In situ NIR spectroscopy monitoring of plasmid production processes: effect of producing strain, medium composition and the cultivation strategy

• Published in: Journal of chemical technology and biotechnology (1986) 2015-02, Vol.90 (2), p.255-261
• Main Authors: Lopes, Marta B., Gonçalves, Geisa A. L., Felício-Silva, Daniel, Prather, Kristala L. J., Monteiro, Gabriel A., Prazeres, Duarte M. F., Calado, Cecília R. C.
• Format: Article
• Language: English
• Subjects: Cultivation; Culture; Escherichia coli; in situ monitoring; Mathematical models; Media; Monitoring; near infrared spectroscopy; plasmid bioprocess; Real time; Spectroscopy; Strain; Strategy
• ISSN: 0268-2575; 1097-4660
• DOI: 10.1002/jctb.4431

BACKGROUND While the pharmaceutical industry keeps an eye on plasmid DNA production for new generation gene therapies, real‐time monitoring techniques for plasmid bioproduction are as yet unavailable. This work shows the possibility of in situ monitoring of plasmid production in Escherichia coli cultures using a near infrared (NIR) fiber optic probe. RESULTS Partial least squares (PLS) regression models based on the NIR spectra were developed for predicting bioprocess critical variables such as the concentrations of biomass, plasmid, carbon sources (glucose and glycerol) and acetate. In order to achieve robust models able to predict the performance of plasmid production processes, independently of the composition of the cultivation medium, cultivation strategy (batch versus fed‐batch) and E. coli strain used, three strategies were adopted, using: (i) E. coli DH5α cultures conducted under different media compositions and culture strategies (batch and fed‐batch); (ii) engineered E. coli strains, MG1655ΔendAΔrecAΔpgi and MG1655ΔendAΔrecA, grown on the same medium and culture strategy; (iii) diverse E. coli strains, over batch and fed‐batch cultivations and using different media compositions. PLS models showed high accuracy for predicting all variables in the three groups of cultures. CONCLUSION NIR spectroscopy combined with PLS modeling provides a fast, inexpensive and contamination‐free technique to accurately monitoring plasmid bioprocesses in real time, independently of the medium composition, cultivation strategy and the E. coli strain used. © 2014 Society of Chemical Industry