Strategies for Mitigating Commercial Sensor Chip Variability with Experimental Design Controls

Abstract

Surface plasmon resonance (SPR) is a popular real-time technique for the measurement of binding affinity and kinetics, and bench-top instruments combine affordability and ease of use with other benefits of the technique. Biomolecular ligands labeled with the 6xHis tag can be immobilized onto sensing surfaces presenting the Ni2+-nitrilotriacetic acid (NTA) functional group. While Ni-NTA immobilization offers many advantages, including the ability to regenerate and reuse the sensors, its use can lead to signal variability between experimental replicates. We report here a study of factors contributing to this variability using the Nicoya OpenSPR as a model system and suggest ways to control for those factors, increasing the reproducibility and rigor of the data. Our model ligand/analyte pairs were two ovarian cancer biomarker proteins (MUC16 and HE4) and their corresponding monoclonal antibodies. We observed a broad range of non-specific binding across multiple NTA chips. Experiments run on the same chips had more consistent results in ligand immobilization and analyte binding than experiments run on different chips. Further assessment showed that different chips demonstrated different maximum immobilizations for the same concentration of injected protein. We also show a variety of relationships between ligand immobilization level and analyte response, which we attribute to steric crowding at high ligand concentrations. Using this calibration to inform experimental design, researchers can choose protein concentrations for immobilization corresponding to the linear range of analyte response. We are the first to demonstrate calibration and normalization as a strategy to increase reproducibility and data quality of these chips. Our study assesses a variety of factors affecting chip variability, addressing a gap in knowledge about commercially available sensor chips. Controlling for these factors in the process of experimental design will minimize variability in analyte signal when using these important sensing platforms.

Combining the Benefits of Biotin–Streptavidin Aptamer Immobilization with the Versatility of Ni-NTA Regeneration Strategies for SPR

“…For applications that are high throughput like aptamer characterization, the extra step is a worthwhile tradeoff for the ability to run multiple aptamers on the same sensor chip. In addition to reducing the number of sensor chips required, it can reduce variability that might occur between separate chips or separate sensor lots [23]. In future work, we would like to assess the immobilization of other aptamers, particularly ones of different lengths or with affinity for different types of targets.…”

“…There is a much wider range in the calculated B max values, but this is likely due to differences in sensor chip surfaces and immobilization efficiency [23], and experiment-toexperiment variability between the B max values does not affect the relative consistency of the calculated K A s.…”

“…The reproducibility of replicate ligand immobilizations on a chip lends confidence to individual assays as variability in ligand immobilization can cause variation in measurements of analyte binding [23]. The ability to use a chip for multiple immobilizations increases throughput.…”