With its 50th anniversary fast approaching, ELISA remains one of the most popular and trusted immunoassay techniques around. Used to detect and quantify target antigens through serial binding to a solid surface (typically a polystyrene microplate), it benefits from high specificity and sensitivity, easy-to-follow protocols, and a capacity for high-throughput screening that outperforms other immunoassay techniques. ELISA is also readily compatible with complex materials such as serum, urine, and cellular and tissue extracts, making it adaptable to almost any research application. Whether you are setting up your own ELISA, or using a complete off-the-shelf kit, optimizing certain basic elements is key to producing data you can trust.
ELISA can be configured in several ways, all of which involve immobilizing antigens to the microplate surface before blocking, probing with antibodies, and measuring the resultant signal. Although antigens may be directly immobilized (an approach that is often used to monitor antibodies in body fluids), a sandwich ELISA is often a preferred choice—especially for complex samples—since it provides greater specificity.
The ELISA format is largely dictated by the aims of the experiment and the available reagents. When setting up an ELISA in-house, conjugated primary antibodies can be used to shorten protocols, but where the target is of low abundance, using conjugated secondary antibodies for indirect detection can offer valuable signal amplification. In many cases, researchers prefer to use an off-the-shelf ELISA kit since these are supplied fully-optimized to save time, money, and sample material.
A robust washing technique is one of the most effective ways to minimize background signal in an ELISA. Optimizing the number, duration, and volume of washing steps, as well as the detergent concentration of wash buffers, is fundamental to ensuring removal of any unbound reagents that might compromise results. For more consistent ELISA data, automated plate washers can be a sensible choice; many modern instruments are fitted with features such as a programmable shaking function to eliminate bubbles, and precise pipetting to achieve near complete elimination of residual wash buffer.
Other ways of minimizing background in an ELISA include reducing the concentration of primary and/or secondary antibodies, changing the composition of the blocking solution or length of the blocking step, and reducing the incubation temperature. It is also a good idea to include a reference wavelength measurement to identify non-specific background noise.
The standard curve is essential to obtain quantitative ELISA results since it is used to calculate the concentration of unknown samples. For this reason, the reference material used to produce it must be of high quality and available in sufficient amounts to achieve reproducible performance for the lifetime of the assay. Should the reference material change (e.g. upon receipt of a new lot number), performance should always be compared to existing material.
ELISA data is typically presented as the analyte concentration against the assay readout, be that colorimetric, fluorometric, or chemiluminescent. Using more points across the range of the standard curve (ideally 8 or more) provides the flexibility to eliminate outliers and better define the curve across the range of signal response for an improved fit. For curve analysis, linear fitting is usually suitable with sandwich ELISA, however the 4-parameter logistic (4PL) model yields a better fit for the extreme low or high ends of the concentration range being measured (Figure 1). Correctness of fit can be verified via backfitting.
Figure 1. Same ELISA calibration curve presented with 2 different trendlines: linear (left) and 4-parameter logistical regression model (right).
Repeatability and accuracy are essential to any immunoassay, but when quantitative ELISA data is used to drive key decisions such as whether to progress a potential drug candidate for further testing, requirements can be especially stringent. Safeguarding measures include increasing the number of replicates (e.g. triplicate rather than duplicate testing) and incorporating a standard curve not only within each experimental run, but on each plate within the same run. For extra assurance of inter-assay reproducibility, adding another internal control to complement the standard curve provides greater confidence in results. As a general rule, the coefficient of variation (CV) of duplicate readings should be no more than 20%.
Another good practice in the case of sandwich ELISA is to opt for plates pre-coated with capture antibody instead of using uncoated plates (development kits), as this can reduce signal variability between wells. Off-the-shelf ELISA kits can offer significant advantages here since they are supplied fully validated and backed by the manufacturer’s guarantee.
RayBiotech offers a comprehensive portfolio of ELISA kits, all of which are ISO certified and validated for exceptional reproducibility. To learn more, visit raybiotech.com.