L3.1: Circuits: Introduction to Transcription Networks. Cellular Design Principles Prof. Jenna Rickus

Transcription

1 L3.1: Circuits: Introduction to Transcription Networks Cellular Design Principles Prof. Jenna Rickus

2 In this lecture Cognitive problem of the Cell Introduce transcription networks Key processing network of the cell What is a transcription factor? Review basic mechanism of gene expression Prokaryotes and eukaryotes Network view of real transcription factor networks

3 Cognitive Problem of the Cell Concept articulated by Alon in Introduction to Systems Biology Extracellular Intracellular Available Nutrients Stressors Mechanical stimulation Chemotactic signals Other cells Self Competition Cooperation Sensing Internal Representation of External Signals Change Gene Expression Cell State Sensing > Membrane Transporters/Receptors, Direct Protein Regulation Representation & Processing > Transcription Networks

4 Transcription Network Figure Alon: Introduction to Systems Biology

5 Information Processing Cell as an integrated device several thousand types of interacting proteins E. coli: 4500 genes (~ 4500 protein types) E. coli: 4 x 10 6 protein molecules / cell E. coli: ~ 300 transcription factors (degrees of freedom) information processing function is largely carried out by transcription networks What is the job of the network? monitor the environment calculate the amount at which each type of protein is needed determine rate of gene expression (protein production)

6 Transcription Factors Proteins (therefore encoded in genes) Bind DNA to regulate the rate at which specific target genes are read or transcribed DNA Often designed to transit rapidly between active and inactive molecular states Rate of activation modulated by specific environmental signal Binding of a signal ligand Phosphorylation Binding to other proteins active inactive P

7 Transcription Factors Activator increases rate positive control Repressor decreases rate negative control Activation more common than repression 60 80% of interactions are positive in E. coli & yeast TF usually acts as an activator OR repressor Sometimes a transcription factor can act as both 1 TF can act on multiple genes master regulators: TF that influences many genes

8 Ref. Figure Alon. Introduction to Systems Biology simplest view of transcription Promoter region Rate ->[# molecules/time] Ribosome Promoter region

9 Ref. Alon. Introduction to Systems Biology Transcription factors as activators Rate ->[# molecules/time]

10 Transcription factors as repressor Rate ->[# molecules/time] Ref. Alon. Introduction to Systems Biology

11 Gene Expression in Prokaryotes Vs. Eukaryotes Prokaryotes (e.g. bacteria) No nucleus Transcription / translation in same location Translation occur before transcription is done Gene organized as operons Multiple genes on one mrna strand No introns No alternative splicing Simpler genome structures Fewer genes Smaller promoters Ref: ThermoScientific: Protein Expression

12 Gene Expression in Prokaryotes Vs. Eukaryotes Eukaryotes (e.g. yeast, human, mouse) Contain introns and exons Alternative splicing of mrna to get different gene products 1 gene 1 mrna 1 protein doesn t hold up mrna must be translocated out of the nucleus mrna location, transport, half life becomes important Translation occurs outside the nucleus Transcription factors: a proteins must re-enter the nucleus Ref: ThermoScientific: Protein Expression

13 E. coli Transcription Network ~20% of interactions are shown in this network. Highly connected nodes Node gene or gene operon Arrow directed edge node i regulates node j N = # of nodes = 420 E = # of edges = 520 Structure, connectivity is not random --> functional consequences for stability & dynamics of the network Ref. Alon. Introduction to Systems Biology

14 RegulonDB Curated Regulatory Transcription Network in E. coli K12 TF TF Network RegulonDB.

15 Curated TF Gene Network in E. coli K12 in RegulonDB When we engineer and re-engineering cells at the level of DNA. Or chemically perturb gene expression. We are operating inside such networks. Highlights a need for systems level views. Ability to work at many levels of abstraction.

16 For Further Knowledge Alon. Chapter 2 Biology, Eighth Edition (Raven) Chapter 15 RegulonDB (version 8.0): Omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more. Salgado H, et al J. Nucleic Acids Research 2012 Nov; doi: /nar/gks1201 PMID: PMC: PMC w0/chapter15/processing_of_gene_inf ormation prokaryotes_vs eukaryot es.html

17 Coming Up Mathematical Representation of Gene Expression Models of Simple Transcription Network Motifs Negative autoregulation Feed Forward Loops