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© 2017 DSM All Rights Reserved
Bright Science at DSM: Industrial Enzymes in Food
Application
John Perkins
DSM Biotechnology Center
DSM Food Specialties
July 24, 2017
HEALTH, TASTE & APPEAL
Drive for healthier food that tastes,
looks and feels great
COST & PRODUTION EFFICIENCY
Food that is quick, easy and cost
efficient to produce as well as affordable
to consumers
NATURAL & SUSTAINABLE
Food that is as close to nature as possible and produced in the
most sustainable way
DSM Food Enzymes portfolio supports industry trends
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© 2017 DSM All Rights Reserved
Our solutions
Consumer benefit
Better tasting
Better texture or appearance
Prolonged
shelf-life
Healthier (reduce toxic
elements)
Customer benefit
Speed up production
process
Save costs
Simplify or make production
easier
Planet benefit
Require less raw material
Reduce energy use
Reduce waste
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© 2017 DSM All Rights Reserved
History of biotechnology at DSM
3
Classical (1870‘s) Modern (1980‘s) Industrial (2000‘s)
Yeast, Ethanol, Yeastextracts, Vitamins Penicillin, Butanol (ABE), Enzymes, Citricacid
Recombinant enzymes,
Metabolic engineering,
Biocatalysis
Cell culture technology
Enzymes & Yeast,
Bioprocess engineering,
Integrated biorefining,
Biobased chemicals &
advanced biofuels
Biotechnology has a central role in DSM history
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DSM’s enzyme cell factories for enzyme production
Kluyveromyces
lactis
Bacillus subtilis
Aspergillus niger
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Building the engineering cycle
cloning
transformation
DNA design
fermentation
strain design
characterization
Data & Sample
tracking
design better – build faster – test more – learn and apply faster
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A brief history of protein engineeringtechniques
6
Site-directed
mutagenesis
Error-prone
PCR
DNA
shuffling
smart
library
design
Importance of protein structure:
low high
Cassette/sat.
mutagenesis
computational
design?
Key drivers:- Commodity DNA sequencing
- Progressively cheaper DNA synthesis
- Advanced bioinformatics & modeling
?1970 1980 1990 2000 2010 2020
Key drivers:- HT screening robotics
- HT DNA sequencing
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Smart library design accelerates development
8
• Fewer variants tested
• High activity, hit rates
• Short timelines
• Screen close to application
• Many variants tested
• Low activity, hit rates
• Long timelines
• “Artificial” HT assay needed
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Towards computational design of new enzymes
9
In collaboration with
Noah Ollikainen &
Tanja Kortemme
(UCSF, San Francisco)
Our new computational protein
design tool improves specificity
predictions in enzymes with 70%!
Coupling protein side-chain and backbone flexibility
improves the re-design of protein-ligand specificity
Ollikainen, de Jong, Kortemme (2015), PLOS Comp Biol
11(9):e1004335. doi: 10.1371/journal.pcbi.1004335
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0
50
100
150
200
250
300
WT 6E1a 9E2c 3E5avar1 var2 var3
Error Prone PCR Variants
10.000 clones tested
Example of tuning enzyme activity and pH optimum: Random mutagenesis versus design
Essential mutations around active site
10 clones tested
WT Design 7 Design 9
Smart library design based on 3D structure and using the known sequence space
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The interaction of enzyme and application
Enzyme characteristics
Process factorsComposition APPLICATION
BIOCHEMICAL ASSAY
Complex concentrated matrix
Complex (in)accessible substrate
Simple aqueous matrix
Simple defined substrate
pH, time
temperature
ingredient
type, ratio
Macro scale
Change ingredient ratio
to determine effect on
enzymatic conversion
Micro scale
Localize enzyme and
substrate in matrix
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Benefits of new technologies
STRAIN DEVELOPMENT
ENZYMEAPPLICATION
PROTEIN ENGINEERING
SMART DESIGN
- 3D models for
visualization and
simulation
- Better predictions
INTEGRATION
- Relate composition,
process and enzyme
parameters
- Integrate micro- and
macroscopic events
PRECISION GENOME
EDITING
- Computer aided design
- Automated strain
engineering
SPEEDKNOWLEDGE
PREDICTION
12
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13
Acknowledgments
STRAIN ENGINEERING Hans Roubos
PROTEIN ENGINEERING Rene de Jong
ENZYME APPLICATION Margot Schooneveld
The Rosalind Franklin
Biotechnology Centre
Delft NL