SLIDE 1
Network and motifs
T ranscriptional network of E. coli Other modules
A B A A B
A b c d e
A
Motifs
b
Information Processing in Genetic Regulatory Networks Ofer Biham - - PowerPoint PPT Presentation
Information Processing in Genetic Regulatory Networks Ofer Biham - - PowerPoint PPT Presentation
Information Processing in Genetic Regulatory Networks Ofer Biham Mor Nitzan Hanah Margalit Yishai Shimoni Pascale Romby Baruch Barzel Pierre Fechter Adiel Loinger Azi Lipshtat Oded Rosolio Assaf Peer Yael Altuvia Network and motifs
SLIDE 2
SLIDE 3
Regulation Mechanisms
Difgerent levels of regulation
Transcriptional regulation Post-transcriptional regulation (by sRNA-mRNA int.) Post-translational regulation (by protein-protein int.)
gene a gene b
m
B
m
A
B A
gene a gene b
B m
B
S A
Transcriptional regulation Post-transcriptional regulation
SLIDE 4
Information processing
Transcriptional regulation
c
m C C A
B
SLIDE 5
Input Functions
Diverse two-dimensional input functions control bacterial sugar Genes, Kaplan, Bren, Zaslaver, Dekel and Alon, Molecular Cell 29, 783 (2008).
SLIDE 6
Transcription factor Transcription regulation Post-transcriptional regulation ncRNA Post-transcriptional regulation by ncRNA Transcription regulation Integrated network
Multi-layer feed-forward loop
Multi-layer regulatory circuits
Asaf Peer, Mor Nitzan, Zohar Itzhaki, Hanah Margalit
SLIDE 7
Combination of regulations at difgerent levels
gene b
SB
gene a gene c
mC m A C A
SLIDE 8
Staphylococcus aureus
Pathogenic bacteria Cause a wide range of human diseases Disease manifestations depend on the
expression of numerous virulence factors
Within S. aureus virulence
pathways lies a regulator switch that is induced by a quorum sensing signal
SLIDE 9
Quorum sensing for a growing population
At low numbers, violent bacteria will be
quickly targeted for degradation
Only at higher numbers, the bacteria become
virulent.
SLIDE 10
Quorum sensing for a dense population
Outer bacteria act as a shield Inner, protected bacteria excrete violent
proteins
SLIDE 11
- S. aureus virulence path
SLIDE 12
hla
Quorum Sensing Quorum Sensing
spa
RNAIII Rot
Adhesins, camouflage proteins (defensive state) Adhesins, camouflage proteins (defensive state) Exotoxins,
- hemolysin
α (offensive state) Exotoxins,
- hemolysin
α (offensive state)
The Switch
SLIDE 13
Target 2 Target 1 Regulator
A Simpler Switch
SLIDE 14
Selector Switch
SLIDE 15
Target 2 Target 1 activator
Selector Switch without activator/repressor
repressor
SLIDE 16
Target 2 Target 1 Top Regulator Bottom Regulator
Double Selector Switch
SLIDE 17
The model- rate equations
.
(sRNA regulator) (mRNA transcripts of TF ) (TF protein) (TF - promoter complexes) (mRNA transcripts of target 1) (mRNA transcripts of target 2) (Target 1 proteins) (Target 2 proteins ) (sRNA - target mRNA complexes)
SLIDE 18
Switching on and ofg
Target 2 Target 1
sRNA
TF
Time (min)
SLIDE 19
Response to a spike
SLIDE 20
Leakage of Target 1
1 (1 ) (1 )
T T T s T m
b TP u b b TP s u d
N Leakage N N = + +
Target 2 Target 1
sRNA
TF
SLIDE 21
Mixed Feedback Loop
SLIDE 22
Bifurcation Diagrams
SLIDE 23
Stochastic Trajectories
SLIDE 24
Life-times of bistable states
SLIDE 25
Deterministic vs. Stochastic Models
S S S A
P τ τ τ = +
SLIDE 26
Probability Distribution
SLIDE 27
sRNA-target interaction
- E. Levine, Z. Zhang, T. Kuhlman and T. Hwa, Plos. Biol. (2007)
SLIDE 28
Fine-tuning of target expression
- E. Levine, Z. Zhang, T. Kuhlman and T. Hwa, Plos. Biol. (2007)
SLIDE 29
miRs targets Post transcriptional network in HEK293 Cells
SLIDE 30
Crosstalk between Competing endogeneous RNAs (ceRNAs)
miR-Y mRNA target 1 mRNA target 2
Salmena et al., Cell 146, 353 (2011); Tay et al., Cell 147, 344 (2011) ; Bosia et al., Plos One 8, e66609 (2013); Figliuzzi et al., Biophys J. 104, 1203 (2013)
SLIDE 31
Crosstalk between ncRNAs
SLIDE 32
Crosstalk between mRNAs through their common regulators
SLIDE 33
Fast Transmission of Signals
(a) Wild-type (c) (a) Wild-type (b)
T0 T0 T1 T1 T2 T2 T0 T0 T1 T1 T2 T2 T0 T0 T1 T1 T2 T2 T0 T0 T1 T1 T0 T0 T1 T1 R0 R0 R0 R0 T0 T0 T1 T1 T2 T2 R0 R0 R1 R1 R0 R0 R1 R1 R0 R0 R1 R1 R0 R0 R1 R1
(c) (d) (b)
T0 T0 T1 T1 R0 R0
Knock-down
- f T0
Knock-down
- f T0
Knock- down of T10 Knock- down of T10
A C
(a) Wild-type (c) (b)
B
Over-expression
- f R0
Over-expression
- f R0
T1 T1 R0 R0 R1 R1 T1 T1 R0 R0 R1 R1 T1 T1 R0 R0 R1 R1
SLIDE 34
Signal Propagation – Experimental Data
SLIDE 35
T0 T0 T1 T1 T2 T2 R0 R0 R1 R1 R4 R4 T3 T3 T4 T4 R2 R2 R3 R3 T5 T5 R5 R5
Subnetwork of sRNA Regulators and theirTargets
SLIDE 36
T0 T0 T1 T1 T2 T2 R0 R0 R1 R1 R4 R4 T3 T3 T4 T4 R2 R2 R3 R3 T5 T5 R5 R5
Decay Rate of the Signal
SLIDE 37
Correlations in the Network
SLIDE 38
Summary
We have studied information processing in
genetic regulatory networks that involve difgerent levels of regulation
These networks combine sharp on/ofg type
regulation with fjne tuning processes, fast and slow processes, synchronization and subtle coordination
Further progress will require experiments
both at the single cell level and at the cell population level
SLIDE 39
Transcriptional vs. Post-transcriptional regulation
Transcriptional Post-transcriptional Response time Slow Fast Regulation type Sharp On/Ofg Enables fjne-tuning Regulator-target interaction Non-stoichiometric Stoichiometric Regulation strength determined by TF copy number and afginity to promoter Relative copy numbers of sRNAs and mRNAs and their afginity Directionality Directional – from regulator to target Bi-directional Energetic cost Protein synthesis RNA synthesis
SLIDE 40
Combination of regulations at difgerent levels
gene b
SB
gene a gene c
mC m A C A
SLIDE 41
Target 2 Target 1
TF
sRNA
Target 2 Target 1
sRNA
TF
Target 2 Target 1
TF TF
Three variants of the DSS
SLIDE 42
Dynamics of DSS variants
SLIDE 43