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Predicting genetic diversity of spontaneous drug-resistance in bacteria - Alejandro Couce

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QUANTITATIVE LAWS
June 13 -June 24

Published in: Science
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Predicting genetic diversity of spontaneous drug-resistance in bacteria - Alejandro Couce

  1. 1. LAKE COMO SCHOOL OF ADVANCED STUDIES "QUANTITATIVE LAWS II" Predicting genetic diversity of spontaneous drug-resistance in bacteria Alejandro Couce 1,2 1Unité Mixte de Recherche 1137 (IAME-INSERM), Paris, France. 2Centro Nacional de Biotecnología (CNB-CSIC), Madrid, Spain.
  2. 2. PREDICTING GENETIC DIVERSITY OF SPONTANEOUS DRUG- RESISTANCE IN BACTERIA Diversity after a drug-induced bottleneck
  3. 3. PREDICTING GENETIC DIVERSITY OF SPONTANEOUS DRUG- RESISTANCE IN BACTERIA - Short-term diversity - Long-term diversity
  4. 4. PREDICTING GENETIC DIVERSITY OF SPONTANEOUS DRUG- RESISTANCE IN BACTERIA - Short-term diversity - Long-term diversity
  5. 5. Background
  6. 6. Mutation, spontaneous or induced?
  7. 7. Induced mutation
  8. 8. Spontaneous mutation Adapted from: Ycart B (2013) PloS One
  9. 9. Fluctuation test
  10. 10. The Luria-Delbrück distribution
  11. 11. What about diversity? Adapted from: Ycart B (2013) PloS One
  12. 12. The richness vs evenness paradox
  13. 13. The richness vs evenness paradox
  14. 14. Simple, deterministic model
  15. 15. Simple, deterministic model r = 5 r = 3 r = 2 r = 1.6 r = 1.2
  16. 16. High sensitivity to mutant's growth rate
  17. 17. Impact of 'jackpot' cultures
  18. 18. Impact of 'jackpot' cultures
  19. 19. Impact of phenotypic lag
  20. 20. Impact of phenotypic lag
  21. 21. Variability on mutant's growth rate
  22. 22. Variability on mutant's growth rate
  23. 23. Experimental setting Small vs Large population size Presence vs absence of antibiotic
  24. 24. Experimental system Resistance to fosfomycin in P. aeruginosa arises from loss-of-function of transporter
  25. 25. Experimental setting no AB with AB Small vs Large population size Presence vs absence of antibiotic
  26. 26. Experimental setting x
  27. 27. Experimental setting
  28. 28. Experimental setting Couce (2016) Genetics
  29. 29. PREDICTING GENETIC DIVERSITY OF SPONTANEOUS DRUG- RESISTANCE IN BACTERIA - Short-term diversity - Long-term diversity
  30. 30. Adaptive dynamics in bacteria can be complex
  31. 31. Experimental evolution data 2,000-generations evolution of >100 E. coli populations to low-resource, high-temperature conditions Olivier et al (2012) Science
  32. 32. Experimental evolution data FosR appeared early, and typically stayed at low frequency
  33. 33. Experimental evolution data Dynamics suggesting multiple, unsuccesful sweeps
  34. 34. ● Focusing on mutations ≥2% reveals huge divergence ● It highlights the role of historical contingency
  35. 35. O. Tenaillon lab (Paris, France) J. Blazquez lab (Madrid, Spain) Acknowledgements

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