Integrated Reactor Feeding System
Amino Acid Feedback Control and Productivity Gains - E.Coli


Controlled feeding of select amino acids,controlled by the ARS-M,
increased production of protein by more than 30%.

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Summary
A study was conducted to demonstrate the efficiency and viability of a fully automatic reactor feeding system to regulate essential amino acid concentrations in a microbial fermentation.   These studies were conducted using an online amino acid HPLC system integrated with an ARS-M Reactor Sampling System and a programmable Reactor Control System controlling amino acid feedstock pumps.  Baseline studies were conducted to determine which amino acids were consumed by the fermentation process and the rates of consumption.  Subsequent studies were conducted in which those amino acids were fed to maintain a desired concentration for the entire course of the fermentation. Green Fluorescent Protein (“GFP”) was used as a marker for specific productivity measurement.  Initial results indicate that productivity is positively correlated to maintaining appropriate levels of essential amino acids.  Future studies are in progress to optimize the media and feedstocks.

Figure 1

Experimental Method:

Fermentations were performed using stock inoculation cultures and stock media. The cycle ran for 24 hours. Samples were extracted periodically by the ARS-M through the course of the cycle and submitted automatically to the HPLC for amino acid analysis by the standard method. Data was reduced to typical report form by the HPLC operating system software. Selected chromatogram data sets were identified by the user in a pre-run setup process and then extracted automatically from the chromatogram report on each subsequent chromatogram assay by the Groton HPLC Data Wizard for retransmission to the Reactor Control System. The Reactor Control System pump control algorithms reduced each selected chromatogram data point (concentration) to a Process Value, compared that value to a desired Set Point Value, and then calculated a correct feed pump duty cycle for the next forward interval. This process iterated to the end of the fermentation cycle.

Results
Amino Acid Baseline - BL21 E.Coli
A baseline experiment was performed using stock culture and stock media.  No feeding was performed in order to map consumption rates of amino acids to determine potential single essential amino acid feedstocks.  Raw chromatograms from AAA assay are shown (see Figure 2) at selected times in the fermentation cycle. Note the consumption of serine (see Figure 3).  Other amino acids also exhibited consumption or expression during the fermentation.  Serine was selected for the feeding evaluation (see Figure 4).

Figure 2 - Raw Amino Acid Chromatograms - No Feedback Control

Figure 4 - No Feedback Control; Amino Acid Profile, rBL21; All amino acids above limit of detection; Casamino acid media; Derived from chromatogram data.

Serine Feedback Control - Bioreactor Profile with OPC, rBL21
Feedback control was enabled for the reactor via the Groton ARS-M Agilent HPLC with OPC Interface Kit connected to the Reactor Control System.  This kit acquires automatically selected chromatogram data from each chromatogram, stores said data in an OPC server, and retransmits said data on request of any OPC enabled client – in this case the Reactor Control System that was enabled to programmatically control duty cycles for up to 6 feed pumps per reactor.  The selected amino acid for assay and feeding for this demonstration was serine (see Figure 5).

In this experiment manual samples were collected periodically (dark blue trace in Figure 5) by extraction through a diptube using a syringe and standard technique for analysis by HPLC using the same HPLC and method used automatically by the ARS-M.  These samples were filtered to the same criteria used by the ARS-M automatic sampling system – cell free filtered to 0.22 µ – and stored at 4 °C until assayed.  The automatically collected and processed serine data is shown in light green (in Figure 5). Each horizontal segment of the trace is the Process Value acquired by HPLC AAA assay as transmitted to the Reactor Control System.  The system was programmed to acquire samples and perform the AAA assay periodically through the course of the entire fermentation cycle.  Note the correlation between the automatic and the manual (“standard”) assay values (see Figure 5).

Also note the red trace at the bottom of the screen.  This is the duty cycle trace for the serine feedpump.  The feed pump was set to a constant flow rate.  The Reactor Control System proportionally turned the pump on and off to achieve an overall serine feed in units of mg/min of “on” time. Note that the duty cycle is inversely proportional to OPC serine Process Value – long when concentration is low, short when concentration is high.

See Figure 6 for the time course of serine concentration through the entire process cycle.

rGFP-BL21 Serine Feedback Productivity
An initial study was performed to demonstrate structured amino acid feeding as described above and its correlation to productivity of the fermentation process.  The selected e.coli strain expresses Green Fluorescent Protein (“GFP”) that was used as a marker for specific productivity in this study.

Figure 7

In this study, a control experiment was performed as described above to measure Green Fluorescent Protein titer under control conditions (no feeding) – shown above in light blue.  In the controlled feeding study operating as described the titer for product, Green Fluorescent Protein shown as dark blue, is shown to yield 33% more product with continual feeding of one amino acid – serine – but otherwise identical culture conditions.

Conclusion
Strategic feeding of bioreactors under controlled conditions using real time feedback control and intelligent algorithms is shown to yield improved yields of desired products.  The yield of Green Fluorescent Protein, the marker protein tracked in this current study, increased by 33% through intelligent feeding of one amino acid, serine, shown to be essential for this e.coli strain.

Acknowledgements
Groton Biosystems acknowledges the MIT Bioprocess Engineering Laboratory, Agilent, and DASGIP for their contributions to this study.