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In memory of John Maynard Smith

In memory of John Maynard Smith. Phenotypic variability is omnipresent in nature. It takes all the running you can do to keep in the same place. If you want to get somewhere else, you must run at least twice as fast. Lewis Carroll, 1871. environmentally. intraspecific. induced adaptation.

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In memory of John Maynard Smith

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  1. In memory of John Maynard Smith

  2. Phenotypic variability is omnipresent in nature

  3. It takes all the running you can do to keep in the same place If you want to get somewhere else, you must run at least twice as fast Lewis Carroll, 1871

  4. environmentally intraspecific induced adaptation variability • • • • • • A A A B B B Lamarckian Paradigm natural natural selection selection • • • • • • B A A B B A Darwinian Paradigm

  5. Darwinian evolution : variability, selection, transmission Number of copies time Adaptives mutations : 0 1 2 3 4 5 6 Can be applied to any «amplifiable  information» (Dawkins, 1976, « the selfish gene »)

  6. wildtype mutS+ Mutator mutS- • 10-5 • 10-4 • 10-8 • 10-3 • 10-2 • 10-6 Different types of MUTATIONS • Neutral • Lethal • Deleterious • Adaptives Estimated total mutation rate for bacteria 1 mutation / 300 genomes replicated An invariant in evolution of DNA !? (Drake rule)

  7. nucleotide pool Fidelity of synthesis post-replication control DNA repair Mechanisms controlling the maintenance of genetic information

  8. Photoactivation Repair in E. coli • Exposing UV treated cells to blue light results in a reversal of the thymine dimer formation • Enzyme, photoactivation repair enzyme (PRE) absorbs a photon of light (from blue light) and is able to cleave the bond forming the thymine dimer. • Once bond is cleaved, DNA is back to normal

  9. Excision Repair Like other repair system It is conserved throughout evolution, conserved from bacteria (where first discovered) to man where they are involved in a variety of disease

  10. Xeroderma Pigmentosum & Nucleotide Excision Repair • Xeroderma pigmentosum (XP)- is a rare genetic disorder that predisposes an individual to skin abnormalities • Individuals lose the ability to undergo NER • UV radiation exposure leads to reactions from freckling and skin ulceration to skin cancer • Studies suggest many different genes may be involved in excision repair • XP-variant is encoding a lesion by-pass DNA polymerase (SOS)

  11. By-pass polymerases can lead to error free or error prone (mutagenic) synthesis depending on the lesion

  12. Oxidation of guanine lead to transversion

  13. Mismatch site The Mismatch Repair System CH3 MutS MutL GATC-site MutH ExoI, ExoVII, RecJ, UvrD, PolIII, SSB, Ligase • Mismatch repair system • corrects replication errors • ensures global genomic stability • prevent tumour formation CH3

  14. The frequencies of mutator among E. coli vary with the associated pathologies Denamur J. bacteriol. 2002

  15. only in non-mutator strains Number of virulence factors correlates with in vivo virulence Picard Infect.Immun. 2001

  16. Mutation rates are higher among strains with intermediate virulence Picard Infect.Immun. 2001

  17. Modelling mutators frequencies during adaptation to a new environment Mutator frequency Time (generations)

  18. Selecting for mutators is easier in larger population Tenaillon Genetics (1999)

  19. When mutation is rate limiting large population adapt much faster log (population size) Tenaillon Genetics (1999)

  20. Mutator can speed up adaptation (even when rare) log (population size) Tenaillon Genetics (1999)

  21. An in vivo model: an animal with a controled microbial flora Kiss me I ’m germ-free Giraud

  22. mutS- mutS- mutS+ Evolution of population size 10,2 10,0 9,8 log (population size) 9,6 9,4 mutS+ 9,2 9,0 8,8 days 0 5 10 15 20 Mutator bacteria adapt faster to a new environment Giraud Science 2001

  23. mutS-/ 50 000 mutS+ mutS-/mutS+ mutS-/ 50 mutS+ The initial population size influence the outcome of the competition 5 4 3 2 1 0 Mean log(mutator/wild type) -1 -2 -3 -4 -5 0 1 2 3 4 5 6 7 8 9 10 Time (Days) Giraud et al Science 2001

  24. The population threshold for mutator victory is 1/(mutation rate) Mutator victory threshold is frequency independent Le Chat

  25. The victory is stochastic with a constant expected gain Le Chat

  26. Naive adapted Once adaptation is achieved the mutator advantage is reduced 3.5 3 2.5 2 1.5 1 Mean log(mutator/wild type) 0.5 0 -0.5 -1 0 1 2 3 4 5 6 7 8 9 10 Time (Days) Giraud et al Science 2001

  27. 3 3 WT+Mut Mut WT 2 2 Log(mutS-/ mutS+) 1 Log(mutS-/ mutS+) 1 0 0 Days -1 0 2 4 6 8 10 Days -1 0 2 4 6 8 10 Mutators & migration in vivo The benefit of the mutator is reduced in presence of migration

  28. Controlling migration timing in vitro migration migration WT Mut V V V V media: LB + Spc Mut : mutS- 24 h 24 h 0 12 15 24 18 21 hours Le Chat

  29. " m i g r a t i o n " 3 1 0 9 , 5 2 , 5 9 2 8 , 5 1 , 5 log (mutator/WT) 8 log (CFU) 7 , 5 1 7 0 , 5 6 , 5 6 0 5 , 5 - 0 , 5 5 9 1 2 1 5 1 8 2 1 2 4 9 1 2 1 5 1 8 2 1 2 4 The benefit of the mutator disappears if adaptation is over before migration Mutator population adapt faster mutator non mutator

  30. Mutator bacteria suffer from genetic amnesia nd nd non mutator Emerging mutator 30 25 20 Mean % of auxotrophs 15 10 5 mutS- ancestor mutS+ ancestor 0 100 150 200 250 300 Days post inoculum Giraud et al Science 2001

  31. 1 mouse 1 mouse 11 11 10 10 9 9 8 8 7 7 6 6 5 5 4 4 3 3 2 2 0 5 10 15 20 0 5 10 15 20 fos spc fos spc R population Rif Impact of antibiotic treatments on mutation rates 4 mice 11 10 9 8 7 6 Log (population size) 5 4 3 2 10 15 0 5 20 fos spc

  32. 1 mouse 1 mouse 11 11 10 10 9 9 8 8 7 7 6 6 5 5 4 4 3 3 2 2 0 5 10 15 20 0 5 10 15 20 fos spc fos spc streptomycin Nalidixic acid fos Day 0 : inoculation spc time Measures of population sizes

  33. 11 10 9 8 mutator 7 6 Log ( population size) 5 4 non mutator 3 2 0 5 10 Impact of mutation rates on bacterial survival to antibiotic treatments str + nal

  34. a g a i n st m u t a t o r b a c t e ri a  ? H o w m a ny a n t i b i o ti c s s h o u l d be u s e d P er c e nt a g e o f t re at m e n t fa i lu r e N u m b er of an tibi o ti c s a d m ini s t e r ed s im u lt a n eo usl y A n ces tra l g en ot y p e 1 2 3 + A nt i m u t a tor ( m ut S ) 100 0 ( + 17*) n.d. - M u t a tor ( m ut S ) n.d. 70 0 - * e m e r gin g mut a to r ( 2 m u t S ) Giraud AAC (2002)

  35. Mutator bacteria are more likely to become antibiotic resistant Denamur J. bacteriol. 2002

  36. Non mutator (A) and mutator (B) phenotypes on antibiograms Denamur et al J. bacteriol 2002

  37. Mutators are abundant and more antibiotic resistant among P. aeruginosa infecting Cystic Fibrosis patients Mutator (CF) Non-mutator (CF) Non-CF Oliver Science (2000)

  38. Resistance accumulate 3 times faster in patients colonised by mutators Non mutator Mutator Probability of increased resistance delay (days) Moumile

  39. Cell number time Cell number time Mutator can speed up cellular evolution Adaptives mutations 0 1 2 3 4 5 6 Mutator sub-population

  40. The bacterial Red Queen

  41. Moumile Diard

  42. www.necker.fr/tamara/ Join Fun & Science in Paris

  43. Hyper-recombination phenotypes of mismatch repairmutants Denamur Cell (2000)

  44. Homologous Recombination A • exchange of DNA • 1strands to form • heteroduplex DNA • cleavage of Holliday • junction at A or B • religation to • recombinant products • A: splice products • B: patch products B B Holliday junction A + Splice + Patch

  45. The barrier to recombination is DNA sequence divergence Vulic PNAS (1997)

  46. Homeologous Recombination mismatch - mismatch + • divergent sequences • do not recombine efficiently • mismatch repair prevents • formation of recombination • intermediates • in mismatch repair deficient • background homeologous • recombination proceeds to • generate mosaic genes and • genomes Holliday junction + Splice + Patch

  47. Effect of Mismatch Repair System on Interspecies Recombination

  48. Inhibition of Mismatch Repair System • increases homeologous recombination to the level of • homologous recombination and thus allows • interspecies recombination • allows broadest genetic variability in vivo • broad area of applications • generation of novel low molecular weight entities • generation of modified and optimised macromolecules • generation of (micro)organisms with desired properties

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