Improving Your Assay By Reducing Nonspecific Background Binding

Whether in diagnostics or R&D, getting biomolecules to behave in a measurement assay is always a tricky business. And getting them to behave twice (or better yet a thousand times) is exponentially harder. But to develop a successful assay, one that ultimately helps people, you can’t just throw your hands up and lament how sticky proteins are. Scientists have been dealing with biomolecules for decades, and several strategies have been developed to reduce background signals that contribute to poor assay performance. Even better, new technologies are being released to market that make the most finicky aspects of blocking a thing of the past.

Biomolecules Getting in the Way of Your Biomolecular Measurement?

Nonspecific binding is a headache for researchers on all biosensor platforms, whether you’re struggling on a Western blot, ELISA, immunohistochemistry stain, PCR system, SPR platform, or BLI tool. Extracting an accurate measurement of the biomolecules being studied requires optimizing your blocking strategy to increase the signal to noise ratio of the system, where noise is any unwanted signal. Common sources of noise include capture molecule or ligand adsorbing nonspecifically on the sensor surface, target analyte binding directly to the sensor surface, and other molecules in buffer binding to the sensor surface or to the capture molecule via hydrogen bonding between hydrophobic regions. When the entire measurement depends on the sensor surface seeing only a particular chemistry (i.e. the capture molecule binding to the target), anything else happening turns into unwanted signal.

Just Put More BSA On It

Thankfully, these effects can be reduced through proper blocking, and steady incremental improvements have been made over time. Ultimately, all blocking strategies revolve around saturating unoccupied binding sites on the sensor surface with a compound (like BSA) that simultaneously passivates the sensor surface and does not interfere with the chemistry between the capture molecule and the target analyte. There are many resources available that describe the benefits of detergent blockers versus protein blockers versus polymer blockers. More often than not though, these resources end with some nonspecific advice on how to solve your nonspecificity issues.

But improving the blocking chemistry is only one side of the coin. Improving, or even switching, your readout platform is another way to improve your signal to noise and get more accurate results with lower detection limits, which can save you from many frustrating experiments with confusing results.

If At First You Don’t Succeed, Try, Try, Try Again, and Then Upgrade Your Sensor

Field Effect Biosensing (FEB) is a new technique that does not suffer from the same constraints as historical biomolecular measurement tools since it uses an electronic readout rather than an optical readout. FEB is well-suited for investigating binding kinetics of antibody-antigen pairs or small molecule binding for pharmaceutical assay development while using fewer steps and fewer interfering compounds. As an example, FEB can perform sophisticated kinetic analysis of antibody-antigen binding down to the fM range without the use of BSA or milk or fish guts. FEB is also successful at measuring more exotic biomolecular systems including peptides, aptamers, and fragments.  FEB assays can function in complex media such as serum without the use of additional blocking steps and importantly, without significant changes in the sensitivity.

So, if nonspecific binding is an issue for your assay, you can continue designing experiments swapping Tween for serum for BSA for casein for PEG endlessly until something magically does the job (reproducibly), or you can simply change your sensor and get better results right away on an easier-to-use platform.

Related Literature

For more about non-specific binding with FEB technology:

Blocking and Quenching to Reduce Nonspecific Interactions in High Quality Biosensors

Nonspecific Binding is Prevented on Agile R100