Self-Cycling Fermentation: Bioprocessing for the -omics era

Department of Chemical Engineering and Materials Engineering

University of Alberta

Edmonton, Alberta, Canada

Zachary J. StormsAnd

Dominic Sauvageau

BioPacific Rim ConferenceDecember 9, 2014

Microbial Cells as Factories

Zack Storms

Introduction

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The -omics Era:Expanding our understanding of microbial cells

Zack Storms

Introduction

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Genomics:

Gene function

(DNA)

Transcriptomics:

Gene expression (RNA)

Metabolomics:

Biochemical Reactions

How can we tailor large-scale bioprocessing to complement the knowledge we are gaining through –omics?

Biomass Production of E. coliduring Self-Cycling Fermentation

Self-Cycling Fermentation

Zack Storms

Features of SCF

• Cyclical Semi-continuous Reactor

• Contents halved upon depletion of limiting nutrient– Replenished with fresh media

• Cycle period = cell doubling time

• Maintains exponential growth– Reproducible, stable

• Induces cell synchrony

Storms et al. (2012) Self-Cycling Operation Increases Productivity of Recombinant Protein in Escherichia coli. Biotechnol Bioeng. 109: 2262-2270

412/9/2014

Cell Synchrony

Zack Storms

Asynchronous cell growth Ideal synchronized cell growth

Cell division occurs throughout entire cycle

Cell division occurs at infinitely small time interval in cycle

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Features of SCF

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Growth of E. coli during a SCF Cycle

Zack Storms

• Cell division occurs in middle of cycle

• Synchrony Index ≈ 0.6-0.7

• Growth of culture behaves like individual cell

• Cell metabolism slows down– Doubling time ~150 minutes

Cell Density in synchronized cycle

Sauvageau D, Storms ZJ, Cooper DG (2010) Synchronized Populations of Escherichia coli Using Simplified Self-Cycling Fermentation. J Biotechnol. 149: 67-73.

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Note: Error bars represent the standard deviation

Features of SCF

How can we use –omics to take advantage of these properties in large scale fermentation?

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Studies on synchronized cells with Bacteriophages

Zack Storms

• How does cell division cycle effect cell productivity?

• Bacteriophage infections at different points in cell division cycle

• Parameters measured– Burst size: phages/cell

– Lysis time: phage incubation period

– Intracellular RNA and DNA

Storms ZJ, Brown T, Cooper DG, Sauvageau D, Leask RL (2014) Impact of the cell life-cycle on bacteriophage T4 infection FEMS Microbiol. Lett. 353: 63-68.

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Increasing productivity using SCF

Cell Growth and

DNA Replication

Cell Division

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Studies on synchronized cells with Bacteriophages

Zack Storms

• How does cell division cycle effect cell productivity?

• Burst size largest immediately preceding cell division

• Lysis time shortest immediately preceding cell division

Storms ZJ, Brown T, Cooper DG, Sauvageau D, Leask RL (2014) Impact of the cell life-cycle on bacteriophage T4 infection FEMS Microbiol. Lett. 353: 63-68.

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Increasing productivity using SCF

Results from cells infected by phage T4 at different points in their cell division cycle

Cell Division

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Studies on synchronized cells with Bacteriophages

Zack Storms

• How does cell division cycle effect cell productivity?

• Burst size largest immediately preceding cell division

• Lysis time shortest immediately preceding cell division

• Productivity highest immediately preceding cell division

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Increasing productivity using SCF

Phage productivity of cells infected by phage T4 at different points in their cell division cycle

Cell Division

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Storms ZJ, Brown T, Cooper DG, Sauvageau D, Leask RL (2014) Impact of the cell life-cycle on bacteriophage T4 infection FEMS Microbiol. Lett. 353: 63-68.

Studies on synchronized cells with Bacteriophages

Zack Storms

Storms ZJ, Brown T, Cooper DG, Sauvageau D, Leask RL (2014) Impact of the cell life-cycle on bacteriophage T4 infection FEMS Microbiol. Lett. 353: 63-68.

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Increasing productivity using SCF

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• Why does cell productivity change with cell age?

• Intracellular resources– RNA– Protein Synthesizing System– Transcriptomics

• Burst size positively correlated to total cellular RNA

• Lysis time negatively correlated to total cellular RNA

• Productivity positively correlated with cellular RNA

Zack Storms

• Synchronized host:– Maintains same level of

phage production

– Lower cell concentration

– The number of phages per cell (burst size) is larger for a synchronized culture

Sauvageau D and Cooper DG. (2010) Two-stage, self cycling process for the production of bacteriophages Microbial Cell Factories, 9:81

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Increasing productivity using SCF

Self-Cycling Fermentation

Bacteriophage Production

Implications for large scale production processes: bacteriophage production

Infected E. coli cultures

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Implications for large scale production processes:recombinant protein production

• β-galactosidase production using recombinant bacteriophage– Induce production at different time

points in SCF cycle

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Storms et al. (2012) Self-Cycling Operation Increases Productivity of Recombinant Protein in Escherichia coli. Biotechnol Bioeng. 109: 2262-2270

Note: Error bars represent the standard deviation

Increasing productivity using SCF

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0.0E+00

1.0E+04

2.0E+04

3.0E+04

4.0E+04

5.0E+04

6.0E+04

7.0E+04

0 50 100 150 200 250

Sp

ec

ific

In

teg

rate

d P

rod

uc

tivit

y

(U/L

/h/O

D)

Induction Time (minutes)(Cell Age)

Unsynchronized Culture

Implications for large scale production processes:recombinant protein production

• β-galactosidase production using recombinant bacteriophage– Induce production at different time

points in SCF cycle

• Productivity of synchronized cultures

– Maximum in productivity 50% larger than in non-synchronized culture

– Maximum occurs 45 minutes earlier

Zack Storms 13

Storms et al. (2012) Self-Cycling Operation Increases Productivity of Recombinant Protein in Escherichia coli. Biotechnol Bioeng. 109: 2262-2270

Note: Error bars represent the standard deviation

Increasing productivity using SCF

12/9/2014

0.0E+00

1.0E+04

2.0E+04

3.0E+04

4.0E+04

5.0E+04

6.0E+04

7.0E+04

0 50 100 150 200 250

Sp

ec

ific

In

teg

rate

d P

rod

uc

tivit

y

(U/L

/h/O

D)

Induction Time (minutes)(Cell Age)

Unsynchronized Culture

Synchronized Culture

Implications for large scale production processes:recombinant protein production

• β-galactosidase production using recombinant bacteriophage– Induce production at different time

points in SCF cycle

• Productivity of synchronized cultures

– Maximum in productivity 50% larger than in non-synchronized culture

– Maximum occurs 45 minutes earlier

– Two distinct maxima observed

Zack Storms 14

Storms et al. (2012) Self-Cycling Operation Increases Productivity of Recombinant Protein in Escherichia coli. Biotechnol Bioeng. 109: 2262-2270

Note: Error bars represent the standard deviation

Increasing productivity using SCF

12/9/2014

0.0E+00

1.0E+04

2.0E+04

3.0E+04

4.0E+04

5.0E+04

6.0E+04

7.0E+04

0 50 100 150 200 250

Sp

ec

ific

In

teg

rate

d P

rod

uc

tivit

y

(U/L

/h/O

D)

Induction Time (minutes)(Cell Age)

Synchronized Culture

Implications for large scale production processes:recombinant protein production

• β-galactosidase production using recombinant bacteriophage

• Productivity of synchronized cultures

– Maximum in productivity 50% larger than in non-synchronized culture

– Maximum occurs 45 minutes earlier

– Two distinct maxima observed• Before and after cell division

Zack Storms 15

Storms et al. (2012) Self-Cycling Operation Increases Productivity of Recombinant Protein in Escherichia coli. Biotechnol Bioeng. 109: 2262-2270

Note: Error bars represent the standard deviation

Increasing productivity using SCF

12/9/2014

1.5E+09

2.5E+09

3.5E+09

4.5E+09

5.5E+09

0.0E+00

1.0E+04

2.0E+04

3.0E+04

4.0E+04

5.0E+04

6.0E+04

7.0E+04

0 50 100 150

Ce

ll D

en

sit

y a

t T

ime

of

Ind

uc

tio

n (

ce

lls

/mL

)

Sp

ec

ific

In

teg

rate

d P

rod

uc

tivit

y (

U/L

/h/O

D)

Induction Time (minutes)(Cell Age)

Productivity

Cell Density

Cell

Division

Current Studies with Self-Cycling Fermentation:Engineering metabolic pathways for high-value products

Zack Storms 16

Combining metabolomics with SCF

Tyrosine: Key precursor for high-value secondary metabolites in plants (Morphine, Resveratrol, noscapine, etc.)

Genomics

+Transcriptomics

+Metabolomics

High-value products naturally produced in plants

Engineer yeast to produce the high-value products

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Current Studies with Self-Cycling Fermentation:Engineering metabolic pathways for high-value products

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Combining metabolomics with SCF

OverproduceShikimic Acid

Tyrosine Pathway Engineering: Knockout secondary pathways through gene deletions

OverproduceTyrosine

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How will SCF improve Tyrosine yield in this process?

• Current study by a masters’ student

• Optimize resource allocation

• Tighter control of metabolic fluxes

• Increased cell productivity

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Combining metabolomics with SCF

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Summary and Future Work with the SCF

• Cell productivity increases under synchronous growth

• Complete transcriptomic and metabolic analysis of synchronized culture

• High cell density synchronized cultures– Fed-batch SCF

– Constant volume continuous phasing

• Pulsing in nutrients periodically

• Induces synchrony, achieves high cell density

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Future Directions

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Acknowledgements

• SCF Pioneers

– Dr. David Cooper

– Dr. Richard Leask

• Yeast Engineering

– Dr. Vince Martin (Concordia University)

– Dr. Peter Facchini (University of Calgary)

– Dr. Jill Hagel (University of Calgary)

• Students

– Roman Agustin

– Sauvageau Research Group

Zack Storms

Acknowledgement

2012/9/2014

Synchrony Index

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Extra Slides

If N0 is the number of cells at the beginning of the time interval and Nt is the number of cells at the end of the interval, Nt,e is the number of cells produced by typical batch culture exponential growth, then F, the fraction of cells dividing in excess of those expected by exponential batch growth is given as (g is the generation time)

gtt

tg

t

t

t

t

et

ett

N

NF

N

eNN

N

eNNF

g

eNN

N

NNF

/

0

0

))2ln(

(

0

0

0

0,

0

,

2

)2ln(

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𝑈

𝑚𝑙= [𝑂𝐷420−(1.75 × 𝑂𝐷550)] ×

1

0.0045×1 𝑛𝑎𝑛𝑜 𝑚𝑜𝑙𝑒 𝑜 − 𝑛𝑖𝑡𝑟𝑜𝑝ℎ𝑒𝑛𝑜𝑙

𝑚𝑙×1

𝑡

Β-galactosidase Unit Definition

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Extra Slides

1 Unit of β-galactosidase is defined as the amount of enzyme which produces 1 nano-mole o-nitrophenol/min at 28°C, pH 7.0. Under the conditions of the Assay, 1 nano-mole/ml o-nitrophenol has an optical density (420 nm) of 0.0045 using a 10-mm light path. Knowing the sample volume of the culture, 𝑣 in ml, and the reaction time, 𝑡 in minutes, one can calculate the units after measuring the absorbance at 420 nm.

• β-galactosidase + ONPG galactose + o-nitrophenol

• ONPG: ortho-Nitrophenyl-β-galactoside

• o-nitrophenol is yellow, (absorbance at 420 nm)

• Concentration of o-nitrophenol proportional β-galactosidase concentration and reaction time

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Induction Dynamics – β-galactosidase

• Induction Time: – Induce lytic state by

raising temperature

• Enzyme activity increases until cell lysis occurs

Zack Storms

Productivity =

2

1

)(t

t

ODdtV

Activity

Storms et al. Self-Cycling Operation Increases Productivity of Recombinant Protein in Escherichia coli. Biotechnol Bioeng. 109: 2262-2270

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Extra Slides

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