Ecology, evolution, and antibiotic resistance

1. Ecology, evolution, and antibiotic resistance Carl T. Bergstrom Department of Biology University of Washington University of MichiganDecember 8th, 2005

2. Humankind has conquered infectious disease.

4. The SARS virus The SARS virus

5. H5N1 Avian Influenza

6. The New York TimesJune 13, 2000 Antibiotic Misuse Turns Treatable to Incurable

7. Vancomycin-resistant Enterococcus in US hospital intensive care National Nosocomial Infections Surveillance System Report, 2003

8. How evolution works Variation: different individuals have different traits. Heritability: offspring tend to be somewhat like their parents. Selection: individuals with certain traits survive better or reproduce more. Time: successful variations accumulate over many generations.

9. From “Battling bacterial evolution: The work of Carl Bergstrom” Understanding Evolution, University of California.

12. 2 3 1 Antibiotic-sensitive Antibiotic-resistant Dead

13. Variational Process Transformational Process

14. 2 3 1 1. Where does the variation come from? 2. What does the selecting?3. What are the consequences? 4. How can we intervene?

15. 1 1. Where does the variation come from?2. What does the selecting?3. What are the consequences? 4. How can we intervene?

16. Mutation • Macrolide antibiotics block protein synthesis by binding to bacterial ribosomes. From Hanson et al (2002) Molecular Cell

17. Mutation • A single point mutation in the green binding region can prevent macrolide binding and confer resistance. Modified from Hanson et al. (2002) Molecular Cell

18. Mutation • Genome size: ~ 5 x 106 base pairs • Mutation rate: ~ 2 x 10-3 per genome • Population size: 1010 to 1011 per g fecal matter • A single gram of fecal matter is likely to contain a novel point mutation conferring macrolide-resistance!

19. Natural ecology of antibiotics Soil microbes produce antibiotics to kill competitors.

20. Lateral Gene Transfer Electron micrograph: Dennis Kunkel. http://www.denniskunkel.com

21. Unknown source A. orientalis Vancomycin resistance Lateral gene transfer Vancomycin Resistant Enterococcus

22. 2 1. Where does the variation come from? 2. What does the selecting?3. What are the consequences? 4. How can we intervene?

23. Most resistant strains are commensals

24. Extremely high rate of drug use

25. Hospital staff act as disease vectors ~

26. High rate of patient turnover ~

27. Agricultural use 25 million pounds per year into animal feed! Union of Concerned Scientists, 2001 Much of this being erithromycin, one of the macrolides discussed earlier.

28. Agricultural use 400,000 excess days of diarrhea a year due to floroquinilone resistance (mostly?) in Camphylobacter from chickens.

29. 3 1. Where does the variation come from?2. What does the selecting?3. What are the consequences? 4. How can we intervene? Doesn't take a rocket scientist, let alone an evolutionary biologist. 1 million resistant infections acquired each year in US hospitals. Imposing a financial cost 4-5 billion dollar cost and considerable extended stay times and mortality.

30. Resistance in the Intensive Care UnitNational Nosocomial Infections Surveillance System Report, 2003 Klebsiella pneumoniae Pseudomonas aeruginosa 23 % 10 % 28 % 52 % Enterococcus sp. Staphylococcus aureus

31. In the Community : Macrolide resistance Streptococcus pneumoniae Helicobacter pylori 32 % 20-90 % Up to 70 % Ineffective Haemophilus influenzae Streptococcus pyrogenes

32. Methicillin against . macrolide resistance Vancomycin used . against MRSA MRSA

33. Linezolid? Methicillin against . macrolide resistance Vancomycin used . against MRSA Linezolid against VRE MRSA VRE

34. 2 3 1 1. Where does the variation come from? 2. What does the selecting?3. What are the consequences? 4. How can we intervene?

35. Antimicrobial cycling One-time shift of drugs clears up resistance outbreaks. Antimicrobial cycling takes the same idea further: Try repeated, scheduled rotations among different drugs. • Gentamicin, Piperacillin/Tazobactam and ceftazidime for gram-negatives in a neonatal ICU (Toltzis et al., Pediatrics 2002) • Imipenem/cilastatin, pip / tazo, and ceftazidime + clindamycin / cefepime in a pediatric ICU (Moss et al., Critical Care Medicine 2002) • Carbapenems and ciprofloxacnin + clindamycin, followed by cefepime + metronidazole and pip / tazo in postoperative patients (Raymond et al. Critical Care medicine 2001)

36. Antibiotic cycling • "The `crop rotation' theory of antibiotic use • [suggests] that if we routinely vary our `go to' • antibiotic in the ICU, we can minimize the • emergence of resistance because the • selective pressure for bacteria to develop • resistance to a specific antibiotic would be • reduced as organisms become exposed to • continually varying antimicrobials."- M. Niederman (1997) Am. J. Respir. Crit. Care Med.

37. Infected Susceptible In our black box:Begin with a traditional SI model

38. Community Hospital

39. Translate the gearbox into equations S:patients colonized with sensitive bacteria R:patients colonized with resistant bacteria X:uncolonized patients

40. We can solve explicitly for equilibrium behavior For example, resistance will be endemic when Left side is R0 for the resistant strain. Right side measures the availability of colonizable hosts

41. We can study the dynamics using numerical solution E.g., things change fast. Non-specific control does appreciably reduce resistance.* Formulary changes can rapidly eradicate resistant bacteria.*When resistance is rare in the community

42. Extend our model to multiple resistant strains Community Hospital

43. An ODE model • Two resistant strains, one sensitive strain. • No dual resistance yet.

44. Dynamics of cycling:90 day cycles

45. How do we judge whether cycling works? • Total resistant infections: R1 + R2 • Probability of dual resistance arising by lateral gene transfer: R1 * R2 Baseline for comparison: In each case, compare the outcomes under cycling to an approximation of the status quo: Mixing of the two drugs, in which at any given time half of the patients receive drug 1, the other half drug 2.

46. Total resistant infections Cycling Mixing

47. One year Three months Two weeks Total resistant infections by cycle length Cycling Mixing

48. Average total resistanceincreases with cycle period Cycling Mixing

49. One year Three months Two weeks Rate of emergence of dual resistance

50. Rate of dual resistance evolution is greater with cycling.