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General topic: how do pathogen/pest populations respond to deployment of host resistance?. Selective effects of qualitative resistance (R genes) Natural vs. human-created systems How does evolution to virulence affect pathogens – is there a cost to virulence?

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General topic how do pathogen pest populations respond to deployment of host resistance l.jpg

General topic: how do pathogen/pest populations respond to deployment of host resistance?

  • Selective effects of qualitative resistance (R genes)

    • Natural vs. human-created systems

    • How does evolution to virulence affect pathogens – is there a cost to virulence?

    • Can durability of R genes be predicted

  • Selective effects of quantitative (partial) resistance

  • Evolution of pathogen populations with host-selective toxins (HSTs)

  • What affects evolutionary potential of pathogen populations


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Terminology

  • Using Vanderplank’s definitions:

    • Virulence: specific disease-causing ability

    • Aggressiveness: non-specific disease-causing ability

  • Other definitions are used, especially in host-pathogen co-evolution (natural systems, human infectious diseases)

    • Virulence: damage a pathogen strain causes to a host


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Selective effects of R genes on pathogen populations

  • Natural, co-evolving systems vs. artificial, agricultural/horticultural systems

  • In co-evolving systems

    • “Arms race” model (discussed in Holub, 2001, “The arms race is ancient history in Arabidopsis, the wildflower,” Nat. Rev. Genet. 2:516-527.)

      • Transient polymorphism: continual selective turnover of alleles; “selective sweeps” where R genes driven to extinction


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  • Evolution of R genes in local populations: Transient polymorphism model of co-evolving host-pathogen system (Holub et al)

  • Resistance alleles would be relatively young, nearly identical in sequence to susceptible alleles


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In contrast: the “trench warfare” model of natural (co-evolutionary) systems:

  • Balanced or “dynamical” polymorphism

  • Epidemics alternate with periods of high host resistance and low pathogen population

  • Resistance and susceptibility alleles would be old, differ greatly in DNA sequence


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Trench warfare model – natural system

  • Around Rpm1 deletion site, divergence between R and S alleles indicates Rpm1 polymorphism arose 9.8 Million years ago – old!


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Corroborating evidence: Puccinia coronata on Avena sterilis (wild oat) in Israel, a stable coevolving pathosystem in the center of origin

  • Virulence/avirulence polymorphisms are highly diverse –

    • extreme genetic diversity in the host (many resistance types)

    • matched by broad range of virulence patterns in pathogen

    • Accumulation of many R and vir genes

  • Natural selection prevented from going to fixation of R genes and Vir genes – balancing selection

  • Prevalence of low-reaction resistance types over 17 years; Pc genes effective in the 1960s and 1970s are still effective against a large proportion of isolates 20-30 years later

  • “…An example of stability of wild pathosystems that consist of natural mixtures of resistance and virulence.”

Leonard et al, 2004, Phytopathology 94:505-514


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More on evolution of resistance and virulence in natural systems:

  • Tellier and Brown, 2007, Polymorphism in multilocus host–parasite coevolutionary interactions, Genetics,177: 1777–1790.

  • Thrall and Burdon, 1997, Host-pathogen dynamics in a metapopulation context: the ecological and evolutionary consequences of being spatial, Journal of Ecology 85:743-753

  • Thompson and Burdon, 1992, Gene-for-gene coevolution between plants and parasites, Nature 360:121-597


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Some conclusions from natural systems

  • There is substantial polymorphism at R and Avr loci both within populations and across spatially separated subpopulations

  • Some of these polymorphisms are ancient, indicating that selective forces are preserving them

  • Spatial dynamics are key (see Thrall and Burdon):

    • The stability of host-parasite interactions strongly affected by spatial substructuring

    • Patchiness promotes persistence of resistance/virulence polymorphisms

  • Extreme “booms” and “busts” appear to be a feature of human deployment of resistance


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Pathogen populations evolve differently in human-influenced systems

  • R-gene breakdowns in agricultural systems tend to be dramatic and relatively complete

    • In artificial systems, humans constrain host evolution, deploy R genes in vast swaths

    • Pathogens evolve virulence

    • Humans deploy new R genes

    • Etc.


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Comomnly deployed wheat powdery mildew (Pm) resistance genes in NC

% isolates virulent


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Less commonly deployed Pm genes in NC

% isolates virulent


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How does evolution to virulence affect pathogens?

  • Is there a fitness cost to having a virulence gene?

  • Vanderplank, 1963 & 1968:

    • Releasing a new R gene causes directional selection: virulent pathotypes increase in frequency

    • When R gene is defeated, withdrawing it from production leads to “stabilizing selection”: pathogen races with unnecessary virulence genes are eliminated


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Types of natural selection

Step 1

Step 2


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What is pathogen fitness?

  • The combined ability of an organism to survive and reproduce

  • Quantifiable

    • Reproductive rate

    • Infection efficiency

    • Aggressiveness (amount of disease caused)

      • Disease severity

      • AUDPC

    • Frequency of a strain relative to other strains can be used as an estimator of fitness


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Estimating fitness

Genotype A: 10 lesions/lesion/day

  • Fitness (W) is a relative parameter -- expressed relative to the most fit genotype (with fitness = 1.0)

    • Relative fitness of B = WB: 0.9

Genotype B: 9 lesions/lesion/day

  • Selection coefficients (s) are also compared to estimate changes in fitness of isolates over time; they measure the intensity of natural selection on a genotype (e.g., Zhan et al, 2002, J. Evol. Biol. 15:634-647)

    • Selection coefficient = the proportion by which the fitness of a genotype is less than that of the most fit

    • selection coefficient (s) of most fit (most frequent strain) is set to 0, so its W = 1. Relative fitness of other isolates is 1 – s.


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For example: (Zhan et al)

  • Co-inoculate multiple strains in equal proportions early in season, let them compete throughout season

  • Measure end-of-season frequencies

  • Most fit strain = highest-frequency strain

  • Selection coefficient of Gi (the ith genotype) =

    si = 1 - pit pj0

1/t

pjt pi0

Where p = frequency, t = time, and 0 = inoculation time

0 ≤ s ≤ 1.

  • Bottom line: we infer that end-of-season frequency of a strain reflects relative fitness

  • Selection coefficient measures the intensity of selection on that genotype (larger s = higher negative selection against that genotype). Fitness = 1 – s.


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Is there a cost to virulence?

  • How dissociate effect of virulence gene from pathogen’s genetic background?

    • Near-isogenic lines (NILs) of pathogen (Leonard, 1977, Phytopathology 67:1273-1279; Klittich & Bronson,1986, Phytopathology 76:1294-1298)

    • Averaging over large isolate collection (Leonard, 1969, Phytopathology 59:1851-1857)

    • Crosses to dissociate virulence alleles from genetic background (Bronson & Ellingboe, 1986, Phytopathology 76:154-158)

    • Mutants (Prakash & Heather, 1986, Phytopathology 76:266-269)

    • Genetic transformation (Keller et al., 1990, Phytopathology 80:1166-1173)

    • Site-directed mutagenesis (Lindemann and Suslow, 1987, Phytopathology 77:882-886)


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Xi et al. , 2003, Mycol. Res. 107:1485-1492

Fig. 1. Frequency of pathotypes E97-2 and H97-2 of Rynchosporium. secalis co-inoculated over 4 cycles on two barley cultivars: (a) ‘Earl,’ susceptible to E97-2, and (b) ‘Harrington,’ susceptible to both.

E97-2 had complex virulence (to Earl, Harrington, and 5 more cvs).

H97-2 had simple virulence (to Harrington and 1 other cv, not Earl).


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  • “E97-2, a pathotype with unnecessary virulence genes against a susceptible cultivar, had greater parasitic fitness compared with H97-2, a pathotype without unnecessary genes for virulence.” (Xi et al)


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Same pathosystem, different conclusion:

  • Among 8 R. secalis isolates, negative correlation between complexity on barley differentials in GH and competitive fitness in the field Abang et al, 2006, Differential selection on Rynchosporium secalis during parasitic and saprophytic phases in the barley scald disease cycle, Phytopathology 96:1214-1222.

  • “Our finding that virulence complexity was negatively correlated with fitness suggests that directional selection against unnecessary virulence operates in this pathosystem.”


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Aggressiveness scores negatively correlated with isolate complexity


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Opposing Vanderplank: little evidence of long-term cost to “unnecessary” virulences

  • Parlevliet, 1981, Stabilizing selection in crop pathosystems: an empty concept or a reality? Euphytica 30;259-269:

    • “stabilizing selection” occurs in two-step process

      • Avr -> vir temporarily decreases fitness

      • Selection for fitness modifiers that overcome loss of fitness

  • Evidence from antibiotic resistance:

    • In Bacillus subtilis, both fitness modifiers and alternative alleles amelioriate fitness losses (rifampicin resistance) (Cohan et al., 1994, Evolution, 48:81-95)

    • With time, antibiotic-resistant bacteria that initially are less fit in absence of antibiotic regain relative fitness via “compensatory mutations” (Morrell, 1997, Antibiotic resistance: road of no return, Science, 278:575-576)


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Contrary evidence from malaria parasite

  • In 1993, Malawi became the first country in Africa to replace chloroquine with the combination of sulfadoxine and pyrimethamine for the treatment of malaria.

  • At that time, the clinical efficacy of chloroquine was less than 50%.

  • Molecular marker for chloroquine-resistant Plasmodium subsequently declined in prevalence and was undetectable by 2001

  • Chloroquine once again effective in Malawi.

  • How did the frequency of the drug-resistant allele change in Plasmodium?


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So: if you remove a defeated R gene from commercial production, will the corresponding virulence in the pathogen population decline in frequency?

  • One would expect this to happen IF virulence carries a fitness penalty

  • It’s assumed by some:

    • E.g.,“Deployment of disease resistance genes by plant transformation – a ‘mix and match’ approach,” Pink and Puddephat, 1999, Trends in Plant Science, 4:71-75


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“A great advantage of the strategy is that it does not depend upon a supply of new resistance genes….Existing resistance genes can be recycled. For example, if a gene, or gene combination, is withdrawn because the frequency of the matching virulence increases in the pathogen population it can be re-introduced when thefrequency of the matching virulence allele(s) reduces.” (Pink & Puddephat)


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Best guess:

  • In general, if R gene is removed from use, frequency of virulence may decrease, but will likely remain sufficient to “flare up” again if R gene is redeployed

  • But magnitude of fitness penalty and length of time needed to restore fitness via compensatory mutations probably varies from virulence mutation to virulence mutation

  • So R genes may vary in durability (compared “head to head,” i.e., deployed on equal acreage, etc.)


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Is there some way to predict durability of particular R genes?

  • Leach et al, 2001. Pathogen fitness penalty as a predictor of durability of disease resistance genes, Annu. Rev. Phytopathology 39:187-224.

    • Reviews evidence related to hypothesis that durability of a resistance gene is a function of the amount of fitness penalty imposed on pathogen.


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Differences in durability of single-gene mediated resistance

  • Some single R genes have proven durable –

    • Monogenic resistance to Fusarium oxysporum in crucifers has lasted 90 yrs

    • Lr34 resistance to wheat leaf rust (Puccinia triticina) has lasted over 30 yrs

  • Xa3, Xa4 resistance in rice to Xanthomonas oryzae durable 10-15 yrs before virulence emerged, still has some effect.


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Some avr genes contribute to fitness

  • Bacteria: Some avr genes control both virulence and avirulence (both elicitors of HR and agents of pathogenicity)

    • Xanthomonas spp. (bacterial pathogens of pepper, tomato, citrus, etc.)

      • avrBs2 -> protein that’s secreted into plant cells; avrBs3 family -> ability to multiply intercellularly; lesion length

    • Pseudomonas syringae pv. tomato

      • avrRpt2 -> blocks activation of defense responses


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Fungal genes with dual function in virulence and avirulence - necrotrophs

  • Cladosporium fulvum (tomato pathogen)

    • Elicitors Avr4, Avr9: Avr4 protects pathogen against chitinase (van den Burg et al, 2006, MPMI, 19:1420–1430)

  • Rynchosporium secalis (barley scald)

    • NIP1 = AvrRs1: kills host cells, releases nutrients

  • Magnaporthe grisea (rice blast)

    • AVR-Pita -> protease expressed after pathogen is inside plant; fitness function unclear


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Avr genes and fitness (summary)

  • Not all avirulence genes make a measurable contribution to fitness

    • Mutations in Xanthomonad genes avrXa10 and avrBs3 did not cause measurable loss in aggressiveness

  • Some do, and relative magnitude of contribution to fitness may vary, even within highly similar gene family

    • avrXa mutants to virulence exhibit different fitnesses (discussed later)

  • Avr genes may contribute to different fitness attributes

    • Intercellular multiplication

    • Exit of intercellular spaces to leaf surface, etc.


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So if avr genes affect fitness differentially, mutations in them should differentially affect fitness, and R genes corresponding to them should be differentially durable.

  • Fitness penalty due to loss of avr function may be compensated by functional redundancy

    • There may be many copies (e.g., PWL genes in M. grisea, or avrBs3 genes in xanthomonads) some functioning as fitness but not recognition factors, or vice versa

  • Some of structural requirements for fitness and avirulence may be different – it may be possible to lose avirulence function without losing virulence function

    • AvrPto single amino-acid mutants lost avr but not vir function

  • In some cases, amount of avirulence protein can be down-regulated to avoid induction while maintaining virulence function

    • Phytophthora parasitica produces v low levels of elicitin


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Can we PREDICT which R genes will be more/less durable? Example #1:

  • Bai et al knocked out individual avr genes in X. oryzae (2000, MPMI 13:1322-1329).

  • Assayed isolates for fitness (also growth on IR24 leaves, not shown)

  • Avr gene with biggest effect on fitness predicted to correspond to R gene with greatest durability: which one? avrXa7

Tested in field with NILs, natural inoculum. Over 3 yrs, durability of Xa7 > Xa10.


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Example #2:

  • Laugé et al: screen for elicitors (avr products) that are important virulence factors, then search for resistance (1998, PNAS 95:9014-9018)

    • Knew avr4 and avr9 could be knocked out without detectable fitness penalty (Cladosporium fulvum on tomato)

    • Knew ECP2 was important virulence factor because ECP2 knockouts only weakly pathogenic

    • Identified 21 lines with resistance beyond known R genes, challenged them with ECP2: 4 had HR

    • If virulence and avirulence do not involve separate domains in ECP2, new R gene Cf-ECP2 expected to be durable


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How do pathogen populations evolve in response to quantitative resistance?

  • Selection is operating on pathogen aggressiveness

    • non-specific pathogenic ability (usually polygenic)

    • the average amount of disease across several host cultivars with different degrees of partial resistance

    • Can be measured as AUDPC or disease at a particular timepoint

  • Model predicts increasing levels of quantitative host resistance select for increasing levels of damage by parasite, while qualitative host resistance does not have same effect (Gandon and Michalakis, 2000, Proc. R. Soc. Lond. B 267:985-990).

  • Not much empirical data!


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Do partially resistant hosts select for more aggressive pathogen populations?

  • Potato cyst nematodes (Globodera pallida) reared several generations on R potato cultivars had increased reproductive rate, those on S cultivars did not (Schouten and Beniers, 1997, Phytopathology, 87:862-867).

  • Greater multiplication by Lettuce mosaic virus in PR lettuce cultivars may have led to new, more aggressive viral pathotypes (Pink et al, 1992, Euphytica 63:169-174)


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Cowger and Mundt, 2002, Aggressiveness of Mycosphaerella graminicola isolates from susceptible and partially resistant wheat cultivars, Phytopathology 92:624-630

  • Planted six wheat cultivars varying in level of partial resistance; natural epidemic developed

    • Epidemics are initiated by ascospore showers, then develop via rainsplash of conidia

  • Collected M. graminicola isolates early in growing season, and again late (after time for selection on each host)

  • Inoculated isolates on seedlings of same six cultivars in greenhouse (5-10 isolates bulked by cultivar of origin, field rep, and collection date)

  • Found no difference in aggressiveness of late-season isolates from MR vs. S cultivars. Then looked at difference between early and late collections:


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Mycosphaerella graminicola (Septoria leaf blotch) on wheat

Cowger & Mundt, 2002


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  • Contrary evidence from Zhan et al:

    • Mean selection coefficients (s) for 6 isolates of M. graminicola lower on Madsen (MR) than on Stephens (S)

    • Pathogen populations collected from Madsen maintained highest genotype diversity, showed smallest change in genetic structure during one growing season

    • Supported hypothesis that PR hosts can retard rate of evolution in pathogen populations

  • However, Abang et al, 2006 Phytopathology 96:1214-1222 used similar method on Rhynchosporium secalis (barley scald)

    • Mean selection coefficients for 5 isolates were significantly higher on MR cultivar than on three S cultivars

    • Showed differential selection during parasitic and saprophytic phases – mutant pathotypes able to infect newly released resistant cultivars may grow in frequency more slowly than expected if they are good competitors during saprophytic phase.


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Mundt et al., 2002

Probably 1 major gene (Stb4?)

No known major gene

= start of commercial production


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Bottom line on PR

  • Majority of evidence is that moderate resistance selects for more aggressive pathogen strains than does susceptibility

  • But the breakdown of moderate resistance is likely slower than that of a single major gene


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Host-selective toxins (HSTs)

  • HSTs categorized as

    • Small proteins

      • Pyrenophora tritici-repentis PtrToxA (cause of tan spot in wheat)

      • Phaeosphaeria nodorum SnTox series

      • Cassiicolin (Corynespora cassiicola causes leaf fall on rubber)

    • Secondary metabolite clusters, e.g., AAL-toxins (Alternaria alternata on tomato)

  • Keep in mind: some fungal phytotoxins in both categories are not host-selective, rather they have broad activity:

    • Small proteins:

      • NIPs in Rynchosporium secalis (cause of barley scald)

    • Secondary metabolite clusters

      • Gibberellins and tricothecenes in Gibberella zeae = Fusarium graminearum (cause of Fusarium head blight or scab of small grains)

      • Aflatoxins (Aspergillus)


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First HSTs identified in 1930s-40s

Many important fungal pathogens in the class Dothideomycetes produce host-specific toxins (at least 20 fungal spp.)

Only active against specific host; most required for pathogenicity

“Inverse gene-for-gene” system; HSTs are “agents of compatibility” (Walton, 196, Plant Cell 8:1723-33)

How do fungal pathogen populations evolve in response to host resistance when HSTs are central to pathogenesis?

Pyrenophora tritici-repentis causes red smudge on durum wheat kernels; purified Ptr necrosis toxin on wheat leaves

No Disease

Disease

No Disease

No Disease


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  • Not an HST, nor even a toxin!

  • Most are secondary metabolites, often clustered in fungal genome

  • Some are individual small proteins

Wolpert et al, 2002, Host-selective toxins and avirulence determinants: What’s in a name? Annu. Rev. Phytopathol. 40:251-285


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Fig. 3. VIGS-mediated suppression of Hm1 results in barley susceptibility to CCR1… (b and c) Typical appearance of lesions caused by CCR1 on normal barley leaves (b) or leaves in which the Pds gene is suppressed via VIGS (c). (d–f ) CCR1-caused expanding lesions on barley leaves in which Hm1 was suppressed alone (d and e) or in combination with Pds ( f). (g) Resistant lesions of Hm1-suppressed barley to an HC toxin-deficient isolate of CCR1.

HC-toxin detoxified directly by maize HM1, which encodes HC-toxin reductase (Sindhu et al, 2008, PNAS 105:1762-1767)

  • All grass species have Hm1 homologs

  • HC-toxin is not a HST

  • It’s the malfunction of Hm1 in maize that makes HC toxin host-specific

  • Why are dicots, which have no Hm1 homologs, resistant to HC toxin?


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  • Not an HST, nor even a toxin!

  • Most are secondary metabolites, often clustered in fungal genome

  • Some are individual small proteins

Wolpert et al, 2002, Host-selective toxins and avirulence determinants: What’s in a name? Annu. Rev. Phytopathol. 40:251-285


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  • Evidence for very recent horizontal transfer of ToxA from P. nodorum to Ptr(Friesen et al, 2006, Nature Genet. 38:953-956)

    • Horizontal transfer: another force for increasing fungal pathogen diversity

  • Same ToxA gene present in Pyrenophora tritici-repentis (Ptr, cause of tan spot of wheat) and in Phaeosphaeria nodorum; high homology between ToxA genes

  • Tan spot wasn’t a problem in U.S. until first described in 1941

Tan spot

ToxA

P. nodorum

P. tritici-repentis


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HSTs may be under diversifying selection

Example: P. nodorum (anamorph = Stagonospora nodorum), cause of leaf and glume blotch of wheat

(Septoria = Stagonospora, Leptosphaeria = Phaeosphaeria)


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Diversifying selection = disruptive selection; two ore more phenotypes favored simultaneously

Types of natural selection

Step 1

Step 2


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  • SnToxA confers pathogenicity to wheat with Tsn1 (sensitivity gene)

  • Of 788 P. nodorum isolates from 8 regions, SnToxA amplified in 199

  • Deletion of SnToxA was detected by PCR (repeated and confirmed with Southern blot analysis)

  • SNPs at 25 polymorphic sites in 123 amplicons

  • SnToxA has 13 haplotypes in P. nodorum

Stukenbrock and McDonald, 2007, Geographical variation and positive diversifying selection in the host-specific toxin SnToxA, Mol. Plant Pathol. 8:321-332


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P. n.

Ptr


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Australia (N = 13)

Cent Am (N = 4)

Cent Asia (N = 27)

Strong differences in P. nodorumSnToxA haplotype diversity by region

E Asia (N = 2)

Europe (N = 19)

Mid East (N = 18)

N Am (N = 20)

S Africa (N = 21)

All isols (N = 124)


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  • Fig. 3. P. nodorumSnToxA parsimonious haplotype network of 123 P. n. isolates

  • Shows relatedness of haplotypes 1-13, and their geographic distribution

  • Few mutational steps missing; suggests large fraction of existing SnToxA diversity present in this analysis

    • Hypothesis: many mutations have accumulated in relatively short timeframe to counter-adapt to new alleles of host Tsn1 locus, or in response to a second plant gene interacting with the toxin

  • No pattern of geographical grouping

    • Most frequent haplotype (43 isolates) in Central America, Europe, Middle East, North America


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Evidence for diversifying selection in SnToxA

  • Calculate ω = ratio of non-synonymous (N) to synonymous mutations (S) (excluding H3)

    • If purifying selection dominates, removes N substitutions, then ω < 1.

    • If NS mutations are beneficial, diversifying selection maintains them, ω > 1.

  • Results: Of 66 possible pairwise comparisons of 12 functional SnToxA alleles,

    • ω > 1 in 34

    • ω < 1 in 29

    • ω = in 3

      So on average ω >1, diversifying selection may play a role in SnToxA evolution

  • By maximum likelihood test: Evidence for diversifying selection increased when PtrToxA sequences were included, and two amino acids provided particularly strong evidence (ω = 15.99 and 15.77)


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P. nodorum has at least 4 HSTs(Friesen et al, 2008, Plant Physiology 146:682-693)

Host gene – toxin interactions are additive: host genotypes with multiple toxin sensitivity genes are significantly more susceptible than those with sensitivity to a single toxin


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Why does wheat have genes for sensitivity to ToxA, etc.?

  • PtrToxA traverses plant plasma membrane, possibly by receptor-mediated endocytosis

  • Localizes to chloroplast, binds to chloroplast protein ToxABP1

  • ToxA-induced PCD is temperature- and light-dependent, requires active host metabolism, transcription, translation, host signaling mechanisms

  • Conclusions:

    • Ptr and P. nodorum toxins may be turning the host’s resistance mechanism against it

    • Host genes Tsn1, Snn1, Snn2, etc are probably R genes that both (1) recognize toxin and (2) act as gates for internalization


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Conclusions on SnToxA– evolution of a small-protein HST

  • Evolution of SnToxA locus driven by selection for different alleles or for genotypes in which gene not expressed

  • High deletion frequencies in some regions suggest trade-off from presence of SnToxA (i.e., lowered fitness)

  • Different deletion frequencies suggest local conditions (i.e., different Tsn1 alleles in host) select strongly for specific alleles or complete deletion

  • Host gene Tsn1 is located in a recombination hot spot, suggesting that emergence of desensitized Tsn1 alleles is followed by selection for new toxigenic SnToxA alleles to regain compatibility with host gene


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What drives evolution of a secondary metabolite cluster and can we expect rapid appearance of new specificities as in P. nodorum SnTox series?

  • Alternaria alternata: a saprophyte turned parasite that produces HSTs via secondary metabolite clusters and has evolved many variants by mutation

    • specializes on pear, apple, strawberry, citrus, tomato, tobacco

  • “Selfish cluster” theory: clustering confers a selective advantage to the cluster, i.e., the ability to be transferred horizontally, favoring cluster’s dispersal and survival (Walton, 2000, Fung. Gen. Biol. 30:167-171)

Alternaria mali on pear

Alternaria brown spot on citrus

  • HSTs are associated with pathogens of cultivated plants; selection of HST-producing pathogens may be result of co-evolution of necrotrophic pathogens and their host plants grown in monoculture (Prell & Day, 2001, Plant-Fungal Pathogen Interaction: A Classical and Molecular View, Springer, pp. 60-64)

    • Does monoculture agriculture drive diversifying selection of HSTs by breeding cultivars with “new” sensitivities, selecting for mutation and/or horizontal transfer?


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Resistance to HSTs

  • Mechanisms are under investigation

  • Detoxification by plants has been discovered

  • Destruxin B, an HST produced by Alternaria brassicae in the disease Alternaria blackspot of crucifers, is detoxified via hydroxylation and glucosylation (Pedras et al, 2003, Phytochemistry 64:957-963)

    • Hydroxylated destruxin induces phytoalexin biosynthesis (sinalexin and sinalbin A) in resistant but not susceptible crucifer spp.

    • Same crucifer spp. also resist Alternaria blackspot via camalexin, a phytoalexin that inhibits production of destruxin B (Pedras et al, 2001, PNAS, 98:747-752)

  • Detoxification – a redundant resistance mechanism?

Alternaria blackspot on cauliflower


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Conclusions for resistance breeding and resistance management where HSTs are involved

  • Like avr genes, HSTs are under strong selective pressure to diversify, so resistance may have limited durability

  • In HST pathosystems, resistance phenotypes include

    • presence/absence of toxin sensitivity gene or particular alleles

    • presence/absence of detoxification capability

    • induction of phytoalexins to inhibit HST synthesis

    • forms of partial resistance unrelated to toxin defense

  • Modern agriculture is selecting for HSTs with new specificities both within a crop species and potentially across crops (via horizontal transfer)

  • Strategies to reduce selective pressure on pathogen could be expected to extend life of deployed resistances

    • Rotation of host resistance sources in space or time

    • Host heterogeneity (mixed host populations)


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What kind of pathogen populations pose the greatest risk of overcoming host resistance?

  • “…pathogens with the greatest evolutionary potential offer the greatest ‘risk’ of overcoming major resistance genes or evolving to counteract other control methods such as applications of fungicides or antibiotics.”

    • McDonald, http://www.apsnet.org/education/AdvancedPlantPath/Topics/popgenetics/


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Which types of pathogen biology carry higher risk; i.e., confer greater evolutionary potential on pathogen population?

  • Effective population size – large or small?

    • More mutant alleles are present in larger populations


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Large population sizes and mutants: a thought experiment

Blumeria graminis f. sp. hordei (causes barley powdery mildew)

Mature sporulating lesion produces ~104 conidia per day

If 10% of barley leaf area is infected, there are approximately 105 lesions per square meter in a field

109 spores are produced per square meter per day or 1013 spores per hectare

Assume mutation rate = 10-6

Then approximately 107 mutant spores are produced in each hectare each day

Conclusion: mutants for any locus are present in a typical rust or mildew epidemic; the goal is to keep pathogen population sizes as low as possible


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Which types of pathogen biology carry higher risk; i.e., confer greater evolutionary potential on pathogen population?

  • Gene flow – low or high?

    • Populations with high gene flow are more likely to transmit virulent or fungicide-resistant mutants across a large geographical area.

    • Populations with high gene flow are larger, and thus maintain more alleles.


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  • Reproduction / Mating system – asexual, sexual, or mixed?

    • Pathogens that undergo regular recombination pose higher risks than pathogens that undergo no or little recombination. (can include processes other than meiosis such as bacterial conjugation, recombination between viral genomes in plants with mixed infections, and hyphal anastomosis and/or parasexual recombination in fungi)

    • Pathogens with mixed reproductive systems (both sexual and asexual reproduction) pose the highest risk of evolution because they receive benefits from both mechanisms of reproduction.

      • Sexual recombination allows many new combinations of alleles to come together and then be tested in the local environment.

      • Asexual reproduction allows most fit genotypes to reproduce as clones, keeping together fit combinations of alleles, allowing for wide distribution of this combination if the asexual propagules are dispersed over long distances. 


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McDonald and Linde, 2002, Euphytica 124:163-180


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It’s the degree of population variability that counts, not sex by itself

  • Rynchosporium secalis on barley:

    • No known teleomorph

    • Yet breakdown of Atlas 46 barley in California resulted from virulence variability (Jackson and Webster, 1967, Phytopathology 66:719-725)

    • Sources of variability that are NOT SEX:

      • Asexual recombination (parasexual cycle)

      • Somatic recombination

      • Mutation

      • Migration (seedborne; windblown crop debris)

      • Differential selection during parasitic and saprophytic phases

      • Transposons (e.g., Avr-Pita & POT3 transposon)


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