Bacterial processes are thus under2013.igem.org › files › presentation ›...
Transcript of Bacterial processes are thus under2013.igem.org › files › presentation ›...
Bacterial processes are thus underthe constant threat of
BIOREACTORS
PRODUCTS
Bioreactors are being used more and more to source everyday products
For example, 10% of dairyfermentation collapsedue to phage infection
dxdt
Our solution involved refactoring a recently discovered bacterial
immune system
We have also explored population control of a model system using
CRISPR
This will allow for control of product synthesis in a bioreactor
Current uses in synthetic biology include genome editing, gene editing, gene expression tuning
Loci discovered in E. coli
The CRISPR craze
Variable sequences matched to phage genomes
Variable sequences predicted to function at the RNA level to protect against plasmids and phage
Demonstrated acquired resistance to phage
In vitro demonstration of sequence-directed DNA cutting
1987
2005
20072008
2013
2011ASU Georgia TechUSC
Spacer PAM
Exogenou s D NA
cas ... leader repeat repeat ...repeatcas
pre-crRNA
Cas9 crRNA
CRISPR Mechanism
...
......
...
T4
AR1HX10
RB14 ...Host genome ...
Broadly neutralizing repeat spacer repeat arrayVirus speci!c spacers
Bioinformatic pipeline: broadly neutralizing spacers
cas9 tracrRNA Repeat T4 Spacer Repeat
cas9 tracrRNA Repeat T7 Spacer Repeat
cas9 tracrRNA Repeat T4 Spacer Repeat T7 Spacer Repeat
The minimum CRISPR array: our design
Broadly immune
T4 immune
T7 immune
17
2025
35
48
63
75
100
135
180
245Cas9
Control
Ladder
163
Induction dependant survival of CRISPR array harboring clones
Growth kinetics of immune vs susceptible clones
Modeling
Basic assumptions carried through model
Bacteria are grown in a batch reactor
Bacteria with our CRISPR system are completely immune to phage infection
All phages are considered lytic
Basic Monod growth kinetics
0 2 4 6 8 10 12 14 16 18 200
0.1
0.2
0.3
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0.5
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0.9
Time [hours]
OD 60
0
Numerical Predictions€
dXdt
= µe−
XXC
⎛
⎝ ⎜
⎞
⎠ ⎟
m
+ kd⎛
⎝
⎜ ⎜
⎞
⎠
⎟ ⎟
€
X 1− e−αt( )
Monod equation dampening
0 2 4 6 8 10 12 14 16 18 200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Time [hours]
OD 60
0
Experimental DataNumerical Predictions
Experimental growth data fit to model
High inoculums used to mimic bioreactor seeding
0 2 4 6 8 10 12 14 16 18 200
0.1
0.2
0.3
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0.5
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0.8
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Time [hours]
OD 60
0
Experimental DataNumerical Predictions
Predicative power of model for growth data
CRISPR
CRISPR
Extending the model to phage predation
Infected bacteria statistically determined using a poisson distribution
Cell bursts according to a normal distribution
0 4 8 12 160
0.05
0.10
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Time [hours]
OD
600
Predicted Total
Extending the model to phage predation
0 4 8 12 160
0.05
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0.15
0.20
0.25
0.30
0.35
Time [hours]
OD
600
Growth DataPredicted TotalPredicted InfectedPredicted Healthy
Cell Debris
Fitting experimental data to phage the predation model
CRISPR
Extending the model to with a mixed population
Susceptible to phage Resistant to phage
Infected Phage
OCH3
OH
CHO
HO
Extending the model to with a mixed population producing different compounds
CRISPR
CRISPR
Compound A
Compound B
Modeling compound production under phage predation
pH
Flav
ourin
g
Phage
Res
istan
ce
Aroma
Gas
Tol
eran
ce
Starter cultures are used and selected for several key properties
These properties are usually specific to individual strains – not all strains within a species are suitable for fermentation
pH
Flav
ourin
g
Phage
Res
istan
ce
Aroma
Gas
Tol
eran
ce
Phage ResistanceFlavouring
Combining biosynthesis of common flavors with phage immunity we can consolidate strains
Offers control over the strain balance as well as the flavor production
pH
Flav
ourin
g
Phage
Res
istan
ce
Aroma
Gas
Tol
eran
ce
Phage ResistanceFlavouring
CinnamaldehydeProducing
VanillinProducing
For this case study we choose 2 cultures, one producing cinnamaldehyde and the other producing vanillin
We envision tuning different populations in an industry that suffers from phage mediated bioreactor collapse; the yogurt industry
Resistant to Environmental Phage
Cinnamaldehyde VanillaCRISPR
CRISPR
Both strains are resistant to the environmental phage
Susceptible to Control Phage
Cinnamaldehyde VanillaCRISPR
CRISPR
Both strains are resistant to the environmental phage
Only one is immunized against the control phage
Population Control with Controlled Phage Addition
Cinnamaldehyde VanillaCRISPR
CRISPR
Only one is immunized against the control phage
VanillaCRISPR
Biosynthesis of Vanillin
OCH3
OH
CHO
Vanillin
OCH3
CoA
OH
OSO
Feruoyl-CoA
OCH3
OH
OH
Ferulic Acid
O
OHOH
OH
Caffeic Acid
O
OH
OH
p-Coumaric Acid
O
NH2
OH
OH
Tyrosine
O
TAL CMH COMT
FCS
ECH
BBa_K1129000 BBa_K1129046 BBa_K1129041
BBa_K1129024
BBa_K1129022
Biosynthesis of Vanillin
OCH3
OH
CHO
Vanillin
OCH3
CoA
OH
OSO
Feruoyl-CoA
OCH3
OH
OH
Ferulic Acid
O
OHOH
OH
Caffeic Acid
O
OH
OH
p-Coumaric Acid
O
NH2
OH
OH
Tyrosine
O
TAL CMH COMT
FCS
ECH
BBa_K1129000 BBa_K1129046 BBa_K1129041
BBa_K1129024
BBa_K1129022
Conversion of p-Coumaric acid to Caffeic Acid
0
5000000
10000000
15000000
20000000
25000000
30000000
35000000
14 14.2 14.4 14.6 14.8 15 15.2 15.4 15.6 15.8 16
Constitutive 4CMHControl
14.6
97
Abu
ndan
ce
Retention Time (min)
OHOH
OH
Caffeic Acid
O
Abundance
50 100 150 200 250 300 350 400 450 500 550
73.2
110.2147.1
267.1
307.2
351.1 454.3 513.4 554.2
396.2
219.1
m/z
4500000
4000000
3500000
3000000
2500000
2000000
1500000
1000000
5000000
14.697
Biosynthesis of Vanillin
OCH3
OH
CHO
Vanillin
OCH3
CoA
OH
OSO
Feruoyl-CoA
OCH3
OH
OH
Ferulic Acid
O
OHOH
OH
Caffeic Acid
O
OH
OH
p-Coumaric Acid
O
NH2
OH
OH
Tyrosine
O
TAL CMH COMT
FCS
ECH
BBa_K1129000 BBa_K1129046 BBa_K1129041
BBa_K1129024
BBa_K1129022
Conversion of Caffeic Acid to Ferulic Acid
0
5000000
10000000
15000000
20000000
25000000
30000000
35000000
40000000
13 13.5 14 14.5 15 15.5 16
Constitutive COMTControl
14.4
34
OCH3
OH
OH
Ferulic Acid
O
Abu
ndan
ce
Retention Time (min)
14.434
41.2
73.1
115.1146.9 191.1
249.1
293.1
338.2
386.2 442.2 485.1
120000
100000
80000
60000
40000
20000
50 100 150 200 250 300 350 400 450m/z 0
Abundance
Biosynthesis of Vanillin
OCH3
OH
CHO
Vanillin
OCH3
CoA
OH
OSO
Feruoyl-CoA
OCH3
OH
OH
Ferulic Acid
O
OHOH
OH
Caffeic Acid
O
OH
OH
p-Coumaric Acid
O
NH2
OH
OH
Tyrosine
O
TAL CMH COMT
FCS
ECH
BBa_K1129000 BBa_K1129046 BBa_K1129041
BBa_K1129024
BBa_K1129022
Conversion of Ferulic Acid to Vanilin
0
5000000
10000000
15000000
20000000
25000000
30000000
35000000
9 9.5 10 10.5 11 11.5 12
Constitutive EncH and FcS Control
10.4
86
OCH3
OH
CHO
Vanillin
10.486
Abu
ndan
ce
Retention Time (min)
45.1
73.1
104.1137.1 163.0
224.1
254.0299.1
194.1
276.1 326.2 348.2
Abundance350000
300000
250000
200000
150000
100000
50000
060 100 140 180 220 260 300 340m/z
Biosynthesis of Cinnamaldehyde
Cinnamaldehyde
CoAOSO
Cinnamoyl-CoACinnamic acid
OHO HO
NH2
OH
Phenylalanine
O
PAL (EncP) 4-CL (EncH) AtCCR1
BBa_K1129026 BBa_K1129042 BBa_K1129039
Biosynthesis of Cinnamaldehyde
Cinnamaldehyde
CoAOSO
Cinnamoyl-CoACinnamic acid
OHO HO
NH2
OH
Phenylalanine
O
PAL (EncP) 4-CL (EncH) AtCCR1
BBa_K1129026 BBa_K1129042 BBa_K1129039
Conversion of Phenylalanine to Cinnamaldehyde
0
5000000
10000000
15000000
20000000
25000000
30000000
9 9.5 10 10.5 11 11.5 12 12.5 13
10.5
80
11.8
19
Constitutive EncP, 4CL and ATCRR1Control
Abu
ndan
ce
Retention Time (min)
CinnamaldehydeCinnamic acid
HO
45.1
75.1
103.1 161.1
131.1
229.1263.1
299.1 348.2376.2
205.145000
35000
25000
15000
5000
Abundance 10.58011.819
60 140 220 300 380m/z 0
60 140 220 300 380
45.1
73.1
147.1
118.1 175.1220.1265.1
293.1
320.1359.2 409.1
Abundance1200000
1000000
800000
600000
400000
2000000
m/z
OHO
Consolida)ng proper)es of different strains could save the dairy industry millions
What would be the percep)on of this gene)cally modified organism
by the end user, the public.
Industry
Academic
Professional Interviews
Developing iGEM Project
Gathering Information
Developing Public Survey
Conduct Public Survey Partners Telus World of Science
Marketing Professionals
Apply for Ethics Approval
Consult
Analyze Survey Data
Design Marketing Strategy
Human practices workflow
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Health Benefit Environmental Impact
Price Health Hazards Taste
Rela%ve Level of C
onside
ra%on
(5 being M
ost C
onside
red)
GM vs Non-‐GM Yogurt Considera%ons
Non-‐GM Yogurt
GM Yogurt
Conclusions We assembled, expressed and have started characterizing a minimal CRISPR-Cas9 system in E. coli
We developed both mathematical and numerical models to understand mono- and mixed cultures of compound-producing E. coli
We characterized compound generation for all steps in the pathway from p-coumaric acid to vanillin and confirmed cinnamaldehyde production from phenylalanine
We identified consumer concerns with genetically modified foods, proposed a feasible labeling guide and designed a marketing strategy for genetically modified foods
Acknowledgments Dr. Steven Hallam and Dr. Joanne Fox
UBC Life Science Institute UBC Microbiology and Immunology
UBC Michael Smith Laboratories UBC Department of Chemical and Biological Engineering
UBC Faculty of Applied Sciences UBC Faculty of Science
Walter H. Gage Memorial Fund Pfizer Canada Inc.
Engineering Undergraduate Society
Submitted 40 and characterized 25 new biobrick parts
Submitted Cas9 (BBa_K1129006) as our favorite functional part and showed evidence of immunity against phage using CRISPR components.
Obtained ethics approval to survey public’s perception of GMOs with the aim to create a marketing strategy for a GM Yogurt, following interviews with dairy industry and academic professionals
Improved 3 existing caffeine biosynthesis biobricks (BBa_K1129013, BBa_K1129015, BBa_K1129017) from TU Munich 2012 by replacing a yeast consensus sequence with a bacterial ribosome-binding site for prokaryotic engineering
Characterized previous iGEM parts (from TU Munich 2012, KU Leuven 2009, Edinburgh 2007) in vanillin, cinnamaldehyde and caffeine biosynthesis pathways and were able to show functional data for substrate conversion.
We are the only team to show data for vanillin and cinnamaldehyde production in E. coli!
Currently exploring the consequences of off-target activity in the CRISPR system. We are in the process of developing a resource (SPACE-R) to assess the safety and specificity of individual spacer sequences.
Developed comprehensive models that (1) predict growth of CRISPR-expressing E. coli cultures under phage predation, visualized using ‘Gro simulation’ (2) compute the cinnamaldehyde production following population tuning with various initial starting number of viruses.
Acheivements