Quantitative Analyses of all Influenza Type A Viral Hemagglutinins and Neuraminidases using Universal Antibodies in Simple Slot Blot Assays
Bibliographic record
Abstract
Hemagglutinin (HA) and neuraminidase (NA) are two surface proteins of influenza viruses which are known to play important roles in the viral life cycle and the induction of protective immune responses(1,2). As the main target for neutralizing antibodies, HA is currently used as the influenza vaccine potency marker and is measured by single radial immunodiffusion (SRID)(3). However, the dependence of SRID on the availability of the corresponding subtype-specific antisera causes a minimum of 2-3 months delay for the release of every new vaccine. Moreover, despite evidence that NA also induces protective immunity(4), the amount of NA in influenza vaccines is not yet standardized due to a lack of appropriate reagents or analytical method(5). Thus, simple alternative methods capable of quantifying HA and NA antigens are desirable for rapid release and better quality control of influenza vaccines. Universally conserved regions in all available influenza A HA and NA sequences were identified by bioinformatics analyses(6-7). One sequence (designated as Uni-1) was identified in the only universally conserved epitope of HA, the fusion peptide(6), while two conserved sequences were identified in neuraminidases, one close to the enzymatic active site (designated as HCA-2) and the other close to the N-terminus (designated as HCA-3)(7). Peptides with these amino acid sequences were synthesized and used to immunize rabbits for the production of antibodies. The antibody against the Uni-1 epitope of HA was able to bind to 13 subtypes of influenza A HA (H1-H13) while the antibodies against the HCA-2 and HCA-3 regions of NA were capable of binding all 9 NA subtypes. All antibodies showed remarkable specificity against the viral sequences as evidenced by the observation that no cross-reactivity to allantoic proteins was detected. These universal antibodies were then used to develop slot blot assays to quantify HA and NA in influenza A vaccines without the need for specific antisera(7,8). Vaccine samples were applied onto a PVDF membrane using a slot blot apparatus along with reference standards diluted to various concentrations. For the detection of HA, samples and standard were first diluted in Tris-buffered saline (TBS) containing 4M urea while for the measurement of NA they were diluted in TBS containing 0.01% Zwittergent as these conditions significantly improved the detection sensitivity. Following the detection of the HA and NA antigens by immunoblotting with their respective universal antibodies, signal intensities were quantified by densitometry. Amounts of HA and NA in the vaccines were then calculated using a standard curve established with the signal intensities of the various concentrations of the references used. Given that these antibodies bind to universal epitopes in HA or NA, interested investigators could use them as research tools in immunoassays other than the slot blot only.
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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 | 0.000 | 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 | 0.000 |
| 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".