Broadly Neutralizing Anti-Influenza Virus Antibodies: Enhancement of Neutralizing Potency in Polyclonal Mixtures and IgA Backbones
Bibliographic record
Abstract
UNLABELLED: Current influenza virus vaccines rely upon the accurate prediction of circulating virus strains months in advance of the actual influenza season in order to allow time for vaccine manufacture. Unfortunately, mismatches occur frequently, and even when perfect matches are achieved, suboptimal vaccine efficacy leaves several high-risk populations vulnerable to infection. However, the recent discovery of broadly neutralizing antibodies that target the hemagglutinin (HA) stalk domain has renewed hope that the development of "universal" influenza virus vaccines may be within reach. Here, we examine the functions of influenza A virus hemagglutinin stalk-binding antibodies in an endogenous setting, i.e., as polyclonal preparations isolated from human sera. Relative to monoclonal antibodies that bind to the HA head domain, the neutralization potency of monoclonal stalk-binding antibodies was vastly inferior in vitro but was enhanced by several orders of magnitude in the polyclonal context. Furthermore, we demonstrated a surprising enhancement in IgA-mediated HA stalk neutralization relative to that achieved by antibodies of IgG isotypes. Mechanistically, this could be explained in two ways. Identical variable regions consistently neutralized virus more potently when in an IgA backbone compared to an IgG backbone. In addition, HA-specific memory B cells isolated from human peripheral blood were more likely to be stalk specific when secreting antibodies of IgA isotypes compared to those secreting IgG. Taken together, our data provide strong evidence that HA stalk-binding antibodies perform optimally when in a polyclonal context and that the targeted elicitation of HA stalk-specific IgA should be an important consideration during "universal" influenza virus vaccine design. IMPORTANCE: Influenza viruses remain one of the most worrisome global public health threats due to their capacity to cause pandemics. While seasonal vaccines fail to protect against the emergence of pandemic strains, a new class of broadly neutralizing antibodies has been recently discovered and may be the key to developing a "universal" influenza virus vaccine. While much has been learned about the biology of these antibodies, most studies have focused only on monoclonal antibodies of IgG subtypes. However, the study of monoclonal antibodies often fails to capture the complexity of antibody functions that occur during natural polyclonal responses. Here, we provide the first detailed analyses of the biological activity of these antibodies in polyclonal contexts, comparing both IgG and IgA isotypes isolated from human donors. The striking differences observed in the functional properties of broadly neutralizing antibodies in polyclonal contexts will be essential for guiding design of "universal" influenza virus vaccines and therapeutics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".