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In situ NIR spectroscopy monitoring of plasmid production processes: effect of producing strain, medium composition and the cultivation strategy
Author(s) -
Lopes Marta B.,
Gonçalves Geisa A. L.,
FelícioSilva Daniel,
Prather Kristala L. J.,
Monteiro Gabriel A.,
Prazeres Duarte M. F.,
Calado Cecília R. C.
Publication year - 2015
Publication title -
journal of chemical technology and biotechnology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.64
H-Index - 117
eISSN - 1097-4660
pISSN - 0268-2575
DOI - 10.1002/jctb.4431
Subject(s) - bioprocess , plasmid , escherichia coli , partial least squares regression , strain (injury) , composition (language) , food science , in situ , biology , bioproduction , microbiology and biotechnology , chemistry , biological system , biochemistry , dna , gene , computer science , paleontology , linguistics , philosophy , organic chemistry , anatomy , machine learning
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, MG1655 ΔendA ΔrecAΔpgi and MG1655 ΔendAΔrecA , 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