From UV to MIR: the biomass monitoring spectrum
Dörte Solle, Philipp Biechele, Christoph Busse and Thomas Scheper |
Infrared spectroscopy includes spectral areas of near infrared (NIR, 740 nm to 1300 nm) and mid-infrared (MIR, up to 15000 nm). In general, IR light excites different vibrational modes of molecules. Each organic and inorganic compound has a special spectral IR signature from these vibrations. IR spectroscopy offers very fast, robust and sensitive multi-analyte information from the culture broth of bioprocesses. It is a non-invasive process analytical technology, applied in-line by direct beam or optical fiber.
MIR radiation excites fundamental rotational vibrations of functional groups from organic compounds. Molecules such as glucose, lactate, fructose, acetic acid, ammonia, and even antibodies (17) have a characteristic absorption spectrum which can be used to identify single components in bioprocesses quantitative, sensitive, and specific.
A high degree of water absorption appears in MIR spectra. However, in-line measurement in aqueous solutions is possible using appropriate fiber optic probes that incorporate attenuated total reflection (ATR) technology and Fourier transformation (18–20). The measurement principle of ATR probes results in a very short (only few µm) path length and cells cannot be detected because they are too large to enter the measuring zone.
NIR spectroscopy is also based on different vibrational modes, overtone and combination vibrations after excitation. Important targets are the O-H, C-H and N-H bonds. The NIR range is thus suitable for monitoring of substrates such as glucose and lactate, biomass, and the products of a bioprocess (17, 21). As a result of the lower energy of the NIR and the resulting overtone vibrations, the bands are much broader, often overlapping, and not as specific as in MIR spectroscopy (20). Thus, NIR spectroscopy has a more qualitative character, compared to the more precise and quantitative MIR spectroscopy. NIR spectroscopy offers a more global view to a bioprocess, e.g. by batch trajectory (22).
Due to its higher robustness, NIR spectroscopy is better applied for monitoring industrial production processes. MIR spectroscopy is well suited for process development and optimization due to its multiplexing technology and the fact that fragile ATR fibers are used.
UV/Vis spectroscopy uses ultraviolet and visible light (10–740 nm) to excite electrons of molecules, the observable transitions taking place at unsaturated bonds, such as in aromatics (11). A variety of analytes, substrates, metabolites, and products can be determined with UV/Vis spectroscopy, which has high sensitivity, and high resolution spectrophotometers can be compact, inexpensive, and robust, making these instruments interesting for industrial process applications (21). However, UV/Vis spectroscopy does not currently play a major role in bioprocess monitoring (23) despite the use of CCDs or photodiode arrays making UV/Vis spectroscopy even more attractive.
Using fluorescence spectroscopy, many important molecules for bioprocesses can be monitored and controlled, including proteins with aromatic amino acids (tryptophan), NAD(P)H (biomass), ATP, pyruvate, vitamins, pyridoxines, coenzymes, and flavins (12, 21, 24–27). Each fluorescence-active compound has a specific pair of excitation and emission wavelengths. Simultaneous measurement of several different fluorophores in the culture broth is possible by 2-D fluorescence spectroscopy (13, 24, 28–31).
Raman spectroscopy is another form of vibrational spectroscopy. It is based on shifted wavelength scattering of molecules, after excitation by monochromatic light, usually produced by adjustable lasers (32). Several analytes, including glucose, lactate, acetate, formate, glutamine, and glutamate, can be measured (1, 15, 21, 33–37). The use of Raman spectroscopy is limited by the strong fluorescence activity of several biological molecules in the culture broth (34). The fluorescence signals overlay the Raman bands. To avoid fluorescence, low energy lasers can be used, but then heating effects can occur (21, 24, 38).
- A Bluma et al., “In-situ imaging sensors for bioprocess monitoring: State of the art,” Anal Bioanal Chem 398 (6), 2429–2438 (2010).
- M Pohlscheidt et al., “Bioprocess and fermentation monitoring,” Encycl Ind Biotechnol Bioprocess Biosep Cell Technol (2013).
- C Rehbock et al., “Bioprozessanalytik,” Chemie Ing Tech, 80 (3), 267–286 (2008).
- M Rhiel et al., “Real-time in situ monitoring of freely suspended and immobilized cell cultures based on mid-infrared spectroscopic measurements,” Biotechnol Bioeng, 77 (2) 174–185 (2002).
- M Sandor et al., “Comparative study of non-invasive monitoring via infrared spectroscopy for mammalian cell cultivations,” J Biotechnol, 168 (4), 636–645 (2013).
- CA Sellick et al., “Rapid monitoring of recombinant antibody production by mammalian cell cultures using fourier transform infrared spectroscopy and chemometrics,” Biotechnol Bioeng, 106 (3) 432–442 (2010).
- SA Arnold et al., “In-situ near infrared spectroscopy to monitor key analytes in mammalian cell cultivation,” Biotechnol Bioeng 84 (1), 13–19 (2003).
- G Rao, H Lam, and Y Kostov, “Optical Instrumentation for Bioprocess Monitoring,” in Optical Sensor Systems in Biotechnology, 116, 125–142 (Springer Berlin Heidelberg, 2010).
- Y R Matthieu Clavaud et al., “Chemometrics and in-line near infrared spectroscopic monitoring of a biopharmaceutical Chinese hamster ovary cell culture: Prediction of multiple cultivation variables,” Talanta, 28–38 (2013).
- L Noui et al., “Development of a high resolution UV spectrophotometer for at-line monitoring of bioprocesses,” Chem Eng Process Process Intensif, 41 (2), 107–114 (2002).
- M-N Pons, S Le Bonté, and O Potier, “Spectral analysis and fingerprinting for biomedia characterisation,” J Biotechnol, 113 (1–3), 211–230 (2004).
- LNM Duysens and J Amesz, “Fluorescence spectrophotometry of reduced phosphopyridine nucleotide in intact cells in the near-ultraviolet and visible region,” Biochim. Biophys. Acta, 24, 19–26, 1957.
- K Hantelmann et al., “Two-dimensional fluorescence spectroscopy: A novel approach for controlling fed-batch cultivations,” J. Biotechnol., 121 (3), 410–417 (2006).
- MB Haack, A Eliasson, and L Olsson, “On-line cell mass monitoring of Saccharomyces cerevisiae cultivations by multi-wavelength fluorescence,” J Biotechnol, 114 (1–2, 199–208 (2004.
- HLT Lee et al., “In situ bioprocess monitoring of Escherichia coli bioreactions using Raman spectroscopy,” Vib Spectrosc, 35 (1–2), 131–137 (2004).
- C. Cannizzaro et al., “On-line monitoring of Phaffia rhodozyma fed-batch process with in situ dispersive Raman spectroscopy,” Biotechnol Bioeng, 83 (6), 668–680 (2003).
- D Landgrebe et al., “On-line infrared spectroscopy for bioprocess monitoring,” Appl Microbiol Biotechnol, 88 (1), 11–22 (2010).
- C Haake et al., “Online-Infrarotspektros-kopie in der Bioprozess-analytik,” Chemie-Ingenieur-Technik, 81 (9), 1385–1396 (2009).
- B Sonnleitner, “Automated Measurement and Monitoring of Bioprocesses: Key Elements of the M3C Strategy,” in Measurement, Monitoring, Modelling and Control of Bioprocesses, 1–33 (Springer, 2013).
- P Roychoudhury, LM Harvey, and B McNeil, “The potential of mid infrared spectroscopy (MIRS) for real time bioprocess monitoring,” Anal Chim Acta, 571 (2), 159–166 (2006).
- S. Beutel and S. Henkel, “In situ sensor techniques in modern bioprocess monitoring,” Appl Microbiol Biotechnol, 91 (6), 1493–1505 (2011).
- C Hakemeyer et al., “At-line NIR spectroscopy as effective PAT monitoring technique in Mab cultivations during process development and manufacturing,” Talanta, 90, 12–21 (2012).
- MA Liauw, LC Baylor, and PE O’Rourke, “UV-Visible Spectroscopy for On-Line Analysis,” in Process Analytical Technology, 81–106 (John Wiley & Sons, Ltd., 2010)
- V Vojinovic, JMS Cabral, and LP Fonseca, “Real-time bioprocess monitoring: Part I: In situ sensors,” Sensors Actuators B Chem., 114 (2), 1083–1091 (2006).
- B Tartakovsky et al., “Application of scanning fluorometry for monitoring of a fermentation process,” Biotechnol Prog, 12 (1), 126–131, 1996.
- KD Anders et al., “Biotechnological applications of fiber-optic sensing: multiple uses of a fiber-optic fluorimeter,” Sensors Actuators B Chem, 11, 395–403, (1993).
- K Sato et al., “On-line measurement of intracellular ATP of Saccharomyces cerevisiae and pyruvate during sake mashing,” J. Biosci. Bioeng., 90 (3), 294–301 (2000).
- R Ulber, J-G Frerichs, and S Beutel, “Optical sensor systems for bioprocess monitoring,” Anal Bioanal Chem, 376 (3), 342–348 (2003).
- S Marose, C Lindemann, and T Scheper, “Two-Dimensional Fluorescence Spectroscopy: A New Tool for On-Line Bioprocess Monitoring,” Biotechnol Prog, 14 (1), 63–74, (1998).
- J Il Rhee and T-H Kang, “On-line process monitoring and chemometric modeling with 2D fluorescence spectra obtained in recombinant E. coli fermentations,” Process Biochem, 42 (7), 1124–1134 (2007).
- D Boehl et al., “Chemometric modelling with two-dimensional fluorescence data for Claviceps purpurea bioprocess characterization,” J Biotechnol, 105 (1–2, 179–188 (2003).
- T Becker et al., “Future Aspects of Bioprocess Monitoring,” White Biotechnol, 105, 249–293 (2007).
- T Vankeirsbilck et al., “Applications of Raman spectroscopy in pharmaceutical analysis,” TrAC Trends Anal. Chem., 21 (12), 869–877 (2002).
- NR Abu-Absi et al., “Real time monitoring of multiple parameters in mammalian cell culture bioreactors using an in-line Raman spectroscopy probe,” Biotechnol Bioeng, 108 (5), 1215–1221 (2011).
- LG Tensmeyer and MA Heathman, “Analytical applications of Raman spectroscopy in the pharmaceutical field,” TrAC Trends Anal Chem, 8 (1), 19–24, (1989).
- J Whelan, S Craven, and B Glennon, “In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors,” Biotechnol Prog, 28 (5), 1355–1362 (2012).
- J Moretto et al., “Process Raman Spectroscopy for In-Line CHO Cell Culture Monitoring,” Am Pharm Rev, 14 (3), p. 18 (2011).
- F Lottspeich and JW Engels, Bioanalytik Spektrum Akademischer Verlag (2006).
- J Carvell and J Dowd, “On-line Measurements and Control of Viable Cell Density in Cell Culture Manufacturing Processes using Radio-frequency Impedance,” Cytotechnology, 50 (1–3), 35–48 (2006).
- SM Palmer and ER Kunji, “Online monitoring of biomass accumulation in recombinant yeast cultures,” Methods Mol Biol, 866, 165–179 (2012).
- RM Bill, “Recombinant Protein Production in Yeast: Methods and Protocols,” Methods Mol Biol (2012).
- PK Björnsen, “Automatic Determination of Bacterioplankton Biomass by Image Analysis,” Appl Environ Microbiol, 51 (6), 1199–1204, (1986).
- T Maskow et al., “On-line monitoring of lipid storage in yeasts using impedance spectroscopy,” J Biotechnol, 135 (1), 64–70 (2008).
- F Garcia-Ochoa and E Gomez, “Bioreactor scale-up and oxygen transfer rate in microbial processes: An overview,” Biotechnol Adv, 27 (2), 153–176 (2009).
- L Palomares and O Ramirez, “The effect of dissolved oxygen tension and the utility of oxygen uptake rate in insect cell culture,” Cytotechnology, 22 (1–3), 225–237, (1996).
- X Zou, et al., “Oxygen uptake rate optimization with nitrogen regulation for erythromycin production and scale-up from 50 L to 372 m3 scale,” Bioresour Technol, 100 (3), 1406–1412 (2009).
- P Geladi, “Chemometrics in spectroscopy. Part 1. Classical chemometrics,” Spectrochim Acta Part B 58, 58 (5), 767–782 (2003).
- AS Rathore, N Bhushan, and S Hadpe, “Chemometrics applications in biotech processes: a review,” Biotechnol Prog, 27 (2), 307–315 (2011).
- ND Lourenço et al., “Bioreactor monitoring with spectroscopy and chemometrics: a review,” Anal Bioanal Chem, 404 (4), 1211–1237 (2012).
- M Defernez and EK Kemsley, “The use and misuse of chemometrics for treating classification problems ,” Trends Anal Chem, 16 (4), 216–221, 1997.
- SC Potumarthi, “Chemometrics-Based Process Analytical Technology (PAT) Tools: Applications and Adaptation in Pharmaceutical and Biopharmaceutical Industries,” Appl Biochem Biotechnol, 169 (1), 66–76 (2013).
- J Alves-Rausch et al., “Real time in-line monitoring of large scale Bacillus fermentations with near-infrared spectroscopy,” J Biotechnol, 189, 120–128 (2014).
- W Waldraff, R King, and ED Gilles, “Optimal feeding strategies by adaptive mesh selection for fed-batch bioprocesses,” Bioprocess Eng, 17 (4), 221–227, 1997.
- M Navrátil, C Cimander, and C-F Mandenius, “On-line multisensor monitoring of yogurt and filmjölk fermentations on production scale,” J Agric. Food Chem., 52 (3), 415–420 (2004).
- AE Cervera, et al., “Application of Near-Infrared Spectroscopy for Monitoring and Control of Cell Culture and Fermentation,” Am Inst Chem Eng, 25 (6), 2009.
- Y Roggo et al., “A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies,” J Pharm Biomed Anal, 44 (3) SPEC. ISS., 683–700 (2007.
- KJ Clementschitsch Franz, F Pötschacher and K Bayer, “Sensor combination and chemometric modelling for improved process monitoring in recombinant E. coli fed-batch cultivations,” J Biotechnol, 120 (2), 183–196 (2005.
- M Clavaud et al., “Chemometrics and in-line near infrared spectroscopic monitoring of a biopharmaceutical Chinese hamster ovary cell culture: prediction of multiple cultivation variables,” Talanta, 111, 28–38 (2013.
- P Roychoudhury, LM Harvey, and B McNeil, “At-line monitoring of ammonium, glucose, methyl oleate and biomass in a complex antibiotic fermentation process using attenuated total reflectance-mid-infrared (ATR-MIR) spectroscopy,” Anal Chim Acta, 561 (1–2), 218–224 (2006).
- D Solle et al., “Chemometric modelling based on 2D-flourescence spectra without a calibration measurement,” Bioinformatics, 19 (2), 173–177 (2003).
- PK Ghosh and DS Jayas, “Use of spectroscopic data for automation in food processing industry,” Sens. Instrumen Food Qual, 3 (1), 3–11 (2009).
- C Koch et al., “Multi-analyte quantification in bioprocesses by Fourier-transform-infrared spectroscopy by partial least squares regression and multivariate curve resolution,” Anal Chim Acta 807, 103–110 (2014).
- M Milligan et al., “Semisynthetic model calibration for monitoring glucose in mammalian cell culture with in situ near infrared spectroscopy,” Biotechnol Bioeng, 111 (5), 896–903 (2014).
- R Isermann, “Advanced Methods of Process Computer Control for Industrial Processes,” Comput Ind, 2 (1), 59–72, (1981).
- M Navratil et al., “On-line multi-analyzer monitoring of biomass, glucose and acetate for growth rate control of a Vibrio cholerae fed-batch cultivation,” J Biotechnol, 115 (1), 67–79 (2005).
- S Gnoth et al., “Process Analytical Technology (PAT): Batch-to-batch reproducibility of fermentation processes by robust process operational design and control,” J Biotechnol, 132 (2), 180–186 (2007).
- JY Kunlun Hu, “Multivariate statistical process control based on multiway locality preserving projections,” J. Process Control, 18 (7–8), 797–807 (2008).
- AP Teixeira et al., “In situ 2D fluorometry and chemometric monitoring of mammalian cell cultures,” Biotechnol Bioeng, 102 (4), 1098–1106 (2009).
- A Glindkamp et al., “Sensors in disposable bioreactors status and trends,” Disposable Bioreactors, Advances in Biochemical Engineering / Biotechnology, 115, 145–169 (Springer Berlin Heidelberg, 2010).
Dörte Solle, Philipp Biechele, Christoph, Busse, and Thomas Scheper are all based at the Institute of Technical Chemistry, Leibniz University, Hannover, Germany.