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The Mystery of Gene Expression

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  1. The Mystery of Gene Expression Emanuele Leoncini Junior Seminar June 18th 2013

  2. Réseaux , Algorithmes et Probabilités • Communication networks (models and algorithms) • New math tools for probabilistic models of complex networks Stochastic modeling of biological phenomena Bike-sharing system Vélib June 18th 2013 June 18th 2013 June 18th 2013 Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  3. Bacteria Why bacteria? • first life-form on Earth (~4 billion years ago) • bacteria on Earth • independent “simple” organisms The Good (probiotics) The Bad (predator) The Ugly (pathogen) Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  4. Bacteria behaviour “Deterministic” character Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  5. not performant performant Abundant nutriment Lack of nutriment Bacteria -- Two levels of stochasticity 1. Stochastic Decision • “fluctuations” in environment (nutriment) • Pros: • flexibility • simple • Cons: • fluctuations Structural Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  6. No spatial organization • Reactions: stochastic encounters X X X X X Stochastic time X X X X X X X X X Bacteria -- Two levels of stochasticity Bacteria 2.Structural stochasticity 2.Structural stochasticity Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  7. Stochasticity 1. Decision 2. Structural Cell structure design • In order to assure: • flexibility • performance • in stochastic environment ? Fluctuations Deterministic behaviour robust to fluctuations Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  8. Gene Expression Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  9. Gene Expression: • Proteins: the core of biologic processes (enzymes, DNA duplication, cell machinery...) • Lack of one protein can have serious consequences A highly consuming process: • >80% of cell resources • ~3.5 millions of proteins • ~2000 types of proteins constantly produced Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  10. What is a protein? Protein: chain of elementary bricks (amino acids) Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  11. What is a protein? Protein: chain of elementary bricks (amino acids) 3D conformation both determining the protein function Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  12. Central Dogma of Molecular Biology • “It states that such [sequential] information cannot be transferred from protein to either protein or nucleic acid” • Crick (1958) Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  13. DNA • Gene: portion of DNA encoding for • a specific protein Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  14. Gene activation Two states of gene: active and inactive Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  15. Transcription: initiation polymerase Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  16. Transcription: elongation mRNA Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  17. Translation: initiation 50S 30S Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  18. Translation: elongation Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  19. Translation: termination protein Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  20. Stochasticity in gene expression Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  21. Pros: Pros: Math Models • Fine description • Finding of new phenomena • Synthesis • Reproducibility • Cheap Cons: • Expensive • Hard to reproduce(sometimes not conclusive) Cons: • Time consuming • Simple but exhaustive ? How to analyze gene expression? Experiments Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  22. Model Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  23. Protein production • exponentially distributed with parameter • general distribution with density mRNA Poisson Point Process • stochastic • discrete numbers of components Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  24. Protein production Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  25. Protein production • small (few mRNAs)large • large(many mRNAs) small Target protein copies: Two possible strategies: • Good strategy: many mRNAS each • producing a small amount • of proteins Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  26. A few results: • Quantitative characterization of fluctuations • Rigorous (and controlled) analysis:identification of the crucial steps in gene expression • Counter-intuitive (or surprising) results • Identification of critical behaviour • Model as hypothesis-testing framework Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  27. Gene expression: work to do... • Interaction between proteins: how does it impact on fluctuations? • More realistic (treatable) model • Control in stochastic environment More in general... • Deeper cooperation between maths and biology Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013

  28. Sophisticated Many phenomena to be understood Thanks. ...but we love it! Emanuele Leoncini -- Stochastic Gene Expression June 18th 2013