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Pathogen Virulence: Evolutionary ecology Outline: 29 Jan 15 Functionally Dependent Life-History Traits: Virulence Important Example Pathogen Traits Evolve.

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Presentation on theme: "Pathogen Virulence: Evolutionary ecology Outline: 29 Jan 15 Functionally Dependent Life-History Traits: Virulence Important Example Pathogen Traits Evolve."— Presentation transcript:

1 Pathogen Virulence: Evolutionary ecology Outline: 29 Jan 15 Functionally Dependent Life-History Traits: Virulence Important Example Pathogen Traits Evolve via Strain Competition Spatially Structured Transmission Dispersal Limitation Reduces Virulence 1

2 Virulence Property of Host-Parasite Interaction Parasite Generation Time Much Shorter Virulence: Parasite’s “Strategy” for Exploiting Host Virulence Evolution Affects Correlated Demographic Traits Functional Dependence = Pleiotropic Interaction 2

3 Increased Parasite Virulence Faster Consumption of Host Resources  (1) Pathogen Reproductive Rate Increases (2a) Host’s Mortality Rate Increases or (2b) Rate of Clearance by Immune System Increases or (2c) Host Reproduction Decreases 3

4 Virulence Trade-Off Antagonistic Pleiotropy Pathogen Increases Propagule Production (Hence, Infection Transmission) Rate Duration of Infectious Period Decreases Evidence Reviewed 4

5 How Does Virulence Evolve? Pathogen-Stain Competition 2 Phenotypes Differ in Virulence (Resident, Mutant) Compete Between (and) Within Hosts 3 Modes of Strain Competition 5

6 Pathogen-Strain Competition 1. Cross-Reactive Immunity Competition Strictly Between-Host Scale Flu strains 2. Coinfection: Two Strains Exploit Same Host Individual Compete Both Within & Between-Host 3. Superinfection: More Virulent Strain Excludes Other Compete Both Within & Between-Host 6

7 Strain Competition Important Ecological Generality Cross-Reactive Immunity Example of Pre-emptive Competition Two Species (Strains), Same Niche (Allstadt et al. 2009) 7

8 Strain Competition Important Ecological Generality Coinfection: Example of Scramble Competition = Exploitative Competition Two Species Interact Indirectly Through Exploitation of Same Limiting Resource 8 From

9 Strain Competition Important Ecological Generality Superinfection: Example of Interference Competition Two Species Interact Directly Aggressive Exploitation of Same Limiting Resource 9

10 Strain Competition: Adaptive Dynamics Host-Pathogen Dynamics Exert Selection Pressure on Competing Strains Mutant-Resident Competition Competitive Exclusion; Alter Parameters of Dynamics Evolutionarily Stable Strategy (ESS) Resists Invasion Adaptive Dynamics: Interplay of Ecology, Evolution 10

11 Strain Competition: Adaptive Dynamics “Solve” Strain Competition for a Preemptive Case General: ESS Virulence Graphically Virulence Evolution in a Second Preemptive Case Pathogen with Free-Living Stage e.g., Bacteriophage Superinfection, Vary Pathogen Dispersal Distance Impact on ESS Virulence 11

12 Cross-reactive Immunity One Strain per Infected Host Individual Strain Competition : Between-Host Scale Only Ecology: Preemptive Competition 12

13 Host Preemption Assume Homogeneous Mixing Host Population “Optimally Virulent” Strain, Max R 0 Equivalently Minimizes Equilibrium Density Susceptible Hosts No Strain Coexistence (Pure ESS) Recall: Same Niche 13

14 Host Preemption Homogeneous Mixing, No Recovery Transmission-Infectious Period Trade-off  (  ) Transmission Efficiency, Direct Contact  (  ) Virulence, Extra Infected-Host Mortality  Host Exploitation Strategy: d  /d  > 0 14

15 Natural Selection: Optimize  Invasion Dynamics (Conceptual Core) Can Rare Mutant  Invade Resident  * at ecological (dynamic) equilibrium? This case: ESS does Max R 0 (  )  : Background Host Mortality S: Susceptible Density 15

16 Natural Selection: Optimize  SI Transmission Plus Host Birth, Death Resident Pathogen’s Dynamics Sets Resource Availability (Susceptible Density) for Mutant Strain of Pathogen Can Mutant find enough hosts to grow when rare? 16

17 Natural Selection: Optimize  b Per-capitum Birth  Transmission Rate (Mass Action)  Non-Disease Mortality (All) (  +  ) Infective Mortality  : Virulence > 0 No Recovery from Infection 17

18 Dynamics of Epidemic Birth, Infection Transmission, Death 18

19 Analysis 19

20 Natural Selection: Optimize  20

21 21

22 Natural Selection: Optimize  22

23 Natural Selection: Optimize  23

24 Natural Selection: Optimize  von Baalen & Sabelis (1995, Am Nat) 24

25 Natural Selection: Optimize  1. ESS Virulence Maximizes R 0 (for any Susceptible Density) 2. ESS Virulence Minimizes Susceptible Density Too Few Susceptible Hosts for Mutant Invasion 3. Greater Background Mortality   Greater Virulence 25

26 Natural Selection: Optimize  4. ESS May Exhibit Intermediate Virulence Under Host Preemption; Natural Diversity 5. No Strain-Coexistence Possible Under Well-mixed, Preemptive Competition 26

27 Preemptive Host Competition Pathogen with Free-Living Stage Life History: Alternates Intra-Host Environment, External Environment Bacteria/Viruses, Including Bacteriophage “Curse of the pharaoh” Persistent free-living stage costly; Requires conversion of large amount of host resources; Pathogens with persistent free-living stage likely virulent 27

28 Host-Pathogen Dynamics 28

29 Host-Pathogen Dynamics 29

30 30

31 ESS Virulence: Pathogen Strain Competition Preemptive Competition: ESS Minimizes S* Positive Equilibrium Density of Susceptibles Traits: Functionally Dependent Altering Virulence: Antagonistic Pleiotropy 31

32 ESS Virulence: Pathogen Strain Competition 32

33 Functional Constraint: Virulence(Decay Rate) 33

34 Minimize S* 34

35 Minimize S* 35

36 Shed Rate > 0 and Burst Size > 0 36

37 Preemptive Host Competition Strain Minimizing Equilibrium Density of Susceptibles Should be ESS No Coexistence of Different Levels of Virulence (Not True for Coinfection and Superinfection) Curse of the Pharaoh Oversimplifies Strain Competition Caraco annd Wang (2008) J Theor Biol 250:

38 Homogeneous Mixing Host Population Assumed in Dynamics Full Mixing: Hosts Highly Mobile over Timescale of Expected Lifespan Might Preclude Terrestrial Plants, Territorial Animals, etc.: “Viscous Populations” 38

39 Contact Structure, Van Baalen (2000) 39

40 Pathogen: Dispersal Limitation Contact Structures: Constrain Opportunities for Pathogen to Generate New Infections Ecology: Dispersal Limitation, Neighborhood Interactions Ecological Implications: Epidemic Invasion, Endemic Infection Levels Evolutionary Implications: (Including) Virulence 40

41 Pathogen: Dispersal Limitation Contact Structure: (L x L) Lattice Each Site: One of 4 Elementary States Local Neighborhood: All Ecological Interactions Opportunities for Host Reproduction (Open Sites) Sources of Infection 41


43 SPATIAL SUPERINFECTION Virulent Can Displace “Avirulent” Strain Interference Competition Discrete-Time Dynamics Transmission (Virulence); No Recovery Key: Superinfection (Virulence Difference) Within & Between-Host Competition Neighborhood Size: 8, 48 43

44 Develop Concepts 1. Mean-Field Analysis: Homogeneous Mixing 2. Pair Approximation: Local Correlation 3. Simulate Full Stochastic Spatial Model: Large-Scale Correlated Fluctuations, Strong Clustering Possible 44

45 Develop Theory: Deduce Predictions Pairwise Invasion Analyses: Adaptive Dynamics Resident Strain at Ecological Equilibrium Can Invading Strain (Mutant) Advance? Assumed Time Scales Convergence Stability; Evolutionary Stability 45

46 SPATIAL SUPERINFECTION Dynamics: Local Transition Probabilities Stochastic Spatial Model How do local interactions produce ensemble effects (population, community scales)? Model/Theory: Caraco et al. (2006) Theoretical Population Biology 69:

47 Mean-Field Results Pairwise Invasion Homogeneous Mixing Evolution to Criticality Coexistence: Niche Difference 47

48 Mean-Field Results Pairwise Invasion Homogeneous Mixing Coexistence: Niche Difference Competition- Colonization Trade-Off 48

49 Spatial Model Results Increased Virulence Decreased Infection Increased Clustering Pair Correlation Model OK 49

50 Adaptive dynamics spatial process Pair Approximation Convergent Stable Evolutionarily Stable (Local ESS) Virulence Constrained By Contact Structure 50

51 Adaptive dynamics spatial process Simulation Max Virulence Lower Local ESS Reduced 51

52 Adaptive dynamics spatial process Weaker Competitive Asymmetry Via Superinfection Reduce ESS Reduce Coexistence 52

53 predict 1. Spatial Structure Constrains Maximal Virulence Capable of Dynamic Persistence, Through Extinction of Highly Virulent Strains 2. Spatial Structure Reduces Evolutionarily Stable Level of Virulence 3. Larger Neighborhood Relaxes Constraint, Dynamic Penalty of Clustering Attenuated 53

54 predict 4.Spatial Structure Promotes Coexistence: Extended Transmission/Low Virulence, Poor Interference Competitor/Good Colonizer and Attenuated Transmission/High Virulence, Advantage of Superinfection/Poor Colonizer 5. Coexistence Increases with Neighborhood Size 6. Comp. Asymmetry Increases Coexistence 54

55 Contemporary Questions Virulence in Pathogens with Both Contact and Environmental Transmission Avian Flu: Contacts; Virus Persists In Drinking Water Hyperparasites & Hypovirulence Vertical Transmission Sterilizing vs Killing Pathogens 55

56 Contemporary Questions Vector-Borne More Virulent Than Direct Contact (?) FLP: “Curse of the Pharaoh” Conditions for More Virulence Infective Dose: Remarkable Variation Ecological Consequences Strain Competition? 56

57 Contemporary Questions Within-Host Dynamics Parasite, Specific Immune Cell Densities Affects Between-Host Transmission Population Dynamics Host-Pathogen Coevolution Transmission Resistance, Tolerance Virulence, Optimal Immune Response 57

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