How to Analyze ELISA Data: Interpreting Results and Standard Curves
Analyzing your data is just as important as performing your ELISA experiment! Correctly analyzing and interpreting your results with good standard curve data will increase the reliability and robustness, and contribute to overall experimental success.
To understand why the standard curve is so important for an ELISA experiment, consider the overall test principle, or how an ELISA kit works. Here is the test principle for a traditional sandwich format ELISA:
Test Principle:
The microtiter plate provided in this kit has been pre-coated with an antibody specific to the target analyte. Standards or samples are then added to the appropriate microtiter plate wells with a biotin-conjugated antibody preparation specific to the target analyte. Next, Avidin conjugated to Horseradish Peroxidase (HRP) is added to each microplate well and incubated. After TMB substrate solution is added, only those wells that contain the target analyte, biotin-conjugated antibody and enzyme-conjugated Avidin will exhibit a change in color. The enzyme-substrate reaction is terminated by the addition of sulphuric acid solution and the color change is measured spectrophotometrically at a wavelength of 450 ± 10 nm. The concentration of the target analyte in the samples is then determined by comparing the O.D. of the samples to the standard curve.
The ELISA standard curve is therefore essential for determining the concentration of unknown samples. It is generated by preparing a series of known concentrations of the target analyte and plotting their optical density (OD) readings against their respective concentrations. A best-fit curve, typically a four-parameter logistic (4PL) or linear regression, is then used to interpolate sample concentrations.
The standard solution and standard curve should always be prepared as described in the manual in your ELISA kit. In the case of Reddot Biotech ELISA kits, the standard is often prepared as follows:
Standard - Reconstitute the Standard with the specified amount of Diluent Buffer, keep for 10 minutes at room temperature, shake gently (avoid bubbles). The concentration of the standard in the stock solution will be as listed in the manual. Prepare 7 tubes containing 0.5 mL Diluent Buffer and use the diluted standard to produce a double dilution series. Mix each tube thoroughly before the next transfer. Prepare a dilution series with 7 points, and the last tube with Diluent Buffer is the blank at 0 ng/mL.
You can then preform the ELISA experiment with your samples as described in the manual.
Once the ELISA experiment data (including standard curve data) has been collected, the results can be analyzed. For best results, we recommend using curve-fitting software like Curve Expert 1.4.
This example using Curve Expert 1.4 will show how to construct your ELISA standard curve, and how to use the curve equation to calculate your experimental results.
1. Open Curve Expert 1.4, and you should see the following screen.
2. Using the data from your standard curve, input the OD value on the X-axis, against the sample concentration on the Y-axis.
3. Click this icon to open model options.
4. Click the ‘All Off’ button.
5. Select Sigmoidal Models to fit to your ELISA standard curve.
**Please note that the higher the r-value for your equation (or the closer the r-value is to 1), the more reliable values you will get.
6. Hit Ctrl + L in the blank part of the above picture to open the analysis interface.
After inputting the corresponding OD value (x-value), hit “Calculate” to obtain the concentration (Y-value) of the sample. Factor in any dilutions if necessary.
7. Click the button on the top left corner to obtain the ELISA curve fitting equation.
8. Logistic Model: y=a/(1+b*exp(-cx))
Coefficient Data:
a = -1.19763443774E+004
b = -8.45403498052E+001
c = 1.30213993104E+000
Click the button “copy” and you will get the figures for curve equation showed in the above screen shot.
Logistic Model: y=a/(1+b*exp(-cx))
Coefficient Data:
a = -1.19763443774E+004
b = -8.45403498052E+001
c = 1.30213993104E+000
The model for data analysis used in this example is a Logistic model. However, we recommend allowing your curve analysis software to select the best fit model based on the data from each individual experiment.
Interpreting ELISA results requires careful evaluation of the standard curve and sample OD values. Here are key factors to consider:
If you have any questions, or require assistance analyzing your data, please Contact Us for more information.
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