Abstract

Raman spectroscopy is a novel tool used in the on-line monitoring and control of bioprocesses, offering both quantitative and qualitative determination of key process variables through spectroscopic analysis. However, the wide-spread application of Raman spectroscopy analysers to industrial fermentation processes has been hindered by problems related to the high background fluorescence signal associated with the analysis of biological samples. To address this issue, we investigated the influence of fluorescence on the spectra collected from two Raman spectroscopic devices with different wavelengths and detectors in the analysis of the critical process parameters (CPPs) and critical quality attributes (CQAs) of a fungal fermentation process. The spectra collected using a Raman analyser with the shorter wavelength (903 nm) and a charged coupled device detector (CCD) was corrupted by high fluorescence and was therefore unusable in the prediction of these CPPs and CQAs. In contrast, the spectra collected using a Raman analyser with the longer wavelength (993 nm) and an indium gallium arsenide (InGaAs) detector was only moderately affected by fluorescence and enabled the generation of accurate estimates of the fermentation’s critical variables. This novel work is the first direct comparison of two different Raman spectroscopy probes on the same process highlighting the significant detrimental effect caused by high fluorescence on spectra recorded throughout fermentation runs. Furthermore, this paper demonstrates the importance of correctly selecting both the incident wavelength and detector material type of the Raman spectroscopy devices to ensure corrupting fluorescence is minimised during bioprocess monitoring applications.

Highlights

  • Raman spectroscopy is a non-invasive, non-destructive spectroscopic technique that exploits molecular vibrations for the qualitative and quantitative analysis of molecules [1]

  • Fluorescence is a major problem experienced by many scientists and engineers implementing Raman spectroscopy to monitor and control biopharmaceutical processes

  • This paper is the first direct comparison of two different Raman spectroscopy devices on the same fermentation highlighting the significant influence of incident wavelength and detector material on fluorescence levels detected by each device

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Summary

Introduction

Raman spectroscopy is a non-invasive, non-destructive spectroscopic technique that exploits molecular vibrations for the qualitative and quantitative analysis of molecules [1]. A technique known as shifted excitation Raman difference spectroscopy (SERDS) involving the collection and subtraction of two Raman spectra in succession at slightly different laser wavelengths was demonstrated to eliminate fluorescence during the analysis of biological samples [17,18] This technique creates a derivative-like spectrum with the background fluorescence signal eliminated, enabling better resolution of the important Raman features [19]. The detector material of the device can be highly influential on observed fluorescence, little research has been reported on the importance of this selection criteria in the application of Raman spectroscopy to fermentation monitoring To address this issue and advance the use of this technology in fermentation applications, two Raman spectroscopic analysers were implemented on a highly fluorescence fungal fermentation process. This work highlights the need to better understand the fundamental principles of fluorescence on recorded Raman spectra and demonstrates the importance of correct probe selection in future applications of this novel technology to the biotechnology sector

Microorganism and Media
Bioreactor Conditions
Raman Spectroscopy Devices
Raman Spectra Preprocessing and Wavelength Selection
Partial Least Model Generation
Validation of PLS Model
Raman Spectroscopic Fundamentals
Fluorescence Observations
Glucose Predictions of 903 and 993 nm Raman Spectroscopic Devices
API Predictions of 993 nm Raman Spectroscopic Device
Conclusions
Fluorescence and background baseline increase
Cosmic Peaks
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