Immunoassay Signal and Evaluating Standard Curves – Common Q-Plex FAQ

Immunoassay Signal and Evaluating Standard Curves – Common Q-Plex FAQ

What is chemiluminescent signal?

In general, chemiluminescence is the production of light by a chemical reaction. Quansys chemiluminescent multiplex ELISA kits utilize a secondary antibody, or other molecule as applicable, labeled with the enzyme horseradish peroxidase (HRP) as the reporter molecule and a modified form of luminol as the substrate. In this reaction, the immobilized HRP catalyzes the oxidation of luminol, and this reaction is accompanied by the emission of light at 428 nm. Chemiluminescent signal decreases over time, which is why it is recommended to wait no longer than 10 minutes to image a chemiluminescent Q-Plex plate.

What is IR fluorescent signal?

Fluorescence is the emission of light by a material that has absorbed electromagnetic radiation. Quansys IR fluorescent multiplex ELISA kits utilize an immobilized secondary antibody, or other molecule as applicable, labeled with a fluorescent dye as the reporter molecule. This dye has an optimal excitation wavelength of 774 nm and an emission wavelength of 789 nm. The IR fluorescent signal can be imaged up to for 24 hours if the plate is stored in a dry and dark environment.

Why doesn’t the signal diffuse during imaging?

The reporter molecule is immobilized onto to a specific capture spot during the assay process. Light is only produced at the site of the immobilized reporter molecule.

How does the Q-View Software determine pixel intensity and concentration?

In the plate layout view of Q-View software, the pixels within each overlay circle are averaged using a proprietary weighting algorithm which is designed to prevent potential well background from having a large impact on the calculation. The Q-View Software allows the user to choose one of seven curve fit options: 5PL, 4PL, Log-Log, Linear, Point to Point, Qualitative, and Auto-Select (this option fits standard curves for each system individually based on the lowest AIC value). The concentrations of the unknown samples are then assigned using the regression model applied to the standard curve data. The user can also choose to have limit values such as ULOQ, LLOQ, and LLD, applied to the calculated concentrations, or to mask values so they are not included in any calculations.

I only see a few points of my standard curve in the image, why can’t I see the entire standard curve?

Many computer monitors cannot display as many levels of gray as are present in high-resolution Q-Plex images. To visualize dim or bright spots in Q-View, go to Image Processing > Image Options > Adjust Gamma. To evaluate curve quality properly, see below.

What does adjusting gamma in Q-View do?

Why does my imported image appear dimmer in Q-View?
Gamma settings in many imaging programs, including Q-View, control how image brightness and contrast are displayed but do not affect underlying data. Gamma options are useful for visualizing very bright or dim spots but are generally not saved outside that program. Thus, an imported image may appear dimmer because only the original image is brought into the new program without any adjustments to gamma settings.

How can I evaluate the quality of my standard curves?

The criteria in the Q-View Software for a standard curve point to be used for quantitation is that the %backfit must be 120%-80%, replicates must have a %CV of < 30%, and the pixel intensities must be above that of the average of the Negative Control wells. To see if your standard curve points fit the first two criteria, view the %Backfit and %CV of your standard curves points in Data Analysis > Report tab. You can simplify the report using the View button. Pixel intensities can be viewed in either the Report or Data tabs. Additionally, you can check the curve statistics listed at the top of each chart in Data Analysis > Charts tab. If a standard curve point did not perform as expected, first ensure that all plate overlay spots are aligned and dilution factors have been assigned. Then, consider masking points that may be outliers if the %CV between replicates is greater than 30%, or the %Backfit is outside 80%–120%.

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