Stochasticity in gene expression, evolution & evolvability

1. Stochasticity in gene expression, evolution & evolvability 17th June 2010 Jean-Pascal Capp LISBP, UMR CNRS 5504, UMR INRA 792 INSA de Toulouse France capp@insa-toulouse.fr 3rd Workshop on MAS in Biology at meso or macroscopic scales, LaBRI,Bordeaux, 2010

2. Content 2 17/06/2010 Background Stochasticity in gene expression & evolution Hypothesis & Proposal for MAS n°1 Stochasticity in gene expression & evolvability Hypothesis & Proposal for MAS n°2

3. For instance : PNAS, 1957, 43:553-566 Background 3 17/06/2010 Early studies have shown that the levels of gene expression vary from cell to cell • The production of -galactosidase in individual cells is highly variable • The induction increases the proportion of cells expressing the enzyme rather than increasing every cell’s expression level equally However, for a long time, reliable single-cell assays of gene expression were lacking

4. Background 4 17/06/2010 The first studies to use an expression reporter in single cells were done at the beginning of the 90s. • The expression of a glucocorticoid-responsive transgene encoding -galactosidase reveals a large cell-to-cell variability • Increasing the dose leads to an increased frequency of cells displaying a high level of expression rather than a uniform increase in expression in every cell  Dose dependence is a consequence of changing the probability that an individual cell would express the gene at a high level

5. Background 5 17/06/2010 How could we explain such a variability (or noise) in gene expression ? • The stochastic nature of chemical reactions may create variations among identical cells because • The reactions underlying gene expression involve small numbers of molecules and may therefore exhibit stochastic fluctuations This stochastic nature of gene expression may generate population variation that could have important biological implications

6. Experiment in E. coli Double reporter construction Background 6 17/06/2010 Development of single cell analysis by flux cytometry and construction of synthetic gene networks led to the discovery of large fluctuations in gene expression levels among individual cells in isogenic populations (Elowitz et al. 2002) Noise in gene expression is the stochastic variation in the expression level of a gene under constant environmental conditions (Raser and O'Shea 2005).

7. Double reporter construction Experiment in S. cerevisiae Background 7 17/06/2010 • Extrinsic fluctuations are those that affect the expression of both copies of the gene equally in a given cell, e.g. variations in the numbers of RNA polymerases or ribosomes • Intrinsic fluctuations are those due to the randomness inherent to transcription and translation, and affecting each copy of the gene independently

8. Background 8 17/06/2010 In eukaryotes (yeast) : • Noise arising from transcription contributes more than noise generated at the translational level (in contrast to observation in prokaryotes). • Downstream effects of noise can have profound phenotypic consequences, drastically affecting the stability of gene expression.

9. Stochasticity in gene expression & evolution 9 17/06/2010 • In unicellular organisms, variability could be an advantage in that it would allow heterogeneous phenotypes even in clonal populations, • enabling a population of organisms to contain subpopulations with different behaviours • favouring emergence of adapted cells when environment is fluctuating and when stress appears (Fraser and Kaern 2009) •  Adaptive advantage ? As noise could be advantageous in regard to environmental fluctuations, are genes related to stress responses noisier than housekeeping genes ?

10. Stochasticity in gene expression & evolution 10 17/06/2010 A strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Dramatic protein-specific differences in noise that are strongly correlated with a protein’s mode of transcription and its function. Proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet.  Protein noise levels seem to have been selected to reflect the costs and potential benefits of this variation

11. 2 mutant versions of the promoter controlling ZeoR expression Survival of the « high noise » strain with intermediate Zeocine concentrations Stochastic gene expression creates non-genetic heterogeneity that favours the appearance of resistant sub-populations Stochasticity in gene expression & evolution 11 17/06/2010 « low-noise » expression Number of cells « high-noise » expression Expression level Stochastic gene expression is a major source of phenotypic diversification that can be modulated to change the population dynamics in response to stress

12. 2009 Recent works showing how selection influences phenotypic fluctuations in evolutionary experiments. Important study on E. coli providing evidence that mutants with a large degree of phenotypic fluctuation emerged under strong selection pressure Stochasticity in gene expression & evolution 12 17/06/2010  increase in phenotypic fluctuation through noise in gene expression is clearly a relevant evolutionary strategy

13. KEY Different coefficients of variation Number of cells Hypothesis & Proposal for MAS n°1 13 17/06/2010 Technological and industrial yeast strains which have evolved in stressful conditions are more tolerant to stress and fluctuating environments Questions : Do technological yeast strains exhibit higher noise levels in the expression of genes involved in technological traits than classical lab strains ? Are ethanol, osmotic and heat tolerances linked to high stochasticity in genes implicated in the response to these stresses ?

14. Stochasticity in gene expression & evolvability 14 17/06/2010 Evolvability = intrinsic capacity of organisms to evolve (Sniegowski and Murphy 2006) Industrial and pathogenic yeasts exhibit high genomic instability during vegetative growth compared to laboratory strains (Querol and Bond 2009) • Wine yeasts exhibit genomic instability even in stable laboratory conditions (Lucena et al, 2007)‏ • Genomic instability seems to be a environmental-dependent (epigenetic) phenomenon because the rate of appearance of karyotype abnormalities is variable and dependent on the medium (Nadal et al, 1999)‏ • Yeasts undergo genomic changes in response to environmental stress during a single round of fermentation (James et al, 2008)‏ or a single passage through host (Forche et al. 2009) • Variations in the Rate of Genetic-Variant Generation (RGVG) in stressful conditions are observed in yeast (also observed in bacteria and cancer cells)

15. Stochasticity in gene expression & evolvability 15 17/06/2010 Studies on bacteria have revealed mechanisms of regulated increase in the RGVG entirely consistent with the modern Darwinian concept of adaptation by natural selection on randomly occurring variation (Foster 2007). Nevertheless equivalents in eukaryotic systems have not been observed. An alternative model is needed for the appearance of genetic plasticity in fluctuating environments and the modulation of evolvability. CAPP JP, Genetics, June 2010, In press

16. Stochasticity in gene expression & evolvability 16 17/06/2010 • Model based on the fact that : • regulated variations of the RGVG in bacteria occur through expression of DNA Repair and Maintenance Gene (DRMG) rather than by mutations in these genes (mutators alleles) • the rate of appearance of genetic variants in yeast or cancer cells rapidly vary with the level of environmental stress  argues against structural changes in DRMG (Capp, 2005, Bioessays) Variations in DRMG expression are more likely the cause of variations of the RGVG Hypothesis : • DRMG are expressed stochastically like any other gene • DRMG expression levels strongly influence efficiency and fidelity of DNA Repair and Maintenance Pathways (DRMP) • Following variability of DRMG expression, DRMP may display variable efficiency and fidelity from cell to cell.

17. Capp, 2010 Expected link between heterogeneity in DRMG expression and the RGVG Stochasticity in gene expression & evolvability 17 17/06/2010 Consequently, appearance of genetic alterations could also be variable among the population as consequence of stochastic appearance of DRMP malfunctioning

18. Question : Is noise in DRMG expression an evolvable trait that can evolve depending on the pressure of their environment ? KEY Different coefficients of variation Number of cells Hypothesis & Proposal for MAS n°2 18 17/06/2010 Industrial and pathogenic yeasts or cancer cells have to ability to rapidly acquire genetic modifications and to tune the RGVG  role of the noise ? Is adaptation through genetic modifications conferring higher variability in DRMG expression a relevant evolutionary strategy ?