While mass photometry is well-established for protein characterization, applying it to mRNA introduces distinct physiochemical challenges. Standard protocols optimized for proteins often fall short due to mRNA’s conformational dynamics and ion dependence, making dedicated experimental design necessary for accurate and reproducible results.
This whitepaper provides a data-driven framework for optimizing mRNA mass photometry. It details how key experimental parameters, including slide selection, calibration, detection range, sample concentration, buffer selection, and automation, affect measurement quality, and identifies evidence-based best practices for experimental design.
Download this whitepaper to explore
- How slide surface, calibration, sample concentration, and buffer conditions affect mass photometry data
- Calibration and detection considerations for different mRNA size ranges
- Data quality indicators such as unbinding events, relative error, and sigma values
- Considerations for automating the measurement of multiple samples in one run
