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Genregulation Literature - Alberts/Lehninger - Kim Sneppen & G. Zocchi: Physics in Molecular Biology - E. Klipp et al. : Systems Biology in Practice Systems biophysics 2010/05/11 Physics of transcription control and expression analysis
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Genregulation

Dec 31, 2015

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Genregulation. Physics of transcription control and expression analysis. Systems biophysics 2010/05/11. Literature Alberts/Lehninger Kim Sneppen & G. Zocchi: Physics in Molecular Biology E. Klipp et al. : Systems Biology in Practice. From genetic approach to sytemic approach. - PowerPoint PPT Presentation
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Page 1: Genregulation

Genregulation

Literature

- Alberts/Lehninger- Kim Sneppen & G. Zocchi: Physics in Molecular Biology- E. Klipp et al. : Systems Biology in Practice

Systems biophysics 2010/05/11

Physics of transcription control and expression analysis

Page 2: Genregulation

From genetic approach to sytemic approach

genregulation

mRNA regulation

DNA mutations / evolution

protein functions

spatiotemporal structure formationMorphogenesis

signal transduction=> Topics of systems biophysics

Page 3: Genregulation

Biological Pattern formation and Morphogenesis11.05.2010

Zur Anzeige wird der QuickTime™ Dekompressor „TIFF (LZW)“

benötigt.

E S k1 ES k2 E P

k 1 Enzymatic Reactions

Michaelis-Menton-KineticsInhibation, Regulation

Reaction-Diffusion-Model of Morphogenesis

Biochemical Network

Page 4: Genregulation

E.coli as model system

E.coli has a single DNA molecule which is 4.6 106 basepairs long. It encodes 4226 proteins and a couple of RNA molecules. The information content of the genome is is bigger than the structural information of the encoded Proteins-> regulatory mechanisms are encoded

Genregulation allows adaption to changing environmental conditions, and regulation of metabolism

Page 5: Genregulation

Content of this lecture:

Basics: Monod Model, Lac Operon

Statistical Physics of DNA-binding Proteins

Modelling of genregulatory Networks

(ODE & Boolian Networks)

Dynamics of Protein-DNA binding

DNA looping

Analysis of gene expression data

Synthetic Networks

Page 6: Genregulation

Operon-Modell

operon

Operon: Genetic subunit, that consists of regulated genes with similar functionality.It includes- Promotor: Binding site for RNA polymerase - Operator: controls access of the RNA-Polymerase structural gene - Structural genes: Polypeptide encoding genes

Francois Jacob und Jaques Monod, 1961

Page 7: Genregulation

The Trp Operator as a switch:• Within the promotor lies a short DNA region as binding site for a

repressor. A bound repressor prevents the Polymerase from binding.

Page 8: Genregulation

The OUTSIDE of proteins can be recognized by proteins

Distinct basepairs can be recognized by their marginsDNA binding motivs

Small channel

Large channel

Page 9: Genregulation

Binding of Tryptophane to the Tryptophane-Repressorproteine changes the conformation of the repressor, Repressor can bind to the repressor binding site

Page 10: Genregulation

Identification of promotor sequences

Page 11: Genregulation

Transcription-Activation proteins switch on genes

Page 12: Genregulation

Gen-Regulation with Feedback:lac-Operon

LacI

IPTG, TMG

Page 13: Genregulation

Campbell, N.A., Biology

A cis-regulatory element or cis-element is a region of DNA or RNA that regulates the expression of genes located on that same strand. This term is constructed from the Latin word cis, which means "on the same side as". These cis-regulatory elements are often binding sites of one or more trans-acting factors.

IPTG (Isopropyl β-D-1-thiogalactopyranoside)This compound is used as a molecular mimic of allolactose, a lactose metabolite that triggers transcription of the lac operon. Unlike allolactose, the sulfur (S) atom creates a chemical bond which is non-hydrolyzable by the cell, preventing the cell from "eating up" or degrading the inductant. IPTG induces activity of beta-galactosidase, an enzyme that promotes lactose utilization, by binding and inhibiting the lac repressor. In cloning experiments, the lacZ gene is replaced with the gene of interest and IPTG is then used to induce gene expression.

Non-metabolizable inducer are used to induce gene expression

Page 14: Genregulation

Variation of Protein-Concentration with IPTG

Northern Blot: measurement of the messenger RNA (mRNA) concentration

External and internal Inductor-concentration is equal in equilibriumThe mRNA concentration increases linear with the concentration of inductor, saturation over 60%

The operon enables a variation of Protein concentration. What is missing to make a switch?

60

40

20

0

[mR

NA

]

0.100.00[IPTG Induktor]Long, C et al, J.Bacteriol. 2001

Page 15: Genregulation

Transkription und Translation in E.coliTypical times and rates

1 Molecule / cell = 1nMComplete mass2.5 106 Da

TRANSKRIPTIONrate 1/s - 1/18sTranskriptionsrate: 30bps-90bps

TRANSLATION10.000-15.000 RibosomesTranslation rate 6-22 codons/s(40 Proteine/mRNA)

Page 16: Genregulation

The arabinose system1

Uptake

Reporter

Regulator

Break down

pBAD24 2

~55 copies/cell

[1] R. Schleif. Trends in Genetics, 16(12):559–565, 2000[2] L. M. Guzman, D. Belin, M. J. Carson, and J. Beckwith. J.Bacteriol., 177(14):4121–4130, 1995[3] D. A. Siegele and J. C. Hu. Proc. Natl. Acad. Sci. USA, 94(15):8168–8172, 1997

Page 17: Genregulation

automated data aquisition

define ROIs

measure total intensity

DICtn

N

DICt0

Fluorescencet0

t1

tn

background correction

calibration and conversion into molecular units

Time-lapse Fluorescence Microscopy and Quantitative Image Processing

Page 19: Genregulation

8x105

6

4

2

0

To

tal F

luo

resc

en

ce [

a.u

.]

806040200

Time [min]

0.2% arabinose

Single cell expression kinetics

30min 40min 60min50min 70min

5min 15min 35min 45min25min

Saturating induction

Subsaturating induction

Image series correspond to blue curves

Fluorescence measurement• Cell outlines are determined using bright field images• The signal is integrated within the outline in each fluorescence image

8x105

6

4

2

0

To

tal F

luo

resc

en

ce [

a.u

.]

806040200

Time [min]

0.01% arabinose

Page 20: Genregulation

Gene expression model

Deterministic rate model with time delay d

8x105

6

4

2

0

Z(

) [a

.u.]

806040200

[min]

Reporter module Uptake module

Induction: t=0min

Page 21: Genregulation

Curve Fitting

Fixed Parameters

Saturating induction

Subsaturating induction

Fit Parameters

Fit expression function

Time delay

Protein synthesisrate

Literature

Measured

8x105

6

4

2

0

To

tal F

luo

resc

en

ce [

a.u

.]

806040200

Time [min]

0.01% arabinose

8x105

6

4

2

0

To

tal F

luo

resc

en

ce [

a.u

.]

806040200

Time [min]

0.2% arabinose

Page 22: Genregulation

Ohter example: Quorum Sensing

Page 23: Genregulation

Squid with floodlamp

Phänomena:Squid (Euprymna scolopes) emmits light due the night Squid isn´t recognized as prey in the moonlight

Explanation:

Light organ of the squid collects luminescent bacteria (Vibrio fischerei)

Question:

Why does V. fischerei emmit light within the lightorgan of the squid, but not in open sea?

Page 24: Genregulation

Quorum sensing

Bakterien detect their own cell density Density regulates the expression of luminescent genes

K. Nelson, Cell-Cell Signalling in Bacteria

Bacteria increase exponentialOD: optical density

Page 25: Genregulation

Molekular picture of QS

• Bakteria export oligopeptides (Pheromones)• Oligopeptides accumulate with increasing cell density• Oligopeptide diffuse into cell membrane and regulates the expression of luminescent genes

Page 26: Genregulation

Searching the binding site

Page 27: Genregulation

Searching the binding site: timescales

D kT

6R

P(r, t) 1

4tDexp

r2

4Dt

tdiffusion d2

2D

Stokes Einstein equation(z.B. DGFP=3-7µm2/s)

Probability distribution

1µm

Typical timescale for a proteine to find an arbitrary point in an E.coli: tD 0.1s

Page 28: Genregulation

Diffusion to a target site (binding disc)

J D4r2 dC

dr

dC

dt

1

r2D

d

dr4r2 dC

dr

C(r) J

D4r C()

C() N V

C() 0

J 4DN

V

on V

4DN20s N

Page 29: Genregulation

Residence times for transcription factors

1

off

1

on

V exp G kT 4D M exp G kT

(from on=20s/N follows, that 1 molecule in 1µm3 occupies half an Operator)

for specific bindings (operon) with 1M-1=1.6nm3 and Gspez=-12.6kcal/mol, =1 follows

off 20s

for unspecific binding sites with Guspez=-10-4 kcal/mol, follows

off 10 4 s

Page 30: Genregulation

Search of the binding sites on a DNA strand

DayssD

L2000.200

2 1

2

Unspecific binding events of TFs is a problem, since the time to find a binding site is increased. For a infinite staytime, a 1D- random walk over the strand would last:

(L=1.5mm und D1≈D)

Page 31: Genregulation

Accelerated search: jumps between strands decrease time to find a binding site.

l2

D1

L

l

Ll

D1

Mit L=1.5mm, l=150nm follows

50s

Page 32: Genregulation

Boolian Networks, or what cells and computers have in common.

Page 33: Genregulation

(Nature, Dec 99)

Page 34: Genregulation

Combinatoric gene regulation: Genetic networks

transcriptiontranscription

translationtranslation

Genregulatoric proteineGenregulatoric proteine

Page 35: Genregulation

A transcription-activator and a transcription-repressor regulate the lac-Operon

Page 36: Genregulation

Thermodynamicc model of a combinatoric transcription logics

P : bindingprobability

Gerland et al. PNAS, 2005

Gene regulation follows the mechanics of „Boltzmann-machines“

Page 37: Genregulation

Statistical physics of protein - DNA binding

CI O CIO

K k

k

CI O CIO

CIO Ototal

CI

K CI

Binding-isothermes:

Page 38: Genregulation

Cooperativity due to dimer binding

CI D O CIO

KD CI M 2

CI D

CIO Ototal

CI M 2

K KD CI M 2

Cooperative binding

CI M CI M

CI D

Page 39: Genregulation

The statistical weight of the „on“ state

Pon Z(on)

Z

Pon

Poff

Z(on)

Z(off )

c

exp G kT CI K

The free-energy difference is normalized to 1mol/l . The real change in free energy of the binding event depends on the concentration of TF in solution [Cl] :

G* kT ln Z(on) ln Z(off ) G kT ln CI

Page 40: Genregulation

A model for lac networks

Glukoseconc.constant

GFP: Reportermolekül, Abbildung durchFluoreszenz-Mikroskopie=> je höher das Fluoreszenz-Signal desto mehr LacZ,Y wird exprimiert

Page 41: Genregulation

Experimental proof for a switch

Start: not induced

After induction exist 2 populations:

green: induced bacteria

white, not induced population

Bistable area (grey)

Arrow marks the start state:

on-off state of bacteria depend on the on-off state in the beginning!

switch with hysteresisOzbudak et al, Nature 2004

Page 42: Genregulation

modelling of genregulatory networks: example

Page 43: Genregulation

Modelling in mRNA level

Page 44: Genregulation

Timetrace of mRNA concentrations

Problem: kinetic binding constants are usually not known and hard to measure

Steady state

Page 45: Genregulation

Simplification of genregulatory networks

transcriptiontranscription

translationtranslation

Genregulatory proteinGenregulatory protein

Page 46: Genregulation

Abstraction of genetic networks

Gen X

Gen Y

Gen Z

+

-

Page 47: Genregulation

Boolean networks(Kauffman 1989)

Page 48: Genregulation

Boolean networkmodel

• N Genes (nodes)

• with 2N different states

• with possible rules

• K is the number of possible inputs per node

22K

Page 49: Genregulation

Boolean rules for N=2 und K=2

Page 50: Genregulation

Back to the example:

We learn: if a=0, then follows0101 stationary

if a=1, then follows oscilatory behaviour1000->1001->1111->1010->1000