optimization of fermentation parameters in phage production using

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Sung-Hye Grieco, Ph.D.

ManagerFermentation FacilityCentre for Blood ResearchUniversity of British ColumbiaVancouver, Canada

Optimization of fermentation parameters in phage productionusing response surface methodology

Optimization of fermentation parameters in phage productionusing response surface methodology

2.Design of Experiments for Bioprocesses

Topics

3.Case Study: Production of filamentous phage from E.coli

1. Introduction about our fermentation facility

4.Performance and Analysis of DOE

5.What we’ve learned about our process

1. Introduction about our fermentation facility

• The Centre for Blood Research at the University of British Columbia

� Located at Life Sciences Institute� Opened in 2005, Multidisciplinary biomedical research institute � Over 40 professors from multiple faculties and departments� 7 core facilities with state-of-the-art technologies� Pursue basic science, biotechnology, engineering, and clinical

research to investigative methods to address blood or health-related science questions

• Fermentation Facility (since 2006)

� Successfully conducted over 500 fermentations� Fermentation equipment (1 liter to 50 liters scales)� Clients (Academic users, Industry users)� Fermentation: Production of targets (peptides, proteins) from

diverse organisms. 10 genus tested – Streptomyces, Rhodobacter,

Escherichia, Salmonella, Pseudomonas, Bacillus, Kluyveromyces, Pichia, Saccharomyces, Spodoptera

1. Introduction about our fermentation facility

1. Introduction about our fermentation facility

• Special Services and Training Courses� Pichia pastoris Fermentation

�Genetic and phenotypic understanding of Pichia system�Compare media, feeding strategies, MeOH induction.

� Design of Experiment (DOE) Bioprocess Optimization�Introduces the concept of DOE for bioprocess optimization�RSM, CCD (3 factors, 20 fermentations)

� High Cell Density Fermentation (high titer fermentation)�Fed-batch fermentation for exponential growth to maximize

biomass and target production

Design of Experiments in Bioprocesses

2.Design of Experiment for Bioprocesses

• Goal of the optimization of bioprocesses such as fermentation:� Maximize target production with consistency

• How:� Maintain optimal and homogenous reaction conditions� Reduce microbial stress exposure� Enhance metabolic accuracy

• Fermentation Parameters:� Temperature� pH� Dissolved Oxygen (DO) level in the media

• Temperature:

� According to their temperature optima, organisms can be classified in three groups:

�Psychrophiles (Topt < 20C)�Mesophiles (Topt = between 20C to 50C)�Thermophiles (Topt = > 50C)

� Growth rate is maximum at the Topt� The Topt for growth and production maybe different

� Temperature affects growth rate, target production as well as rate-limiting steps in fermentation process

2. Design of Experiments for Bioprocesses

• pH:

� Affects activity of enzymes and the microbial growth rate� The pHopt for growth maybe different from that for production� Optimal pH:

� Bacteria (3 to 8)� Yeast (3 to 6)� Molds (3 to 7)� Plant cells (5 to 6)� Animal cells (6.5 to 7.5)

� pH change in the cells:� Ammonium (NH4

+) releases H+, decreases pH� Nitrate (NO3

-) consumes H+, increases pH� Production of organic acids, amino acids, CO2, bases

2. Design of Experiments for Bioprocesses

• DO (dissolved oxygen level in the media):

� Important substrate in aerobic fermentations� limiting substrate if:

[rate of oxygen consumption] > [the rate of oxygen supply]� Critical oxygen concentration:

the oxygen concentration where the specific growth rate become independent of DO (at this oxygen concentration, there is a sufficient and unlimiting amount oxygen available for cells to grow at it’s maximum rate)

� Critical oxygen concentration� Bacteria and yeast (5% to 10%)� Mold (10% to 50%)

� Saturated DO (100%) is often referred as the concentration of DO in water at 25C, 1 atm pressure �about 7 ppm

2. Design of Experiments for Bioprocesses

2. Design of Experiments for Bioprocesses

• Fermentation parameters are controlled by bio-controllers

Temperature (+) Heating (1) (-) Cooling (4)

Output signals

(+) Base (2)(-) Acid (3)pH

Bio-controller

dissolved oxygen(DO)

(+)O2 (5)(+)rpm (10)(-) N2 (6)

5 10 SP 65 SP 6

5 10 SP5 SP10 SP

2 SP 3

1 SP 4

Input signals

Case Study: Production of filamentous phage from E.coli

3.Production of filamentous phage from E.coli

TRENDS in Microbiology Vol.14 No.3 March 2006

Filamentous bacteriophage and its host cells

Phage display techniques for mining applications

3.Production of filamentous phage from E.coli

Phage-display library in P3 peptide (109)

ZnS

CuFeS2(chalcopyrite)

Panning allows specific bindingMinor cacid protein III (P3)

Target: Bacteriophage (non-lytic)Host: E.coli

� Typical culture for bacteriophage production(Flask culture at 37C after infection process)

� Typical yield: 1010 Transducing Units (TU/ml of media)

� Original fermentation � Media selection: NZY, SB, LB� Basic fermentation parameters (37C, pH 7.4, 100% DO) � Bacteriophage production increased by approximately 10 timesGrieco et al., Maximizing filamentous phage yield during computer-controlled fermentation (2009) Bioprocess Biosystem Engineering 32(6):773-779

� Conventional culture temperature for phage production is 37 C� Phage infection is done at permissive temperature (42 – 44 C)� No systematic study about fermentation condition for the production of phage from

E.coli host cells

�Further analysis of fermentation condition using DOE methodology

Host

bacteriphage

3.Production of filamentous phage from E.coli

Performance and Analysis of DOE

Factor A (Temperature) (20C – 37C)

Factor B (DO)(40% – 100%)

Factor C (pH)(4.0 – 9.0)

Region of Interest

Factorial points (8)

Axial points (6)

Center point (1)

- (-1.682) + (1.682)

14.2 42.8

20.0 120.0

2.3 10.7

Mean (0)

28.5

70.0

6.5

Total: 20 experiments

+ 5 repeats

Factor

A (Temperature)

B (DO)

C (pH)

Low (-1) High (+1)

20.0 37.0

40.0 100.0

4.0 9.0

Region of Operability

Central composite design

4.Performance and Analysis of DOE

Collect supernatant (bacteriophage)

Infect E.coli

Quantify bacteriophage

Prepare bacteriophage-infected E.coli

-80C

10-ml X 21

X 21 plates

X 7 days = 21 fermentations

Off-line measurement

Starter culture preparation

Fermentation

DOE Analysis

4.Performance and Analysis of DOE

InfectedHost (Tetr)

Produced phage(Tetr)

phage(Tetr)

Non-infectedHost

+

Purifiedphage(Tetr)

Tetracycline containing solid media (Agar)

Fermenter

Infected Host (Tetr)

Off-line measurement

Cell pellet(Tetr)

4.Performance and Analysis of DOE

TU/ml

� The perturbation plot indicated that factor B (DO level) showed insensitivity to the experiment and was insignificant to the process model.

A: TempB: DOC: pH

Model equation:Ln(Bacteriophage) = 1.98A +12.39C -0.04A2 - 0.90C2 -44.10

� The process model equation indicated that not only was factor B insignificant and eliminated, it also eliminated the two-factor parameter, AC, due to it’s insignificance to the model as well. This indicated that the significant factors, A and C, influenced the outcome independently and that there was no synergistic effect between the two.

Result Analysis with Design-Expert® software by Stat-Ease Inc.

4.Performance and Analysis of DOE

� The 3D map shows our theoretical optimal condition expects to produce 7 timeshigher than the production of the current condition, which had already improved onthe original flask culture results by 10 times. This was confirmed after executingvalidation runs.

� (Grieco et al., J. Ind. Microbiol. Biotechnol. (2012) DOI 10.1007/s10295-012-1148-3)

4.Performance and Analysis of DOEResult Analysis with Design-Expert® software by Stat-Ease Inc.

What we’ve learned about our process

5.What we’ve learned about our process

• Biological Parameters

� Temperature: significant�Suggested optimal condition was 28.1C�37C produces seven times less�Recent study shows 28C displayed maximum peptides

suggesting that Topt for bacterial growth and Topt for the protein maturation for phage particle assembly are different.

� pH: significant�Suggested optimal condition was at 6.9�Small change of pH shows significant changes (0.5, 20%)�There is no reference supporting this pH to be the optimal

5.What we’ve learned about our process

• Biological Parameters

� DO: insignificant, really?�Calibration: DO probe is calibrated at two points, 0% with

pure nitrogen gas and 100% with air.�Even though it is determined to be insignificant by DOE,

one value within the range of interest has to be chosen.�A value in the mid-region of the range could be considered

“robust” because variation from the mid-point would not have a detrimental effect on the response.

5.What we’ve learned about our process

• Take home messages

� Understand the differences in the experimental meaning between the pilot scale (conventional scale) vs. DOE scale if they are different – Reviewers’ comments(1 X 1011 TU/mL vs 4.95 X 1010 TU/mL)

� Interpret the DOE data with your background knowledge

� Don’t assume that conventional conditions are the best

� Do diligent work to screen factors before bring to DOE

Thank You

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