Fermentation Analytical Technology (FAT): Monitoring industrial E. coli fermentations using absolute quantitative 1H NMR spectroscopy
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Background: To perform fast, reproducible, and absolute quantitative measurements in an automated manner has become of paramount importance when monitoring industrial processes, including fermentations. Due to its numerous advantages – including its inherent quantitative nature – Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy provides an ideal tool for the time-resolved monitoring of fermentations. However, analytical conditions, including non-automated sample preparation and long relaxation times (T1) of some metabolites, can significantly lengthen the experimental time and make implementation in an industrial set up unfeasible. Results: We present a high throughput method based on Standard Operating Procedures (SOPs) and 1H NMR, which lays the foundation for what we call Fermentation Analytical Technology (FAT). Our method was developed for the accurate absolute quantification of metabolites produced during Escherichia coli industrial fermentations. The method includes: (1) a stopped flow system for non-invasive sample collection followed by sample quenching, (2) automatic robot-assisted sample preparation, (3) fast 1H NMR measurements, (4) metabolites quantification using multivariate curve resolution (MCR), and (5) metabolites absolute quantitation using a novel correction factor (k) to compensate for the short recycle delay (D1) employed in the 1H NMR measurements. The quantification performance was tested using two sample types: buffer solutions of chemical standards and real fermentation samples. Five metabolites – glucose, acetate, alanine, phenylalanine and betaine – were quantified. Absolute quantitation ranged between 0.64 and 3.40 mM in pure buffer, and 0.71–7.76 mM in real samples. Significance: The proposed method is generic and can be straight forward implemented to other types of fermentations, such as lactic acid, ethanol and acetic acid fermentations. It provides a high throughput automated solution for monitoring fermentation processes and for quality control through absolute quantification of key metabolites in fermentation broth. It can be easily implemented in an at-line industrial setting, facilitating the optimization of the manufacturing process towards higher yields and more efficient and sustainable use of resources.
Originalsprog | Engelsk |
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Artikelnummer | 342722 |
Tidsskrift | Analytica Chimica Acta |
Vol/bind | 1311 |
Antal sider | 10 |
ISSN | 0003-2670 |
DOI | |
Status | Udgivet - 2024 |
Bibliografisk note
Funding Information:
The accuracy and precision of the quantitative method as well as limit of detection and quantification (LOD and LOQ, respectively) were evaluated for selected analytes by calibration curve experiments and spiking experiments. In the method validation experiment, phosphate buffer (PB) and phosphate buffer + fermentation broth (PB\u2013S) were spiked with different volumes of stock solutions A and B at increasing concentration levels (Fig. 1). The concentration range was designed to match the expected range in the real fermentation samples. Annotated 1H NMR spectra of stock solutions A and B in PB are shown in Fig. S1 (Supplementary data). For each compound, the spin-lattice relaxation time of the individual resonances was estimated with T1 inversion recovery experiments with solvent suppression (t1irpr). To obtain an accurate estimation of T1 values, five samples from each method validation set (PB + stock A, PB + stock B and PB-S + stock A and PB-S + stock B) ranging from low to high concentration level were analysed and the average T1 value estimated and used to calculate the signal-specific correction factor k. The estimated average T1 values and standard deviations are shown in Table 1 together with quantification performance estimators of the five selected analytes in PB and PB-S.Jakob Rune H\u00F8gh Nielsen and his team at Novo Nordisk A/S are acknowledged for sponsoring the PhD project to S\u00F8ren Balling Engelsen and University of Copenhagen with the aim of investigating yield of fermentation reactions in bioreactors with spectroscopy. Data was generated though accessing research infrastructure at the University of Copenhagen, including FOODHAY (Food and Health Open Innovation Laboratory, Danish Roadmap for Research Infrastructure).
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© 2024 The Authors
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