Low density microarrays for vaccine related protein quantification, potency determination and efficacy evaluation
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Publication Number
US-10261081-B2
Publication Date
2019-04-16
Expiration Date
Abstract
Methods for the quantification of influenza HA proteins and anti-influenza antibodies for the fields of vaccine-related protein quantification, potency determination, and efficacy evaluation are provided. According to the technology, quantification is achieved by providing capture agents attached to an array in a series of decreasing concentrations. Serial dilutions of a reference material also may be introduced. The reference material within each solution binds to the capture agents on the array and is labeled with a label agent capable of producing a detectable signal used to construct a calibration curve. A target material of unknown concentration is introduced to a separate identical array, and the target material binds to the capture agents and also is labeled by a label agent to produce a detectable signal. The calibration curve based on the reference material is then utilized to determine the concentration of the target material without the need to perform replicate experiments.
Core Innovation
The invention provides a method for quantification of influenza hemagglutinin (HA) in a sample using an array-based format. A plurality of capture agents is immobilized on a solid support in a plurality of discrete areas, where each discrete area contains only a single unique capture agent and the discrete areas are arranged in a configuration of decreasing concentration of the single unique capture agent.
Reference material and a target material are contacted with the immobilized capture agents to allow binding. The bound reference or target is detected by contacting the replicates with at least one antibody label agent to produce a detectable signal indicative of binding, and the detectable signals are processed using a ratio of detectable signals to detectable signals from an internal reference encoded on the array to yield a normalized signal.
A concentration calibration curve is constructed using normalized signals as a function of the concentration of reference material applied to the replicates, using a maximum signal response achieved on each array for each concentration of reference and target material. The concentration calibration curve is analyzed using linear regression or non-linear regression to provide regression parameters, and the amount of HA in the sample is quantified using the regression parameters and the detectable signal indicative of binding.
The claims further specify first anti-influenza A H1 antibody capture agent, second anti-influenza A H3 antibody capture agent and third anti-influenza B antibody capture agent, and determining the presence of influenza A H1 hemagglutinin, influenza A H3 hemagglutinin, and influenza B hemagglutinin by observing a detectable signal in the corresponding discrete areas.
Claims Coverage
The document provides two independent claims covering array-based quantification of influenza hemagglutinin (HA) using discrete capture-agent areas arranged by decreasing concentration, replicate reference binding, labeled detection, normalization to an internal reference, and calibration curve-based regression to quantify target HA, with additional subtype presence determination for H1, H3, and B in one claim. The main inventive features number 7 per independent claim, with one key regression-method difference and one key presence-determination feature in the second claim.
Concentration-graded capture-agent array on discrete areas
A provided array comprising a solid support onto which a plurality of capture agents is affixed in a plurality of discrete areas, wherein each discrete area contains only a single unique capture agent and the discrete areas are arranged in a configuration of decreasing concentration of the single unique capture agent.
Replicate binding with reference and target material
Contacting at least three replicates of the array with reference material at different concentrations to allow binding between the reference material and the plurality of capture agents, and contacting a replicate of the array with at least one target material to allow binding between the target material and the plurality of capture agents.
Detectable signal from labeled binding
Contacting the replicates of the array with at least one antibody label agent to produce a detectable signal indicative of binding between reference or target material and capture agent.
Normalization using an internal reference encoded on the array
Processing detectable signals of the replicates using a ratio of detectable signals to detectable signals from an internal reference encoded on the array to yield a normalized signal.
Calibration curve using maximum signal response
Constructing a concentration calibration curve comprising normalized signals as a function of the concentration of reference material applied to the replicates, wherein constructing uses a maximum signal response achieved on each array for each concentration of reference and target material.
Regression-based quantification from the calibration curve
Analyzing the concentration calibration curve using linear regression or non-linear regression to provide regression parameters and quantifying the amount of influenza hemagglutinin in the sample using the regression parameters and the detectable signal indicative of binding.
HA subtype capture agents and presence determination
The plurality of capture agents comprise a first anti-influenza A H1 antibody capture agent, a second anti-influenza A H3 antibody capture agent and a third anti-influenza B antibody capture agent, and the presence of influenza A H1 hemagglutinin, influenza A H3 hemagglutinin, and influenza B hemagglutinin is determined by observing a detectable signal in the corresponding discrete areas.
Across the independent claims, the claims center on an array-based HA quantification workflow with concentration-graded discrete capture-agent areas, replicate reference binding, antibody-label-based detectable signals, internal-reference normalization, maximum-signal calibration curve construction, and regression-based quantification. One claim further specifies non-linear regression and determines the presence of influenza A H1, influenza A H3, and influenza B hemagglutinin by observing detectable signals in the corresponding capture-agent discrete areas.
Stated Advantages
Reduced time and labor compared with prior approaches.
Improved limit of detection (LOD).
Enables multiplexing (e.g., simultaneously measuring H1/H3/B).
Normalization avoids batch-by-batch standard dilution issues.
Supports potency determination using strain-specific antibodies, universal antibodies, or sialic-acid glycopeptide/protein capture agents.
Supports vaccine efficacy evaluation using an array-based hemagglutinin inhibition (HI) format that yields quantitative values via normalized maximum signal (Smax-norm).
Documented Applications
Potency determination for influenza vaccination using strain-specific anti-HA antibodies, universal antibodies, or sialic-acid glycopeptide/protein capture agents.
Vaccine efficacy evaluation using an array-based hemagglutinin inhibition (HI) format with HA antigens capturing patient antibodies and fluorescent detection to yield quantitative Smax-norm values, including a format that eliminates red blood cell readout.
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