Fourier transform infrared (FT-IR) spectroscopy combined with multivariate statistical analyses was investigated as a physicochemical tool for monitoring secreted recombinant antibody production in cultures of Chinese hamster ovary (CHO) and murine myeloma nonsecreting 0 (NS0) cell lines. Medium samples were taken during culture of CHO and NS0 cells lines, which included both antibody-producing and non-producing cell lines, and analyzed by FT-IR spectroscopy. Principal components analysis (PCA) alone, and combined with discriminant function analysis (PC-DFA), were applied to normalized FT-IR spectroscopy datasets and showed a linear trend with respect to recombinant protein production. Loadings plots of the most significant spectral components showed a decrease in the C-O stretch from polysaccharides and an increase in the amide I band during culture, respectively, indicating a decrease in sugar concentration and an increase in protein concentration in the medium. Partial least squares regression (PLSR) analysis was used to predict antibody titers, and these regression models were able to predict antibody titers accurately with low error when compared to ELISA data. PLSR was also able to predict glucose and lactate amounts in the medium samples accurately. This work demonstrates that FT-IR spectroscopy has great potential as a tool for monitoring cell cultures for recombinant protein production and offers a starting point for the application of spectroscopic techniques for the on-line measurement of antibody production in industrial scale bioreactors. © 2010 Wiley Periodicals, Inc.
- Fourier transform infrared spectroscopy
- Mammalian cell culture
- Partial least squares regression
- Principal components analysis
- Recombinant antibody production