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Bio 402/502 Section II, Lecture 7. Systems Biology of the Nucleus Dr. Michael C. Yu. Section II exam. Short answer/questions - each question has multiple parts. Answer can be in words or a combination of picture & words.
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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. • 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) • Dr. Yu’s section = 70% of the test, Dr. Cullens = 30%
Chromosome arrangements are probabilistic and have a preferred average position Human Chr 18 (gene poor) Homologous to Human Chr 19 Human Chr 19 (gene dense) Homologous to Human Chr 18 (Tanabe et al, 2002) 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 (Tanabe et al, 2002) Relative radius in % • 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 Green: HSA3, blue: HSA5, red: HSA11 (Foster & Bridger, 2005) • 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? • Term coined at 1960s, however theoretical people and experimental biologists diverged • Renaissance at 1990s • Biology becoming cross-disciplinary, information based, high throughput science • 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
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 • Functional genomics • Functional proteomics • Large-scale microscopy • Establishment of networks (i.e. transcription) using bioinformatics • Reverse engineer gene regulation?
Strategies for the development of comprehensive system models (Gorski, S. et al.,2005)
Systems information in the cell nucleus (Gorski, S. et al.,2005)
Functional genomics tools used in systems biology • 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 - Profiles of protein-bindings in a genome: ChIP-chip • 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): • 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 Ratio Cy5/Cy3>1 = protein bound (Abcam website)
Functional proteomics tools used in systems biology studies • 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 - Protein arrays • Relatively new technology • Manufacturing of protein arrays requires a lot of resources • Quick identification of many interactions at once
Proteomic identification using mass spec • Identification requires only a small amount • Also allows for identification of post-translational modifications on proteins (George Hilliard)
Strategy for employing a proteomic approach in identifying proteins • These can be “affinity purified” samples separated on PAGE (George Hilliard)
Functional proteomics applied to determine global protein interactions • Entire yeast proteome was tagged with Tandem-affinity purification (TAP) tag (Gavin et al, 2002) • 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 • 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 (Gavin et al, 2002)
Establishment of interaction network from proteomic analysis • Clearly, very complex • How does this compare with that of in vivo network? (Gavin et al, 2002)
Protein arrays allows rapid identification of a single protein • 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 (Schweitzer et al, 2003)
Large-scale microscopy studies • Application to determine different chromosome territories • Where is the location of every protein in a cell? (Pepperkok and Ellenberg 2006)
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 • Why? Can provide valuable insights on the design of natural systems • Allows for us to bridge our gaps in understanding what happens in nature • Start out with simple devices • Re-engineer certain “parts” to facilitate a specific biological task (i.e. biofuel?)
Rational biological designs: wave of the future? Light-sensation in E. coli Release of auto-inhibition (repressed by GTPase-binding domain) Activation of Arp2/3 complex In the presence of S-gal (substrate for LacZ) (Drubin et al, 2007) Ligand: allows you to turn it on/off at your will Input switch is changed! Engineered signal transduction examples
Requirements and goals of a systems approach in the nucleus (Gorski, S. et al.,2005)