Poster Presentation 50th Lorne Proteins Conference 2025

MMS EVALUATION OF HOS FOR IGG SAMPLES SPIKED WITH BSA (#209)

Peter Davis 1
  1. ATA Scientific, Caringbah, NSW, Australia

P.Davis1*, L.Wang3, B. Kendrick2, J. Zonderman3, E. Ma3.

1ATA Scientific, 47 Cawarra Road, Caringbah, NSW, 2229 Australia* Non-author Presenter*

2KBI Biopharma, 1450 Infinite Drive, Louisville, CO 80027

3RedShift BioAnalytics, Inc., 131 Middlesex Turnpike, Burlington, MA 01803

Microfluidic Modulation Spectroscopy (MMS) is a novel protein characterization technique that combines rapid modulation of sample and reference through a microfluidic flow cell with a tunable mid-IR Quantum Cascade Laser (QCL). Five key measurements are provided to assess the similarity, comparability, quantitation, denaturation, and aggregation of proteins by analyzing their higher order structure. A series of 20 mg/mL IgG samples (predominantly β-sheet) spiked with 20 mg/mL BSA (predominantly α-helical) was evaluated on the MMS platform at BSA concentrations of 0, 2, 4, 6, 8 and 10% to demonstrate the sensitivity of MMS for detecting small differences in secondary structure and measure the system Limit of Quantitation (LOQ). Differential absorbance spectra were collected, and second derivative spectra were calculated to evaluate similarity, comparability, and LOQ of MMS relative to FTIR. As BSA concentration was increased across the series, the α-helix absorbance peak at 1656 cm-1 increased and the β-sheet absorbance peak at 1637 cm-1 decreased accordingly. MMS was able to detect changes in secondary structure for the 2% BSA spiked samples with a calculated LOQ of 0.76% versus results from a similar FTIR study where structural differences were detected in the 8-10% BSA spiked samples with a significantly higher calculated LOQ of 22.7%. This study demonstrates the effectiveness of MMS as a powerful characterization technique for the analysis of protein secondary structure with an ability to generate accurate and high sensitivity HOS data using an automated IR platform.