Sensor combination and chemometric modelling for improved process monitoring in recombinant E. coli fed-batch cultivations.

The key objective for the optimisation of recombinant protein production in bacteria is to optimize the exploitation of the host cell's synthesis potential. Recent studies show that the novel concept of transcription rate control allows the tuning of recombinant gene expression in relation to the metabolic capacity of the host cell. To adjust the inducer-biomass ratio to a tolerable level, real-time knowledge about key process variables is paramount. Since there are no reliable online-sensors for key variables such as biomass or recombinant product, it is necessary to relate available online signals to process variables by mathematical models. To improve chemometric modelling of process variables, dielectric spectroscopy and a multi-wavelength online fluorescence sensor for two-dimensional fluorescence spectroscopy were applied in a series of recombinant Escherichia coli fed-batch cultivations applying two different process operation states. Dielectric spectroscopy signals were closely correlated to biomass, while two-dimensional fluorescence spectroscopy allowed the monitoring of fluorescent biogenic components. Chemometric modelling of key process variables with two different modelling techniques showed that this sensor combination greatly improved the estimation (i.e. reduce error magnitude) of process variables in recombinant E. coli cultivations, thereby enhancing process monitoring capabilities.

[1]  J. Swartz,et al.  Advances in Escherichia coli production of therapeutic proteins. , 2001, Current opinion in biotechnology.

[2]  P. Servais,et al.  Using light scatter signal to estimate bacterial biovolume by flow cytometry. , 2001, Cytometry.

[3]  Lisbeth Olsson,et al.  On-line cell mass monitoring of Saccharomyces cerevisiae cultivations by multi-wavelength fluorescence. , 2004, Journal of biotechnology.

[4]  P. Schleyer Encyclopedia of computational chemistry , 1998 .

[5]  S. Arnold,et al.  Use of at‐line and in‐situ near‐infrared spectroscopy to monitor biomass in an industrial fed‐batch Escherichia coli process , 2002, Biotechnology and bioengineering.

[6]  G Kastberger,et al.  Visualization of multiple influences on ocellar flight control in giant honeybees with the data-mining tool Viscovery SOMine , 2000, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[7]  Douglas B. Kell,et al.  GMP — good modelling practice: an essential component of good manufacturing practice , 1995 .

[8]  B Sonnleitner,et al.  Instrumentation of biotechnological processes. , 2000, Advances in biochemical engineering/biotechnology.

[9]  Dmitry Kirsanov,et al.  Fermentation monitoring using multisensor systems: feasibility study of the electronic tongue , 2004, Analytical and bioanalytical chemistry.

[10]  Carl-Fredrik Mandenius,et al.  Recent developments in the monitoring, modeling and control of biological production systems , 2004, Bioprocess and biosystems engineering.

[11]  T. Bachinger,et al.  Searching for process information in the aroma of cell cultures. , 2000, Trends in biotechnology.

[12]  R Fehrenbach,et al.  On-line biomass monitoring by capacitance measurement. , 1992, Journal of biotechnology.

[13]  Claire Komives,et al.  Bioreactor state estimation and control. , 2003, Current opinion in biotechnology.

[14]  Beata Walczak,et al.  Comparison of Multivariate Calibration Techniques Applied to Experimental NIR Data Sets , 2000 .

[15]  C. Hewitt,et al.  Studies related to the scale-up of high-cell-density E. coli fed-batch fermentations using multiparameter flow cytometry: effect of a changing microenvironment with respect to glucose and dissolved oxygen concentration. , 2000, Biotechnology and bioengineering.

[16]  Felipe Miguel Aparicio Acosta,et al.  Radial basis function and related models: An overview , 1995, Signal Process..

[17]  Gary A. Montague,et al.  Application of radial basis function and feedforward artificial neural networks to the Escherichia coli fermentation process , 1998, Neurocomputing.

[18]  E. Skibsted,et al.  On-line bioprocess monitoring with a multi-wavelength fluorescence sensor using multivariate calibration. , 2001, Journal of biotechnology.

[19]  D B Kell,et al.  On-Line, Real-Time Measurements of Cellular Biomass using Dielectric Spectroscopy , 2000, Biotechnology & genetic engineering reviews.

[20]  J. Nielsen,et al.  On-line and in situ monitoring of biomass in submerged cultivations , 1997 .

[21]  Gerald Striedner,et al.  Evaluation of the GFP signal and its aptitude for novel on-line monitoring strategies of recombinant fermentation processes. , 2004, Journal of biotechnology.

[22]  J. Thibault,et al.  Electrical conductivity as a tool for analysing fermentation processes for production of cheese starters , 2000 .

[23]  Gerald Striedner,et al.  Tuning the Transcription Rate of Recombinant Protein in Strong Escherichiacoli Expression Systems through Repressor Titration , 2003, Biotechnology progress.

[24]  Hector Budman,et al.  Evaluation of spectrofluorometry as a tool for estimation in fed-batch fermentations. , 2003, Biotechnology and bioengineering.

[25]  A. Cheruy,et al.  MODELLING IS AN INDISMISSIBLE TOOL TO UNDERSTAND AND CONTROL BIOPROCESSES , 1997 .

[26]  Thomas Scheper,et al.  Two‐Dimensional Fluorescence Spectroscopy: A New Tool for On‐Line Bioprocess Monitoring , 1998, Biotechnology progress.

[27]  K. Schügerl,et al.  Progress in monitoring, modeling and control of bioprocesses during the last 20 years. , 2001, Journal of biotechnology.

[28]  Diego Matteuzzi,et al.  Assessment of In‐Line Near‐Infrared Spectroscopy for Continuous Monitoring of Fermentation Processes , 2003, Biotechnology progress.

[29]  Carl-Fredrik Mandenius,et al.  Sensor fusion for on-line monitoring of yoghurt fermentation. , 2002, Journal of biotechnology.

[30]  F. Studier,et al.  Use of bacteriophage T7 RNA polymerase to direct selective high-level expression of cloned genes. , 1986, Journal of molecular biology.

[31]  F. Studier,et al.  Use of T7 RNA polymerase to direct expression of cloned genes. , 1990, Methods in enzymology.

[32]  P. Chomczyński,et al.  Estimation of cellular DNA content in cell lysates suitable for RNA isolation. , 1990, Analytical biochemistry.

[33]  Thomas Scheper,et al.  Optical sensor systems for bioprocess monitoring , 1999 .

[34]  Dörte Solle,et al.  Chemometric modelling with two-dimensional fluorescence data for Claviceps purpurea bioprocess characterization. , 2003, Journal of biotechnology.

[35]  Wang,et al.  On-line monitoring and controlling system for fermentation processes. , 2001, Biochemical engineering journal.

[36]  K. von Meyenburg,et al.  Automatic analysis of gas exchange in microbial systems , 1968 .

[37]  Stephens,et al.  Assessment of bacterial viability status by flow cytometry and single cell sorting , 1998, Journal of applied microbiology.