Iterative immunogen optimization to focus immune responses on a conserved, subdominant viral epitope

Area of Science:

• Virology
• Immunology
• Protein Engineering
• Machine Learning

Background:

• Genetically diverse viruses like influenza and HIV mutate rapidly, evading immune responses and complicating vaccine design.
• Conserved viral regions are ideal targets for broad immunity but are often subdominant, meaning they are not typically targeted by natural immune responses.
• Current vaccines often fail to elicit responses against these crucial conserved epitopes.

Purpose of the Study:

• To engineer novel protein immunogens that direct immune responses towards conserved, subdominant viral epitopes.
• To utilize advances in machine learning for protein structure prediction and design in immunogen engineering.
• To develop a strategy for creating broadly protective vaccines against highly mutable viruses like influenza.

Main Methods:

• Integrated machine learning for protein structure prediction and design to engineer immunogens.
• Focused on a conserved, subdominant hemagglutinin (HA) epitope relevant for influenza.
• Employed iterative computation-guided optimization and in vivo analyses.
• Vaccinated animals with engineered immunogens to assess immune response redirection.

Main Results:

• Successfully engineered immunogens that accurately displayed the target conserved HA epitope.
• Demonstrated that vaccination with these immunogens redirected humoral immune responses towards the targeted epitope.
• Achieved a significant focus of immune responses on a previously subdominant site.
• Validated the computational approach for designing targeted immunogens.

Conclusions:

• Protein engineering approaches, enhanced by machine learning, can effectively focus immune responses on conserved viral epitopes.
• This strategy provides a blueprint for designing immunogens capable of eliciting broadly protective immunity.
• The findings may significantly inform the development of next-generation, broadly protective influenza vaccines.
• This approach holds promise for tackling other genetically diverse viral pathogens.