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

Doppler, Philipp; Veiter, Lukas; Spadiut, Oliver; Herwig, Christoph; Rajamanickam, Vignesh

doi:10.3390/pr8040461

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

^1,†

^1,2,†,

^1,2,3

and

Vignesh Rajamanickam

^1,*

Institute of Chemical, Envirionmental and Bioscience Engineering, Research Area Biochemical Engineering, TU Wien, Gumpendorfer Strasse 1a, 1060 Vienna, Austria

Competence Center CHASE GmbH, Altenbergerstraße 69, 4040 Linz, Austria

Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, TU Wien, Gumpendorfer Straße 1a, 1060 Vienna, Austria

Author to whom correspondence should be addressed.

^†

Philipp Doppler & Lukas Veiter contributed equally to this work.

Processes 2020, 8(4), 461; https://doi.org/10.3390/pr8040461

Received: 27 March 2020 / Revised: 7 April 2020 / Accepted: 10 April 2020 / Published: 14 April 2020

(This article belongs to the Special Issue Measurement Technologies for up- and Downstream Bioprocessing)

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Abstract

Monitoring process variables in bioprocesses with complex expression systems, such as filamentous fungi, requires a vast number of offline methods or sophisticated inline sensors. In this respect, cell viability is a crucial process variable determining the overall process performance. Thus, fast and precise tools for identification of key process deviations or transitions are needed. However, such reliable monitoring tools are still scarce to date or require sophisticated equipment. In this study, we used the commonly available size exclusion chromatography (SEC) HPLC technique to capture impurity release information in Penicillium chrysogenum bioprocesses. We exploited the impurity release information contained in UV chromatograms as fingerprints for development of principal component analysis (PCA) models to descriptively analyze the process trends. Prediction models using well established approaches, such as partial least squares (PLS), orthogonal PLS (OPLS) and principal component regression (PCR), were made to predict the viability with model accuracies of 90% or higher. Furthermore, we demonstrated the platform applicability of our method by monitoring viability in a Trichoderma reesei process for cellulase production. We are convinced that this method will not only facilitate monitoring viability of complex bioprocesses but could also be used for enhanced process control with hybrid models in the future. View Full-Text

Keywords: cell viability; prediction; chromatogram fingerprinting; filamentous fungi; Penicillium chrysogenum; Trichoderma reesei Rut-C30; HPLC-SEC

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Doppler, P.; Veiter, L.; Spadiut, O.; Herwig, C.; Rajamanickam, V. A Chemometric Tool to Monitor and Predict Cell Viability in Filamentous Fungi Bioprocesses Using UV Chromatogram Fingerprints. Processes 2020, 8, 461. https://doi.org/10.3390/pr8040461

AMA Style

Doppler P, Veiter L, Spadiut O, Herwig C, Rajamanickam V. A Chemometric Tool to Monitor and Predict Cell Viability in Filamentous Fungi Bioprocesses Using UV Chromatogram Fingerprints. Processes. 2020; 8(4):461. https://doi.org/10.3390/pr8040461

Chicago/Turabian Style

Doppler, Philipp, Lukas Veiter, Oliver Spadiut, Christoph Herwig, and Vignesh Rajamanickam. 2020. "A Chemometric Tool to Monitor and Predict Cell Viability in Filamentous Fungi Bioprocesses Using UV Chromatogram Fingerprints" Processes 8, no. 4: 461. https://doi.org/10.3390/pr8040461

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

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