Biophysics of Systems

Dieter BraunSystems Biophysics

Master Program Biophysics:http://www.physik.uni-muenchen.de/studium/studiengaenge/master_physik/ma_phys_bio/curriculum.html

Lecture + SeminarDi 10.15-13.30 Uhr

Website of Lecture:http://www.physik.uni-muenchen.de/lehre/vorlesungen/sose_10/Biophysics_of_Systems/index.html

Content: Biophysics of Systems

20.4. Introduction

27.4. Evolution Part 1

4.5. Evolution Part 2

11.5. Gene Regulation and stochastic effects in regulatory networks

18.5. Pattern formation

25.5. Modelling of biochemical networks

1.6. No Lecture (Pfingstdienstag)

8.6. Bacterial Chemotaxis

15.6. Chemotaxis of Eukaryotes

22.6. Regulation using RNA

29.6. High Throughput Methods of Systems Biology

6.7. Game theory and evolution

13.2. Oral exams (15 minutes per student)

Macrophage hunts down Bacterium

A physical view of the (eukaryotic) cell

• Macromolecules– 5 Billion Proteins

• 5,000 to 10,000 different species

– 1 meter of DNA with Several Billion bases

– 60 Million tRNAs– 700,000 mRNAs

• Organelles– 4 Million Ribosomes– 30,000 Proteasomes– Dozens of Mitochondria

• Chemical Pathways– Vast numbers– Tightly coupled

• How is a useful approach possible?

www.people.virginia.edu/~rjh9u/cell1.html

Biosystems: Feedback Loops

Regulation

Cell-Cell Communication

RNA Interference

Protein-Interactions

Reaction Networks

Organelles

Epigenetics

Promotors,Inhibitors

Amplification

DiffusionNoise

Compartments

Biosystems: Feedback Loops

What is a „Bio-System“ ?

InputOut-put

* Komponents (Molecules, Proteins, RNA...)* Network-like Connections (kinetic Rates)* Substructures (Knots, Module)* Functional Input-Output-Relations

* Finding building principles (reverse engineering) (also: tracking how evolution has build it) • Quantitative Models to describe the system• Test the model with experimental data• Prediction of the System behavior

Networks

Goal

Systems Biology Definition

• Systems Biology integrates experimental and modeling approaches to study the structure and dynamical properties of biological systems

• It aims at quantitative experimental results and building predictive models and simulations of these systems.

• Current primary focus is the cell and its subsystems , but the „systems perspective“ will be extended to tissues, organs, organisms, populations, ecosystems,..

b g Ga

Signal Pathway in dictyostelium discoideum

PIP2PIP3

CRAC

cAMP

PI3K*b g

PH

PTENRac/Cdc42

Actin polymerization

RAS

Cellpolarization

pleckstrinhomologydomain

+

Acetylcholin-Aktivierung

Levels of discription of the Signal Transduction

Biochemical Rate Equations

+ Definition of Reaction Compartments

+ Diffusion Processes (Reakt.-Diff-Eq.)

+ Stochastic Description

Signal-Networks are „complex“

Connection Maps: Signal Transduction Knowledge Environment www.stke.org

How to Approach Complexity

Classical Approach: System Analysis

- Quantitative Data Recording- Mathematical Modeling- Simulation- Comparison with Experiment

Useful analogy: Signaltransduktion and Elektronic Circuits

Biological Signalnetworks are Combinatorical

Modular view of the chemoattractant-induced signaling pathway in Dictyostelium

Peter N. Devreotes et al.Annu. Rev. Cell Dev. Biol. 2004. 20:22

Hierarchical Structure of biologic Organisms(Z. Oltvai, A.-L. Barabasi, Science 10/25/02)

Modular Biology

as advocated in the influential paper (Nature 402, Dec 1999)

Stochastic GenesFrom Concentrations to Probabilities

Stochastic Genes

Number of mRNA/cell 4000Number of rRNA/cell 18,000Number of tRNA/cell 200,000Number of all RNA/cell 222,000Number of polysaccharides/cell 39,000Number of lipopolysaccharide/cell 600,000Number of lipids/cell 25,000,000Number of outer membrane proteins 300,000Number of porins (subset of OM) 60,000Number of lipoproteins (OM) 240,000 Number of nuclear proteins 100,000Number of ribosomal proteins 900,000Number of all proteins in cell 2,600,000 Number of external proteins (flag/pili) 1,000,000Number of all proteins 3,600,000

Inventory of an E-coli: do counting molecules matter?

Note the low number of mRNA !

From Concentrations to Probabilities

Repetition: Gen-Expression

With the Genes fixed: how can a bacteria adapt to the environment?Answer: Regulation of Gen-Expression

Repressors & Inducers

• Inducers that inactivate repressors:– IPTG (Isopropylthio-ß-galactoside) Lac repressor

– aTc (Anhydrotetracycline) Tet repressor

• Use as a logical Implies gate: (NOT R) OR I

operatorpromoter gene

RNAP

activerepressor

operatorpromoter gene

RNAP

inactiverepressor

inducerno transcription transcription

Repressor Inducer Output

0 0 10 1 11 0 01 1 1

RepressorInducer

Output

The Effect ofSmall Numbers

e.g. by reducing the transkription rateor the cell volume

=> Protein levels are constant,but the fluktuations increase

Search for differences between intrinsic noise from biochemical processes of e.g. Gen-Expression) and extrinsic noise from fluctuations of other cell compartments, e.g. the conzentration of RNA Polymerase.

Idea of Experiment:Gene for CFP (cyan fluorescence protein) und YFP (yellow fluorescence protein) are controlled by the same, equal promotor, i.e. the average concentration of CFP und YFP are the same in a cell: differences are then attributed to intrinsic noise.

A: no intrinsic noise => noise is correlated red+green=yellow

B: intrinsic noise => Noise is uncorrelated, differenz colors

Elowitz, M. et al, Science 2002

Intrinsic NoiseExtrinsic Noise

Intrinsic Noise

Stochastic Gen-Expression

Elowitz, M. et al, Science 2002

Unrepressed LacI Repressed LacI +Induced by IPTG

Intrinsic NoiseExtrinsic Noise Extrinsic Noise

Stochastic Gen-Expression

Science, 307:1965 (2005)