Strategies for Mitigating Commercial Sensor Chip Variability with Experimental Design Controls.

Area of Science:

• Biochemistry
• Analytical Chemistry
• Biotechnology

Background:

• Surface Plasmon Resonance (SPR) is a key real-time biosensing technique for measuring binding kinetics and affinity.
• Ni-NTA immobilization is a common method for ligand attachment in SPR, offering sensor regeneration but potentially causing signal variability.
• Reproducibility challenges in SPR experiments using Ni-NTA chips hinder reliable data generation.

Purpose of the Study:

• To investigate factors contributing to signal variability in Ni-NTA SPR sensor chips.
• To develop strategies for enhancing the reproducibility and data quality of SPR experiments.
• To address the knowledge gap regarding variability in commercially available SPR sensor chips.

Main Methods:

• Utilized the Nicoya OpenSPR system as a model for studying SPR variability.
• Employed ovarian cancer biomarker proteins (MUC16, HE4) and their antibodies as model ligand/analyte pairs.
• Assessed non-specific binding, chip-to-chip variability, maximum immobilization differences, and ligand density effects on analyte response.

Main Results:

• Observed significant non-specific binding across multiple Ni-NTA chips.
• Demonstrated greater consistency in ligand immobilization and analyte binding on the same chips compared to different chips.
• Identified varying maximum immobilization capacities and a relationship between ligand density and analyte response, attributed to steric crowding.

Conclusions:

• Chip-to-chip variability and ligand immobilization density are critical factors affecting SPR data reproducibility.
• Calibration and normalization based on ligand immobilization levels can significantly improve data quality and minimize variability.
• Implementing these strategies in experimental design enhances the reliability of SPR sensing platforms for biomolecular interaction analysis.