# Selecting HA glycosylation for improved vaccine responses

> **NIH NIH R01** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2021 · $821,674

## Abstract

Selecting HA glycosylation for improved vaccine responses
This application responds to PA-18-859 "Advancing Research Needed to Develop a Universal Influenza
Vaccine" and addresses the goal to “support rational design of universal influenza vaccines”.
The low Influenza A virus (IAV) vaccine effectiveness (VE) stems from the ability of the virus to evade existing
immunity. Its error-prone polymerase enables rapid evolution of the surface glycoprotein antigens hemagglutinin
(HA) and neuraminidase (NA). Significantly, among the more prevalent mutations that occur as an IAV strain
undergoes antigenic drift is the appearance of new N-glycosylation consensus sequences (sequons) on the HA
globular domain. The appearance of new glycosites shields underlying amino acid residues from antibody
contact. However, because the host receptor binding sites (RBSs) also reside in the HA head group, variations
in head group glycosylation have the simultaneous potential to harm viral fitness by interfering with virus binding
to its host receptor.
HA glycosylation is macro- and micro-heterogeneous, meaning that each HA glycosite has a distribution of
glycoforms that differ in their physicochemical and lectin-binding properties. HA therefore consists of
heterogeneous populations that differ by glycosylation, antigenicity, and immunogenicity. Unfortunately, the
glycosylated structures of HA populations most suited for vaccine use remain unknown for IAV strains. This lack
of information results in over-reliance on genomic information that cannot predict the level of glycosylation at a
given site, the compositions of the attached glycans, and which glycosylated populations of HA are most
immunogenic.
We propose to use glycoproteomics, molecular modeling, and antigenic cartography of HA glyco-populations to
develop a detailed understanding of the relationship between HA glycosylation and immunogenicity for
representative H1N1 strains.
This study will enhance our understanding of the natural history of influenza viruses. In addition, we anticipate
that this knowledge could be employed to select HA sequences for producing recombinant influenza vaccines
with enhanced immunogenicity and VE. Unlike vaccines based on attenuated or inactivated virus, recombinant
vaccines are created synthetically and can be prepared in advance of the emergence of a seasonal or pandemic
strain of virus. Knowledge of the optimal HA glycosylation pattern would provide important guidance in
recombinant vaccine design.

## Key facts

- **NIH application ID:** 10298131
- **Project number:** 1R01AI155975-01A1
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** XIUFENG HENRY WAN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $821,674
- **Award type:** 1
- **Project period:** 2021-06-09 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10298131

## Citation

> US National Institutes of Health, RePORTER application 10298131, Selecting HA glycosylation for improved vaccine responses (1R01AI155975-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10298131. Licensed CC0.

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