Probeless non-invasive near-infrared spectroscopic bioprocess monitoring using microspectrometer technology

Abstract

Real-time measurements and adjustments of critical process parameters are essential for the precise control of fermentation processes and thus for increasing both quality and yield of the desired product. However, the measurement of some crucial process parameters such as biomass, product, and product precursor concentrations usually requires time-consuming offline laboratory analysis. In this work, we demonstrate the in-line monitoring of biomass, penicillin (PEN), and phenoxyacetic acid (POX) in a Penicillium chrysogenum fed-batch fermentation process using low-cost microspectrometer technology operating in the near-infrared (NIR). In particular, NIR reflection spectra were taken directly through the glass wall of the bioreactor, which eliminates the need for an expensive NIR immersion probe. Furthermore, the risk of contaminations in the reactor is significantly reduced, as no direct contact with the investigated medium is required. NIR spectra were acquired using two sensor modules covering the spectral ranges 1350-1650 nm and 1550-1950 nm. Based on offline reference analytics, partial least squares (PLS) regression models were established for biomass, PEN, and POX either using data from both sensors separately or jointly. The established PLS models were tested on an independent validation fed-batch experiment. Root mean squared errors of prediction (RMSEP) were 1.61 g/L, 1.66 g/L, and 0.67 g/L for biomass, PEN, and POX, respectively, which can be considered an acceptable accuracy comparable with previously published results using standard process spectrometers with immersion probes. Altogether, the presented results underpin the potential of low-cost microspectrometer technology in real-time bioprocess monitoring applications.

Measurement Techniques to Resolve and Control Population Dynamics of Mixed-Culture Processes

“…The aforementioned optical methods focus on classic UV/VIS spectroscopy, but there is also a large potential for longer wavelength spectroscopy in the range of near-infrared (NIR) to Raman (Box 2) [86,87]. Beside a large number of medical applications, NIR is an established technique to monitor biomass, substrates, and metabolic products of well-known monoculture processes [88,89]. The direct determination of different microbial species in a mixed culture might be challenging by NIR, but indirect investigation of mixed culture (compositions) was shown by Grassi and colleagues, who cultured Lactobacillus bulgaricus and Streptococcus thermophilus for lactic acid formation [90].…”

Scale-Up Technologies for the Manufacture of Adherent Cells

“…In the in situ system, an in line analyser tests the sample and then returns it back into the bioreactor; while in the ex situ approach the sample does not return to the bio-analyser after been measured ( 30 ). While in line analytical methods to monitor the pH, dissolved oxygen and temperature are already available, other parameters like the substrate density are still being measured offline through laborious and error prone methods ( 31 ). An example in which components of a bioreactor can be monitored offline, with the help of biomass separation methods, is the High-Performance Liquid Chromatography (HPLC) system.…”

“…Instruments facilitating these measurements are based on optical density, fluorescence or conductivity and are providing online measurements which subsequently will be verified using offline methods such as microscopy ( 34 ). At-line monitoring of substrate and reagents density can be performed using optical sensors, ultrasound sensors, UV-Vis, fluorescence and RAMAN spectroscopy ( 31 ). RAMAN and near infra-red (NIR) spectroscopic methods are popular in the pharmaceutical industry and are based on the interaction between light and matter.…”

“…NIR advantages include easy maintenance, being non-invasive and the identification of multiple analytes in the media. However, FTIR probes are expensive and the immersion of probes into the bioreactor broth requires thorough sterilization ( 31 ). Finally, it is worth mentioning in situ microscopy, this is capable of taking images of cells from inside a bioreactor without the need to take the sample out ( 38 ) since the field of view is fixed ( 34 ).…”

A Chemometric Tool to Monitor and Predict Cell Viability in Filamentous Fungi Bioprocesses Using UV Chromatogram Fingerprints

“…Three different modelling techniques were used for the prediction of viability using UV chromatogram fingerprints at 260 nm; namely, partial least squares (PLS), orthogonal PLS (OPLS) and principle component regression (PCR). The modelling techniques have been well defined and explained in many publications [41][42][43][44][45][46]. PLS is the most commonly used multivariate method to assess the relationship between a descriptor matrix X and the response matrix Y. PLS is usually used for prediction of quantitative Y data; however, qualitative Y data can be used for discriminant analysis (PLS-DA).…”