the applicability of the Motifier pipeline to complex biological samples like serum.
• To determine if serum profiling using Motifier can identify specific biological conditions, such as viral infections.
• To assess the potential of Motifier-derived markers for diagnostic applications.

Main Methods:

• Analysis of ferret sera infected with H3N2 influenza A strains as a model system.
• Application of the Motifier computational pipeline to profile serum antibody repertoires.
• Development of a Random Forest classifier using identified peptide-motif markers.

Main Results:

• Each ferret exhibited a distinct and strong baseline antibody signature.
• Specific peptide-motif markers associated with influenza A infection were identified.
• The Random Forest classifier accurately characterized the biological condition and predicted unseen samples.

Conclusions:

• The Motifier pipeline is applicable to complex serum samples for identifying antibody signatures.
• Infection-specific peptide-motif markers can be detected in serum.
• Motifier-based serum profiling shows promise as a diagnostic tool for viral infections.