Local adaptation and effect of host genotype on the rateof pathogen evolution: an experimental testin a plant pathosystem

J. ZHAN,* C. C. MUNDT,� M. E. HOFFER� & B. A. MCDONALD*

*Institute of Plant Sciences, Phytopathology Group, ETH Zentrum ⁄LFW, Zurich, Switzerland

�Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA

Keywords:

DNA fingerprinting;

evolution of virulence;

host–pathogen interaction;

local adaptation;

Mycosphaerella graminicola;

reproductive fitness;

selection coefficients;

Septoria tritici;

trade-offs.

Abstract

Virulence is thought to be a driving force in host–pathogen coevolution.

Theoretical models suggest that virulence is an unavoidable consequence of

pathogens evolving towards a high rate of intrahost reproduction. These

models predict a positive correlation between the reproductive fitness of a

pathogen and its level of virulence. Theoretical models also suggest that the

demography and genetic structure of a host population can influence the

evolution of virulence. If evolution occurs faster in pathogen populations than

in host populations, the predicted result is local adaptation of the pathogen

population. In our studies, we used a combination of molecular and

physiological markers to test these hypotheses in an agricultural system. We

isolated five strains of the fungal pathogen Mycosphaerella graminicola from

each of two wheat cultivars that differed in their level of resistance to this

pathogen. Each of the 10 fungal strains had distinct genotypes as indicated by

different DNA fingerprints. These fungal strains were re-inoculated onto the

same two host cultivars in a field experiment and their genotype frequencies

were monitored over several generations of asexual reproduction. We also

measured the virulence of these 10 fungal strains and correlated it to the

reproductive fitness of each fungal strain. We found that host genotypes had a

strong impact on the dynamics of the pathogen populations. The pathogen

population collected from the moderately resistant cultivar Madsen showed

greater stability, higher genotype diversity, and smaller selection coefficients

than the pathogen populations collected from the susceptible cultivar

Stephens or a mixture of the two host cultivars. The pathogen collection

from the mixed host population was midway between the two pure lines for

most parameters measured. Our results also revealed that the measures of

reproductive fitness and virulence of a pathogen strain were not always

correlated. The pathogen strains varied in their patterns of local adaptation,

ranging from locally adapted to locally maladapted.

Introduction

Virulence, here defined as the damage a pathogen strain

causes to a host (Read, 1994; Frank, 1996), is thought to

be a driving force in host–pathogen coevolution.

Improved knowledge of the factors that affect the

evolution of virulence may have practical applications

for controlling infectious diseases. The topic has therefore

received considerable theoretical treatment (e.g. Frank,

1992; Bonhoeffer & Nowak, 1994; Lenski & May, 1994;

May & Norvak, 1995; Lipsitch et al., 1996; Ebert &

Weisser, 1997; Mosquera & Adler, 1998; Boots & Sasaki,

1999; Regoes et al., 2000).

Correspondence: B. A. McDonald, Institute of Plant Sciences, Phytopa-

thology Group, ETH Zentrum ⁄LFW, Universitatstrasse 2, CH-8092 Zurich,

Switzerland.

Tel.: +411 632-3847; fax: +411 632-1572;

e-mail: bruce.mcdonald@ipw.agrl.ethz.ch

634 J . E V O L . B I O L . 1 5 ( 2 0 0 2 ) 6 3 4 – 6 4 7 ª 2 0 0 2 B L A C K W E L L S C I E N C E L T D

Virulence is thought to be detrimental both to hosts

and parasites (e.g. Bull, 1994). Natural selection should

favour parasites having little or no virulence because

parasites with less virulence have more time to exploit

their hosts, reproduce and transmit their progeny to the

next generation, thus increasing their own fitness

(Regoes et al., 2000). However, many parasites maintain

an intermediate level of virulence in nature. The

conventional explanation for this evolutionary dilemma

is the trade-off theory. The trade-off theory proposes that

virulence is an unavoidable consequence of parasites

evolving towards a higher rate of intrahost reproduction

(Lehmann, 1993; Read, 1994; Frank, 1996; Ebert, 1998;

Mackinnon & Read, 1999). Higher intrahost reproduc-

tion increases the probability that parasites will infect

new hosts, but also decreases the life span of infected

individuals and the density of host populations (Bull,

1994). As a consequence, the number of new infections

(transmission rate of a parasite) over the lifetime of an

infected host will be low when parasites have too high as

well as too low virulence (or intrahost reproduction). An

optimum level of virulence will be maintained to

maximize the overall fitness of the parasite. The trade-

off model predicts a positive correlation between the

degree of virulence and the reproductive fitness of a

pathogen strain.

A pathogen strain might cause significant damage on

one type of host but cause relatively little damage on

another host. For example, a pathogen strain may infect,

reproduce, disseminate progeny more readily and cause

more damage on the hosts that are less able to defend

themselves (Ewald, 1983). This scenario suggests that

virulence is a property of the specific host–pathogen

interaction, and that the evolution of virulence might be

tightly associated with the demographic and genetic

structure of the host populations (Lipsitch et al., 1995;

Ebert & Mangin, 1997; Van Baalen, 1998; Regoes et al.,

2000). For example, Gandon & Michalakis (2000)

demonstrated that host populations carrying quantitative

resistance genes selected for a higher level of virulence in

pathogen populations than host populations carrying

qualitative resistance genes. Host populations can influ-

ence not only the outcome of evolution for virulence but

also the rate of evolution (Cramer & May, 1972; Barrett,

1980; Dobson, 1990; Gould et al., 1991; Ebert &

Hamilton, 1996; Lannou & Mundt, 1997). It has been

proposed that virulence will evolve more slowly on hosts

that carry quantitative resistance genes (also called partial

resistance; Gould et al., 1991). In this case, resistance is

thought to be nonspecific and thus all pathogen strains

will have similar abilities to survive, reproduce and

transmit their progeny (Vanderplank, 1968). It is also

thought that increasing genetic diversity in host popula-

tions could retard the rate at which virulence evolves

(Burdon, 1987). Heterogeneity increases genetic differ-

entiation in the host populations, inhibiting the ability of

pathogens to evolve virulence by increasing the diver-

gence in selection pressure exerted by individual host

genotypes (Barrett, 1980; Ebert & Hamilton, 1996).

In the host–pathogen interaction, pathogens and hosts

are thought to evolve at different rates. Pathogens have

relatively short generation times and are usually abun-

dant in number compared with their hosts (Price, 1980;

Imhoof & Schmid-Hempel, 1998). These advantages may

allow pathogens to quickly overcome host defence

mechanisms and stay ahead in the coevolutionary �arms

race� (Kaltz & Shykoff, 1998). The temporal lag in

developing invasive mechanisms in pathogen popu-

lations and defensive mechanisms in host populations

could lead to local adaptation of the pathogen popu-

lation. Pathogens are considered to be locally adapted if

they perform better on sympatric hosts than on allopatric

hosts. Pathogens can also be thought of as locally adapted

if particular strains demonstrate higher fitness on

associated hosts than the potentially competing strains

from other hosts. We will use the second definition of

local adaptation in this manuscript.

Empirical tests of the theoretical hypotheses regarding

the evolution of virulence are relatively limited and the

results are often contradictory (e.g. Karban, 1989; Soler

& Møller, 1990; Bull et al., 1991; Bull & Molineux, 1992;

Ni & Kemp, 1992; Sork et al., 1993; Ebert, 1994;

Memmott et al., 1995; Davelos et al., 1996; Ebert &

Mangin, 1997; Hawthorne, 1997; Lannou & Mundt,

1997; Roy, 1998; Mackinnon & Read, 1999; Messenger

et al., 1999; Mutikainen et al., 2000; Davies et al., 2001).

Empirical study of the evolution of virulence in natural

systems is very difficult. Many biological and ecological

processes that affect hosts and pathogens independently

can introduce �noise� that influences the interpretation of

experimental results (Read, 1994; Roy, 1998). In this

case, experimental studies under controllable and

repeatable environments are essential to obtain inform-

ative results (Read, 1994).

Most theoretical and empirical works have considered

only the simplest case of host–pathogen interactions, i.e.

cases where a host can harbour only a single pathogen

strain (mono-infection). However, it has been shown

that multiple infections are a common phenomenon in

nature (e.g. McDonald & Martinez, 1990; Mahuku et al.,

1996; McDonald et al., 1999b; Morales-Espinosa et al.,

1999; Gratton et al., 2000). The evolutionary pattern of

virulence in multi-infection systems is different from

that in mono-infection systems. In mono-infection sys-

tems, natural selection favours pathogen strains posses-

sing an optimal level of virulence (e.g. Lenski & May,

1994). On the other hand, in a system where several

pathogen strains can coexist on one host, pathogen

strains having a greater than optimum level of virulence

will be favoured by natural selection (Hellriegel, 1992;

Van Baalen & Sabelis, 1995; Ebert & Mangin, 1997;

Taylor et al., 1998).

In our study, we used an agricultural system to address

questions on the evolution of virulence. The host

Host-driven selection in pathogen populations 635

J . E V O L . B I O L . 1 5 ( 2 0 0 2 ) 6 3 4 – 6 4 7 ª 2 0 0 2 B L A C K W E L L S C I E N C E L T D

cultivars belonged to the same species, Triticum aestivum.

These cultivars shared many genetic and morphological

characteristics. The major difference among these culti-

vars was their level of resistance to a common wheat

pathogen. The wheat cultivars in our experiment origin-

ated from and were grown for many years in the same

geographical location where our experiments were con-

ducted. All of these circumstances assisted our interpret-

ation of results, as many of the problematic biological and

environmental �noises� were significantly reduced (Read,

1994; Roy, 1998). The pathogen used in our experiment

was Mycosphaerella graminicola (Fuckel) Schroeter (ana-

morph Septoria tritici Rob. ex Desm). This pathogen has

been the subject of intensive population genetic studies

for more than a decade (e.g. McDonald et al., 1995,

1999a), and hence is a suitable pathogen for addressing

questions related to the evolution of virulence (Roy,

1998).

We began our experiments by introducing 10 genetic-

ally distinct pathogen strains into host populations that

differed for level of resistance and genotype diversity. We

then used DNA fingerprints to trace each pathogen strain

through time. We monitored the change in pathogen

genotype frequencies over several generations of survi-

val, reproduction and competition, and estimated their

relative reproductive fitness. Then we correlated the

reproductive fitness of each pathogen strain to the actual

host damage caused by these strains. We measured the

fitness of a pathogen strain both through monitoring

genotype frequency (which is analogous to the trans-

mission rate used in many other studies) and by

estimating selection coefficients. Unlike measures of

genotype frequency or transmission rate, the selection

coefficient is a parameter reflecting the overall fitness of

any genotype ⁄phenotype relative to the most fit strain

during the entire process of infection, colonization,

reproduction and survival. Thus we consider selection

coefficients to offer the most inclusive measure of the

fitness of the genotype ⁄phenotype in an experimental

setting (Endler, 1986; Antonovics & Alexander, 1989).

The principal objectives of our experiments were to

determine: (1) the relationship between the reproductive

fitness and virulence of pathogen strains; (2) how host

populations affect the evolution of pathogen populations

and (3) whether pathogen strains were better adapted to

the hosts from which they originated.

Materials and methods

Experiment 1 – Fitness and its components

The experiment was conducted at the Oregon State

University Botany and Plant Pathology Field Laboratory

in Corvallis, Oregon during the 1994–95 winter wheat

season. Two wheat cultivars, Madsen and Stephens,

were used for this field experiment. Madsen was

moderately resistant to M. graminicola and Stephens

was highly susceptible (Ahmed et al., 1996). The two

cultivars were planted in pure stands and in 1 : 1

mixtures in a randomized complete block design with

three replications. Plots were 3.3 m (12 rows) wide and

5.3 m long. Each plot of wheat was separated by an

equal-sized plot of barley, a nonhost for M. graminicola at

this location. Ten fungal strains were randomly sampled

at the end of an epidemic cycle in 1994 from a naturally

infected field located 110 km north of Corvallis. Among

these 10 strains, M1–M5 originated from infected flag

leaves of Madsen and S2–S5 originated from infected

flag leaves of Stephens. Strain S1 was a contaminant of

unknown origin that replaced the original S1 strain

during routine subculturing. Its identity as a con-

taminant was not discovered until completion of the

experiment. Each strain, including the contaminant S1,

had a unique DNA fingerprint (Fig. 1). Spores from the

10 strains were mixed in equal proportions to a final

concentration of 106 spores mL)1. A surfactant (Tween)

was added to the spore solution at the rate of one drop

per 50 mL. Spores were applied to the point of run-off

on each plot on 18 November 1994 (seedling stage)

using a 6-L capacity pump-action sprayer. After inocu-

lation, each plot was covered with a black plastic tarp for

4 days to ensure adequate moisture for the establish-

ment of infections. Samples of infected leaves were

collected twice from all treatments during the growing

season. The first samples were collected on 10 February

1995 (early tillering stage, hereafter referred to as

early-season) and the second samples were collected

on 2 June 1995 (grain filling stage, hereafter referred to

as late-season). In addition, another sample was collec-

ted only from the Stephens plots on 3 April (stem

elongation stage, hereafter referred to as middle-season).

For each collection, 100 infected leaves were collected at

regular intervals along transects within the inner eight

rows of each field plot. One fungal strain was isolated

from each leaf and an average of 67 isolates was isolated

from each plot for each collection. In addition, the

amount of host damage caused by these inoculated

strains was recorded in each field plot through the

growing season by visual estimation of the percentage of

leaf area covered by M. graminicola lesions. Additional

details on experimental design and sampling strategies

were given in Zhan et al. (1998).

Experiment 2 – Virulence measurements

Plants were raised in 10-cm plastic pots filled with a

greenhouse mix and watered via drip irrigation.

Approximately 15 seeds of a cultivar were sown in each

pot. At 19 days after seeding, plants were thinned to 10

per pot. Plants were fertilized once, at sowing, with

0.6 g pot)1 of Osmocote (14% N, 14% P, 14% K: Sierra

Chemical Co., W. Sacramento, CA, USA). Greenhouse

temperature was maintained at 20–25 �C, and sodium-

halide lights were used to extend day length to 16 h.

636 J. ZHAN ET AL.

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To prepare cultures for inoculation, we plated long-

term fungal cultures stored on silica gel on yeast maltose

agar (YMA) slants with 50 mg L)1 gentamicin. After

3–4 days, blastospores were streaked onto YMA plates.

Two days after streaking, each strain was transferred to a

separate YMA slant. The strains were used for inocula-

tions after an additional 3 days of growth by adding

10 mL of sterile water to a slant of each of the strains, and

suspending the spores by scraping. Suspensions were

adjusted to 106 spores mL)1.

We inoculated plants 20 days after planting by placing

groups of four pots (two each of the cultivars Madsen and

Stephens) on a turntable at 16 rpm and applying 25 mL

of spore suspension using hand-operated sprayers. Two

groups of plants were inoculated for each of the 10

strains to provide four replications of each strain · cul-

tivar combination.

After inoculation, the plants were kept in a moist

chamber (wooden frame covered with a polyethylene

sheet) for 4 days. High humidity (95% or above) was

maintained using a humidifier (ultrasonic, cool mist type)

inside the moist chamber. Fluorescent tube lights above

the moist chamber provided supplemental illumination

when necessary. The pots were subsequently returned to

a greenhouse bench in a completely random design until

virulence was scored. Four additional pots of each

cultivar were sprayed with water only, but otherwise

were treated in the same manner as inoculated plants.

The percentage of leaf area covered by lesions is

negatively correlated with host fitness for many fungal

pathogens (e.g. Torres & Teng, 1993; Tefferi et al.,

1996). We used percentage of leaf area covered by

lesions as a measure of virulence for each fungal strain.

Visual estimates of virulence were made on the second

leaf from the base of each of the 10 plants in each pot

3 weeks after inoculation. A single observer conducted

all virulence assessments and pots were assessed ran-

domly with regard to treatments. Only lesions obvi-

ously caused by M. graminicola were included. For

example, chlorosis of leaf margins not associated with

pycnidia or pycnidial initials was excluded from the

assessments, as such symptoms are often caused by

natural senescence.

DNA extraction, restriction digestion, Southernblotting and hybridization

Total DNA from each fungal strain was extracted using a

hexadecyltrimethylammonium bromide (CTAB) extrac-

tion protocol described previously (McDonald & Marti-

nez, 1990). DNA concentrations were measured using a

DNA fluorometer (Hoefer TKO 100, Hoefer Scientific

Instruments, San Francisco, CA, USA). Five micrograms

of DNA from each fungal strain was digested with the

restriction enzyme PstI, and the DNA fragments were

separated by electrophoresis through 0.8% agarose gels.

The DNA fragments in the agarose gels were transferred

to nylon membranes (Bio-Rad Zeta Probe) by alkaline

capillary transfer. The DNA fingerprinting probe pSTL70

was radioactively labelled with dCT32P via nick transla-

tion according to the manufacturer’s instructions. The

labelled probe was hybridized to the membranes over-

night at 60 �C in a hybridization incubator. Following

hybridization, the membranes were washed and exposed

(a) (b)

Fig. 1 Autoradiograms showing DNA fingerprints of Mycosphaerella graminicola: (a) the 10 M. graminicola strains used in this experiment;

(b) fungal strains recovered from one of the field plots in the middle-season collection. The lanes marked with letter A indicates isolates that

were �novel�, originating either from immigration or intermating of the 10 inoculated strains. The lane marked with letter N could not be

scored because of the low DNA concentration.

Host-driven selection in pathogen populations 637

J . E V O L . B I O L . 1 5 ( 2 0 0 2 ) 6 3 4 – 6 4 7 ª 2 0 0 2 B L A C K W E L L S C I E N C E L T D

to X-ray film at )80 �C. After the films had been

developed, the radioactive probe was stripped off the

membranes as described previously (McDonald & Mar-

tinez, 1990).

Estimating selection coefficients

Classic methods (e.g. Leonard, 1969) to estimate selec-

tion coefficients were developed to measure competition

between two genotypes. These methods could not be

applied directly to our experiment because we were

measuring competition among 10 genotypes simulta-

neously. In this section, we describe a new method to

estimate selection coefficients based on the standard

theory of selection. This method can be applied to the

case of clonal competition among several strains of

haploid organisms.

Selection coefficients of the inoculated strains within

the same replication were estimated simultaneously by

setting the selection coefficient of the most-fit strain (the

strain with the greatest increase in frequency over the

time period considered) to zero as follows. Let the initial

frequency for genotype G1, G2, . . .Gi be p01, p0

2, . . . p0i and

their selection coefficients per generation be s1, s2, . . .si

respectively. The average fitness for this population at

generation t ¼ 0 ( �WW0 ) will be:

�WW0 ¼ p01ð1 � s1Þ þ p0

2ð1 � s2Þ þ � � � � � � p0i ð1 � siÞ ð1Þ

And the frequency for genotype Gi after one generation

of selection (P1i ) will be:

p1i ¼ p0

i ð1 � siÞp0

1ð1 � s1Þ þ p02ð1 � s2Þ þ � � � � � � p0

i ð1 � siÞ¼ p0

i ð1 � siÞ�WW0

ð2Þ

Thus, the frequency for genotype Gi after t generations of

selection (Pti) will be:

pti ¼

p0i ð1 � siÞt

Qt�1

k¼0

fpk1ð1 � s1Þ þ pk

2ð1 � s2Þ þ � � � � � � pki ð1 � siÞg

ð3Þ

Let Gj (i „ j) be the most-fit genotype, i.e. sj ¼ 0, then

from eqn 3, we obtain:

p0j

ptj

¼Yt�1

k¼0

fpk1ð1 � s1Þ þ pk

2ð1 � s2Þ þ � � � � � � pki ð1 � siÞg ð4Þ

The selection coefficient for Gi can be obtained by

substituting eqn 4 in eqn 3, leading to the general

solution of:

si ¼ 1 �pt

i p0j

ptj p0

i

( )1=t

ð5Þ

For strains such as M2 that occurred at intermediate

frequencies in the early- and middle-season and then

became extinct, 1 ⁄N was substituted for the late-season

genotype frequency to estimate the selection coefficient,

where N was the total number of strains included in the

late-season collection.

Estimating the number of asexual generations

Temperature and rainfall data were recorded daily during

the growing season. These data were used to calculate

the average temperatures for specific periods during the

growing season and to determine the dates of new

epidemic cycles. Latent periods for a calculated mean

temperature were estimated using the results of Shaw

(1990). Because rainfall is required to release and

disperse pycnidiospores of M. graminicola, a cycle of

asexual reproduction was not considered to be complete

until after a day with at least 5 mm of rainfall. By this, we

estimated that the M. graminicola populations underwent

six cycles of asexual reproduction between the first

collection and the final collection. Three cycles occurred

between early-season and middle-season collections and

three cycles occurred between the middle-season and

late-season collections.

Statistical analyses

The fungal collections contained both inoculated and

novel strains. The novel strains had DNA fingerprints that

differed from the 10 inoculated strains as a result of

ascospores immigrating from outside of the experimental

field and intermating among the 10 inoculated strains

(Zhan et al., 1998). We estimated the genotype frequen-

cies of the inoculated strains in each collection by

excluding the novel strains from our calculations. This

allowed us to measure changes in the frequencies of the

inoculated genotypes across host treatments over time.

Analyses of variance for genotype frequencies,

virulence and selection coefficients were performed with

general linear models by using the SAS program (SAS

Institute, 1988). Genotype frequencies were first trans-

formed by natural logarithms to better satisfy the

assumptions of analysis of variance. The standard

deviations of the selection coefficients were calculated

for each of the strains based on variation among the three

replications. The overall selection coefficients among the

fungal strains collected from different hosts were further

compared with linear contrasts in general linear models

(Ott, 1992). The logistic growth model was fit to the

resulting disease progress curve for each plot to estimate

logistic growth rates (Vanderplank, 1963) of the Septoria

tritici leaf blotch epidemic in the experimental plots. The

genetic structure of fungal collections from different

sampling times of the same hosts and from different hosts

of the same sampling time was compared by contingency

v2 tests (Everitt, 1977). In these comparisons, fungal

collections from different replications were pooled

together, because homogeneity tests indicated that the

fungal collections from the three replications within the

same host treatment were not significantly different.

638 J. ZHAN ET AL.

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Genotype diversities were calculated with the method of

Stoddart & Taylor (1988) and compared using a t-test as

described by Chen et al. (1994).

Results

DNA fingerprints were assayed for 1365 fungal isolates in

total. Among these isolates, 275 had DNA fingerprints

that did not match the inoculated strains. These �novel�strains originated from immigration and recombination

as described previously (Zhan et al., 1998). The propor-

tion of novel isolates increased from 3% in the early

season to 39 and 31% in the mid- and late-season

collections, respectively. All novel DNA fingerprints were

present once in the sample, except for one fingerprint

that was found twice. Novel strains were excluded from

the analysis of selection.

Variation in fitness and virulence

Variation in frequencies and virulence of fungal strainsThere were highly significant differences (P < 0.0001) in

genotype frequencies (Fig. 2) and virulence (Fig. 3) for

the 10 inoculated strains within each host collection. On

Stephens, the frequencies of all fungal strains changed in

a directional manner over the growing season except for

M5 (Fig. 2c). The mean frequency of strain M5 increased

from 0.05 to 0.16 between the early-season and the

middle-season and decreased from 0.16 to 0.07 during

the period between the middle-season and the late-

season. The pattern and relative degree of change in

genotype frequency was consistent across all three

replications for each strain (examples in Fig. 4). Strains

S4 and S5 had very low initial frequencies, and we were

therefore unable to evaluate whether they showed a

directional pattern of change over time.

Variation in selection coefficientsSelection coefficients of the six most common strains

ranged from 0.00 to 0.18 on Madsen, 0.10–0.27 on the

mixture and 0.01–0.55 on Stephens (Table 1). The selec-

tion coefficients of strains M4, S2, S4, and S5 were not

estimated because these strains occurred at frequencies

that were too low to provide meaningful estimates. There

were significant differences in the selection coefficients

among fungal strains both within a host treatment and

across different host treatments (Table 2).

Correlation between fitness and virulenceof fungal strains

There was not a significant correlation between the

reproductive fitness and virulence of fungal strains for

either resistant or susceptible hosts (Fig. 5), although for

some strains, results from the virulence assay were

consistent with observed changes in genotype frequen-

cies. For example, strains S4 and S5, which never

reached significant frequencies in any collection, also

caused less damage on all hosts. On the other hand, M1

had a modest level of virulence on seedlings, and

occurred at the highest frequency at the start of the

season on all host treatments, suggesting that it was

initially very successful at infecting plants. But its overall

fitness was low in the field experiment.

(a)

(b)

(c)

Fig. 2 Frequencies of 10 Mycosphaerella graminicola strains on

different host treatments over the growing season. Differences in

genotype frequencies were significant (P ¼ 0.0001) for each treat-

ment in each collection. Numbers in parentheses were sample sizes

for each collection. (a) Madsen; (b) 1 : 1 mixture of Madsen and

Stephens; (c) Stephens (three collections).

Host-driven selection in pathogen populations 639

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Effect of hosts on the evolutionary rates of pathogenpopulations

Changes in genetic structure (genotype frequencies)over timeThe genetic structure of the fungal collection in the

early-season was significantly different from that in the

late-season collection for the mixture but not for

Madsen (Table 3). On Stephens, the genetic structure

of the fungal collection in the middle-season was

significantly different from that in the early-season

and late-season, and the genetic structure in the early-

season was significantly different from that in the late-

season.

Changes in genetic structure according to host populationIn the early-season, the genetic structure of fungal

collections from Madsen and Stephens was not statisti-

cally different from that of the mixture (Table 4). But the

genetic structure of fungal collections from Madsen

differed significantly from that of Stephens. In the late-

season, the collections from Madsen and Stephens were

significantly different from the mixture, and the differ-

ence between Madsen and Stephens was highly signifi-

cant.

Genotype diversity in the pathogen collectionsacross host populationsGenotype diversity in pathogen collections from all three

host treatments increased slightly (Table 5) but signifi-

cantly (P < 0.0001) over the growing season. The

collection from Madsen had higher genotype diversity

than the collections from the mixture or Stephens. In the

early-season, genotype diversity in the fungal collections

from Madsen and the mixture did not differ from the

Stephens collection. But the genotype diversity in the

collection from Madsen was significantly higher than in

Fig. 3 The virulence of 10 Mycosphaerella graminicola strains on

cultivars Madsen and Stephens as measured by the percentage of leaf

area covered by lesions.

(a)

(b)

(c)

(d)

(e)

Fig. 4 Frequencies of five common Mycosphaerella graminicola strains

in the three replications of fungal collections sampled from

Stephens: (a) strain M1; (b) strain M3; (c) strain M5; (d) strain S1;

(e) strain S3.

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the collection from the mixture. In the late-season, the

genotype diversities among fungal collections were

significantly different. These observations suggest that

the differences in genotype diversity among fungal

collections were correlated with differences in degree of

resistance in host treatments and the number of

generations of selection (Table 6).

Selection coefficients of pathogen strains in differenthost populationsPathogen strains had the highest overall selection coef-

ficients on Stephens and the lowest overall selection

coefficients on Madsen (Table 1). On Stephens, three of

six strains had selection coefficients >0.20. No strains had

selection coefficients >0.20 on Madsen. Further compar-

isons with linear contrasts indicated that the overall

selection coefficient of fungal strains on Madsen was

significantly lower than on Stephens. The overall selec-

tion coefficient of fungal strains on the mixture was not

statistically different than the average of the two pure

stands (Table 2).

Epidemic development in the fieldThe disease progress curve for the mixture was interme-

diate between the susceptible cultivar Stephens and the

moderately resistant cultivar Madsen (Fig. 6). Logistic

growth rates were 0.028, 0.021 and 0.018 for Stephens,

the mixture and Madsen, respectively. All infection rates

were significantly different from each other at P ¼ 0.05.

Local adaptation

Fungal strains varied in their degrees of adaptation to

particular hosts as indicated by a highly significant host–

pathogen interaction (P ¼ 0.0005) in the analysis of

variance. Strains M2, M3 and S3 showed the best

evidence for directional selection according to host

genotype (Fig. 2). The frequency of strain M2 increased

from 0.15 in the early-season to 0.23 in the late-season

on Madsen while decreasing from 0.03 to 0.00 on

Stephens. Over the course of the experiment, strains

M3 and S3 significantly increased in frequency on

Stephens but did not change significantly on Madsen.

Strain M1 had a similar frequency on all host treatments

and showed a significant overall decline from 0.47 to

0.28 over the course of the season. On average, fungal

strains caused slightly more damage and had slightly

higher fitness on the hosts from which they originated,

but these differences were not statistically significant

(data not shown).

Discussion

Variation in fitness and virulence of fungal strains

The 10 fungal strains used in our experiments were

originally isolated from the same field and hence

belonged to the same geographical population. Before

they were re-inoculated onto the host populations, the

spores of these 10 fungal strains were mixed in equal

proportions. Thus, our first null hypothesis was that the

frequencies of all 10 fungal strains would be nearly equal

in the M. graminicola populations collected from the same

host populations in the early-season. Our second null

hypothesis was that all 10 fungal strains would possess

the same level of virulence, therefore causing the same

degree of damage on both hosts. We observed significant

differences in genotype frequencies and selection coeffi-

cients, as well as in the amount of damage caused on

different hosts, suggesting that genetic variation for

reproductive fitness and virulence existed among the

field strains of M. graminicola used in this experiment.

The variation in reproductive fitness and virulence

among the pathogen strains might be attributed to

differences in the abilities of fungal spores to germinate,

penetrate and colonize the different hosts during the

process of infection. The observed variation might also

be caused by differences in the abilities of the pathogen

strains to reproduce and transmit their progeny to

uninfected leaves after they infected the host plants.

The high genetic variation found in this pathogen could

be the result of repeated cycles of sexual reproduction

year round (Chen & McDonald, 1996; Kema et al.,

Table 1 Selection coefficients and their standard deviations (in

parentheses) of six Mycosphaerella graminicola strains on each of three

host treatments. Selection coefficients of strains M4, S2, S4 and S5

were not estimated because they occurred at frequencies that were

too low to provide meaningful estimates. Mean values followed by

different letters within a column differ significantly at P ¼ 0.05.

Numbers with bold font indicate that the selection coefficients

differed significantly from 0 at P ¼ 0.05.

Strains Madsen Mixture Stephens

M1 0.18 (0.01) a 0.27 (0.05) a 0.22 (0.02) b

M2 0.07 (0.03) bc 0.24 (0.05) a 0.55 (0.04) a

M3 0.12 (0.02) ab 0.11 (0.11) a 0.01 (0.01) c

M5 0.00 (0.00) c 0.16 (0.10) a 0.09 (0.05) c

S1 0.13 (0.03) ab 0.13 (0.10) a 0.26 (0.06) b

S3 0.12 (0.04) ab 0.10 (0.05) a 0.04 (0.02) c

Table 2 Analysis of variance for the selection coefficients of six

inoculated strains of Mycosphaerella graminicola.

Sources d.f. F-value P > F-value

Replication 2 0.93 0.4055

Host 2 4.23 0.0228

Strain 5 7.27 0.0001

Host * strain 10 4.27 0.0005

Madsen vs. Stephens 1 7.93 0.0080

Mixture vs. mean of 1 0.54 0.4694

Madsen and Stephens

Host-driven selection in pathogen populations 641

J . E V O L . B I O L . 1 5 ( 2 0 0 2 ) 6 3 4 – 6 4 7 ª 2 0 0 2 B L A C K W E L L S C I E N C E L T D

1996b; Zhan et al., 1998, 2000; Hunter et al., 1999),

large effective population size (Zhan et al., 2001),

co-infection events (May & Nowak, 1995; Nowak &

May, 1995; McDonald et al., 1999a; Linde et al., 2002),

high degree of gene flow among the natural populations

(Boeger et al., 1993; McDonald et al., 1995, 1999a) and

host specificity (Saadaoui, 1987; Gupta et al., 1994;

Kema et al., 1996a).

Trade-off hypothesis and effect of hostson the evolution of virulence

Our experiments demonstrated that the reproductive

fitness and virulence of a fungal strain were not correlated

(Fig. 5). The correlation coefficients between these two

parameters were very low on both the moderately

resistant cultivar Madsen and the susceptible cultivar

Stephens when we used genotype frequencies to measure

the fitness of the pathogen strains. Although these

correlation coefficients increased substantially when we

used selection coefficients as the measure of fitness, none

of them reached a significant level. These observations

falsify the trade-off hypothesis, namely that natural

selection favours pathogens with an intermediate level

of intrahost replication (Lively, 2001). Our findings also

do not support the hypothesis that virulence is a by-prod-

uct of pathogens evolving towards more rapid replication.

The observation of no trade-off between the reproduc-

tive fitness and virulence of the pathogen in our study

could be attributed to several factors. We consider three

possibilities. (1) The indicator of virulence in this

experiment was the percentage of leaf area covered by

lesions. The formation of lesions may be a response of the

host plant to a toxin produced by the pathogen. A fungal

strain producing higher levels of toxin on a host does not

necessarily have a higher fitness on the same host, unless

the toxin is the main determinant of the ability of a

fungal strain to infect, survive, reproduce and compete.

(a) (d)

(e)(b)

(c) (f)

Fig. 5 Correlations between reproductive fitness and virulence of fungal strains: (a)–(c) are the results for the moderately resistant cultivar

Madsen; (d)–(f) are the results for the susceptible cultivar Stephens.

642 J. ZHAN ET AL.

J . E V O L . B I O L . 1 5 ( 2 0 0 2 ) 6 3 4 – 6 4 7 ª 2 0 0 2 B L A C K W E L L S C I E N C E L T D

Because the measure of virulence used is only partially

correlated to the actual virulence of the pathogen (i.e.

the negative effect on fitness of the host), this will

unavoidably introduce noise into the analysis of the

correlation between the two parameters. (2) The fitness

of the 10 fungal strains was estimated simultaneously by

inoculating them together onto the hosts and allowing

them to compete over several cycles of infection. On the

other hand, the virulence of the fungal strains was

evaluated individually in a single cycle of infection. It has

been shown that competition has a strong impact on the

evolution of virulence (e.g. Taylor et al., 1998). It is

possible that the 10 fungal strains we used responded

differently to the two systems of infection. Some fungal

strains might perform better under the condition of

competition for resources (multi-infections) but other

strains might have the advantage when there is not

intrahost competition (mono-infections). (3) The limited

number of data points used for the correlation analysis

was not sufficient to provide a biologically correct

interpretation.

Our results also showed that host populations had a

significant effect on the rate of evolution in the pathogen

populations. When the rate of evolution from different

hosts was compared, we found that pathogen popula-

tions evolved more slowly on the moderately resistant

host Madsen. The pathogen populations collected from

Madsen maintained the highest genotype diversity and

showed the smallest change in genetic structure over the

course of the experiment. The populations from Madsen

also had smaller selection coefficients distributed over a

narrower range compared with Stephens (Table 5). This

result supports the hypothesis that partially resistant

hosts can retard the rate of evolution in pathogen

populations (Vanderplank, 1968; Gould et al., 1991).

We found that the host mixture did not select for a

more diverse and less rapidly evolving pathogen popu-

Table 3 Pairwise comparisons of genotype frequencies between

Mycosphaerella graminicola collections made from the same host

populations at different sampling times. Numbers following the v2

values (in parentheses) are the degrees of freedom. Sample sizes for

Madsen, the mixture and Stephens were 179, 198 and 184 in the

early-season collection and 115, 137 and 150 in the late-season

collection, respectively. The sample size for Stephens in the middl-

season collection was 129.

Hosts

Early vs.

mid-season

Mid- vs.

late-season

Early vs.

late-season

Madsen – – 9.38 (7)

Mixture – – 23.75 (8)**

Stephens 16.23 (8)* 7.90 (8)* 41.42 (8)***

*Significant at P ¼ 0.05; **significant at P ¼ 0.01; ***significant at

P ¼ 0.001.

Table 4 Pairwise comparisons of genotype frequencies between

Mycosphaerella graminicola collections made from different host

treatments at the same point in time. Numbers above and below the

diagonal are v2 values and their corresponding degrees of freedom

(in parentheses) for the early- and late-season, respectively. The

sample size for each collection was the same as shown in Table 3.

Hosts Madsen Mixture Stephens

Madsen – 11.96 (8) 26.24 (8)**

Mixture 17.09 (7)* – 9.70 (8)

Stephens 48.24 (8)*** 16.25 (8)* –

*Significant at P ¼ 0.05; **significant at P ¼ 0.01; ***significant at

P ¼ 0.001.

Table 5 Genotype diversities and their standard deviations (in

parenthesis) in Mycosphaerella graminicola collections made from

different host treatments and times. The sample size for each

collection is the same as shown in Table 3.

Treatments Early-season Late-season

Madsen 3.750 (0.081) 4.960 (0.101)

Mixture 3.365 (0.080) 4.498 (0.097)

Stephens 3.457 (0.089) 3.739 (0.066)

Table 6 Pairwise comparisons of genotype diversity among Mycos-

phaerella graminicola collections made from different host treatments.

Numbers above and below the diagonal are t-values and their

corresponding degrees of freedom (in parenthesis) for the compar-

isons of pathogen collections from the early- and late-season,

respectively.

Treatments Madsen Mixture Stephens

Madsen – 1.669 (375)* 0.832 (363)

Mixture 2.332 (252)** – 0.730 (382)

Stephens 4.739 (265)*** 2.414 (287)** –

*Significant at P ¼ 0.05; **significant at P ¼ 0.01; ***significant at

P ¼ 0.001.

Fig. 6 Disease progress curves for Septoria tritici leaf blotch epidemics

in plots of Stephens (susceptible), Madsen (moderately resistant),

and a 1 : 1 mixture of Stephens and Madsen. C1–C3 indicate the

days on which the early, middle-, and late-season collections of

Mycosphaerella graminicola were made.

Host-driven selection in pathogen populations 643

J . E V O L . B I O L . 1 5 ( 2 0 0 2 ) 6 3 4 – 6 4 7 ª 2 0 0 2 B L A C K W E L L S C I E N C E L T D

lation compared with the pure stands. The mixture had

lower genotype diversity than Madsen in the early-

season and was midway between the pure stands in the

late-season. The logistic growth rate and seasonal chan-

ges in genetic structure of pathogen populations collected

from the mixture were also midway between the two

component pure stands. Host mixtures have been pro-

posed as an alternative method to retard the evolution of

virulence in pathogens (Burdon, 1987). The results from

this experiment argue against the expectation that the

cultivar mixture would slow down the rate of evolution

in the pathogen population. However, it is noteworthy

that the selection coefficients among the pathogen strains

did not differ significantly in the mixture (Table 1). The

lack of significant differences in selection coefficients was

because of the high variance in genotype frequencies

among different replications of the mixture treatment.

This result suggests that disruptive selection might have

been operating in the host mixture treatment.

Local adaptation

Our data demonstrated that, on average, there is no

indication of local adaptation in the wheat–M. graminicola

system. However, when we considered fungal strains

individually, we found that the patterns of local adapta-

tion were complicated and unpredictable. The pathogen

strains varied in their patterns of local adaptation,

ranging from local adaptation in strains M2 and S3, to

local maladaptation in strain M3. Strains M2 and S3

appeared to be more adapted to their sympatric hosts, the

cultivars from which they originated. Although M3

originated from Madsen, this strain showed greater

adaptation to Stephens by the late stage of the growing

season. On the other hand, strain M1 provides good

evidence of being host nonspecific. This strain had similar

fitness across all host treatments in both the early- and

late-season. Although M1 predominated in all pathogen

collections, it exhibited an overall reduction in genotype

frequency over the growing season, which suggests that

this strain was very successful in initial infection and

colonization of each host treatment but had lower fitness

for competition components such as reproduction and

dispersal.

In addition to the influence of gene flow and mating

system, patterns of local adaptation can also be affected

by other biological, ecological and evolutionary processes

(Caprio & Tabashnik, 1992; Gandon et al., 1996; Morand

et al., 1996; Kaltz & Shykoff, 1998). Interactions among

these factors might lead pathogens to increase their

performance in some foreign host populations, be

unchanged in others and decrease in performance in still

others (Kaltz & Shykoff, 1998), depending on the hosts

compared and the pathogens used. Local adaptation in

the M. graminicola–wheat plant pathosystem might be

counterbalanced by these processes. In M. graminicola,

new immigrants, in the form of ascospores, will continue

arriving from outside of the experimental field during an

epidemic cycle (Kema et al., 1996b; Zhan et al., 1998;

Hunter et al., 1999). It is possible that the 10 fungal

strains we used in this experiment experienced different

evolutionary histories and processes, although they were

originally sampled from the same field population and

the same hosts. Some of these strains might have been

local residents and ⁄or early colonists of the cultivars

Madsen (e.g. strain M2) or Stephens (e.g. strain S3).

These strains were representatives of selected populations

that had sufficient time to exploit and adapt to their

respective host environments before they were collected

and used in our experiments. Others (e.g. strain M3)

could represent the population of recent immigrants that

did not have enough time to adapt to the local host

environment before they were collected.

Environmental factors may also affect the patterns of

local adaptation (Kaltz & Shykoff, 1998). One example is

the performance of strain M5 on Stephens. Its frequency

increased early in the season and decreased late in the

season. The same pattern was exhibited in all three

replications of this treatment (Fig. 4). We speculated

earlier that this pattern was because of changing repro-

duction patterns in this strain, moving from mainly

asexual reproduction early in the season to mainly sexual

reproduction later in the season (Zhan et al., 1998). We

consider it equally likely that this unusual pattern of

change was associated with environmental fluctuations.

The success of a parasite on its host depends on the

susceptibility of the host, the reproduction ability of the

pathogen and the suitability of environment, including

factors such as temperature, light intensity, humidity and

dew period (Levy & Cohen, 1983a,b). It is possible that

strain M5 had highest fitness at moderate temperatures;

therefore, its frequency increased as temperatures

increased from early-season to middle-season but de-

clined from middle-season to late-season when the

temperatures passed the optimum for M5.

Conclusions

Our experiments differ from previous studies in two

ways. First, we investigated the evolution of pathogen

virulence under the condition of competition among

pathogen strains for living resources in an outdoor field

experiment, which we believe offers a reasonable

approximation of what happens in nature. Secondly,

we measured pathogen reproductive fitness based on

changes in the relative proportions of each fungal strain

in each host population. This approach combines many

fitness attributes, including the abilities of pathogen

strains to infect, colonize, reproduce and compete for

new host tissue. This type of experiment has only

become possible with the advent of sensitive genetic

markers (DNA fingerprints) that allow individual fungal

strains to be tagged, released, and recaptured in a field

setting. We found that pathogen strains originating

644 J. ZHAN ET AL.

J . E V O L . B I O L . 1 5 ( 2 0 0 2 ) 6 3 4 – 6 4 7 ª 2 0 0 2 B L A C K W E L L S C I E N C E L T D

from the same field varied in their patterns of local

adaptation, ranging from locally adapted to locally

maladapted. This finding suggests that it might be

necessary to use many pathogen strains or pathogen

populations with high genetic variation to draw appro-

priate conclusions regarding the pattern of evolution for

virulence. Conclusions based on the performance of a

single pathogen strain and ⁄or a population with low

genetic variation may be misleading and could partially

account for the previous contradictory reports (e.g.

Karban, 1989; Soler & Møller, 1990; Bull et al., 1991;

Bull & Molineux, 1992; Ni & Kemp, 1992; Sork et al.,

1993; Ebert, 1994; Memmott et al., 1995; Davelos et al.,

1996; Ebert & Mangin, 1997; Roy, 1998; Mackinnon &

Read, 1999; Mutikainen et al., 2000; Davies et al.,

2001).

Acknowledgments

This project was supported by National Science Founda-

tion grant number DEB-9306377. We thank B. A. Roy

for her comments and suggestions on this manuscript.

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