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Evolution on empirical adaptive landscapes

Yoav Ram
April 06, 2017

Evolution on empirical adaptive landscapes

The increasing availability of empirical adaptive landscapes in microbes pro- vides an opportunity, for the rst time, to study evolutionary theory on real- istic adaptive landscapes. We demonstrate this new approach by simulating adaptive evolution of a haploid, asexual population on the A. nigeri and the E. coli TEM empirical landscapes. Our results demonstrate some interesting evolutionary phenomena. First, adaptation starts with a big leap forward, but additional tness increases become smaller and further apart. Second, in the smooth E. coli TEM landscape, every genotype along the evolutionary trajec- tory reached high frequency before the next genotype emerged and increased in frequency. In contrast, in the rugged A. niger landscape, only four genotypes reach a high frequency, although adaptation proceeds through seven di erent genotypes. These di erences have profound e ects on our ability to predict the trajectory and pace of adaptation. We consider this new approach critical for our understanding of many biological phenomena, from emergence of drug resistance to formation of microbial communities.

Yoav Ram

April 06, 2017
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  1. Evolution on empirical adaptive landscapes Yoav Ram Stanford University ISM,

    April 2017 1
  2. Adaptive landscapes Sewall Wright, Genetics 1931 Yoav Ram / ISM

    2017 2
  3. Adaptive landscapes Simple or Rugged? Yoav Ram / ISM 2017

    3
  4. Evolution on adaptive landscapes Adaptive peak shifts Yoav Ram /

    ISM 2017 4
  5. Ecology of adaptive landscapes Speciation* * Gavrilets, Evolution 2003 Yoav

    Ram / ISM 2017 5
  6. Empirical adaptive landscapes 6

  7. Evolution of Citrate utilization in E. coli Blount et al.,

    Nature 2012 Yoav Ram / ISM 2017 7
  8. Mt. Citrate Quandt et al, PNAS 2014 Kryazhimskiy & Desai,

    PNAS 2014 Yoav Ram / ISM 2017 8
  9. Empirical adaptive landscapes How to get them? • Evolutionary experiments

    • Phylogeny • Random mutagenesis de Visser & Krug, Nat Rev Gen 2014 Yoav Ram / ISM 2017 9
  10. Example 1: E. coli TEM • β-lactamase TEM gene in

    E. coli • 5 point mutations • Increase resistance to cefotaxime ~100,000-fold. Weinreich et al., Science 2006 Image: Wikipedia Yoav Ram / ISM 2017 10
  11. Example 1: E. coli TEM Single peak landscape Yoav Ram

    / ISM 2017 11
  12. Example 2: Aspergillus niger The black mould Fungus • 5

    auxotrophic mutations • 2 resistance mutations • 1 spore color mutation. de Visser et al., Evolution 1997 Image: Wikipedia Yoav Ram / ISM 2017 12
  13. Example 2: Aspergillus niger Yoav Ram / ISM 2017 13

  14. Example 3: tRNA gene • 65,000 yeast mutants in the

    gene • Fitness ~ biophysical properties of tRNA molecule • 1% single point mutations are beneficial • 42% are deleterious C. Li et al., Science 2016 Yoav Ram / ISM 2017 14
  15. Example 4: E. coli lac system • lac operator mutants

    • Measured expression and repression ability de Vos et al., PNAS 2015 Yoav Ram / ISM 2017 15
  16. Example 4: E. coli lac system • Adaptation facilitated by

    environmental changes • Population can escapes local peaks de Vos et al., PNAS 2015 Yoav Ram / ISM 2017 16
  17. Combining experiments & theory Simulations on empirical landscapes Experiments: -

    genotype ➡ fitness mapping Simulations: - test hypotheses - make predictions Yoav Ram / ISM 2017 17
  18. Simulating evolution Wright-Fisher model Yoav Ram / ISM 2017 18

  19. Simulating evolution Wright-Fisher model • Natural selection: • Mutation: •

    Random genetic drift: Yoav Ram / ISM 2017 19
  20. Simulations on E. coli TEM landscape Obolski, Ram & Hadany,

    2017 Yoav Ram / ISM 2017 20
  21. Simulations on A. niger landscapes Obolski, Ram & Hadany, 2017

    Yoav Ram / ISM 2017 21
  22. Comparison: A. niger vs. E. coli TEM Obolski, Ram &

    Hadany, 2017 Yoav Ram / ISM 2017 22
  23. Comparison: A. niger vs. E. coli TEM Obolski, Ram &

    Hadany, 2017 Yoav Ram / ISM 2017 23
  24. Applications in Microbiology • Generate testable predictions • Use predictions

    to intervene in evolution: • drug & pesticide resistance • virulence • conservation • Study open questions in evolution Yoav Ram / ISM 2017 24
  25. What's next? • Experimental side • More organisms, bigger landscapes,

    precise measurements • Estimates of mutation rates, population sizes, environmental changes • Theoretical side • New methods & models for communities, host-symbiont interactions... Yoav Ram / ISM 2017 25
  26. Thank you! • Collaborators: • Lilach Hadany, Tel-Aviv University •

    Uri Obolski, Univ. of Oxford • Preprint: Obolski, Ram & Hadany, bioRxiv 2017. doi: 10.1101/112177 • Source code: github.com/yoavram/ISM2017 • Homepage: www.yoavram.com • Funding: Yoav Ram / ISM 2017 26