Surely you’ve found yourself in a research situation where your experimental results left you scratching your head. Any type of lab work will sometimes do that to you, and Surface Plasmon Resonance (SPR) is no exception.
Like in any analytical assay, the quality of SPR results depends heavily on the quality of the starting material. Don’t believe it? Here’s 4 situations that may sound familiar, where taking a step back and getting better quality protein samples can solve your problems.
We all know that in science, if a result hasn’t been generated at least three independent times, it doesn’t count. If a result cannot be reproduced, a new hypothesis is postulated and new experiments are devised. Starting over can absolutely be the right thing to do — or it can be premature, especially when the only reason the results look different is that the protein used in the assay is behaving differently. Maybe something went wrong during the purification of the last batch of protein, or maybe the aliquot used in the last repeat was accidentally left out and lost its function. Things like this happen to the best of us, but they don’t have to throw our research off track. Retracing your steps and reexamining your sample material may be the answer.
Sometimes, the literature or orthogonal techniques clearly show that there is an interaction between the molecules you’re investigating. Other times, it might just be a really strong gut feeling that there should be one. But what if your SPR assay doesn’t show that interaction? Before you let that shake your confidence in your scientific capabilities, consider whether the protein may be the culprit: it’s possible it just wasn’t able to actually perform the interaction. Maybe the low pH used to immobilize the ligand has denatured it. Maybe the ligand protein just reeeeally doesn’t like to be immobilized, or tagged, and its structural integrity is affected. Or maybe the analyte protein has been sitting in the SPR instrument at room temperature for too long, waiting to be injected, and it has unfolded in the meantime. Maybe one (or both!) of your proteins denatured in storage long ago. In most cases, unfolded protein isn’t functional and can’t perform the interactions it evolved to perform, so this may be the reason you’re not seeing what you’re expecting.
Often, you have an idea of how strong the interaction you’re investigating should be, either from the literature or from comparing to mutants or variants of your protein(s). If the affinity and kinetics aren’t what you expect, it may again be due to unfolded or denatured analyte — just this time, the protein is only partially unfolded, instead of all the way. Again, this can happen in storage or during the assay run time if the wrong buffer is used or if the protein is kept at concentrations where it’s not stable. Let’s say 50% of protein molecules in the sample are still functional — that still means that 50% aren’t, and that’s going to show in the results, simply because the numbers plugged into the calculations are also off by 50%. The same problem arises if the protein isn’t monomeric like you thought, but has dimerized or oligomerized. The numbers won’t be right, and so the results can’t be right either. By finding these things out ahead of time, you can use the right numbers in the calculations, and get the correct results.
In situations where you can’t make sense of experimental results at all, it’s good scientific practice to consider all possible causes. It’s easy to suspect your SPR instrument when something goes wrong, due to its complex microfluidics systems that need regular maintenance, service, and part replacements. It can lead to costly headaches and time sucks with on-site support and hidden service fees, adding up to a few thousand dollars (or euros) and delaying valuable experiments. And the kicker is: sometimes, after all this is done, the problem persists! If it wasn’t the instrument’s fault, then what’s to blame? Again, it could be bad quality proteins. For example, aggregated analyte can stick to the tubing and get randomly dislodged later, causing weird signals in your (or the next person’s) experiment. Also, it can stick directly to the sensor chip surface and cause inconclusive data (and ruin the chip). It’s definitely something to look into before you call in the experts!
You’ve probably heard the phrase “garbage in, garbage out.” The phrase itself originated in computer science, but the concept applies to all fields, including lab work: if you feed a system (like your SPR instrument) with suboptimal input, how can the outcome be optimal? Let’s tackle these issues at the roots and make sure to work with the best quality protein samples you possibly can, to get the best possible quality of output — those results you need to confirm your hypothesis, or the data you need to publish. Let’s change our mindset to “gold in, gold out!”