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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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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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History of biotechnology at DSM

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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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Basis of smart library design

7

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Smart library design accelerates development

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• 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

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Acknowledgments

STRAIN ENGINEERING Hans Roubos

PROTEIN ENGINEERING Rene de Jong

ENZYME APPLICATION Margot Schooneveld

The Rosalind Franklin

Biotechnology Centre

Delft NL

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