AN ABSTRACT OF THE THESIS OF
Amy B. Peetz for the degree of Master of Science in Botany and Plant Pathology
presented on July 23, 2007.
Title: Understanding Sporulation and Dissemination of Podosphaera macularis, Hop
Powdery Mildew.
Abstract approved:
Walter F. Mahaffee
Podosphaera macularis causes one of the most important diseases, powdery
mildew, of Humulus lupulus (hop). If left unmanaged, hop powdery mildew can cause
total crop loss due to disease or browning of hop cones rendering the cones unmarketable
to buyers. The Hop Powdery Mildew Infection Risk Index (HOPS) is heavily relied on
for management of the disease. However, HOPS assumes constant inoculum presence,
which is not likely to be true. Evidence suggests that temperature fluctuations influence
inoculum availability. As such, knowledge of inoculum presence and density and their
relationship to environmental conditions may increase management efficacy by reducing
pesticide use and cost of crop production.
Molecular methods for detecting and quantifying P. macularis were developed
and used to analyze air samples taken from hop fields for two seasons. A protocol for
DNA extraction from field samples was modified in order to use PCR to detect and
quantify P. macularis DNA from the field. Primers and a probe designed to the internal
transcribed spacer (ITS) region of P. macularis ribosomal DNA have made inoculum
detection possible using both conventional polymerase chain reaction (PCR) and realtime quantitative PCR (qPCR). DNA extracted from conidia impinged on glass rods
coated in silicon grease has been used as template for qPCR, and we have successfully
detected as DNA extracted from 10 spores
Specific and sensitive detection of P. macularis DNA with conventional PCR was
possible under conditions typically used to evaluate qPCR; however results from field
samples indicated that sensitivity was an issue, in that spores were not detected in
samples from fields with high disease pressure.
The effects of constant exposure (5, 10, 15, 20, 25, 30, and 35°C) and 6 hr
exposure (18, 22, 26, 30, 34, and 38°C) on sporulation of P. macularis were tested.
Exposure to constant low and high temperatures decreases sporulation, which indicates
that inoculum may not always be available once the epidemic has started. Sporulation is
also decreased during brief exposures to temperatures above 30°C. These data indicate
that inoculum availability is reduced when the temperature exceeds 30°C in the field. A
modification of HOPS should be examined to incorporate an algorithm which takes the
findings in this study into account.
Understanding Sporulation and Dissemination of Podosphaera macularis, Hop Powdery
Mildew by Amy B. Peetz A THESIS submitted to
Oregon State University in partial fulfillment of
the requirements for the degree of Master of Science Presented on July 23 2007 Commencement June 2008 Master of Science thesis of Amy B Peetz presented on July 23, 2007
Approved:
Major Professor, representing Botany and Plant Pathology
Chair of the Department of Botany and Plant Pathology
Dean of the Graduate School
I understand that my thesis will become part of the permanent collection of Oregon State
University libraries. My signature below authorizes release of my thesis to any reader
upon request.
Amy B Peetz, Author
ACKNOWLEDGEMENTS
I would like to thank my major professor, Dr. Walter Mahaffee for the
opportunity to work toward a Masters of Science degree with him at the USDA-ARS
HCRL, and for the mentorship which reflected his own excellent standard of research,
patience, and generosity. This is experience was not absent of challenge, and I learned a
great deal of how to work through failure with a shrug and a smile in the pursuit of higher
knowledge. I am also grateful to an excellent graduate committee, who guided and
supported me through this research.
I wouldn’t have had a good start without the mentoring of Meredith Larson, and
the technical and emotional support of Tara Neill was a constant throughout this process.
I greatly appreciate the countless conversations I had with Brenda Shaffer, Marcella
Henkels, Ruth Price, and Virginia Stockwell in Dr. Joyce Loper’s lab at the USDA-ARS
HCRL over troubleshooting molecular methods. The tips and techniques I picked up in
those conversations were priceless, and my research was stronger for their input. The
statistical analysis of my data was greatly enhanced by generous advice of Dr. Niklaus
Grunwald.
I am grateful to Madeline Dildine and Patricia Wallace for helping with the
enormous task of processing field samples. Clair Elliott also generously contributed
countless hours helping with temperature experiments. The field scouting reported in this
study would not have been possible without the help of Andrew Albrect, Baird Chrisman,
and data shared by Dr. David Gent of the USDA-ARS FSCRL and members of his lab.
CONTRIBUTION OF AUTHORS
Dr. Walter Mahaffee was involved in the method development, data analysis,
writing, and editing of all research reported in this thesis. Dr. John Jackson was involved
in developing the first primer set used in this research to amplify Podosphaera macularis
DNA. Dr. Gary Grove assisted in the design of methods used in the research reported in
Chapter 3, including validation of the spore traps as a viable method for air sampling.
Dr. David Gent collected the majority of the field disease incidence data reported in
Chapter 3.
TABLE OF CONTENTS
Page
Introduction......................................................................................................................... 1 Sporulation of the Powdery Mildews ................................................................................. 3 Introduction..................................................................................................................... 3 Ascospores ...................................................................................................................... 5
Conidia............................................................................................................................ 7 Conclusion .................................................................................................................... 18 Detection and quantification of airborne Podosphaera macularis conidia in hop yards . 19 Introduction................................................................................................................... 19 Materials and Methods.................................................................................................. 24 Results........................................................................................................................... 33 Discussion ..................................................................................................................... 44 Effects of Temperature on the Sporulation of Podosphaera macularis on Humulus lupulus............................................................................................................................... 50 Introduction................................................................................................................... 50 Materials and Methods.................................................................................................. 52 Results........................................................................................................................... 57 Discussion ..................................................................................................................... 60 Conclusion ........................................................................................................................ 64 Appendix........................................................................................................................... 66 Appendix A: Podosphaera macularis ITS Region Consensus Sequence and Primer Target Locations ........................................................................................................... 67 Appendix B: Alignment of ITS sequence of Podosphaera macularis and Podosphaera clandestina .................................................................................................................... 68 Bibliography ..................................................................................................................... 70 LIST OF FIGURES Figure
Page
3.1 Custom spore trap used to collect air samples in hop fields.............................. 30 3.2 Agarose gel electrophoreses of PCR-amplified products using template
extracted using different lysis solutions................................................................... 33 3.3 Melt curve analysis of products amplified using the Sybr-green assay............. 37 3.4 Sybr-green quantitative polymerase chain reaction (qPCR) standard curve of
the log of the starting quantity of pHPM DNA versus the corresponding cycle threshold (Ct) values................................................................................................. 38 3.5 Taqman quantitative polymerase chain reaction (qPCR) standard curve of the
log of the initial concentration of template versus the corresponding cycle
threshold (Ct) values................................................................................................. 39 3.6 Disease progress curves of hop powdery mildew found in hop fields
throughout the Oregon region with detection events indicated with asterisks…...... 41 3.7 Disease progress curves of hop powdery mildew found in hop fields
throughout the Washington region with detection events indicated with asterisks... 42 3.8 Number of P. macularis conidia detected from field samples versus disease incidence found by field scouting in Oregon: A 2005 and B 2006........................... 43 3.9 Number of P. macularis conidia detected from field samples versus disease incidence found by field scouting in Washington: A 2005 and B 2006.................... 43 4.1 Prepared plants in plastic vessels mounted with custom impaction spore
sampler...................................................................................................................... 53 4.2 Temperature recorded within a vessel in each growth chamber used for the 6 hr exposure experiment.................................................................................................. 54 4.3 Effect of constant temperature on sporulation of hop powdery mildew............. 57 4.4 Effect of 6 hr exposure at different temperatures on sporulation........................ 59 LIST OF TABLES Table
3.1 Summary of specificity testing results................................................................
Page
35 3.2 Sensitivity of PCR for detection of P. macularis conidia after extraction using the FastDNA Spin Kit................................................................................................ 36 3.3 Detection P. macularis and disease incidence in OR and WA during 2005 and 2006........................................................................................................................... 40 DEDICATION
I dedicate this thesis to my husband, my son, and my father; whose patience,
surprise, and support, throughout this process was beyond measure.
Introduction
Podosphaera macularis is an obligate fungal plant pathogen which causes
powdery mildew of Humulus lupulus, hops. The epidemic begins shortly after bud break
in the spring, and can cause devastating damage if left unmanaged. Successful
management of powdery mildew is heavily dependent on early control and well timed
applications of fungicides. The Hop Powdery Mildew Infection Risk Index (HOPS) (70)
that was adapted from the Gubler/Thomas model for grape powdery mildew (48) is
currently used for management of hop powdery mildew. The HOPS uses weather data
such as temperature and precipitation to assess risk of infection. It runs on the
assumption that inoculum is ever present, which is not likely to be true. Our limited
understanding of inoculum presence and movement may be expanded through the use of
molecular techniques. Such information could improve the accuracy of disease
forecasting models, and would likely decrease the cost of production and the number of
fungicide applications recommended by such models.
The use of molecular techniques such as the polymerase chain reaction (PCR),
and real-time quantitative PCR (qPCR) has greatly improved the accuracy and speed at
which fungal plant pathogens are detected in agricultural crops (133;134). The
intertranscribed spacer (ITS) region of ribosomal DNA is a common target for molecular
studies involving phylogenetics of Erysiphales (91), and detection of other plant
pathogenic fungal species from environmental samples (98). The ITS region can be a
reliable target for use in detection and quantification studies as it is fairly stable, typically
has a high copy number, and is usually a region of high conservation within species.
2
Recent studies indicate that temperature has an important influence on disease
progress (71;118). As such, it is possible that temperature is also an important factor in
sporulation. If the presence of inoculum is dictated by temperature, and is not constantly
present throughout the growing season, then the disease forecasting models could be
improved by accounting for this.
The objectives of this thesis were: (i) develop primers specific to the internal
transcribed spacer region of P. macularis (ii) develop a method for extraction and
detection of P. macularis spores from field samples (iii) identify and develop an
appropriate real time quantitative PCR assay to quantify P. macularis DNA from field
samples (iv) determine whether the number of spores trapped correlate to disease levels
in the field, and (v) gain further understanding about how temperature affects sporulation
of P. macularis.
3
Sporulation of the Powdery Mildews
Introduction
The Erysiphales are obligate fungal biotrophic plant pathogens (94), which are
commonly called powdery mildews in reference to their visible superficial white mycelia
and conidia on the surface of leaves, stems, fruits, buds, and flowers (15;107). They
cause important and severe disease epidemics in many agricultural crops world wide
(19;39;57;61;82), but particularly in regions with dry summer climates similar those
found in the Pacific Northwest region of the United States (44;70;102). Severe leaf
infections usually result in coalescing lesions that often cause wilting, chlorosis, curling,
stunting, and/or senescence of the leaves (34;39;84;114) while infection of inflorescences
and fruit can result in flower and fruit abscission, loss in fruit quality due to blemishes,
cracking, and deformation is more common (2;84;127). Economic losses are generally
associated with reduction in crop quality and cost of control but can also be due to yield
reductions (60).
The Erysiphales are capable of 25-40 generations per growing season, and they
can reproduce both sexually and asexually. They overwinter as either sexually derived
ascospores within chasmothecia, or asexually as mycelia on perennated buds or on
protected plant foliage (15;60). The following season, either ascospores or conidia
derived from the overwintering mycelia serve as the primary inoculum with conidia
serving as the inoculum for all subsequent generations. Only the asexual phase of some
species may be observed, depending on crop or geographic region. As such, conidia are
4
the primary source of inoculum in many agricultural crops (17;101;115;128). Abundant
production of conidia, which are readily wind disseminated throughout the growing
season, underlies the explosive nature of the epidemic (2;13;27;101).
The influence of environmental factors on infection by conidia is fairly well
understood (3;15;60;127), but limited for ascospore infection. Inversely, factors that
influence ascospore production and dissemination are better understood than those
influencing conidial production and dissemination.
5
Ascospores
Ascospores are produced primarily at the end of the growing season within
chasmothecia (ascocarps) (38;60) when complementary hyphae come in contact with
each other (109). As such, high levels of disease are positively associated with
production of chasmothecia (101). When compatible hyphae come into contact, sexual
recombination begins and initiates the cascade of events which results in the production
of ascospores housed within a chasmothecium (9). The vast majority of Erysiphales
species are heterothallic (37;87;110), with a few exceptions being homothallic (110).
Maturation of chasmothecia is evident by morphological changes, and coincides
with the maturation of ascospores. The main distinction between young and mature
chasmothecia is the presence or absence, respectively, of primary appendages. Primary
appendages, otherwise referred to as receptive hyphae, are present on immature
ascocarps, and act to anchor the ascocarp to the vegetative hyphae beneath it (9;43).
Secondary, or true, appendages emerge from all parts of the chasmothecium, and except
for Phyllactinia, are thought to function as anchors during transport (9). Gadoury and
Pearson (36) found that as chasmothecia age, the quantity and distribution of lipids in the
cytoplasm of the ascospore changes. As ascospores mature, the lipids became more
aggregated. The authors speculated that it is possible that the conversion of lipids to a
nonhydrophobic substance such as carbohydrates may lead to a decrease in water
potential in the cytoplasm. Ascospore differentiation has been shown to be greatest after
a period of wetness (77), however there is no information on how this process occurs.
6
When fully developed, ascospores are club shaped and number from 1-8 asci per ascus
(9).
Ascospore dispersal occurs either within chasmothecia or freely. After the
connection between the receptive hyphae and the vegetative hyphae is broken, mature
chasmothecia may be carried long distances in wind currents or on plant material (grove,
plant disease 200?). Generally, chasmothecia are dislodged from leaves by wind, rain
splash, or mechanical movement and become lodged in bark, bud scales, other cracks and
crevices, or remain on fallen leaves (45)until dehiscence (38;127).
Chasmothecia dehiscence is a function of the weakening of the chasmothecial
wall, a coinciding decrease in water potential of the ascospore cytoplasm, and swelling of
asci and ascus (36). The chasmothecia wall significantly weakens as the chasmothecia
age, and is also dependent on a corresponding warming event, such as conditions found
in temperate regions in early spring (36;95). As ascospores mature, a decrease in water
potential of the ascospore cytoplasm is associated with a decrease in glycogen content of
the ascus (58), and is thought to lead to an increased pressure potential of viable
ascospores as the ascocarp ages (36;58). The increased pressure potential, coupled with
wetting causes chasmothecia to imbibe water. The ascus and the asci then begin to swell
and continue to do so until the chasmothecia wall ruptures and the ascospores are
discharged (36;58) (81).
Ascospores appear to be forcefully discharged (95) from chasmothecia and are
disseminated in wind currents or rain splash. Ascospores are reported to be ejected from
3 to an impressive 31mm above the chasmothecia (95;130). Optimal conditions for
7
release are species dependent (45;59;60). In general, release follows a period of
dormancy (69), exposure to free water(26;45;60;95;130), or repeated wetting events (36),
and temperatures between 5-20°C(29;69;87). Ascospore release is most likely to occur in
the morning when the temperature is rising but there is still high relative humidity (7).
Conidia
Production. Conidiophores develop from hyphal cells and, depending on species,
produce either a single conidium or chains of 2 to 8 or more conidia every 24 hr. Nonchain forming conidiophores are characterized as having a simple structure consisting of
a basal cell, a generative cell above it, and one or two maturing conidia on the distance
end. Non-chain forming conidiophores produce a single conidia every 24 hr(64). Chain
forming conidiophores consists of a long basal cell, 1-3 cylindrical cells above it, and a
chain of 2 or more swollen conidia (64). Chain forming conidiophores produce 2-8
conidia every 24 hr. For both groups, a maturing conidium is separated from the cells
below it by a gradual increasing constriction of the septa that link the cells together (50).
However, it is evident that the two types of conidiophores differ in their diurnal cycle of
spore production (64).
The influences of temperature, relative humidity, available light, and rainfall on
sporulation have been examined for their individual impacts on the rate of conidial
production (23;24;60;64;83;127). However, the effects of these individual factors are
confounded and difficult to separate in practice because they directly impact the growth
and sporulation of the pathogen as well as the growth of the host, which in turn impacts
8
the pathogen. Temperature and light are two such variables which are closely linked and
have confounding effects on the host-pathogen dynamic. Under natural conditions,
temperature begins to rise shortly after the sun rises, continues through mid day, and then
begins to fall prior to the setting of the sun.
There are many plausible effects of this daily event on the host and the pathogen.
Host photosynthesis increases with increasing sunlight (to a point) which results in
increased nutrient availability to the powdery mildew. Increased photosynthesis, coupled
with increasing temperatures, leads to an increase of respiration the host. Increased host
respiration ultimately results in higher relative humidity within the canopy of a field crop
and at the leaf surface it results in higher relative humidity and lower temperatures within
the boundary layer (30) . Higher nutrient availability (65;66), an increase in relative
humidity at the leaf surface(18;89;121), and lower temperatures within the boundary
layer are to parameters which are likely to enhance pathogen growth or sporulation and
increased disease development. However, light striking the leaf surface also causes an
increase in leaf surface temperature (14;24). If extreme, this rise in temperature could
lead to the host closing its stomata to preserve water, thereby lowering the relative
humidity within the boundary layer and removing the buffer from extreme temperatures,
both are parameters which can be unfavorable conditions for germination, infection, or
sporulation (30;71;93;132). High temperatures can also cause alterations in the host
physiology that result in reduced infection (71) such as increased thickness of the host’s
cuticular layer to thicken. Host maturity is also a factor which influences host resistance
to powdery mildew infection(40). The obligate nature of the Eryisphales dictates that
9
each environmental component will have both indirect and direct effects on sporulation.
It is this complex interaction of environmental parameters with the pathogen and host that
ultimately affect the rate of sporulation. As such, it is important to keep the complexity
of the system in mind when trying to interpret how individual factors affect sporulation.
Temperature appears to be the most influential environmental parameter on spore
production. It has been shown to significantly impact the latent period, spore size,
number of spores produced, etc. Optimal temperatures for conidial production appear to
be species specific, ranging from 18-27ºC (22;30;46;89;117;121;132).
Stavely and Hansen (112) found a positive correlation between increasing
temperature and spore size. Exposure to below-optimal temperatures delayed the onset
of conidial production and caused a significant decrease in conidial length. Exposure to
above-optimal temperature (28°C) severely inhibited sporulation. The authors speculated
that the change in size of conidia was attributed to the host’s response to the
temperatures. If the metabolism of the host was slowed at the below-optimal
temperatures for disease development, it is possible that there were fewer nutrients
available for the fungus to use for conidial production.
The latent period of Eryisphales is generally 14 days or greater at temperatures
below 10°C(30;67;112;124-126), and shortest (5-7 days) around their optimal
temperature (15-25°C depending on species)(22;30;46;67;89;124-126). Generally,
temperatures above 25°C often result in inhibition or death of a sporulating colony
colonies (30;73)(Newton and Cherewick, (89;112;121;132). For instance, exposure to
30°C for only 2 hr can reduce the risk of infection for Podosphaera macularis that grows
10
on Humulus lupulus by 50% (71). Additionally, infection of E. necator conidia drops to
60% at 26C(22) and down to 10% and less when exposed to temperatures between 33
and 35°C. (30;93;132).
The maximum rate of sporulation occurs from 15-23°C, and the numbers of
spores produced every 24hr varies with species(73) (22;23;89;121;132). In general,
conidia production declines as temperatures decrease from around 15-20°C
(23;49;65;121), and as temperatures rise above 26°C (22;89;132).
Reports on the effect of temperature on the number of conidia produced vary.
The differences in these reports are due to factors such as possible differences in
experimental methods, and species specific response to temperature. In 1953, Last (65)
reported that conidia of Erysiphe graminis were produced 10 times faster at 14°C than
conidia produced at 7°C. This dramatic effect was not confirmed in a subsequent
study(121), which reported conidial counts at 14°C were twice those recorded at 7°C. It
is possible that the difference between these studies is due to different colony age, as this
detail is not available in the study completed by Last. At 19°C, E. necator is reported to
produce double the number of conidia when grown on Vitis vinifera ‘Carignane’ as
compared to the numbers produced when it grows on Vitis vinifera ‘Chardonnay’(22).
However this difference is less dramatic when temperatures rise above 22°C.
Chain forming and non-chain forming species may respond differently to changes
in temperature. Cole (23) reported no change in conidial production of E.
cichoracearum, a non-chain producing powdery mildew, at 18 and 24°C in an alternating
hot-cold regime over 24hr. This may indicate that, in a 24hr period, the effect of
11
temperature on the number of conidia produced is more dramatic for chain producing
powdery mildews than for non-chain producers. Further research on how exposure to a
range of constant temperatures affect conidial production of non-chain producing
powdery mildews is needed.
The effect of relative humidity on disease development has been controversial in
that there is no clear indication of whether high humidity is beneficial or detrimental to
infection and sporulation. Some of this controversy stems from differences in how
individual species respond to moisture stress. Some species are reported to have a high
tolerance to low humidity (30;85;131), while others are not (131). Still other species are
reported to be both strongly influenced developmentally and have a positive correlation
of conidial production to an increasing relative humidity (18;89;121). Yarwood (1936)
reported that E. polygoni on clover and bean has a high tolerance to low humidity. In
1954, Delp reported that exposure to high (99%) and low (≤25%) humidities had little, if
any effect on development of U. necator on leaves. A range of 12-100% humidity was
found to have no effect of the development of S. macularis(85). This is in contrast to
development of E. polygoni on mustard, E. graminis, E. cichoracearum, and S. pannosa,
which were less tolerant of low humidity(131). Ward and Manners(121) found a positive
correlation of conidial production and an increasing relative humidity up to 100% for E.
graminis. Carroll and Wilcox (18) report that humidity strongly influenced development
of U. necator. Optimum relative humidity for development ranged from 83.0% to 86.5%.
Conidial production also generally increased with increasing humidity. Quinn and
Powell (89) report high relative humidities (80-100%) for optimal colony development
12
for Oidium begoniae. When E. graminis conidia were produced in conditions of 40%
and 100% humidity, conidia from the latter group germinated at higher rates. Others
have also reported that viability of E. graminis conidia is greater with exposure to high
humidity. Differences in the conidia germinability produced at different humidity levels
(89) suggest that one or more processes of production were affected. It could be that
conidia production at high humidity results in higher water content of conidia and
therefore increased germination rates (18;89;121). However, the specific processes of
conidial production that humidity effects are still unknown.
Conidial production is strongly influenced by components of light such as near
U.V. light, direct sunlight, and indirect or reflected sunlight. However, due to the
obligate nature of powdery mildews, the effects of these parameters on the pathogen are a
function of how the light impacts the host. Conidial production appears to follow a
circadian rhythm(60;83;131), where conidial production slows in the dark and is
completed in the light (24;25;64;89). This phenomenon may suggest that there is some
level of photosensitivity for the maturation stage. Laboratory studies show that conidia
develop faster when exposed to constant daylight than they do in periods of constant
darkness (23;25;64;83;89;115;131). When exposed to alternating light and dark periods,
there is a distinct increase in spore production during the light period following a dark
period (24;25;83). This appears to be true for both chain forming and non-chain forming
species of powdery mildews (64).
Conidia are produced more rapidly when exposed to near U.V. compared to
fluorescent light (25) at the same intensity. This suggests that the effect of UV light on
13
sporulation is independent from the effects of light on the host and nutrient availability
due to increased photosynthesis. However, it is possible that the UV light increased
ambient and leaf surface temperature (14), which is likely to affect both the host and the
pathogen.
Direct sunlight can cause the surface of a leaf to be 3-7°C hotter than ambient
temperature due to transference of radiant energy (14). This increase in temperature
could cause the conditions at the leaf surface to be above the upper temperature threshold
conducive for fungal development. Early works suggest that the leaf surface temperature
on a single hop leaf can vary greatly, and as such, different regions of the leaf surface
itself may be more optimal for growth and development than others (14). The effect of
radiant energy gain is probably a contributing factor to the differences in susceptibility of
regions in a grape vine canopy. Regions of the grape that receive the most sunlight or
reflected light from the soil are the least susceptible to infection, while regions receiving
the greatest amount of shading the most susceptible (101).
Shade is reported to be more favorable for various stages of powdery mildew
infection and development (101;127) , but no information is known about how shade may
influence spore production. For several plants the eastern exposed side of the canopy
develops more disease than the western exposed region of the canopy. Another possible
explanation for the differences in susceptibility could be the increased cuticular wax
thickness on leaves that are exposed to more sunlight (30). In the field, high
temperatures are accompanied by increased transpiration which leads to an increase in
humidity within a canopy. In the shaded areas, it is possible that higher levels of
14
humidity are maintained, and the host acts as a buffer from both direct sunlight,
fluctuations in humidity, and extreme temperatures (30). All of which are factors that are
conducive for disease development.
Conidial production is inhibited by rainfall. Physical damage to mycelium (12) or
conidiophores (20;131) may prevent further production of conidia due to a decrease in
available nutrients or a reduction of intact conidiophores. Sivapalan (108) found that
sporulation was greatly reduced with simulated rain, and that sporulating colonies hit
with natural rain may fail to continue to sporulate normally.
Young, healthy host tissue is optimal for sporulation(16). This is likely due to the
relatively high levels of energy and nutrients available in the tissue. Young leaves are a
sink for photosynthates and stored nutrients(56), and they tend to have reduced plant
defenses. In addition to young tissue, succulent new tissue is also highly conducive to
rapid disease development. In a study done on one species of Erysiphe, higher numbers
of spores were caught in crops treated with nitrogenous fertilizer than in crops not treated
with fertilizer (65;66). This suggests that well fertilized crops are more susceptible to
powdery mildew than those which are deficient in nitrogen.
All of the aforementioned factors influence the physiology of the host and thereby
affect the nutrients available to the pathogen and due to the obligate nature of Erysphales
fungi it is difficult to determine direct and indirect effects of these factors. However, it is
clear that knowledge of environmental conditions could be used to help predict the
availability of conidia. This knowledge could then be used to enhance disease
forecasting models.
15
Liberation. Powdery mildews are thought to have a gradual, passive mode of
conidial release that is associated with a decrease in humidity and increase in
temperature. Until the conidium on the distal end of the conidiophore is fully mature, a
pore remains in the septum between it and the cell below it. This cytoplasmic connection
allows fluid to continue to flow into the conidium, and it swells as water fills the vacuoles
(79). Upon maturation, the conidiophore cell wall rapidly invaginates until it is
physically separated from the maturing conidium below. However, there is a
mucilaginous coating on the exterior surface of the conidium that appears to function in
holding the conidium in place (50;76). In response to low humidity and increasing
temperatures, the mucilaginous coating dries and becomes brittle making the conidia
more readily wind dispersed due to the decreased adhesion to the conidiophore (60;115).
This theory is supported by numerous studies monitoring the concentration of air borne
conidia (1;24;25;49;115). The number of conidia trapped from the air is maximal
between 1200 and 1800 hr on days when there are large decreases in humidity with rising
temperature (46;66;86;102;131) and during periods when leaf surfaces are dry
(49;60;115).
Active conidial liberation can be triggered in still air in response to decreasing
relative humidity combined with constant or increasing temperature (1)(Hammerlund,
1925 as cited by (127), where a sudden breakage of the rim of attachment between the
mature conidium to the cell below results in the violent discharge of conidia. A
combination of low relative humidity and high or increasing temperatures is commonly
associated with active conidial release(1;24;25;49;115) but a sudden reduction of relative
16
humidity has been indicated as the main environmental factor (1;83). It is unlikely that
active liberation is effective in conidia spore dissemination on its own, since in the
absence of wind conidia appear to fall to base of conidiophores and form dense mats (50).
Dissemination. Multiple environmental factors contribute to conidial
dissemination. Spore trapping studies (1;15;23;46;49;64;66;89;115) indicate that a
combination of increasing wind speeds, decreasing relative humidity, drying of the
leaves, and increasing temperature are associated with an increase in conidial release(49).
Most spores are caught when temperature and wind speed are at or nearing their peak,
humidity levels are low, and on days with high solar radiation. As with conidial
production, the effects of these factors on conidial liberation are confounded and not
easily separated.
Wind appears to be the most significant factor in dissemination. Wind influences
dissemination by causing leaf flutter and picking up conidia in gusts and transporting
them to different locations. Bainbridge and Legg(4) found that wind speeds which cause
leaves to shake may be more important for dispersal than wind speeds which actually
remove conidia from conidiophores. However, wind speeds speeds greater than 2.25m/s
tend to compact conidial mats (50).
Light induced diurnal periodicity is reported for studies on spore loads in the field
and in the green house for a variety of species(89), (1;15;23;46;49;66;115), reports vary
on the time of day conidial dissemination occurs(64). It is possible that the variance in
the reports is correlated with variance in leaf wetness, temperature, and humidity. In
general, these parameters are most often conducive to spore release at mid day.
17
Rainfall can have a positive and negative effect on dissemination. The
mechanical movement of leaves associated with rain drops hitting them causes a dry
liberation of spores, and this phenomenon is known as “tap-and-puff”(15;108). This led
early researchers to assume that as with many other fungal pathogens, rain and the
presence of free water was beneficial to disease development(11). However, we
understand the powdery mildews to be dry weather fungi (129). Ultimately, continued
rainfall results in spores being removed from the air and potentially washed from leaf
surfaces (49;115). Patterns of spore catch suggest that a dry period with consecutive days
of no rain is necessary for the onset of conidial dispersal (123).
The majority of conidia produced in plants growing close to the ground do not
appear to be disseminated over long distances. Studies done on powdery mildews of
cereal crops and strawberries indicate that most of the inoculum remains within the plant
stand, and very little is found in the air above it (15;66;86). As such, disease develops as
discrete disease foci. However, it is not clear if this holds true for crops such as grapes or
cherries that are not as densely planted. Work on hop powdery mildew indicates that
disease epidemics rapidly become non-focal in nature (117); indicating that dissemination
is either extremely rapid or conidia are disseminated over longer distances than in row
crops.
While dispersal gradients are steep, evidence for long distance travel indicates
spores may travel very long distances. Spores of Erysiphe species have been collected by
suction impactors mounted on airplanes (15;55). Other researchers have collected viable
conidia at altitudes up to 1500 m high(15). The host is also used to help elucidate
18
geographic range and movement of Erysiphalean populations. Molecular markers for
virulence genes have been used to study the movement of Blumeria graminis in wheat
crops across Europe (68).
Conclusion
Further understanding about the factors which initiate and sustain
sporulation and those which result in the death of a sporulating colony is needed in order
to further increase the effectiveness and efficiency of powdery mildew management
programs. Current management practices assume inoculum is continuously available
throughout the duration of the growing season. However, our limited understanding of
the environmental factors effecting sporulation indicates that this assumption is not
correct. Thus, understanding how factors such as humidity and temperature, particularly
periods when temperature is nonconductive to growth of Erysiphales fungi, influence
inoculum availability would be useful in further developing disease or infection risk
forecasters for powdery mildews. A more accurate prediction of disease or infection risk
would likely mean that fewer pesticides would be used in managing powdery mildews
thus increase the economical and environmental sustainability of powdery mildew
management programs.
19
Detection and quantification of airborne Podosphaera macularis conidia in
hop yards
Introduction
Powdery mildew of hop, Podosphaera macularis, Braun & Takamatsu (formerly
Sphaerotheca macularis (Wallr.:Fr.) Lind syn. S. humuli (DC.) Burrill) is one of the most
economically important pathogens of commercially grown hops (Humulus lupulus) (82).
Introduction of this pathogen, and the crop losses associated with infection, have caused
dramatic changes in hop production and management in the U.S. (17;70;118). Despite a
growing understanding of the epidemiology of hop powdery mildew (41;42;70;117;118),
our ability to estimate infection risk is limited due to sparse data on factors influencing
inoculum production and density. The epidemiologically explosive nature of the disease
requires early and efficient management, because it can rapidly become uncontrollable
and result in complete crop loss due to rejection by buyers (70).
Currently, management of hop powdery mildew is strongly influenced by a Hop
Powdery Mildew Infection Risk Index (HOPS) (70) that was adapted from the
Gubler/Thomas model for grape powdery mildew (48). The model assesses the influence
of temperature and precipitation on infection risk, and is used to determine the interval
between fungicide applications that would be the most effective for managing the
disease. While the use of HOPS has reduced the number of fungicide applications, it
does not accurately reflect the epidemic under certain field conditions (41;42;117). In its
present form, HOPS is too conservative, in that shorter intervals for fungicide
applications are recommended than appear necessary in some regions or during specific
20
periods of the growing season. The model assumes that a constant source of inoculum is
present in the field as soon as hop shoots emerge; which is likely an incorrect assumption.
Early in the growing season disease levels are low (70) and the distribution is
random (117), making assessment by field scouts very difficult. Thus, growers have
chosen to assume disease is present and apply protectant fungicides. Sometimes neither
flagshoots nor disease is observed in fields for the entire growing season with little or no
disease observed at harvest (41;42). Thus knowledge of inoculum presence could also be
useful in determining whether to make fungicide applications.
In July and August, high daytime temperatures (30-40°C) are common throughout
the hop growing regions in the U.S. Previous studies indicate that exposure to
temperatures above 30°C for longer than 2 h has a marked effect on disease progress (71)
and inoculum infectivity (Mahaffee, unpublished). This indirectly suggests that there is
likely a decrease in viable inoculum due to the reduction in sporulating colonies
following exposure to supra-conducive temperatures (>30°C). However, this impact may
be less significant if disease severity is high and if supra-conducive temperatures are not
sustained for long periods of time (71).
Our ability to elucidate the impact of environmental factors on sporulation is
limited due to the difficulty in monitoring sporulation in the field, and the inherent
variability of the number of spores produced from individual lesions. The most common
methods for monitoring sporulation use various volumetric spore traps (e.g. Burkard and
Rotorod) which impinge spores on a sticky matrix and rely on visual identification and
enumeration of spores. Due to the rather nondescript nature of powdery mildew conidia
21
(9), and the high abundance of several species in a field on the weeds and neighboring
crops, this method of enumeration is time consuming and inaccurate; often requiring
hours to evaluate individual samples and making assumptions that all powdery mildewlike conidia present are the species of interest. The volume of air sampled must also be
limited in order to prevent dust, pollen and other debris from obscuring the mildew
spores on the sample rod (8). These difficulties might be overcome by using polymerase
chain reaction (PCR) approaches to detect and quantify fragments of DNA that are
specific to a particular species.
PCR methods have been used to detect and quantify numerous pathogens from
environmental samples (92;103;133;134) (5;5;31;53;97;100;104;119;119). Detection of
Fusarium oyxsporum f. sp. niveum and Mycospaerella melonis has been possible using a
range of concentration of templates from 10 pure microconidia or 100 microconidia in 1
g of artificially inoculated soil down to as low as 1ng pure DNA and 103 macroconidia g-1
soil (134). Detection of a single zoospore Phytophthora capsici in g-1 soil has also been
reported using nested PCR (133), a technique where two sets of primers were designed to
target regions of the ITS sequence. This improves the detection time from 2 weeks using
traditional methods to a matter of hours using molecular techniques, which could
dramatically shorten the time it takes to detect disease present in the soil.
The ITS region of ribosomal DNA is a region often used in diagnostic studies
(98). It is attractive because it is stable, has a high copy number, is heterogeneous among
species, and usually approaches near homogeneity within species. As such, there are
many reports on the DNA sequence of this region for the Erysiphales, which expedite
22
designing an assay to specifically target P. macularis DNA in a background of other
potential powdery mildews found in and around hop yards. This region has proven to be
useful for phylogenetic studies of the anamorphic state (28;54;62;91;116). Specific
detection of different powdery mildew species from herbaria specimens has been possible
using this region (62;80). Amplification has been reported from a single conidium of
Oidium neolycopersici using nested PCR (75), and 10 conidia of Erysiphe necator
(Falacy et al. 2007). The sensitivity of quantitative PCR (qPCR) has been reported as
low as 100 copies of the ITS region of Cladosporium sp. (53) isolated from oak leaves.
DNA concentrations equivalent to 0.01 cystosori have been detected using a qPCR assay
for detection of Spongospora subterranean in soil, water and plant tissue samples (120).
These reports indicate that the ITS region could be suitable target for the detection and
quantification of P. macularis in hop yards.
Development and implementation of molecular techniques to detect P. macularis
spores would help to expand our understanding of the parameters which influence
inoculum availability. Eventually, this knowledge could help further refine the HOPS
model in that it would be based off of when inoculum is available, rather than running on
the assumption that inoculum is ever present. Highly sensitive detection could also be
useful in helping growers determine if a field needs to be harvested early due to cone
infection. Late season infections of hop cones which are not visible to the unaided eye
are associated with rapid maturation of the crop and losses due to loss of cone quality
(51). Field observations indicate that harvesting fields just a few days early greatly
reduce cone discoloration (Mahaffee, unpublished)
23
The objectives of this study were to: (i) develop primers specific to the internal
transcribed spacer region of P. macularis (ii) develop a method for extraction and
detection of P. macularis spores from field samples (iii) identify and develop an
appropriate real time quantitative PCR assay to quantify P. macularis DNA from field
samples, and (iv) determine whether the number of spores trapped correlate to disease
levels in the field.
24
Materials and Methods
Plant maintenance. Symphony (John I. Haas, Inc., Yakima, WA) plants were
clonally propagated from greenwood cuttings (52). Rooted cuttings were transplanted to
5 × 5 × 10 cm pots with a mixture of Sunshine Mix #1 (SunGro Horticulture, Bellevue,
WA) and Soil Moist (JRM Chemical, Cleveland, OH) to reduce irrigation frequency.
Plants were fertigated with Champion 17-17-17 fertilizer with micronutrients
(McConkey’s, Portland, OR) with each irrigation. Plant material was kept free from
powdery mildew infection by vaporizing sulfur in the greenhouse (71).
Isolate maintenance. Single chain isolates collected from Oregon, Washington,
England and Germany were grown on ‘Symphony’ plants kept in 29.5 cm × 11.8 cm ×
12.1 cm plastic vessels (SNAPWARE®, Mira Loma, CA). A 10μm filter was used in
place of the lid to allow for air exchange. The isolates were incubated at 18°C with a 16­
h day-length (~300μmol/m2/sec) in a SG-30 controlled Environment Chamber (Hoffman
Manufacturing, Albany, OR), and irrigated as needed. Isolates were transferred every 2
weeks to 3 months to new plants to maintain sporulating colonies.
P. macularis ITS consensus sequence. Conidia from colonies were scraped
from the leaf surface into PCR tubes, pelleted by centrifugation (14,000 × g, 5 sec)
suspended in 100μl of Millipore water, and then incubated at 100°C for 5 min. The
resulting suspension was used as template for PCR amplification using the universal
fungal ITS primers ITS1 and ITS4 (122) to amplify the ITS region with HotMaster™ Taq
DNA polymerase (Eppendorf North America, Inc.) in accordance with the supplier’s
recommendations in a PTC-150 MiniCycler (MJ Research, Inc, Waltham, MA) with the
25
following cycling parameters: 94°C for 2 m, 35 cycles of 94°C for 20 s, 60°C for 44 s,
65°C for 30 s, followed by a final extension step at 72°C for 10min. PCR products were
cleaned using a Microcon kit (Millipore, Bedford, MA) and subsequently cloned into
Escherichia coli Top10 One Shot® Chemically cells using a TOPO TA Cloning® kit
(Invitrogen Life Technologies, Carlsbad, CA). The plasmids were purified using a
Wizard® Plus Minipreps DNA Purification System (Promega Corporation, Madison, WI)
using the recommended protocol. DNA concentration was calculated using an Ultraspec
3100 pro (Amersham Biosciences, Piscataway, NJ).
Sequencing was done with BigDye® Terminator v. 3.1 Cycle Sequencing Kit
(Applied Biosystems, Foster City, CA) using an ABI Prism®3730 Genetic Analyzer and
ABI Prism®3730 Data Collection (version 3.0) and DNA Sequencing Analysis (version
5.2) Software (Applied Biosystems), at the Center for Genome Research and
Biocomputing (Oregon State University, Corvallis, OR). DNA sequences were edited,
aligned, and a consensus sequence was compiled using Vector NTI Advance™ Software
(Invitrogen Life Technologies, Carlsbad, CA).
P. macularis specific PCR Assay. The consensus sequence was aligned with ITS
sequence of all species of Erysiphales in GenBank (NCBI, http;//www.ncbi.nlm.nih.gov)
as of 4/8/2005 in order to identify regions unique to P. macularis. A series of primers
were visually designed and analyzed using a blast search in GenBank to confirm
specificity to P. macularis. Annealing temperature of the primers was optimized using a
RoboCycler® Gradient 96 (Cedar Creek, TX) with the following cycling parameters:
94°C for 2 m, 35 cycles of 94°C for 20 s, 60-72°C for 44 s, 72°C for 30 s, followed by a
26
final extension step at 72°C for 10min. DNA was resolved on a 1% agarose gel with
10% ethidium bromide in 1X Tris-borate-EDTA buffer (90 mM Tris-borate and 2 mM
EDTA). Amplified DNA fragments were visualized under UV light using an
AlphaImager 2000 (Alpha Innotech, San Leandro, CA) after electrophoresis at 70 V for 1
hr.
Primer specificity was tested against DNA extracted from powdery mildew found
growing on several weeds found in and on crops growing near hop fields (Table 1).
Spore suspensions from P. macularis isolates collected from Oregon, Washington,
Germany, and England were used as template for PCR amplification using the P.
macularis specific primers. The 25.0µl PCR reaction consisted of 10.0µl of HotMaster™
Taq DNA polymerase, 2.0µl of 10mM forward primer, 2.0µl of 10mM reverse primer,
9.0µl of nuclease free water, and 2.0µl of template DNA. A PTC-150 MiniCycler was
used to perform the reaction and was programmed with the following cycling parameters:
94°C for 2 m, 35 cycles of 94°C for 20 s, 69°C for 44 s, 72°C for 30 s, followed by a
final extension step at 72°C for 10min. DNA was resolved on a 1% agarose gel with
10% ethidium bromide in 1X Tris-borate-EDTA buffer (90 mM Tris-borate and 2 mM
EDTA). Amplified DNA fragments were visualized under UV light using an
AlphaImager 2000 (Alpha Innotech, San Leandro, CA) after electrophoresis at 70 V for 1
hr. PCR products were cleaned using a Microcon kit (Millipore, Bedford, MA), and
sequenced.
Sybr-Green qPCR. An alignment of the P. macularis ITS region consensus
sequence and all other reported ITS sequence for other Erysiphales species found in
27
Genbank (NCBI, http;//www.ncbi.nlm.nih.gov) as of 4/8/2005 as well as those we
generated for Podosphaera aphanis from Strawberry and caneberries was done using
Vector NTI Suite v.9.0 (Invitrogen, Carlsbad, CA). The primers were visually designed
to target areas within the consensus sequence for the ITS region that had the highest level
of heterogeneity between P. macularis and all other reported ITS sequence for other
Erysiphales species. Primers were then analyzed using a blast search in GenBank to
confirm specificity to P. macularis.
The qPCR reaction was optimized for annealing temperature, primer
concentration (50, 300, and 900nM), and magnesium ion concentration using plasmid
DNA with the ITS region inserted into it as template (96). Bovine Serum Albumin
(BSA) was also examined for effects on binding inhibitors during qPCR to prevent
binding and subsequent inhibition of amplification of target DNA. Melt curve analysis
was performed after each qPCR run to determine whether the optimization was
controlling for non specific amplification.
The final reaction included: 10.0µl of SYBR® Green JumpStart™ Taq ReadyMix™
for Quantitative PCR, Capillary Formulation (Sigma-Aldrich Corp. St. Louis, MO), 1.8µl
of 10mM forward primer, 0.1µl of 10mM reverse primer, 3.9μl of nuclease free water,
2.2µl of 25mM MgCl2, and 2.0 µl of template DNA. Samples were processed using a
three-step protocol with the following thermodynamic parameters: 94°C for 120s, 60
cycles of 94°C for 10s, 69°C for 5s with fluorescence data collection, 72°C for 22s; a
melt curve analysis from 94-65°C at 1.5 s/°C using a LightCycler® II Instrument and
LightCycler® Software 3.5 (Roche Diagnostics Corporation Indianapolis, IN)
28
immediately followed QPCR amplification. A positive control was included in all
experiments which consisted of the PCR product derived the ITS region of P. macularis
amplified using the IT1 and ITS4 primers of White et al. (122) inserted into the TOPO
plasmid (Invitrogen). Standard curves were generated using a dilution series of plasmid
DNA at concentrations of 5.152, 5.151, 5.15, 5.15-1, and 5.15-2ng/ul (Figure 2.3).
TaqMan qPCR. An alignment of the P. macularis ITS region consensus
sequence and all other reported ITS sequence for other Erysiphales species found in
Genbank (NCBI, http;//www.ncbi.nlm.nih.gov) as of 9/12/2005 as well as those we
generated for Podosphaera aphanis from Strawberry and caneberries was done using
Vector NTI Suite v.9.0 (Invitrogen, Carlsbad, CA). A custom TaqMan® primer/probe
set was visually designed to target areas within the ITS region that had the highest level
of heterogeneity between P. macularis and all other reported ITS sequence for other
Erysiphales. The probe was designed with a 6-carboxyfluorescein (6-FAM) reporter dye
on the 3’ end, and a minor groove binder/Non-flourescent quencher (MGBNFQ )
molecule on the 5’ end. The probe was synthesized by PE Applied Biosystems (Foster
City, CA), and the primers were synthesized and HPLC purified by Integrated DNA
Technologies, Inc. (Coralville, IA).
PCR reactions were optimized as above with the final protocol consisting of
12.5µl of TaqMan® Universal PCR Master Mix, 2.0µl of 10mM forward primer, 2.0µl of
10mM reverse primer, 0.5µl of probe, 2.5µl 10X Exo IPC Mix (Applied Biosystems),
0.5µl of 50X Exo IPC DNA, and 5.0µl of template DNA. Optimal annealing temperature
for the primer set was verified at 61°C. Samples were processed with a two-step protocol
29
with the following cycling parameters: 50°C for 2 m, 95°C for 10 min, 55 cycles of 95°C
for 15 s with fluorescence data collection, and 61°C for 105 s using an AB 7500 Fast
System and software (version 1.3.1; Applied Biosystems). An exogenous internal
positive control (IPC) (Applied Biosystems) was included to control for false negatives
due to qPCR inhibition (33). We used a more dilute concentration of the IPC DNA than
the manufacturer recommends in order to directly compare the Ct values of the IPC and
the Ct values of the field samples. All reactions were run in triplicate. There were two
negative controls; one with no template and IPC and another with no template and no
IPC. This allowed us to control for any possible contamination.
The relationship of the number of spores detected to the crossing threshold (Ct)
was determined using air samples (glass rods used to run in spore traps for 7 days) from
Hyslop farm spiked with a dilution series of P. macularis spore suspensions in 0.05%
Tween (71) resulting in 0, 1×103, 7.0×103, 2.5×104, or 6.25×105 spores present on a set of
rods. For consistency, the spore suspensions were aliquoted onto the rods in the equal
volumes (222.2 μl) of 0.05% Tween solution. DNA was then extracted as above and
used as template in the qPCR reactions described above. Verification of the spore
concentrations was done using qPCR and comparing Ct values for each of the Hyslop
farm samples. Each concentration of spore suspension in the extractions was then pooled
together to create a consistent source of template for the standard curves to be generated
with each qPCR reaction. A standard curve was generated by plotting the crossing
threshold (Ct) value against the log10 of the number of spores in each dilution series of the
30
P. macularis spore suspensions. As Ct
values are known to fluctuate slightly
between experiments, the standards were
run on each plate used to analyze field
samples.
Spore Sample Collection. Air
borne spores in the field were trapped using
a custom spore trap (Figure 3.1) similar to
a Rotorod (Multidata, Plymouth Meeting,
PA), that sampled 334 ±7 liters/min using
two 50 × 1 mm glass rods coated with high
vacuum grease (Dow Corning, Midland,
MI) mounted on the rotating arm of the
spore trap. The traps were deployed in
Figure 3.1 Custom spore trap used to collect air
samples in hop fields. Air was sampled at 334
±7 liters/min.
fields on the leeward side of the prevailing
wind direction. Samples were collected
weekly at the time of disease assessment
and stored at -20°C until processing. Occasionally, sample periods were longer due to
field management practices (e.g. pesticide application). Air samples that had a low
probability of containing spores of P. macularis from Humulus spp. were also collected
during July and August, 2006 at the Hyslop Crop Science Field Research Laboratory in
31
Corvallis, Oregon. This location was chosen due to it was remote in its proximity to
known plantings of Humulus sp. and local wind patterns.
DNA extraction from spore trap samples. The FastDNA Spin kit (Qbio gene,
Morgan Irvine, CA), PowerSoil, UltraClean soil and Plant (MO BIO Laboratories, Inc.,
Carlsbad, CA) DNA Kits were tested for use in extracting P. macularis DNA from
sample rods that was suitable for PCR using the manufacturers protocols. The FastDNA
kit protocol for isolating plant DNA with the following modifications: 1) Plant DNA
lysis solutions were used and the CLS-VF solution was amended with 2%
polyvinylpyrrolidone (PVP-40) (Sigma-Aldrich, St. Louis, MO); 2) Samples were
homogenized for 30 s at speed setting 5.0 in the FastPrep FP 120 homogenizer (BIO
101/Savant, Vista, CA) and repeated after a 5 min chilling period on ice (Falacy et al,
2007); 3) After incubation, the DNA binding matrix centrifuged for 5 m instead of 10 s,
as described by the manufacturer (Qbio gene). DNA extraction efficiency was tested by
extracting 10 replicates of 10, 100, and 1000 conidia. For consistency, the spore
suspensions were aliquoted onto the rods in the equal volumes in 1.76μl of 0.05% Tween.
Glass, nylon, and acrylic rods, and various coating (vacuum grease, lecithin, honey, and
petroleum jelly) were then tested for suitability for DNA extraction using the Fast
Protocol with glass rods coated with vacuum grease being the most suitable (data not
shown). A subset of field samples which tested positive for the presence of P. macularis
DNA were randomly selected and sequenced to insure that amplicons were the target ITS
region from P. macularis.
32
Disease Assessment. In 2005 and 2006, hop fields in the Willamette and Yakima
Valleys of Oregon and Washington respectively, were assessed weekly during the
growing season for leaf (117) and cone (42) disease incidence. Briefly, transects (rows)
were arbitrarily selected, and in each transect either 10 leaves or 25 cones were arbitrarily
selected from the first 60 to 100 plants. A field infection percentage [p=(∑x/∑n)*100]
for each field was calculated based on the number of diseased leaves or cones (x) and the
number assessed (n). Detection of P. macularis spores from field samples collected
using the modified spore samplers was recorded in either a binomial format (i.e.: detected
or not detected) or the number of trapped conidia trapped in each sample which was
extrapolated from a Ct value comparison with standard controls (Figure 3.5).
Statistical Analysis. Analyses were done using general linear model procedures
of the SAS statistical software (SAS Institute Inc., Cary, NC). The relationship between
Ct values and P. macularis spore concentration of the standard curves was analyzed by
regression analysis. The number of spores detected on sample rods was regressed against
percent disease incidence found in the field. Efficiency of the Taqman assay was
calculated using the following equation (88): Efficiency = [101/slope]-1.
33
Results
ITS consensus, specificity and sensitivity of P. macularis detection. The ITS1
and ITS4 (122) primers amplified a 564-bp product. The consensus sequence (Appendix)
was derived from the ITS region obtained from two independent DNA amplifications
from 26 isolates collected from hop fields in Oregon, Washington, Germany, and
England. There were 4 single nucleotide polymorphisms, 6 insertions, and 4 deletions
found in a comparison of the consensus to a prior submission for P. macularis from H.
lupulus (S. humuli AF448224). There was limited heterogeneity of the ITS consensus
sequence of P. macularis to the Genbank accessions off species within the Podosphaera.
There were between 2-11 base pair differences between the new consensus sequence and
the ITS sequence of P. aphanis var. aphanis (formerly S. aphanis var. aphanis (accession
AB000938, AB026136, AB026141,), and P. ferrugunea var ferrugunea (formerly S.
ferrugunea var. ferruginea (accession AB026152, AB027232), and a complete homology
was found with P. filipendulae (formerly S. filipendulae (accession AB022385) (10).
These species of Podospaera are not reported in the U.S., and the plants they grow on are
not reported in the western U.S.
The P. macularis specific primers HPMF2 (5’­
TGAAGCCACGCAGGGCGCCTGTC-3’) and HPMR4 (5'­
ACTATGTTTAGGGGACGCCGAA-3'), amplified a 383-bp product. Detection of P.
macularis conidia was possible when using DNA extracted from 10 conidia as template,
but was detected consistently when using DNA extracted from 1000 conidia as template
(Table 3.2). All samples and were homologous with the consensus (data not shown).
34
DNA extraction. PCR using DNA extracted in the presence of either the glass or
acrylic rods as template did not appear to be inhibited while nylon rods did result in
inhibition (data not shown). Glass rods were chosen as the sample collection rods
because of potential comparison with other studies. Vacuum grease was selected as the
coating material for the glass rods because it did not appear to inhibit PCR amplification
and was readily available as a consistent quality controlled product.
The FastDNA Spin Kit appeared to yield DNA with the least amount of inhibitors
and was further refined to maximize inhibitors removal. Only the plant lysis solutions
provided by the Fast DNA Spin Kit with added 2.0% PVP-40 worked consistently when
using glass or acrylic rods coated with high vacuum grease (Dow Corning Corp.) (Figure
3.2).
.
1
2
3
4
5
6
7
8
8
Figure 3.2 Agarose gel electrophoreses of PCR-amplified products using template
extracted using different lysis solutions. Lanes 1-2, DNA marker; Lanes 3-4, template
from two separate extractions using the Fungal lysis solution from FastDNA Spin Kit in
the presence of environmental debris; Lanes 5-6, template from two separate extractions
using the Plant lysis solutions from FastDNA Spin Kit in the presence of environmental
debris; Lane 7, positive control; Lane 8, negative control.
35
Table 3.1 Summary of specificity testing results
Pathogen Species
Blumeria graminis (DC.) Speer
Erysiphe aquilegiae var. ranunculi (Grev.)
R.Y. Zheng & G.Q. Chen
E. convolvuli
E. cichoracearum DC var. cichoracearum
E. magnicellulata var. magnicellulata U. Braun
E. pisi DC.
E. rhododendri Kapoor
E. trifolii
Leveillula taurica (Lév.) G. Arnaud
E. syringae Schwein. syn Microsphaera
syringae (Schwein)H. Magn
Host
Poa sp.
Aquilegia canadensis
Convolvulus arvensis
Callistephus
Cirsium arvense
Coreopsis sp.
Lactuca serriola L.
Mentha arvensis
Rudbeckia laciniata L.
Taraxacum officinale
Phlox
Medicago sativa
Rhododendron
Trifolium pratense
Allium cepa L.
Syringa vulgaris
Caragana arborescens
Lam.
Ilex verticillata (L.) A. Gray
Acer sp.
Rubus ursinus
Detection with
HPMF2/ TaqMan
HPMR4 c
Assayd
-
-
-
Microsphaera nemopanthis
Sawadea sp.
Podosphaera aphanis (Wallr.) U. Braun & S.
Takamatsub formerly Sphaerotheca macularis
(Wallr.) U. Brauna
Rubus idaeus
Podosphaera aphanis (Wallr.) U. Braun & S.
Takamatsub formerly Sphaerotheca macularis
f. sp. fragariae (Wallr.) U. Brauna
Fragaria sp.
Podosphaera clandestina (Wallr.:Fr.) Lév.
Prunus sp.
+
P. delphinii (P. Karst) U. Braun & S. Takamatsub S. delphinii (P. Karst) S. Blumera
Ranunculus abortivus L.
-
P. fusca (Fr.) U. Braun & N. Shishkoffb
Cucurbita pepo L.
-
formerly Sphaerotheca fusca (Fr.) S. Blumera
P. macularis (Wallr.:Fr.) U. Braun & S.
Takamatsub formerly Sphaerotheca macularis
Humulus lupulus L.
(Wallr.:Fr.) Linda
P. leucotrica (Ell. & Ev.) Salmon
Malus domestica Borkh.
P. pannosa (Wallr:.Fr.) de Baryb formerly
Sphaerotheca pannosa (Wallr:.Fr.) Léva
Prunus persica
Uncinuliella flexuosa Peck
Aesculus sp.
a
Binomial fide Braun (1987) (9)
b
Binomial fide Braun and Takamatsu (2000) (10)
c
The forward primer HPMF2 (5’-TGAAGCCACGCAGGGCGCCTGTC-3’) and the reverse primer
HPMR4 (5'-ACTATGTTTAGGGGACGCCGAA-3')
d
The forward primer HPMTMF (5’-CTGTCCTGCGCGGCTGA-3’), the reverse primer HPMTMR (5’­
ACTATGTTTAGGGGACGCCGAA-3’), and the minor groove binding (MGB) probe HPMTMP (5’­
6FAM - ATGTAGTTAGTGCAGTCTGAGAA - MGBNFQ-3’)
36
Table 3.2 Sensitivity of PCR for detection of P. macularis conidia after extraction using the FastDNA Spin
Kit.
# No. of conidia
# No. of
Amplifications
# No. of successful
Percent successful amplifications
per extraction replicates
per extraction
amplifications
per PCR reactiona
1000
10
2
20
100%
100
10
2
12
60%
10
10
2
2
10%
a
The percentage of successful amplifications from 20 attempts to amplify DNA extracted from 1000, 100,
or 10 conidia.
Sybr-green qPCR. The Sybr-green assay indicates that the primer sets HPMF2
(5’-TGAAGCCACGCAGGGCGCCTGTC-3’) and HPMR4 (5'­
ACTATGTTTAGGGGACGCCGAA-3') and HPMF2 with HPMR5 (5'­
GGGCTTCTCTGGCGGGCACTCC-3') successfully amplified a 123-bp and a 393-bp,
respectively, fragment from the ITS region of P. macularis ITS DNA inserted into E. coli
(pHPM), from conidia, and from conidia acquired from field samples. Greater specificity
to P. macularis DNA was found with the HPMF2/HPMR4 primer set and it was selected
as the final set for use with the Sybr-green qPCR assay. However, melt curve analysis
(Figure 3.3) showed denaturation of a product at about 85.5ºC and at 90.5ºC, indicating
that nonspecific binding or amplification was occurring. This secondary product was
found to be independent of primer sequence or concentration, magnesium ion
availability, target DNA concentration, template source (i.e. plasmid or spore DNA), or
annealing temperature (Data not shown). Even though the presence of this secondary
product was independent of template concentration, it was of concern because the aim of
the project was to specifically detect P. macularis DNA in field samples, and the nature
of the secondary product remained unknown.
37
The qPCR product was visualized on an agarose gel and showed two bands, the
expected band at 393bp and the second band at around 90 bp. Sequence of the second
band indicated that it was homologous to the 3’ end of the P. macularis consensus
sequence (data not shown). Despite this anomaly, there was a significant (P> 0.0001)
linear relationship between logarithm of the concentration of pHPM DNA, and Ct
(y=3.77x + 21.53; R2=0.99) (Figure 3.4).
Figure 3.3 Melt curve analysis of products amplified using the Sybr-green assay. Products were amplified
from 5.15×102 ng/ul pHPM (green), 5.15×101 ng/ul pHPM (red), 5.15 ng/ul pHPM (black), and 5.15×10-1
ng/ul pHPM (purple), 5.15×10-2 ng/ul pHPM (gray), the P. macularis negative control (blue).
TaqMan qPCR. The taqman primers HPMTMF (5’­
CTGTCCTGCGCGGCTGA-3’), HPMTMR (5’-ACTATGTTTAGGGGACGCCGAA­
3’), and the minor groove binding (MGB) probe HPMTMP (5’-6FAM ATGTAGTTAGTGCAGTCTGAGAA - MGBNFQ-3’), amplified a 368 bp product from
pHPM, from DNA extracted from conidia placed directly onto greased rods, and from
conidia caught in field samples. Initially, DNA from twenty seven different powdery
38
30
26
Ct
22
18
14
10
2.71
1.71
0.71
-0.29
-1.29
Log0
Log of the Quantity of pHPM
Template DNA Used for qPCR
Figure 3.4 Sybr-green quantitative polymerase chain reaction (qPCR) standard curve of the log of the
starting quantity of pHPM DNA, ranging from 5.15×102 ng/ul to 5.15×10-2 ng/ul pHPM versus the
corresponding cycle threshold (Ct) values. y=3.77x + 21.53; R2=0.99
mildews known to occur in or near hop fields failed to be amplify with the
HPMTMF/HPMTMR primer set. However, at DNA concentrations near detection limits
P. clandestina was amplified despite four and two nucleotide differences in the primer
and probe, respectively (Table 3.1).
There was a significant (p<.0038) linear relationship between the log of the
number of spores spiked into each sample from Hyslop farms and the average Ct number
(y = -3.28224x + 41.11132; adjusted R2 = 0.9430) for each qPCR amplification (Figure
3.5). Efficiency of amplification was 101.7%. Some samples which had low levels of
quantifiable P. macularis DNA had an undetectable IPC Ct value (data not shown) and
39
the range of the Ct for the IPC was from 31.18 to 38.02. The mean IPC Ct value was
34.53 ± 1.34.
32
30
Ct
28
26
24
22
20
2.8
3.3
3.8
4.3
4.8
5.3
5.8
Log of the Quantity of P. macularis Conidia Extracted and Used for qPCR
Figure 3.5 Taqman quantitative polymerase chain reaction (qPCR) standard curve of the log of the initial
concentration of template ranging from 1.0×103, 7.0×103, 2.5×104, and 6.25×105 P. macularis conidia
spiked into air samples collected at Hyslop farms, versus the corresponding cycle threshold (Ct) values (y =
3.28224x + 41.11132; adjusted R2 = 0.9430). Data was a composite of nine separate runs of the
TaqmanqPCR assay.
Field detection and quantification of P. macularis conidia. Detection events
were indicated on disease progress curves which were recorded in each field for each
region and for each year samples were collected (Figures 3.6 and 3.7). The number of
conidia detected in field samples was extrapolated from a comparison of the Ct values for
the sample and the Ct values for the standard curve, and plotted against disease incidence
recorded in the field by scouting (Figures 3.8 and 3.9). There was no relationship found
40
between detection or quantification of P. macularis spores and the disease incidence found in the field (Table 3.3). Table 3.3 Detection P. macularis and disease incidence in OR and WA during 2005 and 2006. +
Region &
PCR/- PCR/+Fieldb + PCR/+Fieldc
- PCR/-Fieldd
+PCR/-Fielde
Year
Fielda
OR 2005
1
11
2
12
2
OR 2006
6
1
0
15
0
WA 2005
2
11
7
6
1
WA 2006
0
12
7
1
0
a
The number of field samples which P. macularis ITS region was detected using PCR, but the disease was
not observed in the field.
b
The number of field samples which P. macularis ITS region was not detected using PCR, and the disease
was observed in the field.
c
The number of field samples which P. macularis ITS region was detected using PCR, and the disease was
observed in the field
d
The number of field samples which P. macularis ITS region was not detected using PCR and no disease
observed in the field
e
The number of field samples which P. macularis ITS region was detected using PCR, but field data was
missing for the collection date.
Disease Incidence
41
100
B
A
C
80
60
40
*
20
*
0
1
D
D isease Incidence
*
*
F
E
0 .8
.8
0 .6
.6
0 .4
.4
0 .2
.2
* ** *
0
33// 1
3/ 31
4/ 30
5 / 30
5/
6/ 29
7/ 29
Date of Disease Assessment
8/ 28
9/ 27 33// 1
3/ 31
4/ 30
5/ 30
6/ 29
7/ 29
7/
Date of Disease Assessment
8/ 28
**
**
9/ 27 3/ 1
3/ 31
4/ 30
5/ 30
6/ 29
7/ 29
8/ 28
9/ 27
Date of Disease Assessment
Figure 3.6 Disease progress curves with detection events indicated by asterisks. Weekly incidence is of powdery mildew found in Oregon fields
A, B, C during the 2005 growing season; and in fields D, E, F during the 2006 growing season. Asterisks indicate the occurrence of detection of
P. macularis DNA in field samples. Open boxes indicate sample dates for which no sample was available for processing. Closed boxes indicate
sample dates that samples were available for processing.
42
100
A
C
B
Disease Incid
Incidence
ence
80
60
40
*
*
*
20
*
0
Disease
D
isease Incidence
Incidenc e
100
D
**
* *
*
*
E
F
80
*
60
40
20
0
33/1
/1
3/31
4/30
5/30
6/29
7/29
Date of Disease Assessment
8/28
9/27 3/1
3/31
4/30
5/30
6/29
7/29
Date of Disease Assessment
8/28
3/1
9/27 3/1
3/31
4/30
5/30
6/29
7/29
8/28
Date of Disease Assessment
Figure 3.7 Disease progress curves with detection events in the Washington region. Weekly incidence is of powdery mildew found in
Washington fields A, B, and C during the 2005 growing season; and in fields D, E, F during the 2006 growing season. Asterisks indicate the
occurrence of detection of P. macularis DNA in field samples. Open boxes indicate sample dates for which no sample was available for
processing. Closed boxes indicate sample dates that samples were available for processing.
9/27
43
20000
A
Number of Conidia Detected
Number of Conidia Detected
200000
800
600
400
200
A
5600
4200
2800
1400
0
0
24000
B
80
Number of Conidia Detected
Number of Conidia Detected
100
60
40
20
B
800
600
400
200
0
0
0
5
10
15
20
25
30
Percent Disease Incidence
Figure 3.8 Number of P. macularis conidia detected
from field samples versus disease incidence found by
field scouting in Oregon: A 2005 and B 2006. The
■▲◊ symbols indicate data collected from fields 1, 2,
or 3 respectively.
0
25
50
75
100
Percent Disease Incidence
Figure 3.9 Number of P. macularis conidia detected
from field samples versus disease incidence found
by field scouting in Washington: A 2005 and B
2006. The ■▲◊ symbols indicate data collected
from fields 1, 2, or 3 respectively.
44
Discussion
Specific and sensitive detection of P. macularis DNA with conventional PCR
using the primer set HPMF2/HPMR4 was possible using the typical evaluation methods
for qPCR (5;31;35;96;98;100;120). Results from field samples indicated that the spore
trapping and PCR methods were not suitable for detection or quantification since spores
were not detected in samples from fields with high disease pressure and rapid disease
spread. The lack of relationship between detection of P. macularis conidia from field
samples to disease levels found in the field may be due to several factors, including:
unresolved inefficiencies of DNA extraction from field samples, misplacement of traps
resulting in a lack of conidia on the samples, degradation of DNA due to exposure to
U.V. radiation caused by natural sunlight, and length of sampling time.
Removal of PCR inhibitors from field samples is notoriously difficult
(74;78;113). Despite using field samples to develop a modified protocol for the FastPrep
kit, it appears that some PCR inhibitors were present as indicated by the variation of Ct
for IPC control. Material adhering to the sample rods consisted of varying levels of soil,
pollen, insects (whole or parts), plant seeds, bird feathers, and other debris. There is also
the potential for pesticide residue to be present. Any number of potential PCR
amplification inhibitors may have been extracted along with the DNA thereby preventing
amplification (74;78;113). It is possible that the modified FastPrep procedure for DNA
extraction was not adequate for the removal inhibitors from some of these sources or that
their concentrations were too high for complete removal. Polyphenolics and lignins are
two compounds which are commonly found in environmental samples, and are known
inhibitors of PCR amplification (64;72).
45
Prior to processing field samples we believed that the modifications to the
FastPrep DNA extraction protocol were sufficient for inhibitor removal. Steps taken to
remove inhibitors included 1) the addition of PVP-40 during the lysis step, 2) additional 5
min centrifugation during the DNA binding step of the extraction protocol, and 3)
amplification was done from a 1:7 dilution of the template DNA in a final attempt to
decrease inhibition. These steps should have removed inhibitors via binding of
polyphenolics by PVP-40, and removal of bound inhibitors from the supernatant so as to
avoid transferring them to the following step during extraction. Also, the 1:7 template
concentration was found to remove inhibitors collected in field samples, yet it was not
dilute enough to cause problems with amplification due to lack of DNA in the sample
(data not shown) (Fallacy, in press).
It is difficult to determine if inconsistent detection was due to the lack of spores
trapped onto the sample rods. For example, in one field where disease incidence reached
100% both years, detection occurred in 2006 but not in 2005. The location of the spore
trap was the same between years, however the field was not trained up onto the trellis
system in 2005, and it was in 2006. In 2005, the canopy would not have been more than
0.5 m above the ground, while in 2006, it reached 5 m. Based on the spatial spread of the
disease in the field (data not shown), there appeared to be aerial spore movement in both
years. It is possible that the P. macularis behaves similar to other powdery mildews
where the aerial spores are not dispersed far above the canopy (15;66;86) and did not
reach the height of the trap (1.5m) in 2005. This scenario is contrary to results from
grape vineyards (Fallacy, in press); however the grape canopy was approximately 0.8m
above the ground with little obstruction of airflow under the canopy.
46
It is possible that the quality of DNA collected in the samples was less than
adequate for detection using PCR. The stability of DNA left on a sampling rod in the
field for up to a week could be an issue. It is not clear if the cells remained intact or were
lysed. The impact of a conidium onto the sampling rod may be sufficient for lysis, and it
is possible that DNA in a desiccated or lysed conidium may become degraded due to
enzymatic action. It is also possible for DNA to be degraded due to ultraviolet radiation
(90) after impingement on the sample rods. However, a similar study using a PCR assay
to detect the Erysiphe necator ITS region in grape fields did not indicate that the quality
of DNA was a problem for samples left in the field for 3-5 days (Fallacy, 2007).
Sequencing of positive field samples from our study indicated that DNA mutation within
the ITS region of these samples did not occur. However, due to the length of sampling
time, it is impossible to know when the conidia were collected on those samples, and
whether lack of exposure was a contributing factor in the positive detection of P.
macularis DNA.
The decision to collect samples weekly was directed by economic and logistic
constraints. Through discussions with Hop growers and field scouts it was determined
that acquiring field samples at frequencies less than 7 days would be cost prohibitive due
to added labor and cost of sample processing. Experiments were planned to address the
question of whether sampling once a week was justified, but disease in Oregon fields
were insufficient or nonexistent during 2005 and 2006 production season. However,
similar studies indicate that this method of spore trapping is effective for sampling
intervals of 3-5 days to detect E. necator DNA (Fallacy, 2007).
47
The assay developed for conventional PCR appeared to be highly sensitive and
specific to P. macularis DNA under both field and laboratory conditions. However, the
modifications in primer design and PCR conditions required for qPCR appeared to result
in a lack of primer specificity for P. macularis DNA. This decrease is likely due to
reduced annealing temperature used in the qPCR reaction in order to accommodate the
IPC control for inhibition in each reaction. An annealing temperature of 61°C resulted in
nonspecific amplification of DNA from P clandestina while no amplification was
observed with an annealing temperature of 69°C (data not shown).
The inclusion of an internal positive control in our qPCR assay had both
advantages and disadvantages. It gave an indication of when false negatives occurred
due to inhibition. However, we believe that ultimately the use of this IPC was not to our
advantage because 1) it restricted the annealing temperature of the reaction to 61°C, 2) it
was not the same size as the target amplicon, and therefore it is difficult to determine
whether it accurately reflects amplification efficiency of the target, and 3) fluctuations in
the Ct values for amplification of the IPC DNA in the presence of field samples did not
indicate the presence of any inhibitors in the field samples. The latter is highly unlikely.
All field samples were first analyzed using conventional PCR, and the positives were
then analyzed with qPCR. The qPCR developed in this study is more sensitive to pcr
inhibitors than the conventional assay, which was indicated both in preliminary analysis
(data not shown) and when amplification of some field samples by conventional pcr and
inability to amplify with qPCR (Figure 3.6 a-d).
The sybr-green assay was compatible with the more specific primers developed
for conventional PCR, however it was not selected for use because melt curve analysis
48
indicated that a second product amplified (Figure 3.3). It is possible, yet unlikely, that
this unidentified amplicon was evidence of a primer-dimer formation. Exhaustion of
options for optimization of the assay indicated that a more specific approach was
necessary, and a TaqMan® qPCR assay was subsequently developed.
A thorough comparison of the sequence data for the P. macularis ITS region and
ITS sequence data reported for other members of the Erysiphales revealed that it may not
be the best location to identify species within the Podosphaera group using qPCR and a
taqman approach. Compromises between recommended assay design, such as a 150bp
amplicon (our amplicon was 363bp), and placement of the probe with the base pair
mismatches on the 3’ end rather than the 5’ end, jeopardized the utility of using this
method for specific detection of P. macularis. The low heterogeneity of the ITS sequence
of the P. macularis consensus generated in this study, and data collected from accessions
of P. aphanis var. aphanis, P. ferrugunea var. ferruginea, and the complete homology of
P. filipendulae supports this conclusion. Additionally, this region is very similar in P.
clandestina, which is found in cherry orchards near hop fields in Washington. Other
regions used in fungal phylogenetic studies, such as within mitochondrial DNA or on the
RNA polymerase II (RPB2) (63) gene may be a better choice for future phylogenetic
work within this group.
The results of this study indicate that there is no correlation of the number of P.
macularis conidia collected in air samples to disease incidence in the field. Detection
and quantification of P. macularis DNA in a laboratory setting was successful. Future
studies using molecular techniques for highly specific detection and quantification of P.
macularis DNA should include the generation of an internal positive control which is
49
similar in length and melting temperatures to the target amplicon, and the use of a
molecular beacon or scorpion probes. These modifications to the assay would increase
specificity because thermodynamic constraints would no longer be an issue.
50
Effects of Temperature on the Sporulation of Podosphaera macularis on
Humulus lupulus
Introduction
Hop powdery mildew, caused by Podosphaera macularis, is an economically
important disease of hops (Humulus lupulus L.) worldwide, which can result in 100%
crop loss if not controlled. It is a polycyclic disease that can have as many as 40
generations in a growing season (7). Healthy sporulating colonies can produce as many
as 3.53x105 conidia/cm2 of lesion area (7), which are readily wind disseminated
throughout the growing season. These traits result in explosive epidemics where every
leaf in a field can become infected within 6 weeks of first infection (Gent, unpublished).
Current management is accomplished by using protectant fungicides applied
based on a calendar program or HOPS, an infection risk forecaster (70) that was adapted
from the Gubler/Thomas infection risk forecaster for grape powdery mildew (47). The
use of HOPS has resulted in the reduction of fungicide applications used to manage hop
powdery mildew (HPM) but it still appears to call for shorter spray intervals than
necessary which results in unnecessary applications (Mahaffee, unpublished). Currently,
HOPS assumes that the secondary spores are always present during the asexual phase of
the epidemic (70). This assumption is probably incorrect.
It is likely that temperature impacts spore availability of P. macularis in a similar
manner to which it impacts other powdery mildews.
For many species that cause
powdery mildew, conidial production is reduced or even severely inhibited as
temperatures rise above 26°C (22;73;89;112;124-126;132). Germination and risk of
51
infection have also been shown to be greatly reduced when temperatures reach 26°C and
higher for P. macularis (71) as well as other species(22;30;73;89;93;112;124-126;132).
Temperatures throughout July and August in the U.S. hop production regions fluctuate
between inhibitory daytime highs of 30-40°C and conducive nighttime lows of 15-20°C
(71).
As such, it is likely that conditions for sporulation and dissemination of P.
macularis do not always precede conditions conducive to infection. Thus, the current
HOPS model would incorrectly classify periods as high risk for infection even when
there are no viable spores available, potentially resulting in excessive fungicide
applications.
The objective of this study was to gain further understanding about how
temperature affects sporulation of P. macularis.
52
Materials and Methods
Plant maintenance. Clonal Symphony (John I. Haas, Inc., Yakima, WA) plants
were propagated from greenwood cuttings (52). Rooted cuttings were transplanted to 5
cm × 5 cm × 10 cm pots with a mixture of Sunshine Mix #1 (SunGro Horticulture,
Bellevue, WA) and Soil Moist (JRM Chemical, Cleveland, OH) to reduce irrigation
frequency. Plants were fertigated with Champion 17-17-17 fertilizer with micronutrients
(McConkey’s, Portland, OR) with each irrigation. Plant material was kept free from
powdery mildew infection by vaporizing sulfur in the greenhouse (71).
Inoculation Procedure. Plants with 2-4 unfurled leaves were chosen for
inoculations. All leaves on the plants and the apical bud were removed with the
exception of two susceptible leaves. Plants were inoculated with spore suspensions of
60,000 conidia/ml with conidia from Oregon field populations of P. macularis using a
handheld atomizer (Nalgene, Rochester, NY) (71). Plants were dried in a growth
chamber at 25°C within an hour of washing the conidia from the leaves of the inoculum
source, and then moved to an incubating chamber set at 18ºC with a 16h day length until
mature sporulating colonies had developed (ranging from 9-14 days after inoculation).
Plant preparation. Once mature and sporulating colonies had developed, the
plants were removed from the incubation chamber. Plants were pruned down to 1
infected leaf/plant. An air supply (14,000kg/m2) was used to blow the spores off the
colonies. Efforts to control for variation were made by using plants with leaves of similar
size and age, and by keeping the leaves 8 cm above the top of the pot.
In order to reduce the potential for disturbance of colonies prior to spore
collection, plant movement was minimized during incubation prior to spore collection.
53
Perforated tubing was placed around the stem
of the plant approximately 4cm below the
infected leaf, and the plants were then placed
in 29.5 cm × 11.8 cm × 12.1 cm plastic
vessels (Snapware, Inc, Mira Loma, CA) with
an airtight lid. The lids of the plastic vessels
were mounted with custom impaction spore
samplers (Figure 4.1) which sampled the air at
57 L/min using 1.5 mm × 32 mm acrylic
collector rods (Multidata, Plymouth Meeting,
Figure 4.1 Prepared plants in plastic vessels
mounted with custom impaction spore sampler.
PA) coated with a thin layer of petroleum jelly
(Vi-Jon Laboratories, Inc., St. Louis, MO).
These vessels were placed in the growth chambers with the plants inside them, and
attached to the air supply. The collector rods were installed and the lids closed. Thus, no
disturbance of the plants occurred prior to turning on the spore traps after the incubation
period (described below).
Effect of Constant Temperature. Four plants within four vessels were placed in
6 different growth chambers programmed to run at a constant temperature of 5, 10, 15,
20, 25, 30, or 35ºC with a 16h photoperiod (18.7 +/-1.7 μmol/s/m2 within a vessel. One
plant was used for visual analysis of how temperature effected sporulation, and the
remaining three plants were used for spore collection. Spore collection occurred
following the 48 h incubation.
54
Effect of 6 hr Exposure at Different Temperatures. Four plants in four vessels
were placed in 6 different growth chambers programmed to run at 18°C for 6h, then at
18, 22, 26, 30, 34, or 38°C for 6 h, and back down to 18°C for 12 h, respectively (Figure
4.2). One plant was used for visual analysis, and the remaining three plants were used for
spore collection. The plants were incubated for 24 h with a 16h photoperiod (18.7 +/- 1.7
μmol/s/m2 within a vessel), which began when the tubes were placed in the growth
chambers. Sample collection occurred following the 24h incubation
40
Temperature within Vessel
35
30
25
20
15
9:36
14:24
19:12
0:00
4:48
9:36
14:24
Time
Figure 4.2 Temperature recorded within a vessel in each growth chamber used for the 6 hr exposure
experiment. Each line represents temperature recorded during the 24 hr incubation prior to sample
collection. 6 hr exposure to 38°C represented the brown line; 34°C is represented by the purple line; 30°C
is represented by the aqua line; 26°C is represented by the yellow line, 22°C represented by the pink line;
and 18°C is represented by the blue line.
Sample Collection. Spore samples were collected by turning the custom
impaction spore samplers on, dislodging the spores with air blasts of 28,000kg/m2 at the
following interval: 1 blast/sec for 15 sec, 1 continuous blast for 10 sec, and 1 blast/sec for
55
5 sec for a total of 30 seconds of air supplied through the perforated tubing. The spore
traps were allowed to run for approximately 5 min, sampling 95× the air volume of the
vessel, prior to collecting the rods and microscopically enumerating the number of spores
trapped on the leading edge of both collection rods. Differences in the way leaves moved
when the air was applied during sample collection were noted (data not shown). The leaf
from each plant was removed and colony area was determined with Assess image
analysis software (APS Press, St. Paul, MN).
Experimental Design and Data Analysis. Each experiment was a randomized
complete block design with 3 replications and 3 sub samples per replication.
Replications occurred in time and growth chambers were randomly assigned a
temperature regime for each replication. A control was placed in each chamber that
consisted of a plant with mature sporulating colonies with spores removed (described
above) and placed inside a vessel (as above) with a HOBO® U10 Temp/RH Data Logger
(Onset Computer Corp., Bourne, MA) suspended from the top of the vessel. The control
was used to monitor temperature within the vessel and visually assess spore development.
Within chamber temperature was also measured using HOBO® U10 Temp/RH Data
Logger (Onset Computer Corp., Bourne, MA).
Data were transformed to number of trapped spores/cm2 of colony area for each
leaf, averaged over sub samples and then over replications. The relationship between the
temperature treatments and sporulation was described following multiple regression
procedures. Quadratic, cubic, and nonlinear effects of constant temperature and 6 hr
exposure to a range of temperatures were tested. Nonlinear models tested included a
square root model proposed for bacteria by Ratkowsky et al. (111), and a thermodynamic
56
model described by Scherm and van Bruggen (99). Equations that resulted in regression
terms whose coefficients were not significantly different from zero (P > 0.05) were
dropped from the analysis.
57
Results
Effect of Constant Temperature on Sporulation. Sporulation increased with
exposure to increasing temperatures up to 20ºC and began to decrease with exposure to
temperatures >25ºC. There was a significant (P < 0.0001) non-linear relationship of
temperature to the number of conidia trapped per cm2 of colony area that was described
by Ratkowsky’s four-parameter equation, R(T)=[b(T-Tmin)(1-ec(T-Tmax)]2 (Fig 4.3). The
number of spores trapped increased with increasing temperature until 25°C and then
decreased with increasing temperature. However, there was increased variation in
numbers of impinged spores at 15 and 25°C.
1400
1200
800
2
Spores/cm Lesion Area
1000
600
400
200
0
0
5
10
15
20
25
30
35
Temperature
Figure 4.3 Effect of constant temperature on sporulation of hop powdery mildew. Each point represents the
mean of 3 replications with 3 subsamples per replication. R(T)=[0.9225(T-9.5748)(1-e0.1986(T-34.5051)]2
Pseudo-R2=, P=0.0001. The error bars represent the standard deviation from the mean of 3 replications
with 3 subsamples per replication.
58
Visual assessment of control plants exposed to 5, 10, 15, 20, and 25°C
consistently indicated apparently healthy sporulating colonies with mature spores
available for collection among these treatments. Spores from colonies exposed to 30°C
appeared desiccated and had fewer mature spores available for collection than plants
exposed to lower temperatures, but less desiccation than colonies exposed to 35°C.
Visual assessment of control plants revealed prolific and consistent desiccation of
colonies occurring on control plants exposed to 35°C, and very few mature spores were
available for collection.
Effect of 6 hr Exposure at Different Temperatures. There was a significant (P
= 0.035) quadratic relationship (y = -0.67x2 + 35.70x – 362.94; adjusted R2 = 0.8205) of
temperature to number of spores/colony area (Figure 4.4). Sporulation increased with
increasing temperature exposure up to 26°C and then decreased. Visual assessment of
plants revealed consistent desiccation of colonies occurring on control plants exposed to
34°C, and this effect was more dramatic on control plants exposed to 38°C. Plants
exposed to 34°C and above appeared to have far fewer mature spores available for
dissemination than plants exposed to 22, 26, and 30°C.
59
200
120
2
Spores/cm Lesion Area
160
80
40
0
16
20
24
28
32
36
40
Temperature
Figure 4.4 Effect of 6 hr exposure at different temperatures on sporulation. Each point is the mean of 3
replications with 3 subsamples per replication, y = -0.67x2 + 35.70x – 362.94; adjusted R2 = 0.8205. Error
bars indicate the standard deviation from the mean for 5 replicates with 3 sub-samples per replication.
60
Discussion
Sporulation of P. macularis was reduced by exposure to temperatures above 25°C
and less than 15°C and almost nonexistent when colonies were exposed to 35°C for 48 h.
These findings indicate that the assumption of continuous inoculum availability by the
HOPS infection risk forecaster is probably incorrect. The reduction in sporulation of P.
macularis is similar to that reported for Erysiphe necator, where exposure to 30°C
dramatically reduces both the number of spores produced and the duration of sporulation
(22;30;132). Also, infectivity of conidia is significantly reduced when exposed to
temperatures between 33 and 35°C (30;93;132).
Despite considerable effort to standardize procedures for spore quantification,
inoculation, and plant growth, there was a high degree of unexplained variation in the
number of spores/colony area among replications. This variation may be due to
inconsistencies in inoculation procedure, disease severity and location, sample collection
among replications, inoculum source, plant age or health, or differences in greenhouse
environment during plant production. Overall, it is difficult to single out an individual
source of this variation and account for that covariance statistically.
Efforts were made to replicate plant inoculations consistently and select plants
with similar colonies location and density, yet there was still variation in distribution of
disease across replications. Some replications had colonies only on the adaxial leaf
surface while other had colonies on both the adaxial and abaxial surfaces which may have
not been visible or inadvertently missed during the first application of air applied to
remove spores. Studies on other powdery mildews indicate that inoculum density and
pattern of application can influence sporulation potential, and differences in infection
61
severity may cause variation in spore catch (83;106). As such, differences in inoculum
density may have reduced colony development and sporulation due to increased
competition for nutrients (22;106). The location of colonies may have influenced the
efficacy with which the applied air blasts caused spores to be dislodged from
conidiophores. The transference of single spores or chains to the leaf could have resulted
in improved consistency in location and density of lesions, but was impractical due to the
time and labor required.
Differences in leaf movement when air was applied during sample collection were
noted, and may have influenced spore release (data not shown). Bainbridge and Legg (4)
showed that the velocity at which a leaf moves is correlated to the number of spores
released. Efforts to control for this variation were made by using plants that were
roughly the same size, and also by manipulating the position of the leaf within the
sampling tube with respect to the air supply.
The large variation of number of spores trapped following exposure to 15 and
25°C for the constant temperature and 18, 22, and 30°C for the 6h exposure could be due
to disparities in how individual isolates in the population used as inoculum respond to
these temperatures. The inoculum used in this study was obtained from conidia produced
from field isolates collected throughout Oregon and maintained continuously in a growth
chamber over the span of 8 years. Conidia of P. macularis collected in the field were
added to the growth chamber yearly in order to maintain an accurate representation of the
field population. Isolates of Erysiphe fischeri have varying responses to temperature (6),
and it is possible that P. macularis isolates have a similar response. There are different
races of P. macularis that are associated with regional variation in the cultivars planted
62
(105); however, it is not known if the different races have adapted to environmental
differences among the regions.
Different levels of oncogenic resistance among the plants used may account for
some of the variation in sporulation rate. Groups of young hop plants used in this
experiment were propagated, transferred, and grown together. While the leaves used for
inoculation were not all of the same age, they were all between 8-12 days old. Hop
leaves are most susceptible to infection when they are about 9 -12 days old with a rapid
decrease after 12 days (118). However, lesion area rapidly decreases as leaves age(118),
which indicates that physiological changes in the host may also influence sporulation.
These physiological changes were partially accounted for by expressing sporulation in
terms of the lesion area present on the leaf, but this would not account for differences in
host factors that influence nutrient availability to powdery mildew colonies (56), which
could result in an increase or decrease of sporulation. Infection, colonization, and
sporulation of Erysiphe species have been shown to be inversely proportional to host leaf
age (21;30;32). Stavely and Hanson (112) observed a positive correlation between
increasing temperature and spore size and speculated that this is indicative of the
fluctuations in available nutrients due to the host response to temperature.
Differences in the number of spores produced per lesion area among leaves of the
same age could also be caused by water stress. It is possible that some of the plants may
have been inadvertently subjected to water stress prior to inoculation. Water stress has
been observed to be associated with decreased susceptibility and lesion development
(Turechek unpublished). This may be associated with the variation in temperature
63
response because it can take weeks for plants to fully recover from being water stressed,
and during that time they are less susceptible to infection (82).
The effects of temperature on sporulation presented here indicate that inoculum is
not always readily available after periods of exposure to temperatures greater 30°C, and
that disease or risk forecasters may be improved by accounting for the effect of
temperature on inoculum availability. Visual observations of conidial desiccation
indicate that further research is needed on the effects of temperature on inoculum
viability and infection potential. These results offer an explanation of why epidemics in
hop yards slow during July and August when temperatures routinely exceed 30ºC for
more than 6h continuously (118).
64
Conclusion
This research was intended to increase understanding of sporulation and
dissemination of Podosphaera macularis, hop powdery mildew, by developing new
methods for detecting and quantifying P. macularis in the field, and determining the
relationship of temperature to sporulation. In order to accomplish these goals, molecular
techniques were developed to detect and quantify DNA from air borne conidia collected
in the field, and disease incidence was recorded by the scouting fields in which air borne
spore samples were being collected. The effect of temperature on sporulation of P.
macularis was examined using controlled environments and novel methods for
assessment.
The intertranscribed spacer (ITS) region of ribosomal DNA was an adequate
target for detection and quantification of P. macularis DNA in a laboratory setting. It
was possible to detect 1000 spores in ten extractions 100% of the time, and 100 spores in
ten extractions 60% of the time. However, no relationship was found between the
number of conidia detected and disease incidence found in the field. This may be due to
inefficiencies of extraction or DNA quality. The limited heterogeneity of this region
among species within Podosphaera contributes to the fact that this region is not adequate
for detection and quantification of P. macularis DNA collected in a field environment.
These results imply that the ITS region is not suitable for the detection and quantification
and another region should be examined.
Temperature had a significant impact on sporulation and may thus have important
implications for inoculum availability in the field. Exposure to constant low and high
temperatures decreases sporulation, which indicates that inoculum may not always be
65
available once the epidemic has started. Sporulation is also decreased during brief
exposures to temperatures above 30°C. These data indicate that inoculum availability is
reduced when temperature exceed 30ºC in the field. Accounting for the inoculum
reduction could further enhance the utility of an infection risk forecaster. Possible
modifications of the Hop Powdery Mildew Infection Risk Index (HOPS) (70) model
would be the inclusion of an algorithm that indicates a reduced potential for infection for
at least 12 h after temperatures were greater than 30°C, and the reduced potential for
infection for 1-2 days after temperatures are greater than 35°C.
66
Appendix
67
Appendix A: Podosphaera macularis ITS Region Consensus Sequence and Primer Target Locations
68
Appendix B: Alignment of ITS sequence of Podosphaera macularis and Podosphaera clandestina
69
70
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