Digital Biology, by Ruediger Trojok

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Digital Biology is the computer programming of bioassays using digital microfluidic biochips based on electrowetting on dielectric technology. Digital Biology allows for wide scale automation of procedures in synthetic biology by improving efficiency between 1000 to 100000 fold compared to manual laboratory work, for the first time enabling wide scale rapid prototyping for the iterative creation of biological systems. To successfully decentralize the Digital Biology technology, we want to develop Bioflux Technology—a platform that will automate the synthetic biology flow with great medical and commercial potential. Bioflux Technology will be a combination of a software suite for biologists to plan experiments, a microfluidic device, electronics hardware to run the experiments and the required wetware (biological reagents) to perform a wide range of standardized bioassays used in synthetic biology. About the speaker: Ruediger Trojok is a Diplom Biologist, that invented a novel contraceptive method based on genetically altered lactic acid bacteria. He worked as a freelance consultant for the office for Technology Assessment by the German Parliament on biohacking and synthetic biology. Since 2014 he works for the Institute for Technology Assessment and Systems Analysis at the Karlsruhe Institute for Technology on the EU program Synenergene. He is currently establishing a citizen science biolab in Berlin, and is supporting open-source biotechnology projects related to public life, politics and the arts.

Health & Medicine

BIOFLUX
presented at
Do It Together - Digital Biology
a seminar organized by
in January 2016, Berlin

Digital Biology
Dipl. Biol. Rüdiger Trojok
Bioflux, ITAS/KIT

What is digital
biology?
Or: can we
program biology?

Shannon‘s information
theory
Nachrichtenübertragung abhängig von:
• Signal-Noise-Ratio
• bandwith / channel capacity
• Available energy
• Mutual Information of Sender / Receiver
• Data compression
Can we apply information theroy on biology?

Landauer Information theory
Rolf Landauers:
“Information is not a disembodied
abstract entity; it is always tied to a
physical representation. It is represented
by engraving on a stone tablet, a spin, a
charge, a hole in a punched card, a
mark on paper, or some other
equivalent. This ties the handling of
information to all the possibilities and
restrictions of our real physical word, its
laws of physics and its storehouse of
available parts.”
The physical nature of information; Rolf Landauer; Physics Letters A 217 (1996) 188-193

Maxwell‘s Demon and Szilard‘s
Machine
Landauer Principle:
• Information gain is entropy loss
• Work is an entropy-less energy
source
• Heat is entropy carried by
energy
observation:
Information processing costs
energy
per bit
dW = kBT ln2
work and
heat
exchange

Biosemiotik AGTC
Sequenz
(digital)
Motif
(analog)
Anabolism
Katabolism
Proliferation
Death
„What we actually call
information - the elementary
unit of information - is a
difference that makes a
difference”
Gregory Bateson

BioSyntax
Jesper Hoffmeyer’s Theorie:
• A monistic Code Duality: digital und analog
• Code Memory of structural relations in space
and time
Creative Plasticity
AGTC
Digital:
Sequence
Analog:
Motif

Biosphere
http://www.google.de/imgres?imgurl=http%3A%2F%2Fecotope.org%2Fanthromes
%2Fbiodiversity%2Fplants%2Fmaps%2Fpng
%2Fellis_2012_Olson_biomes.png&imgrefurl=http%3A%2F%2Fecotope.org
%2Fanthromes%2Fbiodiversity%2Fplants%2Fmaps
%2F&h=720&w=960&tbnid=rzbkGIJ_UVKZAM

Read Write
Analog Biology
Digital Biology

Exponential growth of biological
databases
http://www.kanehisa.jp/en/db_growth.html
14

Exponentially dropping costs
Rob Carlson http://synthesis.cc/
15

Gaudilabs: Generic Lab Equipment
Physical principles used: light (optical sensors, filters, lenses), temperature (peltier),
gravitiy (rotation), electricity (electrodes)

17
Prof. Blaney, Broad Institute http://www.youtube.com/watch?v=66Oc8fLKXlE

Historic Analogy: Printing press
movable type inventions:
Korea: Choe Yun-ui 1377
Germany: Johannes Gutenberg 1436

Advantages of Digital Biology
Technology
Efficiency
lowest speed limit is cell growth rate
Serial / parallel experimentation
Brute force screening
Machine instead of manual standards
Reproducibility
Precision of measurements vs. natural noise
Reductionist vs. systems approach
Single cells vs. Population
Cost efficiency
Wages for operation of equipment
Service costs
Material consumption
Infrastructure requirements

Architecture questions
Decentral vs. Central
'Apple' vs. 'Sharp' model
low tech vs. High tech
open source vs. Closed source
programmable vs. Application specific
online vs. Offline control
technology push and market pull:
- what will be the killer app?
- Who are the users?

Synthetic Biology
Systems approach
(diverging)
Engineering approach
(converging, iterative)
timetime
Systematic screening can be combined with
rational and iterative engineering.
22

DNA Extraction
DNA Amplification
DNA Insertion
Cell Transformation
Cell Incubation
Protein Expresion
DNA Sequencing
DNA Synthesis

Health: Phage Therapy
• Well known since 100 years
• Programmable
• Highly specific
• Safe

Wetware
Software
Hardware 0
Biostrike
Citizens / NGOs / Academics
§§
Personalized
Phages
0

Good
Environm
ent
Human
Bad
Neutral
BSL
1
BSL
4
BSL
3
BSL
2

Comments and
suggestions welcome!
Thanks for listening.
Rüdiger Trojok
rt@openbioprojects.net

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Digital Biology, by Ruediger Trojok

1. BIOFLUX presented at Do It Together - Digital Biology a seminar organized by in January 2016, Berlin

2. Digital Biology Dipl. Biol. Rüdiger Trojok Bioflux, ITAS/KIT

4. Evolution – 3,6 Bn. Years > >

5. What is digital biology? Or: can we program biology?

6. Shannon‘s information theory Nachrichtenübertragung abhängig von: • Signal-Noise-Ratio • bandwith / channel capacity • Available energy • Mutual Information of Sender / Receiver • Data compression Can we apply information theroy on biology?

7. Landauer Information theory Rolf Landauers: “Information is not a disembodied abstract entity; it is always tied to a physical representation. It is represented by engraving on a stone tablet, a spin, a charge, a hole in a punched card, a mark on paper, or some other equivalent. This ties the handling of information to all the possibilities and restrictions of our real physical word, its laws of physics and its storehouse of available parts.” The physical nature of information; Rolf Landauer; Physics Letters A 217 (1996) 188-193

8. Maxwell‘s Demon and Szilard‘s Machine Landauer Principle: • Information gain is entropy loss • Work is an entropy-less energy source • Heat is entropy carried by energy observation: Information processing costs energy per bit dW = kBT ln2 work and heat exchange

9. Biosemiotik AGTC Sequenz (digital) Motif (analog) Anabolism Katabolism Proliferation Death „What we actually call information - the elementary unit of information - is a difference that makes a difference” Gregory Bateson

10. BioSyntax Jesper Hoffmeyer’s Theorie: • A monistic Code Duality: digital und analog • Code Memory of structural relations in space and time Creative Plasticity AGTC Digital: Sequence Analog: Motif

11. Bio-Language AGTC

12. Biosphere http://www.google.de/imgres?imgurl=http%3A%2F%2Fecotope.org%2Fanthromes %2Fbiodiversity%2Fplants%2Fmaps%2Fpng %2Fellis_2012_Olson_biomes.png&imgrefurl=http%3A%2F%2Fecotope.org %2Fanthromes%2Fbiodiversity%2Fplants%2Fmaps %2F&h=720&w=960&tbnid=rzbkGIJ_UVKZAM

13. Facebook

14. Read Write Analog Biology Digital Biology

15. Exponential growth of biological databases http://www.kanehisa.jp/en/db_growth.html 14

16. Exponentially dropping costs Rob Carlson http://synthesis.cc/ 15

17. Gaudilabs: Generic Lab Equipment Physical principles used: light (optical sensors, filters, lenses), temperature (peltier), gravitiy (rotation), electricity (electrodes)

18. 17 Prof. Blaney, Broad Institute http://www.youtube.com/watch?v=66Oc8fLKXlE

19.

20. Historic Analogy: Printing press movable type inventions: Korea: Choe Yun-ui 1377 Germany: Johannes Gutenberg 1436

21. Advantages of Digital Biology Technology Efficiency lowest speed limit is cell growth rate Serial / parallel experimentation Brute force screening Machine instead of manual standards Reproducibility Precision of measurements vs. natural noise Reductionist vs. systems approach Single cells vs. Population Cost efficiency Wages for operation of equipment Service costs Material consumption Infrastructure requirements

22. Architecture questions Decentral vs. Central 'Apple' vs. 'Sharp' model low tech vs. High tech open source vs. Closed source programmable vs. Application specific online vs. Offline control technology push and market pull: - what will be the killer app? - Who are the users?

23. Synthetic Biology Systems approach (diverging) Engineering approach (converging, iterative) timetime Systematic screening can be combined with rational and iterative engineering. 22

24. Digital Biology Semiotics

25. DNA Extraction DNA Amplification DNA Insertion Cell Transformation Cell Incubation Protein Expresion DNA Sequencing DNA Synthesis

26. DNA Extraction DNA Amplification DNA Insertion Cell Transformation Cell Incubation Protein Expresion DNA Sequencing DNA Synthesis

27. DNA Extraction DNA Amplification DNA Insertion Cell Transformation Cell Incubation Protein Expresion DNA Sequencing DNA Synthesis

28. Evironment and Agriculture

29. Health: Phage Therapy • Well known since 100 years • Programmable • Highly specific • Safe

30. Wetware Software Hardware 0 Biostrike Citizens / NGOs / Academics §§ Personalized Phages 0

31. Good Environm ent Human Bad Neutral BSL 1 BSL 4 BSL 3 BSL 2

32.

33. Comments and suggestions welcome! Thanks for listening. Rüdiger Trojok rt@openbioprojects.net

Digital Biology, by Ruediger Trojok

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