Christopher Cannizzaro, Ian William Marison, Martin Rhiel, Sergio Valentinotti, Urs von Stockar
Comprehensive in-situ bioreactor monitoring and control based on a midinfrared spectroscopic sensor system M. Rhiel1, C. Cannizzaro1, S. Valentinotti2, I. Marison1, U. von Stockar1 1 Institute of Chemical Engineering, 2Institute of Automatic Control Swiss Federal Institute of Technology (EPFL), CH- 1015 Lausanne, Switzerland Abstract A mid-infrared spectroscopic sensor system consisting of a spectrometer, a single attenuated total reflectance (ATR) probe immersed in the bioreactor, and a software package for multivariate spectra analysis was used to monitor glucose, ethanol, glycerol, acetic acid, sulfate, phosphate, PPG 2000 antifoam, and biomass in Saccharomyces cerevisiae cultures. The provided ethanol concentration was used to control the feed of a concentrated glucose solution to maintain maximum oxidative growth. Introduction: Bioprocess monitoring and control rely on the use of appropriate sensors. Ideally, these sensors should be in situ and measure simultaneously the concentrations of all major bioprocess metabolites with sufficient accuracy and long-term stability under minimum maintenance. Spectroscopic sensors utilizing the mid-infrared (MIR) electromagnetic range offer many advantages, including simultaneous multi-analyte determinations, in situ sterilizability, low maintenance during operation, and enhanced information about most biologically important species compared to near-infrared (NIR) spectroscopic sensors. bioprocess monitoring. Overlapping absorbance features, however, require the application of advanced chemometric analysis methods. This paper discusses the simultaneous in-situ monitoring of glucose, ethanol, glycerol, acetic acid, biomass, pH, temperature, and bioreactor volume in batch and fed-batch cultures of Saccharomyces cerevisiae with a Therefore, they seem to be good candidates for single-probe mid-infrared spectroscopic sensor (ReactIRTM, ASI Applied Systems). Calibration models for each analyte were established with partial least-squares regression (PLSR) implemented for immediate process analysis (QuantIRTM, ASI Applied Systems). Concentration data was available every two minutes and allowed the implementation of a fed-batch control strategy to maximize biomass production. Materials and Methods: A ReactIRTM 1000 mid-infrared spectrometer (ASI Applied Systems, Millersville, MD) equipped with a diamond ATR immersion probe (DiCompTM , ASI Applied Systems) and QuantIRTM software (ASI Applied Systems) was used for in situ data acquisition and analysis. Saccharomyces cerevisiae CBS426 and S. cerevisiae W303-1A PVD32 cells were grown on defined medium in a 16L stirred tank bioreactor (Bioengineering AG, Wald, Switzerland). A customized bioprocess management and control environment (BioOPT) was developed with LabVIEWTM (National Instruments, Austin, TX). Results: Quantitative spectra analysis was performed by establishing PLSR models for each of the analytes: glucose, ethanol, glycerol, acetic acid, sulfate, phosphate, PPG 2000 antifoam, and biomass. The calibration data set consisted of 60 in situ collected pure component spectra and 40 in situ collected reaction spectra. Maintaining the ethanol concentration reported by the mid-infrared spectroscopic sensor system around 0.7 g/L resulted in an exponential growth rate of 0.255 1/h. Exponential growth was sustained until oxygen, supplied by sparging air, became limiting. Thereafter, the controller adapted automatically and linear growth occurred up to a cell density of 60 g/L.
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