1 Reconstruction of Transcriptional Regulatory Networks Adapted from Chapter 4 of “Systems...
-
Upload
allison-sharp -
Category
Documents
-
view
221 -
download
0
Transcript of 1 Reconstruction of Transcriptional Regulatory Networks Adapted from Chapter 4 of “Systems...
1
Reconstruction of Transcriptional Regulatory Networks
Adapted from Chapter 4 of“Systems Biology: Properties of Reconstructed Networks”
byBernhard O.Palsson
2
What is Transcriptional regulation ?
• Transcriptional regulatory networks (TRNs) are the on-off switches at the gene level
Input Signals
Regulating component
Changed RNA and
protein output
Changed cell behavior and
structures
Adapted from http://genomicsgtl.energy.gov/science/generegulatorynetwork.shtml
3
Why do we care about Regulation?
Regulation has a significant effect on cell behaviorExample: E. coli– Estimated 400 regulatory genes – 178 regulatory and putative regulatory genes found in genome– 690 transcription units (contiguous genes with a common expression
condition, promoter and terminator) identified in RegulonDB– Will have a major effect on model predictions of cellular behavior
4
Hierarchy in Transcriptional Regulation
genes operon
Regulon
Stimulon
5
The lac Operon
CAP site Promoter Operator Structural genes for lactose -metobolizing enzymes
Operation statusCarbon Source
OFFNeither
OFFGlucose and Lactose
CAP RNA polymerase
ONmRNA
Lactose only
lac repressor
OFFGlucose only
6
The GAL Regulon
Operation statusCarbon Source
RNA polymerase
ONmRNA
Galactose only
UASG Mig1 site GAL1 gene required for galactose metabolism
OFFGlucose and Galactose
Mig 1
Tup
OFF (basal)Neither Glucose nor Galactose
Gal4
Gal80
7
Fundamental data types for TRNsComponent data
– Binding sites, transcription factor (TF) molecules etc.Interaction data
– Links are formed by chemical interactions– DNA-protein,protein-protein,metabolite-RNA– Positive and negative controls
Network state data– Reconstructed networks have functional states– Controls for network states assessed by perturbation experiments
• Genetic/environmental/systemic
8
Regulatory vs Metabolic Circuits
Regulatory circuits are poorly characterized
• Less-well understood
• Qualitative statements vs. “hard” stoichiometry
• Not mechanistically conserved across different organisms
Regulatory circuits are more complex
• Multiple effects/transcription factor (TF)
• Multiple regulators/gene
9
Key Considerations for TRN Reconstruction
• How to represent regulatory information?– Is transcription regulation Boolean (switch-like) or continuous?– Should transcription be thought of as a stochastic or
deterministic process?
• What constitutes significant regulation?– Many extracellular signals can affect expression level of a gene.– Which signals are actually physiologically significant?
• Problems with experimental data in the literature:– Experiments done under different conditions (e.g. strain background)– Typically experimentalists concentrate on studying well-known
TF/target pairs in great detail– In vivo vs in vitro
10
Bottom-up Reconstruction
• Pool genomic, biochemical and physiological data, inferring functions where necessary. – include regulatory rules
• Represent rules using Boolean logic, kinetic theory and the like.
• Analyze separately or together with metabolic network as a metabolic/regulatory model.
• Use model to make predictions about the behavior and emergent properties of the system – predictions should be seen as hypotheses which must be tested
experimentally.
11
Top-down Reconstruction
• Problems with bottom-up reconstruction:– Many (most?) TF targets are not characterized– Tedious process, because informative databases are rare
• Alternative approach: Utilize data from well-designed high-throughput experiments to reverse-engineer (or “back-calculate”) regulatory circuits– Gene expression profiles for wild type and deletion strainsunder appropriate conditions (genetic perturbation)– Promoter sequence data and possibly consensus binding sitesfor TFs– Location analysis (ChIP-Chip) data on transcription factorbinding sites
12
Issues with Top-down Reconstruction
• Very complex models and algorithms are required to reverse engineer regulatory circuits– Computational issues: Explosion in the number of structures– Model complexity issues: Explosion in the number of parameters– Optimality issues: Only locally optimal circuits can be found
• Data is not usually available in sufficient quantities or with appropriate quality – computational and experimental people usually don’t work together
• Currently these methods are primarily used to create hypotheses about potential targets of TFs
13
Combining knowledge-based and data-based regulatory network reconstruction strategies.a
a Herrgård M.J. et al , Current Opinion in Biotechnology,2004,15:70-77
14
Graphical Representation of Boolean TRNs in E. coli.
Transcription factors (104)
Metabolic genes (479)
Stimuli (102)
TFs regulating gene expression
Stimuli affecting TF activity
15
Summary
• Transcriptional regulatory networks determine the expression state of a genome
• These networks are presently incompletely defined
• Approaches to regulatory reconstruction are still being developed (especially top-down)
• Models of TRNs will help unravel the “logic” of gene circuits
16
Thank you !