Download Level 3 Genes

Information Storage and Processing in Biological Systems:
A seminar course for the Natural Sciences
Sept. 11
Biological Information,
Sept 16
DNA, Gene regulation
Sept 18
Translation and Proteins
Sept 23
Enzymes and Signal Transduction
Sept 25
Biochemical Networks
Sept 30
Simple Genetic Networks (Dr. Jacob)
Oct 2
Evolution, Evolvability and Robustness
Oct 5
Adventures in multicellularity
Operon-Operator Gene Regulation Model
(Britten-Davidson)
J. Holland: Adaptation in Natural and Artificial Systems
2
Genetic Networks
(genetic regulatory networks)
- a group of genes connected through transcription regulators encoded
within the set of genes
Promoter X
gene X
Promoter Y
gene Y
operator X
3
Genetic Networks
(genetic regulatory networks)
- a group of genes connected through transcription regulators encoded
within the set of genes
Promoter X
gene X
X
Promoter Y
gene Y
operator X
4
Genetic Networks
(genetic regulatory networks)
- a group of genes connected through transcription regulators encoded
within the set of genes
Promoter X
gene X
X
X
gene Y
operator X
Y
5
Genetic Networks
(genetic regulatory networks)
By convention we simplify these diagrams as follows:
Promoter X
gene X
X
X
X
gene Y
Y
operator X
Y
6
Genetic Networks
(genetic regulatory networks)
X
Y
Denotes positive
regulation
Y
Denotes negative
regulation
Z
7
A photomicrograph of three cells
showing the flagella filaments.
Each filament forms an extend helix
several cell lengths long.
The filament is attached to the cell
surface through a flexible ‘universal
joint’ called the hook.
Each filament is rotated by a reversible rotary motor, the direction of the motor
is regulated in response to changing environmental conditions.
The E. coli Flagellar Motor- a true rotary motor
Rotationally averaged reconstruction of electron micrographs of purified hook-basal
bodies. The rings seen in the image and labeled in the schematic diagram (right)
are the L ring, P ring, MS ring, and C ring. (Digital print courtesy of David DeRosier,
Brandeis University.)
Regulation of flagella gene expression:
A three tiered transcriptional hierarchy
• 14 flagella operons
• arranged in a regulatory cascade of three classes
• Class 1 Operon / Gene:
• encodes transcriptional activator of Class 2 operons
• Class 2 Operons / Genes:
• structural components of a rotary motor
• transcriptional activator for Class 3 operons
• Class 3 Operons / Genes:
• flagellar filament structural genes
• chemotaxis signal transduction system
Checkpoint mechanism ensures that Class 3 genes are not transcribed
before functional basal body-hook structures are completed.
10
Regulation of flagella gene expression:
A three tiered transcriptional hierarchy
Positive transcriptional regulators
Alternative sigma factors
Anti-sigma factors
Temporal regulation
11
The “genetic network diagram” for the fla system
A
B
C
D
E
12
The “genetic network diagram” for the fla system
Level 1
flhCD
fliL
fliE
fliF
flgA
flgB
flhB
n=6
flgM
fliD
flgK
fliC
meche
mocha
flgM
fliA
Level 2
n=6
Level 3
13
The Flagella Transcription Hierarchy
1. The Master Regulon
CRP,H-NS,OmpR
other?
FlhCD
14
The Flagella Transcription Hierarchy
1. The Master Regulon
2. The FlhCD Regulon
CRP,H-NS,OmpR
other?
FlhCD
inside
outside
FlgM
FliA
Basal Body
and Hook
other?
15
The Flagella Transcription Hierarchy
1. The Master Regulon
2. The FlhCD Regulon
CRP,H-NS,OmpR
other?
Chemotaxis
proteins
Motor
proteins
FlhCD
inside
outside
FlgM
FliA
Basal Body
and Hook
other?
3. The FliA Regulon
Filament
16
The flhDC promoter integrates inputs from
multiple environmental signals
flhDC
?
CRP - catabolite repression, carbohydrate metabolism
OmpR - osmolarity
IHF - growth state of cell?
HdfR - ?
17
FliA Regulation by FlgM
FlhDC expression leads to activation of Level 2 genes including the
alternative sigma factor FliA and an anti sigma factor FlgM
FlgM accumulates in the cell
and binds to FliA blocking
its activity (i.e. interaction
with RNA polymerase)
preventing Level 3 gene
expression.
Level 3 Genes
inside
outside
18
FliA Regulation by FlgM
Other level 2 genes required for Basal body and hook (BBH)
assembly are made and begin to assemble in the membrane.
Level 3 Genes
inside
outside
Basal Body
and Hook
Assembly
19
FliA Regulation by FlgM
The Basal body and hook assembly are completed.
Level 3 Genes
inside
outside
Completed Basal Body
and Hook
20
FliA Regulation by FlgM
The Basal body and hook assembly are completed.
FlgM is exported through
the Basal Body and Hook
Assembly
Level 3 Genes
inside
outside
Completed Basal Body
and Hook
21
FliA Regulation by FlgM
Level 3 gene expression is initiated.
FlgM is exported through
the Basal Body and Hook
Assembly.
Level 3 Genes
inside
outside
Completed Basal Body
and Hook
22
FliA Regulation by FlgM
Level 3 gene expression is initiated.
FliA can interact with RNA
polymerase and activate
Level 3 gene expression.
Level 3 Genes
inside
outside
Completed Basal Body
and Hook
23
FliA Regulation by FlgM
Level 3 gene products are added to the motility machinery including the
(1) flagella filament,
(2) motor proteins and
(3) chemotaxis signal transduction system.
Chemotaxis
proteins
Motor
proteins
inside
outside
Filament
24
The “genetic network diagram” for the fla system
A
B
C
D
E
25
The “genetic network diagram” for the fla system
Class 1
Class 2
fliL
fliE
fliF
flgA
flgB
flhB
n=6
Level 1
flhCD
flgM
Class 3
fliD
flgK
fliC
meche
mocha
flgM
fliA
Level 2
n=6
Level 3
26
How to Measure Gene Expression
1- Gene Expression Profiling With Real Promoters
Modeling Genetic Networks
- from small defined systems to genome wide Small Defined Networks
High Throughput / High Quality
Expression Profiling
Modeling, Simulation
28
Using reporter genes to measure gene expression
RNA polymerase
Regulator
Organization of operon on chromosome.
flhD
flhC
flhDC promoter
29
Using reporter genes to measure gene expression
RNA polymerase
Regulator
Organization of operon on chromosome.
flhD
flhC
flhDC promoter
Clone a copy of the promoter into a reporter plasmid.
Reporter gene
30
Using reporter genes to measure gene expression
RNA polymerase
Regulator
flhD
flhC
Both the flhDC genes and the reporter
plasmid are regulated in the same way
and thus the level of the reporter
indicates the activity of the promoter.
Reporter gene
Note that the strain still has
a normal copy of the genes.
31
Gene Expression
in Populations
Gene Expression
in Single Cells
Multi-well plate reader
Video microscopy
- sensitive, fast reading
- high-throughput screening
- liquid cultures
- colonies
- mixed cultures
- “individuality”
- cell cycle regulation
- epigenetic phenomenon
Automation: Both approaches are amenable to high throughput robotics
32
Gene Expression in Single Cells: Cell to Cell Variability
Michael Elowitz, Rockefeller University
33
Fluorescence of flagella reporter strains as a function of time
n
ero
Op s
s
Cla
Fluorescence
relative to max
0.6
0.1
0.01
0
Time [min]
600
34
The order of flagellar gene expression is the order of assembly
Early
Cluster 1 Class 1 flhDC
Cluster 2
Late
Cluster 3
Class 2 fliL
Class 2 fliE
Class 2 fliF
Class 2 flgA
Class 2 flgB
Class 2 flhB
Class 2 fliA
Class 3 fliD
Class 3 flgK
Class 3 fliC
Class 3 meche
Class 3 mocha
Class 3 flgM
Master regulator
Activator of class 3
35
Simple Mechanism for Temporal Expression Within a Regulon
[protein]
Induction of
positive
regulator
Time
Promoters with
decreasing
affinity for
regulator
36
Simple Mechanism for Temporal Expression Within a Regulon
[protein]
37
Using Expression Data to Define and Describe Regulatory Networks
With the flagella regulon, current algorithms can distinguish Level 2 and
Level 3 genes based on subtleties in expression patterns not readily
distinguished by visual inspection.
Using our methods for expression profiling (sensitive, good time resolution)
we have been able to demonstrate more subtle regulation than previously
described.
Different mechanisms can give rise to different patterns- in this case temporal
patterns arise by transcription hierarchies (I.e. Level 1 ‡ Level 2 ‡ Level 3)
and by differences in binding site affinities within a level.
“You can not infer mechanism from pattern.”
38
Methods such as the one described here or DNA microarrays can be
used to measure expression of all the genes in a cell simultaneously.
Reverse Engineering challenge – can we use expression data to infer
genetic networks?
C
A
B
M
D
E
F
N
X
Y
W
V
Z
O
U
39