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Soft sensor based on Raman spectroscopy for the in-line monitoring of metabolites and polymer quality in the biomanufacturing of polyhydroxyalkanoates

Studia Prawnoustrojowe 2023 9 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
João Medeiros Garcia Alcântara, Francesco Iannacci, Massimo Morbidelli, Mattia Sponchioni

Summary

Researchers developed an in-line Raman spectroscopy sensor for real-time monitoring of polyhydroxyalkanoate (PHA) biomanufacturing, achieving simultaneous measurement of cell growth, nutrient concentrations, intracellular polymer accumulation, and—for the first time—molecular weight of the bioplastic being produced, all without requiring manual sampling.

Polyhydroxyalkanoates (PHA) are among the most promising bio-based alternatives to conventional petroleum-based plastics. These biodegradable polyesters can in fact be produced by fermentation from bacteria like Cupriavidus necator, thus reducing the environmental footprint of the manufacturing process. However, ensuring consistent product quality attributes is a major challenge of biomanufacturing. To address this issue, the implementation of real-time monitoring tools is essential to increase process understanding, enable a prompt response to possible process deviations and realize on-line process optimization. In this work, a soft sensor based on in situ Raman spectroscopy was developed and applied to the in-line monitoring of PHA biomanufacturing. This strategy allows the collection of quantitative information directly from the culture broth, without the need for sampling, and at high frequency. In fact, through an optimized multivariate data analysis pipeline, this soft sensor allows monitoring cell dry weight, as well as carbon and nitrogen source concentrations with root mean squared errors (RMSE) equal to 3.71, 7 and 0.03 g/L, respectively. In addition, this tool allows the in-line monitoring of intracellular PHA accumulation, with an RMSE of 14 gPHA/gCells. For the first time, also the number and weight average molecular weights of the polymer produced could be monitored, with RMSE of 8.7E4 and 11.6E4 g/mol, respectively. Overall, this work demonstrates the potential of Raman spectroscopy in the in-line monitoring of biotechnology processes, leading to the simultaneous measurement of several process variables in real time without the need of sampling and labor-intensive sample preparations.

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