Bio 402/502 Section II, Lecture 7 Systems Biology of the Nucleus Dr. Michael C. Yu

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Bio 402/502Section II, Lecture 7

Systems Biology of the Nucleus

Dr. Michael C. Yu

Section II exam

• Short answer/questions - each question has multiple parts.

• Dr. Yu’s section = 70% of the test, Dr. Cullens = 30%

• Answer can be in words or a combination of picture & words

• What is being tested? Your ability in understanding how to apply an assay to a relevant biological question

• Open book/notes/journal articles. NO ELECTRONIC DEVICES (cell phones, computers, PDAs, etc)

Chromosome arrangements are probabilistic and have a preferred average position

(Tanabe et al, 2002)

Homologous to Human Chr 18

Homologous to Human Chr 19

Human Chr 18(gene poor)

Human Chr 19(gene dense)

Topological conservation of CTs across the evolution

Radial distribution of CTs within nucleus by quantitative 3D evaluation

Homologous to Human Chr 18

Homologous to Human Chr 19

All DNA

Relative radius in %(Tanabe et al, 2002)

• Chromosome 18 and its homologues are consistently located closer to nuclear periphery

• Chromosome 19 and its homologues are consistently located closer to nuclear interior

Potential mechanisms of chromosome positioning

500 nm

(Foster & Bridger, 2005) Green: HSA3, blue: HSA5, red: HSA11

• Mechanism 1: association with immobile nuclear elements such as scaffolding molecules helps to determine chromosome positions in a nucleus

• Mechanism 2: Self-organization determined by the overall gene expression activity of all of its genes. Determined by the number and pattern of active/silent genes on a given chromosome

NPC plays a functional role in organizing chromatin

(Brown & Silver, 2007

Transcriptional activation at the nuclear periphery in other eukaryotes

(Brown & Silver, 2007

What is systems biology?

(Hieronymous & Silver, 2005)

Emergence of systems biology?

• Approaches to study biology has largely been a reductionist– Focus on a single component (a gene/protein)– Work its way up to the systems level

• New concept: what’s the big picture? Must first know all the pieces in a puzzle

• Challenge: put the pieces together• Attempts to create predictive models of cells, organs,

biochemical processes and complete organisms– Data combined with computational, mathematical and

engineering disciplines– Model <-> simulations <-> experiment

•Term coined at 1960s, however theoretical people and experimental biologists diverged•Renaissance at 1990s

–Biology becoming cross-disciplinary, information based, high throughput science

Systems biologists ask different kinds of questions…

• How does all elements within a single pathway interact instead of how a single element within a single pathway interact?

• Based on the information we obtain, how can we re-constitute a system using different “parts”?

Tools used in systems biology studies

• Reverse engineer gene regulation?

• Establishment of networks (i.e. transcription) using bioinformatics

• Functional genomics

• Functional proteomics

• Large-scale microscopy

(Gorski, S. et al.,2005)

Strategies for the development of comprehensive system models

Systems information in the cell nucleus

(Gorski, S. et al.,2005)

Functional genomics tools used in systems biology

- Profiles of protein-bindings in a genome: ChIP-chip

• Taking advantage of genome sequencing

- Profiles of gene expression: microarrays• Determine total # of transcripts in a cell• Can perform this over different conditions, cell types, etc

• Determine comprehensive binding site of a protein in a genome

• Integration of this data with transcription profiling

Using microarrys to determine total gene expression in a cell

Determining binding of a protein to the whole genome

ChIP-chip (or ChIP2, ChiP-on-chip):

Ratio Cy5/Cy3>1 = protein bound

• Requires protein-specific antibody or epitope tagged protein

• Can look for both “direct” and “indirect” interactions with DNA

• Can be used to study DNA & RNA binding proteins

(Abcam website)

Systems approach to understand mRNA splicing

Functional proteomics tools used in systems biology studies

- Protein arrays

• High-powered mass spectrometer allows for rapid, large scale identification of protein complexes

- High-throughput affinity purification (e.g. TAP)

• Large scale purification of a protein’s total interactors in a cell

• Very labor intensive

• Relatively new technology

• Manufacturing of protein arrays requires a lot of resources

• Quick identification of many interactions at once

Proteomic identification using mass spec

(George Hilliard)

• Identification requires only a small amount

• Also allows for identification of post-translational modifications on proteins

Strategy for employing a proteomic approach in identifying proteins

(George Hilliard)

• These can be “affinity purified” samples separated on PAGE

Functional proteomics applied to determine global protein interactions

(Gavin et al, 2002)

• Entire yeast proteome was tagged with Tandem-affinity purification (TAP) tag

•Isolation of TAP-tagged protein and its interactors, followed by separation using SDS-PAGE

Determining final distribution of protein complexes

(Gavin et al, 2002)

Specific example: polyadenylation machineries

(Gavin et al, 2002)

• Reverse purification of components ID’ed in the first pass

• These newly ID’ed components also co-purified the same components in the complex

• Reverse co-purification establishes the interaction with the complex

Establishment of interaction network from proteomic analysis

(Gavin et al, 2002)

• Clearly, very complex

• How does this compare with that of in vivo network?

Protein arrays allows rapid identification of a single protein

(Schweitzer et al, 2003)

•Fluorescent image of yeast ProtoArray - 5000 different yeast proteins were spotted on a single microscope size slide

• Chemiluminescent detection on microarrays (A) vs. fluorescent detection (B)

• Reciprocal interactions demonstrated

(Pepperkok and Ellenberg 2006)

Large-scale microscopy studies

• Application to determine different chromosome territories

• Where is the location of every protein in a cell?

Large scale yeast two-hybrid analysis creates network information for proteins

Yeast 2-hybrid: protein-protein interactions

Known binding partners for every protein in a cell

Construction of biological systems: synthetic biology

• Start out with simple devices

• Re-engineer certain “parts” to facilitate a specific biological task (i.e. biofuel?)

• Why? Can provide valuable insights on the design of natural systems

• Allows for us to bridge our gaps in understanding what happens in nature

Rational biological designs: wave of the future?

(repressed by GTPase-binding domain)

Engineered signal transduction examples

(Drubin et al, 2007)

Light-sensation in E. coli

In the presence of S-gal (substrate for LacZ)

Activation of Arp2/3 complex

Release of auto-inhibition

Input switch is changed!

Ligand: allows you to turn it on/off at your will

Requirements and goals of a systems approach in the nucleus

(Gorski, S. et al.,2005)

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