Information Storage and Processing in Biological Systems: A seminar - PowerPoint PPT Presentation

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 Biochemical Networks Sept 25 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) 2 J. Holland: Adaptation in Natural and Artificial Systems

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 gene Y X operator X Y 5

Genetic Networks (genetic regulatory networks) By convention we simplify these diagrams as follows: Promoter X gene X X X Y gene Y X operator X Y 6

Genetic Networks (genetic regulatory networks) X Y Denotes positive Denotes negative regulation regulation Y 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 Level 2 fliF n = 6 flgM fliA flgA flgB flhB fliD flgK fliC Level 3 n = 6 meche mocha flgM 13

The Flagella Transcription Hierarchy CRP,H-NS,OmpR 1. The Master Regulon other? FlhCD 14

The Flagella Transcription Hierarchy CRP,H-NS,OmpR 1. The Master Regulon other? 2. The FlhCD Regulon FlhCD inside outside Basal Body and Hook FlgM FliA other? 15

The Flagella Transcription Hierarchy CRP,H-NS,OmpR Chemotaxis 1. The Master Regulon other? proteins Motor 2. The FlhCD Regulon FlhCD proteins inside outside Basal Body and Hook FlgM FliA 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) Level 3 Genes preventing Level 3 gene expression. 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 Level 1 Class 1 flhCD fliL fliE Level 2 fliF Class 2 n = 6 flgM fliA flgA flgB flhB fliD flgK fliC Level 3 Class 3 n = 6 meche mocha flgM 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 Gene Expression in Populations in Single Cells Multi-well plate reader Video microscopy - sensitive, fast reading - “individuality” - high-throughput screening - cell cycle regulation - liquid cultures - epigenetic phenomenon - colonies - mixed cultures 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 C Operon l Fluorescence a s s relative to max 0.6 0.1 0.01 0 600 Time [min] 34

The order of flagellar gene expression is the order of assembly Early Class 1 flhDC Cluster 1 Master regulator Class 2 fliL Class 2 fliE Class 2 fliF Class 2 flgA Class 2 flgB Class 2 flhB Cluster 2 Activator of class 3 Class 2 fliA Class 3 fliD Class 3 flgK Class 3 fliC Class 3 meche Cluster 3 Class 3 mocha Late Class 3 flgM 35

Simple Mechanism for Temporal Expression Within a Regulon Induction of positive regulator [protein] 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 Z O W V U 39