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

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Presentation on theme: "The Mystery of Gene Expression Emanuele Leoncini June 18th 2013 Junior Seminar."— Presentation transcript:

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

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

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

4 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Bacteria behaviour “Deterministic” character

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

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

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

8 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Gene Expression

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

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

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

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

13 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 DNA Gene: portion of DNA encoding for a specific protein

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

15 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Transcription: initiation polymerase

16 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Transcription: elongation mRNA

17 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Translation: initiation 50S 30S

18 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Translation: elongation

19 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Translation: termination protein

20 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Stochasticity in gene expression

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

22 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Model

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

24 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 Protein production

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

26 Emanuele Leoncini -- Stochastic Gene ExpressionJune 18th 2013 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

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

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


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