Abstract
Plant biotrophic oomycetes cause significant production problems and economic losses in modern agriculture and are controlled by fungicide applications and resistance breeding. However, high genetic variability and fast adaptation of the pathogens counteract these measures. As a consequence of the “arms race,” new pathogen phenotypes recurrently occur and may rapidly dominate the population when selected through the pressure of control measures. Intensive monitoring with fast and reliable identification of virulence phenotypes is essential to avoid epidemics and the economic consequences in agriculture. For some of the most important downy mildews and white blister rusts, bioassay-based differentiation has been established to classify infectivity of field isolates or cultivated strains on hosts of defined resistance. However, the testing is laborious, time-consuming, logistically demanding, and prone to impreciseness. Alternatively, host independent classification could overcome these problems and enable fast assessment of the infection risk when monitoring the local pathogen population. The prerequisite would be the identification of pathogen characters correlating with the infection behavior. This review examines the current situation of bioassay-based pathotyping in six of the most important biotrophic oomycetes (Plasmopara viticola, Plasmopara halstedii, Pseudoperonospora cubensis, Peronospora tabacina, Bremia lactucae, and Albugo candida) and gives an overview on attempts and progress to identify genetic markers of the pathogens that correlate with their infection behavior.
I. General aspects
A. Oomycetes, fungus-like organisms of the kingdom Straminipila
The evolutionary peculiarities of oomycetes (Oomycota; also called egg-fungi or pseudofungi) among filamentous organisms have been widely reviewed over the past two decades (e.g. Alexopoulos et al., Citation1996; Dick, Citation2001, Göker et al., Citation2007; Voglmayr, Citation2008; Thines, Citation2013). Hence, their phylogenetic distinctiveness from Mycobionta and relatedness to autotroph Heterokontophyta such as brown algae will not be repeated here. Most likely originating from basal algal parasitic groups in the marine habitat (Beakes et al., Citation2012), various lineages have adapted to freshwater (water molds; Saprolegniales, Rhipidiales, Peronosporales p.p.), and terrestrial habitats (Verrucalvaceae, Albuginales, Peronosporales p.p.) (Thines, Citation2014). Parasitism on angiosperms has evolved independently in at least four lineages, Verrucalvaceae (Saprolegniales), Albuginaceae (Albuginales), and Pythiaceae and Peronosporaceae (Peronosporales). As a consequence of co-evolution with specific hosts, the strategies of infesting plants are different between pathogenic taxa in terms of host development, infection site, penetration mode, mycelium formation, and propagation (for a review see Fawke et al., Citation2015).
The primary infection is often from soilborne inoculum and usually affects roots (e.g. Verrucalvaceae, Pythium and some Phytophthora species), whereas others attack above ground parts such as leaves, flowers or fruits (e.g. downy mildews, Phytophthora p.p., and white blister rusts). Infection can start from sexually formed diploid oospores or frequently from asexual diploid sporangia (or conidia), which are produced for mass propagation and usually distributed by wind. As reminiscence of their heterokontic origin, flagellate zoospores are still formed in several oomycete genera (e.g. Albugo, Pythium, Phytophthora, Plasmopara p.p.; ) despite parasitizing terrestrial hosts. This requires at least temporarily a humid environment as provided in rhizosphere soil or by rain and dew that keeps aerial plant parts sufficiently wet for several hours to accomplish encystement and penetration of the host. Direct germination of sporangia (then often called conidia) has evolved independently in several genera (e.g. Peronospora, Hyaloperonospora, Vientotia; ), rendering them less dependent on water. A facultative switch between these two modes triggered by temperature has been reported from Phytophthora (Judelson and Blanco, Citation2005). A similar report for Bremia lactucae on lettuce, where light and temperature effects were suggested as determinants between direct or indirect germination (Milbrath, Citation1923), remained unique, and yet unconfirmed.
Table 1. Germination mode and trophic type of plant pathogenic oomycetes.
As diverse as the sporangium behavior is the mode of penetration. While root parasitic oomycetes usually form appressoria to invade the inner tissues by directly penetrating rhizodermal cells or squeeze between the middle lamella of cells (e.g. Pythium, Aphanomyces, etc.), other species attack leaves either in a similar way (e.g. Peronospora, Bremia) or use stomata as the plants’ natural “entry ports” for this purpose. This can vary between species of the same genus (e.g. Plasmopara halstedii penetrates through cell walls and P. viticola through stomata).
For further development, plant attacking oomycetes have evolved three different strategies. Necrotrophs, such as Pythium species, kill host cells before ingesting the essential nutrients. Phylogenetically more derived taxa (Peronosporaceae, Albuginales) evolved haustoria as a specialized cellular structure that penetrates the host cell wall but does not disrupt the plasmalemma. In this way, affected plant cells stay alive and their metabolism continuously supports the pathogen. This type of interaction is typical for biotrophs belonging to downy mildews and white rusts. Intermediate to the mentioned trophic types are the so-called hemibiotrophs (e.g. Phytophthora, Aphanomyces, etc.) where the originally mutual coexistence ends in advanced stages of infestation and necrotrophy is induced. Necrotrophs and hemibiotrophs can usually be cultivated on artificial media based on energy-rich carbohydrates and trace elements, whereas this is not possible with biotrophic oomycetes, so far. The inability of biotrophic oomycetes to synthesize sterols adds to the lifetime dependency on living plant cells (Marshall et al., Citation2001; Madoui et al., Citation2009). The formation of long-lasting oospores terminates biotrophic growth and allows the pathogens to bridge the period between two growing seasons of their hosts.
In contrast to necrotrophs and hemibiotrophs, which are often able to infest a broad spectrum of taxonomically distant plants, biotrophic oomycetes usually have a very narrow host spectrum in the genus or even species rank, with only few exceptions (Choi et al., Citation2006, Citation2009; Runge and Thines, Citation2012). This is based on the co-evolution of highly specific interaction mechanisms (e.g. virulence/avirulence genes), which makes their discovery case-specific and laborious. The host restriction of biotrophs has early been recognized by taxonomists and used as an important feature for the species concept (Gäumann, Citation1923).
B. Economic relevance of plant pathogenic oomycetes
Although biotrophs generally do not kill their host plants, thus appearing less harmful, their economic impact in agriculture can be devastating. Large-scale infections in unprotected crops have caused nearly total losses by downy mildews in vineyards (Madden et al., Citation2000), sunflower fields (Novotelnova, Citation1966), cucumber production (Lebeda and Schwinn, Citation1994), and lettuce farming (Subbarao et al., Citation2017).
Hence, it is not surprising that among the top 10 of most intensively studied oomycetes, Kamoun et al. (Citation2015) recently listed three biotrophs with Hyaloperonospora arabidopsidis ranking second, Plasmopara viticola sixth, and Albugo candida on tenth. However, the number of scientific publications on a pathogen does not necessarily reflect its agronomic and economic relevance. So, the intensive investigation of H. arabidopsidis, the first biotrophic oomycete with a completely sequenced genome (Baxter et al., Citation2010), is not due to the extent of damage on Brassicaceae crop plants, but to its role as a model organism with specific host preference for Arabidopsis thaliana (Schlaich and Slusarenko, Citation2008). Considering the potential economic loss based on world-wide cultivated area and crop yield, P. viticola, the downy mildew of grapevine, clearly ranks first, followed by Pseudoperonospora cubensis on cucumbers, squash, and melons as well as P. halstedii on sunflower (). However, in tropical and subtropical regions of Asia and Africa, graminaceous downy mildews such as Sclerospora graminicola or Peronosclerospora sorghi play the prominent role (Thakur et al., Citation2004; Sharma et al. Citation2010; Rashid et al., Citation2013). Including the cost for chemical control measures would change the ranking again, as in sunflower there is usually no chemical treatment except for seed coating, whereas in lettuce, cucumber, and grapevine, regular spraying is almost obligatory.
Table 2. Important biotrophic oomycete pathogens and economic relevance of their hosts based on cultivated area and yield in 2017 (according to FAO database, 2018).
Chemical pathogen control in downy mildews and white rusts affords oomycete-specific active compounds, taking into account the metabolic and developmental differences to eumycotic fungi and the closer physiological relationship to plants (e.g. cellulose in cell walls). In particular, phenylamides, dithiocarbamates, and strobilurines were proved to be very effective against oomycetes. However, regular treatment has frequently resulted in the fast development of fungicide resistance. Gisi and Cohen (Citation1996), when reviewing the increase in phenylamide resistance in Phytophthora infestans populations and other agronomical important Peronosporales, reported that only 2 years after the introduction, the first resistant strains of P. cubensis were detected in cucumber fields in Israel, shortly followed by Plasmopara viticola on grapes in France, B. lactucae on lettuce in England, and Peronospora tabacina in the US (Bruck et al., Citation1982; for a review, see Hollomon, Citation2015). Perhaps oxathiapiproline, the first member of a recently introduced new class of isoxazoline fungicides will lend a more durable protection against oomycetes. The target of this type of compound is the oxysterol-binding protein, an obviously very essential peptide for the sterol deficient biotrophic oomycetes (Pasteris et al., Citation2016). However, assessments on Phytophthora capsici for resistance against oxathiapiprolin showed that fungicide adaptation is possible as well (Miao et al., Citation2016).
This enforces the demand for other protective measures that could help to minimize yield loss. Hence, much effort has been put in resistance breeding in all economically important pathosystems (for details see the following chapters). This environment-friendly approach is a long-term strategy and it has always been very time-consuming until effects could be seen in the field. This accounts particularly for perennial crops such as grapevine or hop where plantations are set up to last for many years. Traditional approaches, such as searching for resistance in wild relatives of a crop, generating F1 populations, selecting resistant phenotypes and backcrossing them several times to maintain the original crop characteristics in almost completely homozygous recombinant inbred lines were successful to reduce downy mildew infections in some crops (e.g. grapevine cultivars Regent, Solaris, or Burner), but it takes many years or even decades until such plants are regularly planted in the field. More recent attempts to use linkage mapping or genome-wide association mapping may strongly reduce the costs and time necessary to generate resistant cultivars. Nevertheless, the protection will only last, until more aggressive and virulent genotypes emerge, either by unintended positive selection from the pathogen population or by newly evolving genotypes with higher virulence.
Compared with the enormous financial efforts made in developing suitable plant protection measures—be it in terms of chemical control, plant breeding, or agro-technology—relative less investment has been made to improve the knowledge about the organisms this warfare is directed against. This explains, why until recently, some downy mildews and white rusts pathogenic to crops erroneously were regarded as being widely distributed in related wild plants, thus forming an uncontrollable refugium for the initiation of epidemics in cultivated plants. Contrary, more detailed studies revealed that, for example, the pathogen on basil is not identical with Peronospora lamii on sage, but represents an independent and highly host-specific species now called P. belbahrii (Thines et al., Citation2009a), which has only recently been introduced to Europe from Africa. Similarly, it was not before 2012 that the sunflower white rust Pustula helianthicola (Rost and Thines, Citation2012) was recognized as being distinctive from its congener species P. obtusata (formerly P. tragopogonis) on goats beard and that the two species are unable to share the same host. These examples may illustrate that improvement of the current state of taxonomy as well as knowledge of peculiarities in the biology and infection strategy of a pathogen, particularly in biotrophs, is the basis to avoid infection and to develop successful counterstrategies. This requires intensive disease monitoring and population studies in order to unravel new species, the virulence spectrum of pathogens, and the fungicide resistance potential in the gene pool of pathogens.
C. Challenges for population studies with biotrophic oomycetes
Population studies in oomycetes pathogens of crop plants are more difficult to conduct as it may appear at first glance. Unlike in wild plants, crops are on private property and permission is required to get access to infected material. Information systems as provided by agronomic cooperations or governmental services may help to overcome this problem. However, concerned farmers do not always recognize the disease fast enough for securing scientifically useful material before intensified fungicide application or phytosanitary measures (e.g. plant elimination in greenhouse cultures) are deployed. Pathogen monitoring is a logistic challenge in terms of the distances between the surveyed cultures as well as the continuity over several growing seasons.
The design of population studies highly depends on the pursued scientific aim. Taxonomic studies may need only minute pieces of sporulating samples for phenotypic or genetic comparison and the material for such analyses must not necessarily be in a vital stage. Recent examples such as for potato late blight, P. infestans, have shown that even with herbarized historic specimens from the 19th-century epidemics in Europe could be ascribed to a single introduction of a genetically distinctive strain (HERB-1) from North America (Yoshida et al., Citation2014). In another case, molecular and chemical analyses of the fatty acids of Pustula helianthicola sporangia taken from desiccated specimens showed near identity between samples from sunflower of Australia, South Africa and Germany (Thines et al., Citation2005) indicating that the occurrence in Germany does not stem from white rusts on local Asteracean wild plants, but most likely from an unintended introduction with seeds from the southern hemisphere in which the pathogen is able to survive (Lava et al., Citation2013). However, studies based on specimens, especially historic ones, are prone to contamination with spores from other pathogens that are probably more readily amplifiable with a given primer set. With increasing age of the samples, even minute amounts of contamination will be amplified instead of the target pathogen because of increasing degradation of the DNA in the specimens. Thus, studies reporting unusual hosts from specimens older than approximately 10 years for otherwise host-specific oomycetes need to be treated with caution (e.g. Salazar et al. Citation2018, unpublished but released GenBank accession series DQ500139-44).
In contrast, biological studies, as for instance the search for mating types in a pathogen population depend on access to living material. This is also the case with some fungicide resistance screenings or the search for virulence phenotypes present in the population. In all three cases, the pathogen must not only be vital for the experiments but also needs to be cultivable for inoculum propagation and experimental replications. This is the major obstacle for population studies on biotrophic oomycetes designed for pathotyping or race classification as it requires establishing and maintaining a host-depending cultivation system. In contrast to standardized in vitro cultures of hemibiotrophs on artificial media, in vivo cultivation techniques for downy mildews and white rusts are species-specific and very sensitive to sporangium quality, inoculation conditions, and the type and age of host tissue. The simultaneous propagation of multiple isolates for a screening study requires safety measures to prevent cross-contamination and needs continuous supply with susceptible host material. Pathogen cultivation on detached leaves in petri dishes, as applied in some of the cases described in the up-coming chapters, can be helpful in saving space for pathogen propagation and infrastructure for host cultivation. The latter is a major obstacle for the work with perennial crops like grapevine or hop due to their resting period, whereas the annual herbaceous crop plants can be raised from seeds year around.
D. Pathotyping versus direct classification of physiological races
Individuals in populations of a taxon, unless recently derived through cloning process from a single genetic source, display a natural diversity which—at a certain degree of taxonomic significance or practical relevance—makes classification of subgroups eligible. In taxonomic systems, the species forms the most fundamental group in the hierarchy of principal ranks (article 3 of the International Code of Nomenclature for Algae, Fungi, and Plants, 2012). To allow subdivision below this level, secondary ranks have been created in the following descending sequence: subspecies, variety, subvariety, form, and subform (article 4). Outside systematics, other categories for circumscription of certain entities have been created. Among those, the terms strain (for microbial organisms) and race (mostly used for domesticated animals, cultivated plants or in socio-political contexts) are very common to characterize individuals either sharing a common ancestry (and genetic background) or common features, respectively. For races, these traits could be phenotypic (including morphological, cytological, developmental, chemical, or physiological) or genotypic. However, sometimes additional categories are in use such as “geographic race” (for populations inhabiting a distinctive area), “ecological race” (preferring specific growth conditions), or “virulence race” (showing different pathogenicity) although they could be seen as part of the physiological race complex.
Exploring the genetic diversity of pathogenic oomycete populations by means of current molecular techniques is relatively easy to achieve, provided the sample material is suitable. However, with regard to agro-economic aspects, genetic diversity is only of interest if it correlates with traits indicating virulence toward the host plant or the tolerance to fungicides. Such differentiation of infectivity of biotrophic oomycetes was carried-out in bioassays with so-called host differentials of defined resistance long before molecular techniques provided tools for the identification of differentiating traits on sporangia or hyphae of the pathogen itself. Thus, the first experimental evidence for the existence of different virulence phenotypes is known from the 1920s for B. lactucae in the US. (Jagger, Citation1926), from the 1940s for P. cubensis in Japan (Iwata, Citation1941), or the 1970s for P. halstedii (Zimmer, Citation1974) and the different entities were called “physiological races,” or indifferently abbreviated just “races.” As it is uncommon in systematics to classify organisms indirectly by defining their characteristics in dependence of either the susceptibility or resistance of another species (e.g. host), the term “pathotype” was introduced to classify “a variety of an organism, especially a microorganism, which causes disease in a particular host or range of hosts” (definition of pathotype in English by Oxford Dictionaries; https://en.oxforddictionaries.com/definition/pathotype, d.o.i. 06.2018). In P. halstedii, for example, the term pathotype replaced the old race nomination in the 1990s when a new and uniform system for testing the virulence phenotype on sunflower differentials was proposed (Gulya et al., Citation1991). Unfortunately, this has not been adopted consequently and in other pathosystems. Therefore, the definition of race/pathotype and the application in the literature is not standard and rather confusing. Sometimes the terms are used synonymously but in other cases with a significantly different meaning. So, in P. cubensis, a pathogen with a previously assumed broad host spectrum, pathotypes are defined by infection bioassays on differentials from different host species (or genera; e.g. Cucumis, Cucurbita, etc.), whereas races are classified on their infectivity to differently resistant genotypes of a single host species (e.g. Cucumis genotypes).
To avoid confusion in the nomination of virulence phenotypes in this review, we will use the term pathotype if classification was based on infection bioassays with host plants of different resistance. In contrast, the term “race” will be reserved for varieties of an organism that can be classified by characters (no matter if molecular, morphological, cytological, physiological) traceable on the pathogen alone (without any host).
The correct identification of virulence phenotypes with infection bioassays is extremely important for agriculture and plant breeding and therefore much more developed than race classification in pathosystems of economically relevant biotrophic oomycetes. However, pathotyping is cumbersome and prone to errors. First, it requires permanent access to living material (seeds or leaves) of the differentials and control for genetic identity if it has to be propagated. Second, the infection results, which are usually evaluated comparing the speed and intensity of symptoms (e.g. sporulation or necrosis), are affected by the experimental conditions, by the fitness of the two partners, and by subjective criteria of the operator in rating the symptoms. Third, field isolates of biotrophic oomycetes may consist of a mixture of different pathotypes (for examples see Gulya et al., Citation1991; Gobbin et al., Citation2003; Zipper et al., Citation2009). This impedes correct interpretation of a bioassay until a genetically homogenous strain of the pathogen has been developed and propagated from a single spore or sporangium.
Therefore, a prominent role of population studies in plant pathogenic oomycetes should be to combine the results from experimental pathotyping with traits (mostly molecular characteristics) used in race classification or phylogenetic genotyping. The data base for molecular comparison has rapidly increased within recent years. Since the publication of the first genome of an obligate biotrophic oomycete, Hyaloperonospora parasitica (Baxter et al., Citation2010), genomes of additional white rusts, and downy mildews have been released (). However, despite the wealth of genomic, transcriptomic or secretomic data, which are intensively used to screen for genes potentially involved in pathogenicity, there is still a big gap between the bioinformatics information and the application for direct race classification in field populations. To bridge this gap first requires the identification of the pathotypes present in the population before the search for genetic markers correlating with specific pathogenicity traits which follows. The discovery of markers for race classification would then allow fast and bioassay independent identification of the prevalent virulence potential in the pathogen population and thus enabling better risk assessment in plant cultivation and the implementation of disease-preventing measures.
Table 3. Genome sequence resources of biotrophic oomycetes.
It is the aim of this review to summarize the current status of population studies and infection phenotyping in some of the economically most important biotrophic oomycete pathogens. The selected examples will show the individuality of the different host-pathogen systems that involve annual and perennial plants, direct and indirect germinating pathogens, genetically diversity and relatively uniform fungal taxa. This survey will help to enforce the identification of infection-relevant molecular markers and help to speed up their introduction as tools for early and easier recognizing plant pathogenic risks.
II. Molecular tools and suitable genomic regions for race population studies
Some of the issues with the co-cultivation of biotrophic pathogens could possibly overcome if the virulence and resistance determinants of hosts and pathogens were known. In this case, knowledge on alleles with a certain virulence or avirulence effects could be detected by means of genome sequencing or enrichment sequencing. As progress with the identification and confirmation of such loci are currently slow, only few important determinants have been screened so far or will be become available in the near future. While studies with a low resolution, i.e. studies that are only able to identify divergent genotypes, e.g. by PCR fingerprinting such as randomly amplified polymorphic DNA (RAPD) in P. halstedii (Roeckel-Drevet et al., Citation2003), amplified fragment-length polymorphism (AFLP) in P. cubensis (Sarris et al., Citation2009), inter-simple sequence repeats (ISSR) in S. graminicola (Jogaiah et al., Citation2009), or the sequencing of highly variable gene parts such as the internal transcribed spacer (ITS) regions of nuclear ribosomal DNA (Spring et al., Citation2006a) have generally shown less or only moderate association between genotype and virulence phenotype, high resolution populations genetics studies using microsatellites, genotyping by sequencing, or genome skimming might be available in the foreseeable future, and reveal quantitative trait loci (QTL) that are associated with certain virulence and resistance phenotypes. However, it should be the ultimate aim to relate virulence and avirulence directly to the genes responsible for these traits, i.e. effector and resistance genes.
In order to be effective, plant pathogens need to suppress the first layer of defense that is incited by elicitors (molecules that trigger resistance reactions; deriving from pathogen or from host). Fawke et al. (Citation2015) listed six different types of such elicitors (often also termed microbe/pathogen-associated molecular patterns; MAMPs/PAMPs) so far identified from oomycetes. Among them are cleaved peptides from surface located proteins (e.g. from a glycoprotein of Phytophthora (Nennstiel et al. Citation1998), or secreted peptides (e.g. the adhesive protein from zoospores of Phytophthora cinnamomi (Robold and Hardham, Citation2005; Hardham, Citation2007), carbohydrates (e.g. ß-1,3-1,6-glucanes from Phytophthora sojae (Klarzynski et al., Citation2000), or characteristic fatty acids (e.g. arachidonic acid as elicitor in potato; Bostock et al., Citation1982).
Elicitors can be host-derived molecules resulting from degradation processes in the course of penetration where enzymes dissolve cuticle, cell wall or membrane structures and act as DAMPs (danger associated molecular patterns) (Tang et al., Citation2012). As most of these elicitors are derived from rather conserved pathways or proteins, their presence could be assessed from genomic data. However, it is to be expected that variation in these characters would be rather low because their role in the physiological process of infection is more general and not likely to vary with a pathosystem.
Effectors, which are aimed at manipulating plant defense to overcome PAMP-triggered immunity, make plants susceptible to the invading pathogen, and can act as secondary elicitors of defense reactions if they are recognized by R-genes or lead to the production of DAMPs. Intracellular effectors have diverse roles in manipulating signal cascades and metabolic pathways and may interfere with signaling pathways or defense proteins in various ways (for review see Selin et al., Citation2016; Sharpee and Dean, Citation2016).
Within the last decade, hundreds of putative effector molecules have been identified by means of motive search (e.g. the RxLR motif in the N-terminal sequence of oomycete effectors, conserved FLAK motif in crinklers, or Cystatin-like domains in protease inhibitors) in genome studies of oomycetes (e.g. Haas et al., Citation2009; Baxter et al., Citation2010; Sharma et al., Citation2015; Derevnina et al., Citation2015). However, screening for avr-causing effectors and their R-gene counterparts has mostly been restricted to model systems, such as the interaction of Arabidopsis thaliana with Hyaloperonospora arabidopsidis (Parker et al., Citation1997; McDowell et al., Citation1998, Citation2005; Bittner-Eddy et al., Citation2000; Van der Biezen et al., Citation2002; Rehmany et al., Citation2005; Allen et al., Citation2008; Nemri et al., Citation2010; Bailey et al., Citation2011). But even in this model system, only a fraction of the virulence/avirulence determinants is known. This highlights that a monumental effort will be necessary before plant-pathogen interactions will be fully understood with respect to avirulence-causing effectors. However, only a fraction of the effectors will have avirulence activity, as the evolutionary significance of effectors is to promote virulence and to enable host colonization (Kamoun, Citation2007; Thines and Kamoun, Citation2010). Currently, the knowledge regarding the significance of certain effectors for the virulence of pathogens is fragmentary, at best. There are only few core effectors well-characterized in this respect in smut fungi (e.g. Hemetsberger et al., Citation2015), any for oomycetes, reports are mostly at the observational level, without deeper knowledge regarding the exact mechanisms leading to a disease-promoting phenotype (Sohn et al., Citation2007; Fabro et al., Citation2011; Caillaud et al., Citation2012; Boevink et al., Citation2016).
Thus, it will likely take decades until the function of the hundreds of putative effectors are understood in a way that they can be used for directly relating their presence and allelic variation to a virulence phenotype, and so far, no specific effector gene has successfully been used as a molecular marker to classify an isolate into a specific physiological race of a pathogen species.
III. Plasmopara viticola
A. Biological features
Plasmopara viticola (Berk. and Curt.) Berl. and de Toni is the causal agent of downy mildew disease on grapevine and a member of the Peronosporaceae (Order Peronosporales) together with other important obligate biotrophs. The pathogen, originating from North America, has a narrow host range restricted to few species of the Vitaceae. Although it has been proposed that P. viticola includes several cryptic species specialized to different Vitis hosts (Schröder et al., Citation2011; Rouxel et al., Citation2013), evidence has shown that European strains are able not only to infect and sporulate on V. vinifera cultivars but also on less related North American and Asiatic Vitis spp. (Gómez-Zeledón et al., Citation2017), prompting new questions on the species concept. In Europe, the pathogen began spreading after plants imported from North America were used to repopulate French vineyards affected by Phylloxera in the 1870s (Gessler et al., Citation2011).
Asexual reproduction via wind- and rain-dispersed sporangia is the main source of propagation and occurs during the vegetation period where it causes local infections on leaves and fruits within less than a week. Overwintering is assured through sexually produced thick-walled oospores, which are produced when the two mating types are present in the same leaf, thus underlining the heterothallic nature of the pathogen (Wong et al., Citation2001; Scherer and Gisi, Citation2006). Infection begins when zoospores released from sporangia penetrate the plant through stomata (Kiefer et al., Citation2002). The high level of water dependence of the pathogen is supported by the fact that zoospore-release does not occur during dry conditions. Its growth on a perennial host characterizes the pathogen’s reproductive strategy and significantly impacts research efforts. Availability of leaf material during a short period of the year constrains the time window for infection studies. For an exhaustive review on the biology of the pathogen refer to Gessler et al. (Citation2011).
B. Economic relevance and control mechanisms
Considering high damage levels of up to 75% of yield loss (Madden et al., Citation2000), P. viticola has been considered one of the biggest threats to viticulture. Because of the large amount of chemicals used every year to control the pathogen, it has been considered one of the most economically important oomycetes (Kamoun et al., Citation2015). For over a century, pesticides have been enabling wine production in Europe. The occurrence of chemical tolerant isolates in the field has led to an increase on the amount of fungicides and the frequency of application. In a very short time, strains of the pathogen have become resistant to the most common groups of fungicides currently applied (Gisi et al., Citation2007; Corio-Costet et al., Citation2011; Genet and Jaworska, Citation2013), especially in regions where high pesticide amounts have recurrently been used (Gómez-Zeledón et al., Citation2013).
Because of the high cost and the potential health risk behind the growing fungicide application, measures have been taken in Europe (directive 2009/128/EC) to reduce the amount of chemicals and improve alternative control strategies. The current situation on pesticide application on grapevine has been reviewed by Gessler et al. (Citation2011), and new control strategies have been developing (Dagostin et al., Citation2011; Leroy et al., Citation2013). Climate-based forecasting systems are important supplementing measures to reduce intensive fungicide usage in the vineyard. PLASMO, a program based on agro meteorological parameters in Italy, simulates the life cycle of the oomycete as influence by specific weather conditions (Rosa et al., Citation1993). Decisions on fungicide application are then based on the prediction of the program for infection outbreak. The warning system VITIMETEO used in Germany, Switzerland, Austria, and north of Italy has enabled the reduction of the number of fungicide applications during the season (Dubuis et al., Citation2012).
Alternative products are already available for organic viticulture, but due to their lower efficacy, a complete copper replacement is not yet possible (Dagostin et al., Citation2011). Resistance inducers have shown a positive but local effect on the response of the plant after downy mildew infection by disease defense priming. The application of the antagonistic fungi, Trichoderma harzianum, positively stimulated the expression of disease response genes in V. vinifera plants (Perazzolli et al., Citation2011). Sulfated laminarin (PS3), an algal polysaccharide known for triggering stress responses in plants was successfully used to induce resistance in grapevine against P. viticola (Trouvelot et al., Citation2008). Thiamine (vitamin B1) has been reported to induce resistance in treated susceptible grapevine cultivars by increasing the levels of H2O2 (Boubakri et al., Citation2012). The defense response of grapevine cultivars has been increased as well following the establishment of arbuscular mycorrhizal symbiosis (Bruisson et al., Citation2016).
The development of new breeding lines resistant to the pathogen is a promising alternative but is difficult to implement in regions where traditional grapevine cultivars are grown. Furthermore, breakdown of resistance has already been reported for tolerant cultivars (Peressotti et al., Citation2010; Delmotte et al., Citation2014) making imperative the incorporation of several resistance loci with different mechanisms in the new breeding lines to achieve a durable resistance (Eibach et al., Citation2007; Schwander et al., Citation2012). A combination of warning systems, chemical and biological treatment, and resistant varieties are on the core of an integrated pest management in viticulture (Pertot et al., Citation2017).
C. Monitoring population diversity
Several studies have shown that populations of P. viticola possess a high genetic diversity (Stark-Urnau et al., Citation2000; Peressotti et al., Citation2010; Gómez-Zeledón et al., Citation2013; Zhang et al., Citation2017) and even on a single leaf, different genotypes might be present (Stark-Urnau et al., Citation2000; Gobbin et al., Citation2003), and this is a requisite to heterothallic sexual reproduction. The ability of the pathogen of recombining every year when forming the oospores increases its genetic diversity and allows rapid adaptation to new conditions in the agroecosystem imposed by fungicide treatments or grapevine cultivars used (Wong et al., Citation2001). Because of this high genetic diversity in P. viticola populations, working with genetically homogeneous material should be a priority and a standard procedure. This can be achieved by single sporing as in most fungal pathogens (Spring et al., Citation1998; Choi et al., Citation1999). Nevertheless, this important issue has been underestimated in many previous studies. Working with heterogeneous samples collected yearly from the field has been the rule instead. This gives rise to concerns about the comparability of the results. Isolates from different regions might differ in pathogenicity and should be studied independently (Gómez-Zeledón et al., Citation2013). It is, therefore, strictly recommended to begin a study by establishing and maintaining single sporangium strains in the laboratory in order to obtain homogeneous and comparable results.
The search for phenotypic traits to monitor population diversity in P. viticola is difficult. Sporangia production size are very plastic in oomycetes and in biotrophs can vary depending on the host plant (Runge et al., Citation2012). Environmental conditions, like temperature and humidity, affect as well physiological characteristics of the pathogen (Denzer et al., Citation1995a; Williams et al., Citation2007; Gessler et al., Citation2011). Most of the efforts to characterize and classify the interaction in the pathosystem P. viticola–V. vinifera/focused on the host. The first efforts to evaluate resistance to downy mildew were based on a visual scale (OIV-452) and considered the whole plant (IPGRI, UPOV, OIV, Citation1997). Further studies have adapted the system to evaluate the resistance of the host using detached leaves or leaf discs (Staudt and Kassemeyer, Citation1995; Kortekamp and Zyprian, Citation2003; Bellin et al., Citation2009; Deglène-Benbrahim et al., Citation2010). Fewer studies have focused on the characterization of P. viticola virulence phenotypes and the first report evaluated the ability of the oomycete to infect different grapevine cultivars (Denzer et al., Citation1995b). More recently, an attempt was made to establish a first classification system for virulence phenotypes (pathotypes) of P. viticola using leaf disk bioassays on specific host genotypes of grapevine cultivars as well as wild Vitis species (Gómez-Zeledón et al., Citation2013). To achieve a better characterization, a set of hosts from different regions (North America, Asia, and Europe) was later proposed to evaluate strain behavior (Gómez-Zeledón et al., Citation2017). In these infection assays, not only just sporulation intensity on the host was evaluated but also the elicitation of necrotic reaction on the host.
The establishment of a defined set of plants with different resistance levels to test the behavior of the pathogen has proven to be effective for pathotype characterization in the closely related oomycete P. halstedii (Gulya et al., Citation1991). In the case of grapevine, a standardized system of hosts is more difficult to establish compared to sunflower, due to the perennial nature of Vitis. To maintain such a set of plants for pathotype characterization is laborious and expensive and cannot be conducted all year around like in the case of annuals. This has limited the development of an international system for P. viticola pathotyping and hinders the comparison of results obtained in different parts of the world. It would be necessary to standardize the host genotypes to achieve a global characterization system which may include cultivars and wild species from different grapevine growing regions worldwide. To fulfill this, genetically uniform plant material should be made available for those interested in P. viticola pathotyping in different countries.
The capacity of a strain to infect a specific host is related to its ability to overcome a certain kind of resistance imposed by the plant. Using a set of hosts with different resistance mechanisms will help to understand how certain pathotypes are able to successfully infect tolerant hosts. The capacity to select and maintain such pathotypes would be important for the breeders as well, which could test their new breeding lines against characterized homogeneous strains. Based on their ability to infect tolerant hosts, strains have been already selected and studied (Peressotti et al., Citation2010; Li et al., Citation2015; Gómez-Zeledón et al., Citation2017). The comparison of such strains with those not able to infect a specific host will result in the discovery of genes responsible for the breakdown of a specific resistance or for higher virulence.
D. Infection/resistance mechanisms
To establish hyphae in the intercellular space of the plant, P. viticola, similar to other obligate biotrophic oomycetes, has developed refined strategies (Fawke et al., Citation2015). The pathogen is able to form haustoria and feed on the parenchymatic cells without killing its host. Detection by means of the plant can hardly be avoided as plants are able to detect a wide range of pathogenic molecules (PAMPs), which activate their defense response (Zipfel, Citation2008). Nevertheless, P. viticola has a wide arsenal of molecules for disabling plant recognition and achieving successful infection (Toruño et al., Citation2016). This arsenal includes a broad group of apoplastic and cytoplasmic molecules called effectors, which have been extensively investigated by several authors (Morgan and Kamoun, Citation2007; Birch et al., Citation2008; Lo Presti et al., Citation2015).
The resistance mechanisms of the plant have not been completely elucidated. Great efforts have been made to develop genetic maps focused on disease resistance for different grapevine cultivars (Fischer et al., Citation2004; Di Gaspero et al., Citation2007; Welter et al., Citation2007; Schwander et al., Citation2012) and several quantitative trait loci (QTLs), called Rpv (resistance to P. viticola), have been found in different chromosomes (Armijo et al., Citation2016) associated with downy mildew resistance (). The genes behind the resistance have not been characterized and additional efforts are needed in this field. Some of the candidate genes found to be associated with P. viticola resistance encode proteins of the NBS-LRR family (Di Gaspero et al., Citation2012; Schwander et al., Citation2012), known as plant-defense activators. In contrast to Helianthus annuus, no resistance (R) gene has been characterized and verified for V. vinifera against the oomycete. The capacity of identifying, introgressing and pyramiding resistance genes in elite cultivars will play a major role in the development of future resistant grapevine varieties.
Table 4. Resistance related loci relevant for grapevine (Vitis vinifera) breeding (modified from the database VIVC, Citation2018).
Resistant V. vinifera cultivars and wild Vitis species possess anatomical barriers, like specialized stomatal structures (Jürges et al., Citation2009) and high trichome density (Kortekamp and Zyprian, Citation1999), to stop the development of the pathogen. At the molecular level, resistant hosts react in many different ways after infection has started. Localized callose deposition (Kortekamp et al., Citation1997; Gindro et al., Citation2003), volatile organic compounds (Lazazzara et al., Citation2018), accumulation of secondary metabolites (Figueiredo et al., Citation2008; Chang et al., Citation2011), and hypersensitive reaction (HR) (Kortekamp et al., Citation1997; Gindro et al., Citation2003; Casagrande et al., Citation2011) have been reported as important mechanisms to avoid downy mildew infection. Strong expression of defense-related genes has been reported as well from resistant hosts (Polesani et al., Citation2010; Figueiredo et al., Citation2012) early after their contact with the oomycete. For an extensive review on grapevine downy mildew resistance refer to Buonassisi et al. (Citation2017).
E. Pathotyping related to race characterization (molecular characterization)
Several molecular markers have been designed for P. viticola, which were mainly focused on population studies (). The first report of using molecular tools (RAPD) to study the pathogen diversity dates to the year 2000 (Stark-Urnau et al., Citation2000). The study was closely followed by the development of five microsatellites (Simple Sequence Repeats; SSRs) 3 years later, investigating disease dynamics and genetic structure (Gobbin et al., Citation2003). The list of microsatellites was extended when in 2006 seven markers were reported aiming on population genetic analysis (Delmotte et al., Citation2006). The first study applying AFLP on P. viticola combined this technique with SSRs to characterize genotypes and mating types of several European isolates (Scherer and Gisi, Citation2006). In the following year, a study on population dynamics and the development of fungicide resistance reported a set of 17 markers to detect SNPs in the mitochondrial DNA of the pathogen (Chen et al., Citation2007). Using nuclear DNA, eight new SNP markers were developed in 2011 from an expressed sequence tag library (Delmotte et al., Citation2011). Primers for the previously developed microsatellite markers (Gobbin et al., Citation2003) were re-designed and the genetic structure of a P. viticola population was characterized on different grapevine cultivars (Matasci et al., Citation2010). The list of markers was expanded in 2012 with the identification of 31 microsatellite markers for P. viticola, significantly increasing the genotyping capacity for this pathogen (Rouxel et al., Citation2012). The development of molecular markers has been, until now, mainly motivated by the interest to study population genetics and diversity.
Table 5. Molecular markers available for Plasmopara viticola strain characterization.
Although the list of molecular markers designed to study the oomycete is not short, any of those markers, present mainly in non-coding regions of the genome, has been linked to a specific virulence phenotype of the pathogen or a specific pathogenicity gene. In the last years, sequencing efforts have been increased and nowadays three different groups in China (Yin et al., Citation2017), Italy (Brilli et al., Citation2018), and France (Dussert et al., Citation2016) have made available the genome of P. viticola local single sporangium strains. Transcriptome analyses have been performed as well, showing which genes are expressed during the first encounter of the pathogen with the plant. The first transcriptome study focused on germinated spores and published an EST database of this pre-infection stadium (Mestre et al., Citation2012). This represents the first list of putative effector genes for P. viticola, but no further characterization was performed. The effector repertoire of the oomycete was enlarged (51 RxLR) when Yin et al. (Citation2015) characterized the secretome of two Chinese and one Australian isolates. Following transcriptome, comparisons revealed differential gene expression of strains on compatible and incompatible interactions (Li et al., Citation2015).
Comparative studies have been performed as well at the species level. In 2016, the expression of two types of effectors was compared between P. viticola and P. halstedii, two closely related oomycetes (Mestre et al., Citation2016). In this case, 45 RxLR and 60 CRN effectors were reported for P. viticola, and a cDNA database for Plasmopara species was released. The search for genes associated with pathogenicity continued, and the ability of a single RxLR effector (PvRxLR28) to enhance plant susceptibility by repressing host defense-related genes was confirmed (Xiang et al., Citation2016). Effectors, if recognized by the plant, can elicit immune responses acting as avirulent proteins. This was the case for PvRxLR16 that induced cell death in N. benthamiana leaves after been infiltrated with this protein (Xiang et al., Citation2017). A subsequent secretome study, designed for gaining a better insight into the mechanism of the pathogen to infect its host, released 100 RxLR and 90 CRN putative effectors together with many other secreted apoplastic proteins, such as cell wall degrading enzymes (Yin et al., Citation2017). The authors showed that most of the effector genes were significantly up-regulated during infection. A recent report revealed that P. viticola genome contains more effector genes than other biotrophs. Using infected leaves at different time infection points, a list of 57 RxLR, 68 CRN, and 128 YxSLK effectors was released together with other apoplastic effectors (Brilli et al., Citation2018).
Germinated spores are a valuable tool to study the secretome of the obligate biotrophic pathogen (Mestre et al., Citation2012). This kind of study has the advantage of working with a host free system, excluding any host-related effects. A higher expression of RxLR effector genes in germinated spores of a high virulence single sporangium strain compared to a low virulence strain was recently identified (Gómez-Zeledón and Spring, Citation2018). Experiments performed on leaf discs showed a similar gene expression trend and supported the results obtained with germinated spores. A host-related effect was detected as soon as 6 h after inoculation when the gene expression of a strain was compared on hosts with different resistance levels. The possibility that effector expression is regulated depending on the host in which the pathogen is growing deserves further studies. An early recognition of signals from the plant might allow P. viticola to adjust the expression of genes necessary to successfully infect a tolerant host. The identification of highly expressed genes at early time points might be a promising tool to discriminate crucial effectors involved in pathogenesis. The detection of these genes and their expression levels on strains with different virulence pathotype would be a major step forward toward a bioassay-independent, direct virulence characterization.
F. Outlook
Although a huge amount of information has been generated in the last 10 years, still, several points are waiting to be addressed in P. viticola research. There is an urgent need to determine if enough phenotypic characters support the separation of the postulated cryptic species. The lack of a uniform and accepted bioassay to classify virulence phenotypes hinders the comparison of results obtained at different grapevine growing regions worldwide and should be overcome. Achieving consensus on the need to generate homogeneous pathotype strains by single sporing is still in process and programs aiming a consequent monitoring of pathotype diversity are still missing.
Comparative transcriptome analyses and genome sequencing have enormously improved the knowledge on the infection mechanisms of the pathogen. Screening for effector diversity will allow linking the presence or expression of genes with the virulence of a strain. Upcoming studies should filter those genes playing a major role for compatible interactions. The analysis of gene expression patterns at different developmental stages will allow the discrimination of decisive genes. Effectors down-regulating plant resistance genes will be certainly in the center of attention and molecular tools to detecting their presence will be necessary for future race characterization. Elucidation of host resistance genes is another important issue to be addressed on this field. The capacity of host-candidate genes to hinder pathogen growth should be verified. Pathogen-effectors recognition and accurate and timely activation of defense reaction are key factors that need to be considered to be incorporated on breeding programs.
IV. Plasmopara halstedii
A. Biological features
Plasmopara halstedii (Farl.) Berlese et de Toni is a highly host specific downy mildew pathogen of sunflower, H. annuus. Unlike suggested earlier in the literature, the pathogen of sunflower does not affect a broad species range of Asteraceae, and recent phylogenetic studies revised the broad species concept splitting up P. halstedii s.l. into several distinctive taxa with narrow host spectrum (for review see Viranyi and Spring, Citation2011). The origin of the sunflower pathogen is most likely in North America, the center of diversity of its host Helianthus. In the US National Fungus Collection, BPI, specimens of 11 wild species of the genus were recorded to be susceptible to downy mildew though infections in wild populations have rarely been documented. First epidemics in cultivated sunflower in the US were reported in the early 20th century, nearly 50 years before the first records of the pathogen in Europe (for review see Novotelnova, Citation1966).
The morphology of the pathogen as well as the two infection modes, via sexually formed oospores and asexual zoosporangia, have been described by Nishimura (Citation1922) and later on in greater detail by Novotelnova (Citation1966). However, it was not until single zoospore infection on sunflower seedlings was achieved that the homothallic nature of sexual propagation of P. halstedii could be demonstrated (Spring, Citation2000). The role of oospores in the epidemic cycle has long been underestimated because of their cryptic nature and relatively low number compared to the mass production of zoosporangia on leaves. However, oospores are the indispensable key element for overwintering in the soil and for long distance dispersal via seed contamination (Cohen and Sackston, Citation1974; Spring, Citation2001; Spring and Zipper, Citation2000). In particular, uncontrolled exchange of oospore-contaminated seeds can be seen as a major reason for the nearly worldwide distribution of the pathogen since the middle of the 20th century.
B. Control mechanisms
Strict quarantine regulations for seed exchange would be an effective measure to inhibit long distance spreading of P. halstedii, but reliable detection of seed contamination in large batches is almost impossible. The traditional test of germinating seeds and checking the plants after 3-4 weeks for infection symptoms is infeasible nowadays with the current frequency, volume, and speed of international seed exchange. On the other hand, molecular testing, though developed and available (e.g. Roeckel-Drevet et al., Citation1999), suffers from the problem of representative and comprehensive sampling required to identify trace amounts of pathogen contamination in large batches of sunflower seeds. Hence, fungicides are used as seed coating to prevent primary infection. However, the options for oomycete-specific, long-lasting, and systemically acting compounds are very limited. In addition, alike many other oomycetes pathogens, P. halstedii quickly developed tolerant genotypes against most active fungicides such as the phenylamides in France (Albourie et al., Citation1998), Spain (Ruiz et al., Citation2000), and Germany (Spring et al., Citation2006b).
This left resistance breeding as the most effective measure to prevent yield loss in oil sunflower cultivation. The over 50 species in the genus (Schilling, Citation2006; Stebbins et al., Citation2013) and their readiness for interspecific hybridization made the wild relatives of crop sunflower a toolbox for breeders in developing cultivars resistant to various diseases (for rev. see Seiler et al., Citation2017). Resistance traits against downy mildew predominantly derived from wild H. annuus genotypes or from other annuals such as H. praecox and H. argophyllus. Only two traits were from H. tuberosus, a hexaploid perennial. Meanwhile, 22 of so-called Pl resistance genes were identified and successfully integrated in the genome of cultivated sunflower (). However, some of them were quickly overcome by newly evolved or selected pathotypes in the population of P. halstedii. While for a relatively long period the Pl6 gene from a wild H. annuus accession provided good protection for sunflower hybrid lines, the situation changed rapidly, after the first highly virulent pathogenic strains were found in 2009. Only the PlArg gene from H. argophyllus still confers full protection against the ca. 40 pathotypes currently recognized worldwide (Viranyi et al., Citation2015). However, this gene has not yet been widely integrated into commercially offered sunflower lines.
Table 6. Plasmopara halstedii resistance genes in sunflower (including the information of Wieckhorst, Citation2011; Gascuel et al., Citation2015; Viranyi et al., Citation2015; Trojanová et al., Citation2017; Seiler et al., Citation2017).
C. Deficient knowledge on infection/resistance mechanisms
Despite almost 50 years of research in sunflower resistance genes against downy mildew since the discovery of Pl1 (Vranceanu and Stoenescu, Citation1970), the progress in unraveling the function of Pl genes is neglectable. QTL mapping has located the position of 16 of the 22 identified resistance traits on five chromosomes (linkage groups; see ), but gene sequences have so far not been reported for any of them. This is surprising considering that the sunflower genome has meanwhile been fully sequenced (Badouin et al., 2017) and intensive transcriptomic data are available. Expression studies on pathogen-inoculated sunflower are required to unravel resistance mechanism encoded by Pl genes and the investigation of specific compatible and incompatible combinations could help to decipher the gene interaction between both partners. Perhaps a newly established data base on P. halstedii proteomes from early infected sunflower will close this gap when it becomes publicly accessible (see Helia Gene; https://www.heliagene.org/).
More sequence information with respect to pathogenicity is available from P. halstedii. The genome of the sunflower downy mildew pathogen has been sequenced recently and more than 600 putative effector genes were identified (Sharma et al., Citation2015). This means that P. halstedii invests about 4% of its total protein for pathogenicity related peptides. As outlined earlier, effectors are assumed to play a key role in interfering with the resistance reaction of the host plant thus being decisive for the compatibility or incompatibility of interaction. Within the secretome of P. halstedii, the majority of putative effector genes belong to the families of RxLR and CRN candidates, which are assumed to act in the host cell, but are functionally not yet characterized. In addition, Sharma et al. (Citation2015) identified a broad spectrum of proteins with putatively pathogenicity related function. Among them are cutinases, pectin degrading enzymes, and phospholipases that may enable the pathogen to penetrate the host tissue independently from stomata and to establish haustoria in parenchyma cells. Other identified candidates are predestined to interfere with the host’s metabolism (lipases, proteases), physiological activities (cytochrome P450s, ABC transporters), or resistance mechanisms (elicitin-like and necrosis-inducing proteins). It will be an upcoming task to unravel the real function of these genes in different phases of the host-pathogen interaction of sunflower downy mildew and correlate effector profiles with virulence phenotypes.
Even less information than for effectors is available for elicitors, the signaling molecules that trigger the host resistance reaction. This field has chronically been understudied in all plant pathogenic oomycetes since effectors entered the scene. Elicitors can be low (e.g. fatty acids, glucans) or high (e.g. proteins) molecular weight molecules that either derive from the pathogen or from the host itself (e.g. cell wall or membrane fragments after enzymatic penetration) (Fawke et al., Citation2015). From P. halstedii, a single elicitor study has been published by Jung et al. (Citation2010), characterizing a 57 kDa polypeptide that induces ethylene production in sunflower, thus initiating one of the fastest and earliest steps in plant resistance. Comparative studies with defined virulence phenotypes will be necessary to shed more light into the potential role of elicitors for pathogen race classification in sunflower downy mildew.
D. Methods to monitor infection diversity
Differentiation of pathogen populations in sunflower downy mildew started in the 1970s, when resistance, introduced with the Pl1 gene from wild H. annuus into the Romanian breeding line AD66 was overcome by P. halstedii isolates form the Red River Valley in the US (Zimmer, Citation1974), thus separating the “old European race” and prevalent “US race 1” from the higher virulent “Red river race” (US race 2). This system, defining the pathogens according to their compatibility with differently resistant sunflower lines was extended in the US up to “race 11,” and unfortunately in parallel in France, using different host lines and another annotation system (French races A-D). It was not until Gulya (Citation1995) proposed to overcome the incongruent classification systems by a uniform new mode of characterizing isolates by testing their infectivity on a defined set of host genotypes. This suggestion included technical aspects with respect to standardized inoculation, cultivation, and evaluation of the infection bioassay as well as the use of standardized host genotypes (Gulya et al., Citation1991). On the base of homozygous sunflower lines with defined Pl genes, a three digit coding system was established, rating the susceptibility of these differentials in three groups (test set I-III) of three genotypes (A-C) each (). Sporulation on genotype A in each group is rated with the virulence factor 1, B with 2 and C with 4. In this way, a pathotype spectrum between 100 (infective to all genotypes lacking Pl genes) and 777 (infecting all 9 genotypes tested) could be assessed. At the time, this system was introduced, some 10 to 15 pathotypes were classified, but their number increased rapidly and hitherto, a total of over 40 different pathotypes of P. halstedii were recorded world-wide as reviewed by Viranyi et al. (Citation2015). For optimization of the bioassays, some differential lines were replaced over time (Tourvieille de Labrouhe et al., Citation2000), but the general resistance gene patterns and the pathogen numbering remained more or less unaffected. Due to some unequivocal reactions of sunflower genotypes with isolates baring the same pathotype number, the extension of the 3 digit system to a new 5 digit coding was propagated in 2012 (Tourvieille de Labrouhe et al., Citation2012) to improve the resolution of pathotyping. However, this system has so far not been broadly applied outside of France and Czech Republic (Drábková et al., Citation2018), because it makes the testing even more laborious and it is difficult to continuously provide sufficient seeds of all 15 lines required for the infection bioassays. In addition, Trojanová et al. (Citation2017) recently reviewed the technical problems linked to the bioassay-based virulence assessment of P. halstedii isolates. This starts with the isolation, cultivation, and maintenance of the pathogen, continues with the use of potentially heterogenic field isolates instead selecting single spore strains, and ends with employment of suitable inoculation techniques. With respect to the latter, previous studies showed that resistance mechanisms can be tissue-specific acting in the hypocotyl (Radwan et al., Citation2011), so that they may confer resistance in bioassays tested with whole seedling immersion and soil drenching techniques, but would fail in tests made by detached leaf inoculation (Spring et al., Citation1997).
Table 7. Pathotyping (adopted according to Gulya, Citation1995; Tourvieille de Labrouhe et al., Citation2000, Citation2012; Gascuel et al., Citation2015; Trojanová et al., Citation2017).
Despite these problems, several pathotype population studies on sunflower downy mildew were conducted within the past 20 years and delivered valuable information on the virulence diversity of P. halstedii, thus helping farmers and breeders to cope with the pathogen situation in the local area (Delmotte et al., Citation2008 for France; Molinero-Ruiz et al., Citation2002 for Spain; Drábková et al., Citation2018 for Czech Republic; Rozynek and Spring, Citation2000 for Germany). Similar to the national level, on the world-wide scale, a continuous increase in pathotype diversity was registered and particularly so-called “hot” pathotypes infective to sunflower carrying the Pl6 resistance gene are on the rise (Gulya, Citation2007; Viranyi et al., Citation2015). It can be questioned whether this increase is just the result of intensified monitoring, or the consequence of population shifts caused by selection pressure due to improved host resistance (e.g. pathotype 100, the prevalent type up to the 1980ies, has disappeared almost everywhere and pathotype 710 gradually seems to meet the same fate within the past 10 years with the introduction of more effective Pl genes). Anyway, there is a high degree of diversity in P. halstedii which enables the pathogen to quickly adapt to new situations. This might be via sexual recombination by outcrossing as suggested by Delmotte et al. (Citation2008), by parasexual processes which recently shown to give rise to new virulence phenotypes (Spring and Zipper, Citation2006, Citation2016), or by other mechanisms of genome instability (e.g. mitotic recombination, gene conversion, transposable elements).
E. Attempts to correlate pathotyping and race classification
Facing the experimental limitations of the bioassay-based pathotyping (see ) and the inability to find morphological characters correlated with the virulence phenotype of P. halstedii (Sakr et al., Citation2008), numerous attempts were made since the 1990s using different molecular tools for race classification (). Starting with PCR fingerprint techniques, RAPD analysis revealed either extensive polymorphism among the tested isolates (Borovkova et al., Citation1992) or the lack of sufficient variability in their samples (Roeckel-Drevet et al., Citation1997), but in any case, did not allow the identification of PCR products diagnostic for specific virulence phenotypes. Attempts to use minisatellite or simple sequence repeat (SSR) primers emphasized the generally high genetic diversity of the pathogen. This allowed differentiation on the level of single field isolates; but also proved to be inappropriate to assign traits characteristic for specific pathotypes (Intelmann and Spring, Citation2002). A first differentiation based on PCR fingerprints was reported by Tourvieille et al. (Citation1996) when testing 12 P. halstedii isolates of six different pathotypes from France, Spain, Morocco, and the US. However, only isolates of pathotype 100 (the old European race 1) showed a unique pattern of amplification products in 4 isolates from Morocco and France, whereas pathotypes 300, 700, and 703 clustered together or were represented only with one sample (pathotype 710 and 730).
Table 8. Attempts for molecular based race characterization of pathotypes (Pt).
With the detection of an unusual length of the internal transcribed spacer Region (ITS) of the nuclear rDNA in P. halstedii (Thines et al., Citation2005) and its sequencing, a new tool, designed for phylogenetic analysis, using multi copy genes became available for pathotype studies. While the ITS1 part is relatively uniform in size, the ITS2 part is highly variable due to multiple repeated elements (Thines, Citation2007), thus providing options for differentiation on the intraspecific level. A study with eight pathotypes from three European countries using partial sequences revealed that no polymorphism occurred in ITS 1; but the diversity found in ITS 2 allowed separation of pathotypes 100-330 from 700-730 (Spring et al., Citation2006a).
Because of the lack of genomic resources at that time, Giresse et al. (Citation2007) attempted to search for differentiating characters in P. halstedii populations by using expressed sequence tags (ESTs). The degree of identified single nucleotide polymorphisms (SNPs) found in 32 isolates from France and Russia confirmed the high level of genetic diversity of the pathogen but were not further attempted to distinguish pathotypes. In a follow-up study, Delmotte et al. (Citation2008) used the same EST-derived markers for a population study on 24 French isolates representing 14 different pathotypes. For diagnostic use in pathotyping, the sampling was not broad enough, but in a Bayesian analysis of the SNP data, three clusters were formed around pathotype 100 (300, 304), pathotype 703 (700, 707, 730, and 307), and pathotype 710 (704, 714, 717, 314, and 334), corresponding with three putatively independent introductions of the pathogen to France in 1966 (100), 1988 (710), and 1989 (703).
A similar EST-sequencing study followed few years later, in which the focus was now laid directly on genes related to the pathogenesis of sunflower downy mildew (As-Sadi et al., Citation2011). Twenty putative effector genes of the RXLR and CRN type were identified in the transcriptome of pathotype 710 and sequence comparison with three additional pathotypes (100, 304, and 703) revealed a total of 22 SNPs. Some of them might be differentiating, but to test their diagnostic usefulness would have required a much broader sampling in terms of both, pathotypes and origin. Nevertheless, this type of analysis of virulence-related genes suggested to be more efficient than random analysis of non-effector genes, and it was subsequently extended by Gascuel et al. (Citation2016) who identified 54 putative CRN and RXLR genes in seven representative pathotypes (100, 300, 304, 334, 700, 703, and 710). Based on SNPs in the effector genes, competitive allele-specific PCR (KASP) markers were designed and tested for determination of 14 pathotypes in 35 French isolates. In a two-level key approach, the 14 pathotypes could be separated into five groups (A:100, 300, 304; B:307, 700, 703, 730; C: 314, 710, 714; D:330, 707; E: 334, and 774) in the first level. In the second level, all pathotypes of group B, D and E could be separated, whereas only the two pathotypes 100/304 from group A and 314/714 from group C could not be separated from each other. Although this system needs to be approved by testing a much broader set of samples and particularly from a wider area of origin, it is a significant progress and a possible base for future race classification.
F. Outlook
Almost 60 years after the beginning of differentiation between virulence phenotypes of sunflower downy mildew, the bioassay-dependent classification of pathotypes is still not yet replaced by a system of direct race characterization. However, the fast progress in sequencing within the past decade is promising that a molecular-based race classification is close. With the switch from random analysis of undefined genetic areas to virulence-related genes, a key step was made which can easily be extended by incorporating the genome information for P. halstedii available since 2015 (Sharma et al., Citation2015), thus expanding the yet screened 54 putative effectors by a factor of ten.
Meanwhile, a second level of differentiating characters seems to be at its exploration as the proteome analysis of seven pathotypes (100, 304, 334, 700, 703, 710, and 730) has recently been announced (INRA Sunflower Bioinformatics Resources, Citation2018). With this tool at hand, it will certainly be possible not only to classify pathogen races but also to better understand the molecular mechanisms of compatible and incompatible reactions with the host plant.
V. Pseudoperonospora cubensis
A. Biological features
The genus Pseudoperonospora includes six widely recognized species, of which P. cubensis and P. humuli are economically most important (Runge et al., Citation2011). Several studies investigated the phylogenetic relationships between these two species. Choi et al. (Citation2005) showed that there are no real differences in morphology between the two species and concluded that, based on the genetic similarity of nrITS sequences, P. humuli could be conspecific with P. cubensis. However, more recent detailed studies using multilocus sequence analysis (nrITS, B-tub, coxII, and ypt1), provided strong support for retaining P. humuli and P. cubensis as separate taxa (Runge et al., Citation2011; Kitner et al., Citation2015). This coroborates with significant differences in sexual reproduction, where P. cubensis was heterothallic (Cohen and Rubin, Citation2012), whereas P. humuli was homothallic (Gent et al., Citation2017). Nevertheless, under laboratory conditions of artificial inoculation, some isolates of P. cubensis can infect hop and have limited sporulation and conversely, P. humuli can infect cucumber with limited success (Mitchell et al., Citation2011; Runge and Thines, Citation2012).
Cucurbit downy mildew (CDM) is a major disease of cucurbits with world-wide distribution in all major growing areas (Lebeda and Cohen, Citation2011; Cohen et al., Citation2015; Holmes et al., Citation2015). The causal agent, P. cubensis (Berk. & Curt.) Rost. (Oomycota, Peronosporaceae) (Choi et al., Citation2005; Runge et al., Citation2011; Runge and Thines, Citation2012), in its original delimitation infects over 60 host species belonging to more then 20 genera of the Cucurbitaceae (Lebeda and Cohen, Citation2011). However, detailed studies on cross-infectivity between distant host genera are pending and extended genetic analysis (e.g. Kitner et al., Citation2015) may suggest to delineate P. cubensis s.l. into several species or subspecies with narrower host spectra.
Pseudoperonospora cubensis was first described by Berkeley in 1868 from herbarium plant material (host species unknown) that originated from Cuba; hence, its species name is cubensis (Lebeda and Cohen, Citation2011). However, on living cucumber plants the pathogen was first observed and described by Rostovcev in The Botanical Gardens of Moscow (Russia) (Rostovcev, Citation1903). Pseudoperonospora cubensis has been known in Europe since the beginning of the 20th century (Skalicky, Citation1961; Lebeda, Citation1991). It was suspected to be introduced before 1902 into Russia (Rostovcev, Citation1903), probably from Japan (first recorded in 1889) and Indonesia (first recorded around 1900) (Zimmermann, Citation1909). During the first decades of the 20th century, the occurrence of the pathogen was reported step-by-step from various European countries (e.g. Austria, England, France, Germany, Hungary, the Czech Republic, Italy, the Netherlands, and former Yugoslavia) (Smolak, Citation1927; Skalicky, Citation1961; Lebeda, Citation1986a, Citation1986b; Lebeda and Schwinn, Citation1994). In North and Central America, including the Carribean Region, the pathogen was known since the end of 19th century. The earliest published records in the United States (USA) are from 1889 on cucumber in New Jersey, Florida, and Texas (Holmes et al., Citation2015). From the first half of the 20th century, no serious epidemics of P. cubensis were reported from Europe and the US (Lebeda and Cohen, Citation2011).
Two basic infection modes are known from P. cubensis. Indirect penetration of the leaf via stomata is the most frequent mechanism of infection and rarely direct (epidermal) penetration occurs (Lebeda and Cohen, Citation2011). Oospores in infected cucurbit leaves were reported from several countries during the 20th century (Cohen et al., Citation2015); however, the basic knowledge about sexual reproduction has been missing for long time (Lebeda and Cohen, Citation2011). Pseudoperonospora cubensis isolates are heterothallic and characterized by two mating types (A1 and A2) (Cohen and Rubin, Citation2012). Co-inoculation with A1 and A2 sporangia produced abundant oospores in detached leaves of melon and cucumber. However, infectivity of oospores in the laboratory was quite erratic, and there are no reports on oospore germination in vitro of P. cubensis (nor in P. humuli) (Cohen et al., Citation2015). It is expected that oospores play a crucial role in overwintering of P. cubensis in temperate zones (Lebeda and Cohen, Citation2011); however, seed transmission appears also possible through hyphae and sporangia in the seed hull or embryonal tissue (Cohen et al., Citation2014).
B. Geographic distribution and economic relevance
Ecogeographic conditions have a great impact on occurrence and progress of the disease cycle, pathogenic processes, symptom expression, and epidemiology of CDM (Lebeda and Cohen, Citation2011). CDM is widely distributed in all continents except Antartica where cucurbit plants are cultivated. It mainly occurs in warm, temperate, subtropic, and tropic areas on field cultures as well as on protected (greenhouse) cucurbit crops. During the last three decades, essential differences were recorded regarding geographic distribution, host range, epidemiology and disease severity of CDM (for reviews see Lebeda and Cohen, Citation2011; Cohen et al., Citation2015; Ojiambo et al., Citation2015).
The first and extremely dangerous epidemics of P. cubensis in Europe occurred on cucumbers in the second half of 20th century. Since 1984, CDM has been considered as a disease of high economic relevance in former Czechoslovakia and in Central Europe (Lebeda and Schwinn, Citation1994). P. cubensis spread from Central Europe/Czechoslovakia (Lebeda, Citation1986a) to Poland in 1985 (Rondomanski, Citation1988), and spread by windblown sporangia to Scandinavia (Finland, Sweden and Norway) (Lebeda and Cohen, Citation2011; Cohen et al., Citation2015), i.e. countries where disease was not known previously. The epidemics were extremely devastating with an estimated loss of 80–90% yield of cucumbers without any efficacy of fungicides used at that time (metalaxyl) (Lebeda, Citation1991). Serious infections were reported also in the following years (Lebeda and Schwinn, Citation1994) leading to a substantial reduction, to about 10–15%, of area of commercial cucumber production in the Czech Republic (Lebeda et al., Citation2011). From 2009 onward, new outbreaks of CDM in Central Europe caused serious damages to other cucurbits (Cucumis melo, Cucurbita spp., Citrullus lanatus, and Lagenaria spp.) (Lebeda et al., Citation2011, Citation2013a, Citation2013b; Citation2014a; see ).
In 2004, an outbreak of CDM in the US resulted in epidemics that stunned cucumber industry in the eastern parts of the country. All major cucurbit crops (cucumber, muskmelon, squashes, and watermelon) were seriously affected. The epidemic began in North Carolina, and the cucumber crops from Florida to the northern growing regions (e.g. Michigan in 2005) were devastated with complete crop loss in several areas. Since the emergence of a “new” population of P. cubensis in 2004, disease severity and yield losses have been significantly higher than in previous years, thus causing yield losses of 40% for cucumber growers in the US (Colucci et al., Citation2006). The spread of disease (Ojiambo and Holmes, Citation2011) was coupled with the failure of fungicide control (Holmes et al., Citation2015). Similarly, more local epidemics were observed in other areas of the world (Lebeda and Cohen, Citation2011; Cohen et al., Citation2015).
C. Current control mechanisms
During the last three decades, there has been substantial progress in the development of various control measures for CDM. At least four different control approaches could be considered as important, i.e. forecasting, prevention and agrotechnical aspects, resistance breeding and crop resistance, and fungicide control, as well as a combination of all those measures. All of these aspects were treated in detail in various review papers (Lebeda and Cohen, Citation2011, Citation2012; Ojiambo et al., Citation2015; Cohen et al., Citation2015; Holmes et al., Citation2015). In the current review, we will focus on two main control aspects, crop resistance, and fungicide control.
Availability of sources of resistance and using appropriate methods for resistance screening are among the basic requirements for successful breeding for resistance (Lebeda and Cohen, Citation2011). To improve crop resistance, efficient screening methods under laboratory and growth chamber conditions were developed to supplement the former field studies and to explore the availability of resistance sources among the most important cucurbits (Lebeda and Cohen, Citation2011).
Screening of large sets of C. sativus germplasm and cultivars provided no single genotype displaying complete resistance to current pathotypes of P. cubensis (Lebeda, Citation1992a; Lebeda and Prášil, Citation1994). Similar results were obtained with other wild Cucumis spp. (Lebeda, Citation1992b). Differences in field resistance were, nevertheless, found in the delay of the onset (7–14 days) and a slower rate of disease progression under strong infection pressure (Lebeda and Doležal, Citation1995). The most recent studies showed large variation in cucumber field resistance against CDM (Call et al., Citation2012a, Citation2012b), which could be used at least as partly efficient control measure. Moreover, intensive screening experiments on various host species (Cucumis spp. and Cucurbita spp.) using different strains of CDM showed a broad range of resistance behavior including general susceptibility to full resistance (Lebeda et al., Citation2016a, Citation2016b, Citation2016c, Citation2017). These results provide invaluable information for future breeding though genetic mechanisms behind the different resistance patterns are yet poorly understood (Lebeda and Cohen, Citation2011; Cohen et al., Citation2015; Holmes et al., Citation2015).
The high evolutionary potential of P. cubensis is not only a problem for resistance breeding but also for fungicide control of CDM. Resistance to various fungicides (e.g. metalaxyl, metalaxyl-M, cymoxanil, phenylamide, mefenoxam, strobilurins, and mandipropamid) is well-documented and has been reviewed widely (Lebeda and Cohen, Citation2011, Citation2012; Cohen et al., Citation2015; Holmes et al., Citation2015; Ojiambo et al., Citation2015). The phenomenon of fast development of fungicide resistance requires a continuous introduction of products with new modes of action (Ojiambo et al., Citation2010, Citation2015; Lebeda and Cohen, Citation2012; Cohen, Citation2015). It is evident that progress in the development of integrated disease management of CDM remains necessary.
D. Knowledge of infection/resistance mechanisms
Oomycetes and especially members of Peronosporaceae are characterized by their complicated relationships with their host plants on various levels of biological organization. Their obligate biotrophic nature dictates strict host specificity and mode of interactions with host plants (Lebeda and Cohen, Citation2011). However, individual genera and species of the Peronosporaceae differ in the level of their host specificity, from a single host species to a relatively large number of species and genera (Lebeda and Schwinn, Citation1994). P. cubensis (in its current delimitation) affects various genera and species within the Cucurbitaceae (Lebeda and Cohen, Citation2011). However, many genotypes (accessions, varieties, lines) of agronomically important host species express resistance against specific virulence phenotypes of the pathogen (Lebeda et al., Citation2006a, Citation2016a, Citation2016b, Citation2017). The mechanisms behind this resistance have not yet been unraveled in detail and new genotypes of the pathogen may quickly evolve to break them.
Infection process and resistance mechanisms of CDM starts with the recognition (compatible/incompatible interaction) between host and pathogen, so it is determined partly before, and fully shortly after infection structures (i.e. penetration peg, primary and secondary vesicles) have developed in the plant cell (Lebeda et al., Citation2008b; Bouwmeester et al., Citation2009). The response of resistant genotypes of cucurbit plants to penetration by P. cubensis is often characterized by a hypersensitive response (Cohen et al., Citation1989; Balass et al., Citation1993). Expression of resistance in C. melo was accompanied by extensive accumulation of phenolics, callose, and lignin at the infected sites that probably limited the growth of P. cubensis mycelium. These changes were followed by a rapid increase in peroxidase activity (Balass et al., Citation1993). Activity of this enzyme was used in C. melo as a marker for resistance to P. cubensis (Reuveni et al., Citation1990; Lebeda and Doležal, Citation1995). The peroxidase activity of C. melo is temperature-dependent and was fully expressed at higher temperatures (21–25 °C), but failed at lower temperatures (12–15 °C) (Balass et al., Citation1992). In many cucurbits, expression of resistance under field conditions is frequently followed by the occurrence of necrotic spots without P. cubensis sporulation (Lebeda and Cohen, Citation2011).
The genetics of host resistance to P. cubensis in many cucurbits (e.g. Cucurbita spp., Citrullus spp., and Lagenaria spp.) is still unknown (Lebeda and Cohen, Citation2011). Basic information on the genetic background of resistance against P. cubensis is available for only a few species, i.e. cucumber and melon (Lebeda and Widrlechner, Citation2003). Monogenic (or oligogenic) resistance occurs in C. sativus and C. melo. The major genes for specific resistance in C. sativus are probably recessive (Cohen et al., Citation2015). The most recent studies using cucumber “Wisconsin 2843” (resistance from PI 197087) led to the conclusion that resistance to P. cubensis is under the control of three recessive genes (dm-1, dm-2, and dm-3) (for details see Cohen et al., Citation2015). The described sources of resistance of C. melo have monogenic or oligogenic character (Lebeda and Cohen, Citation2011). However, there appears to be no general consensus in the literature about the inheritance patterns of resistance in these two crops (Cohen et al., Citation2015). Development of QTL and other molecular markers is in progress (Cohen et al., Citation2015; Holmes et al., Citation2015). Current developments in genetic and genomic research of cucurbits (Grumet et al., Citation2017) will facilitate the breeding progress and development of durable host resistance in cucurbits (Cohen et al., Citation2015; Holmes et al., Citation2015; Ojiambo et al., Citation2015).
E. Methods to monitor pathogenicity/virulence diversity in CDM
The first information about the pathogenic variability of P. cubensis isolates came from Japan in the 1940s (Iwata, Citation1941) and was later elaborated in detail in India, Israel, Japan, the US, and Europe (Lebeda and Widrlechner, Citation2003; Lebeda and Cohen, Citation2011; Cohen et al., Citation2015). A comprehensive and critical overview of this topic was summarized elsewhere (Lebeda et al., Citation2006a; Lebeda and Cohen, Citation2011). The determination of the pathotypes is primarily based on bioassays on leaf discs or segments of leaves (Lebeda and Urban, Citation2010). In contrast to pathosystems with narrow host range (e.g. P. halstedii, P. viticola, P. tabacina, etc.), the terms pathotype and race were historically used with a different meaning in some downy mildew pathogens with broad host spectra (e.g. P. cubensis, B. lactucae). According to Holliday (Citation2001), pathotypes are classified by means of infection bioassays on hosts of different species or even genera (e.g. Cucumis spp., Cucurbita spp. etc.), whereas physiological races of P. cubensis are assigned according to the infection behavior on closely related host differentials (e.g. accessions and cultivars of C. melo). As in this case, the pathotype and race differentiation are independent, one pathotype may harbor different physiological races and one race could comprise multiple pathotypes. This is contradictory to the definition of the term race given in Chapter I which demands host-independent characters of the pathogen for classification. However, to avoid confusion, the traditional concept will be kept here for the reviewed literature on P. cubensis, though knowing that virulence phenotypes of this pathogen infecting hosts of different genera are likely to consist of independent species as was indicated by recent whole-genome sequencing of different isolates of P. cubensis (Thomas et al., Citation2017a)
The first differential set of seven species of the Cucurbitaceae was developed for the identification of P. cubensis pathotypes (Thomas et al., Citation1987). They used Cucumis sativus, C. melo var. reticulatus, C. melo var. conomon, C melo var. acidullus, Citrullus lanatus and Cucurbita pepo based on the results obtained from inoculation of 26 host genotypes in seven genera from which they chose the most susceptible genotypes enabling a clear differentiation of compatibility/incompatibility reaction patterns (Thomas et al., Citation1987). Using this set, five pathotypes of P. cubensis were distinguished according to the different reaction patterns of eight tested isolates originating from the US, Israel, and Japan. The authors described them as “pathotypes 1 to 5” according to the increasing number of hosts on which a virulent (compatible) reaction occurred (Thomas et al., Citation1987). Based on a similar differential set (including Luffa cylindrica), pathotype 6 from Israel was described (Cohen et al., Citation2003). This differential set of Thomas et al. (Citation1987) had, nevertheless, several limitations (Lebeda and Widrlechner, Citation2003): it did not include important host genera (e.g. Benincasa, Luffa, and Lagenaria); differential genotypes were not precisely taxonomically-defined (on species, subspecies, and genotype/accession level) and were not maintained and provided as a complete unit by any competent institution in order to ascertain uniform results when employed by different laboratories. Lebeda and Widrlechner (Citation2003) used an extended set of differential genotypes that also included Lagenaria siceraria, Benincasa hispida, and Cucurbita maxima (). Using this new set, a new denomination system for P. cubensis pathotypes was introduced (Lebeda and Widrlechner, Citation2003; Lebeda and Cohen, Citation2011), which enabled the characterization by distinguishing between 12 “pathogenicity factors” and their combinations. This system is based on numerical tetrade codes (Limpert et al., Citation1994). Based on a binary evaluation of compatible/incompatible reaction pattern (+ or −) of a certain isolate, a numeric tetrade code was created for these isolates (). The set is open and could be extended by the incorporation of new taxa or genotypes in the Cucurbitaceae. It will, thus, be possible to make pathotype differentiation a flexible process that continually develops.
Table 9. Differentials set of cucurbit taxa for determination of P. cubensis pathotypes (modified according to Lebeda and Widrlechner, Citation2003; Lebeda et al., Citation2013a; Rsaliyev et al., Citation2018).
Table 10. Some examples of tetrade numeric codes of pathotypes of P. cubensis. Codes were established on the basis of the reaction of selected Czech isolates with cucurbit plants (differential set, see , Lebeda and Widrlechner, Citation2003) (Lebeda and Cohen, Citation2011).
Using the above-described differentiation set (or similar ones), pathotype variation in P. cubensis populations was studied in detail in the Czech Republic (Lebeda et al., Citation2013b), and more recently in the US (Thomas et al., Citation2017b) and in Kazakhstan (Rsaliyev et al., Citation2018). The pathotype structure in all these countries is extremely variable and diverse. Pathotype structure studies conducted in the Czech Republic with 398 isolates collected from 2001 to 2010 revealed the presence of 67 pathotypes (classified according to Lebeda and Widrlechner, Citation2003). The number of pathotypes recorded ranged from 33 (in 2001) to 5 (in 2007). Pathotypes 15.14.10 and 15.14.11 were the most frequent encountered. One pathotype (15.15.15) named “super pathotype,” was able to infect the entire set of 12 differentials, was detected in 2001, 2003, and 2004, and was especially prevalent in 2008 and 2010 (Lebeda et al., Citation2013b; Citation2014a). At the isolate level, 73.4% of the virulence variation was represented by 11 P. cubensis pathotypes (Lebeda et al., Citation2013b). Eleven unique isolates, originating from C. melo, C. pepo, C. maxima, C. moschata, and C. lanatus, sampled in 2009 and 2010, belonged to seven different pathotypes (Lebeda et al., Citation2013b). A gradual increase in virulence evolved in the Czech Republic from 2001 to 2009 (Lebeda et al., Citation2010, Citation2013a). These first detailed studies clearly showed that in the Czech Republic, Kazakhstan and the US, P. cubensis populations differed in pathotype structure and was also confirmed by molecular studies (Quesada-Ocampo et al., Citation2012). From recent surveys, it is evident that different P. cubensis pathotypes occurred also in China, Vietnam, Russia, and India (Bangalore area, Karnata Province) where severe epidemics were observed on ridge gourd (Luffa acutangula) (Cohen et al., Citation2015).
In addition to the pathotypes infecting different host species, further classification is possible and necessary with respect to lineages that differ in virulence against genotypes of a single host species (e.g. accessions and cultivars of C. melo) (Lebeda and Gadasová, Citation2002; Shetty et al., Citation2002; Lebeda and Widrlechner, Citation2003; Lebeda et al., Citation2006a, Citation2016c, Citation2017). Such lineages were called “races of CDM,” although their classification is made in the same way as that of the aforementioned pathotypes, but based on bioassays with very closely related differentials. From the background of available results, there are at least three candidate groups of cucurbitaceous host plants (Cucumis, Cucurbita, and Citrullus) that could be used for the development of race differential sets for P. cubensis (Lebeda et al., Citation2006a; Lebeda and Cohen, Citation2011). Most recently, this was supported by experimental results that showed enormous variation in interactions between C. melo and Cucurbita spp. genotypes and P. cubensis isolates (various pathotypes), which was expressed by numerous specific reaction patterns (Lebeda et al., Citation2016a, Citation2016b, Citation2016c, Citation2017). Except demonstration of huge race-specific variation, identical P. cubensis pathotypes (in sensu Lebeda and Widrlechner, Citation2003) differ in race-specificity (i.e. virulence) on one host species (C. melo) or related species (Cucurbita spp.), and for the first time, confirmed that same pathotypes could be different races (Lebeda et al., Citation2016c; Citation2017).
Unfortunately, no suitable race differential sets are yet available for the most important P. cubensis host genera, Cucumis, Cucurbita, and Citrullus (Lebeda et al., Citation2006a; Lebeda and Cohen, Citation2011). At least for CDM races on C. melo, host genotypes, originally developed for differentiation of powdery mildew (Lebeda et al., Citation2016d, Citation2018), were also suitable in differentiating P. cubensis races (Lebeda, et al. Citation2018, unpubl. results).
Of course, to accomplish a more detailed view on this complicated phenomenon, we need more information about the phenotypic expression of host-pathogen variation, mechanisms responsible for resistance, and their genetic bases (Lebeda and Cohen, Citation2011). The next steps are also more detailed population studies of virulence variation of P. cubensis races on the level of pathotypes (Lebeda et al., Citation2013b) that can contribute to more understanding and deciffering of high degree of spatiotemporal diversity in CDM populations.
F. Attempts to correlate pathotyping and direct classification of virulence phenotypes
The bioassay-based pathotyping and/or physiological race differentiation is, until now, the most commonly used approach of infraspecific classification in many oomycetes, including P. cubensis (Lebeda and Urban, Citation2010; Lebeda and Cohen, Citation2011). Unfortunately, this approach is still not very well-developed and internationally settled for both virulence categories, i.e. pathotypes and physiological races of P. cubensis. This is also the reason why it is rather difficult to compare virulence variation of P. cubensis detected by bioassay approach with molecular approach and/or genetic studies.
Currently, there is only limited information available on the genetic diversity of P. cubensis in relationship to geographic distribution of virulence phenotypes and pathogenicity of isolates (Lebeda and Cohen, Citation2011). Amplified Fragment Length Polymorphisms (AFLP) and the nucleotide sequence of the ITS1-5.8S-ITS2 subunit of ribosomal DNA (rDNAITS) have been used frequently for studying genetic diversity and for taxonomic and phylogenetic studies in various downy mildew pathogens (Cooke and Lees, Citation2004; Voglmayr, Citation2008; Quesada-Ocampo et al., Citation2012). Genetic diversity of P. cubensis populations from cucumbers (C. sativus) originating from Crete, Czech Republic, and Central Europe; the Western European countries France and the Netherlands were compared using AFLP fingerprinting (Sarris et al., Citation2009). Significant differences were found between these two pathogen populations (Central and West European versus Crete). Isolates were grouped into two separate clusters; one included the Czech (Central Europe) and West European (the Netherlands, France) isolates, and the other included the isolates of Crete. Variation was also detected inside these two main clusters and was attributed to different geographic origin, host cultivar, pathogenicity, and fungicide resistance (Sarris et al., Citation2009). Unfortunately, this variation is not clearly related and/or validated by virulence variation. However, all ITS2 rDNA sequences of Crete and Czech P. cubensis isolates clustered together with isolates from Austria forming a large cluster together with P. humuli, indicating their close taxonomic relationship (Sarris et al., Citation2009). These results need to be validated with a larger number of isolates of P. cubensis originating from largely distinct areas, different host species, and well characterized in their phytopathological attributes (pathotype, race, and fungicide resistance) (Lebeda and Cohen, Citation2011), which can provide the basis for investigating the sources and shifts in genetic diversity within and among P. cubensis populations as well as a better background for diseases management.
The first global population study of genetic structure and variation of P. cubensis was made by Quesada-Ocampo et al. (Citation2012) who investigated the genetic structure of 465 isolates from three continents, 13 countries, and 19 states of the United States, and from five host species using single nucleotide polymorphisms (SNPs) identified in five nuclear and two mitochondrial loci. Bayesian clustering resolved six genetic clusters and suggested some population structure by geographic origin and host because some clusters occurred more or less frequently in particular categories. All of the genetic clusters were present in the sampling from North America and Europe. Differences in cluster occurrence were observed by country and state. Isolates from cucumber had different cluster composition and lower genetic diversity than isolates from other cucurbits. Data showed that P. cubensis populations genetically differ between the continents, inside the continents and countries, as well as between the host crops. The high genetic diversity was clearly demonstrated within P. cubensis isolates affecting cucurbit crops in the US and isolates frequently infecting cucumbers were genetically different from those infecting other cucurbits (Quesada-Ocampo et al., Citation2012). Unfortunately, the great gap of this study is that it is not linked with detailed and internationally comparable studies based on bioassay of pathotypes and physiological races (see above). Such detailed comparative studies can give look inside of population virulence and genetic variation not only from the host but also spatiotemporal viewpoint (Lebeda et al., Citation2013a, Citation2014a).
Recently multilocus sequence analysis (MLSA) of four mitochondrial and two nuclear DNA regions was used to detect changes in the genetic structure of P. cubensis populations that occurred in the Czech Republic (Kitner et al., Citation2015) and might be associated with reported shifts in virulence from Cucumis spp. to Cucurbita spp. (Lebeda and Gadasová, Citation2002; Lebeda et al., Citation2013b, Citation2014a). The analyzed sample set of 67 isolates was collected from 1995 to 2012 in the Czech Republic and some other European countries (Lebeda and Gadasová, Citation2002; Lebeda et al., Citation2013b, Citation2014a). Sequence analyses revealed differences and changes in the genetic backgrounds of P. cubensis isolates. Coclustering was apparent in isolates collected in 2009. They were clearly out-grouped from isolates collected from 1995 to 2008. However, no clustering was observed based on geographical origin or pathotype code (Lebeda et al., Citation2013b, Citation2014a; Kitner et al., Citation2015). Preliminary sequencing data revealed differences and changes in the genetic background between isolates sampled before and isolates sampled after 2009. All isolates of P. cubensis sampled before 2009 exhibited the pre-epidemic genotype of Clade II, which is probably indigenous to East Asia, whereas Clade I (P. cubensis sensu stricto) was observed among isolates sampled from 2009 onward. The change in the genetic structure of Czech P. cubensis populations may be linked with a hybridization or, less likely, a mutation event that rendered strains able to infect a broader spectrum of host species (Kitner et al., Citation2015).
G. Outlook
More than 30 years ago, the first concept of P. cubensis pathotype differentiation (Thomas et al., Citation1987) was formulated, however, until now, it is not completely settled (for differences, e.g. Lebeda and Cohen, Citation2011; Cohen et al., Citation2015) and used internationally (Lebeda and Widrlechner, Citation2003; Lebeda and Cohen, Citation2011; Lebeda et al., Citation2013b). Currently, we are completely missing a well-developed and unified system for determination and denomination of P. cubensis races. It means that currently we do not have robust, classical bioassay background for differentiation of virulence phenotypes, and detailed population virulence studies of CDM (e.g. see Lebeda et al., Citation2006a). Because we are missing these crucial prerequisites for understanding of biological basis of virulence variation, it will be very difficult to replace them by a system of direct (genetic or genomic) pathotype and/or race characterization.
On the other hand, during last years some new approaches for P. cubensis population genetic studies have been tried. Draft genomes of P. cubensis have been published and can be used to perform comparative genomic analysis and develop tools such as microsatellites to characterize individual pathogen isolates and genetic population structure (Kanetis et al., Citation2009; Wallace and Quesada-Ocampo, Citation2017). For biosurveillance of P. cubensis epidemics, Next Generation Sequencing (NGS) could facilitate molecular diagnostics assays (Rahman et al., Citation2017). Nevertheless, only by combination of biological and molecular approaches, can we reach the point where we can understand in details of CDM individuals and populations virulence variation. Future developments in this area are very challenging.
VI. Peronospora tabacina
Peronospora is by far the largest genus in the downy mildews and has historically been represented by anywhere between 75 and 450 described species (Constantinescu, Citation1991; Dick, Citation2001; Thines and Choi, Citation2016). However, Thines and Choi (Citation2016) argued that because most Peronospora spp. have been primarily described from Europe and North America, and based on this, and extrapolation to the rest of world, the number of species may be vastly underestimated. They also contended that a more realistic number of species might be between 3000 and 5000 worldwide. However, unlike some Pseudoperonospora spp., e.g. Ps. cubensis, which can infect multiple host cucurbit species (but see Wallace and Quesada-Ocampo (Citation2017) who implied distinct species with limited host ranges hidden in clades in Ps. cubensis), Peronospora spp. are typically limited to specific hosts or a very limited number of related hosts and can cause severe economic losses to ornamental and field/food crops worldwide. Among these species is P. tabacina, which causes blue mold of tobacco (Nicotiana tabacum).
A. Biological features and economic relevance
P. tabacina Adam (syns. P. hyoscyami f. sp. tabacina, and P. hyoscyami) (see Johnson, Citation1989; Thines and Choi, Citation2016 for more complete taxonomic treatments) or blue mold is a fairly typical downy mildew. It produces sporangiophores that bear sporangia containing multiple, diploid nuclei (Trigiano and Spurr, Citation1987; Trigiano et al., Citation1985). Copious numbers of sporangia (e.g. more than 105 sporangia/cm2 leaf) can be produced from a single lesion under optimum environmental conditions (Cohen, Citation1976) and is the primary means by which the pathogen reproduces and spreads. The sporangia are wind-disseminated over short and long distances (Aylor et al., Citation1982).
Compared to many other oomycete species (e.g. Pythium, Phytophthora, Plasmopara, and Pseudoperonospora species), P. tabacina rarely reproduces sexually by thick-walled oospores (e.g. Patrick and Singh, Citation1981). However, oospores on occasion have been reported to be either extensively formed in or on the surface of infected leaves and stems (Milholland et al., Citation1981; Spurr and Todd, Citation1982; Svircev et al., Citation1989; LaMondia, Citation2010) or from hyphae originating from roots of N. repanda (Heist et al., Citation2002). There are no reports of P. tabacina oospores from the roots of N. tabacum. Oospore production may depend on relative humidity (<95%) (Spurr and Todd, Citation1982) and/or by increased light intensity with lower humidity (Svircev et al., Citation1989). Another factor influencing sexual reproduction is whether or not P. tabacina is homo- or heterothallic. Infection of plants occurs by sporangia that have 15 or more nuclei, which are reported to be derived from the mitotic events emanating from a single nucleus that migrated into the sporangium initial (Trigiano and Spurr, Citation1987). Likewise, this is the case reported for B. lactucae (Tommerup, Citation1981). In both cases, the sporangia would be homokaryotic. However, Davidson (Citation1968) suggested that all the nuclei found in P. parasitica sporangia originated from hyphae supporting the sporangiophores, which could include the possibility of a heterokaryotic sporangium. If a single homokaryotic sporangium infected a plant and produced oospores, then P. tabacina would be homothallic. This possibility was reported by Heist et al. (Citation2002) who inoculated plants with a single sporangium (presumed to be homokaryotic) and reported development of oospores. Similar difficult inoculation of sunflower (H. annuus) plants with individual P. halstedii zoospores was accomplished and resulted in unithalli and genetically identical strains of the pathogen (Spring et al., Citation1998). Nevertheless, there are other plausible mechanisms for introducing mating types on a single plant (see Spring and Zipper, Citation2016). The most probable of the above-mentioned scenarios is co-infection initiated by two or more sporangia in close proximity, harboring different mating types, followed by colony growth and anastomosis, and subsequent completion of the sexual process. If the report of a single nucleus being the progenitor of all nuclei in P. tabacina sporangia proves to be in error, then both mating types could be present in one spore, which would be an alternate explanation for the apparent homothallism reported by Heist et al. (Citation2002). These types of investigations are not easily undertaken and have not yet been completed for P. tabacina.
Oospores of P. tabacina probably germinate via germ tubes (Trigiano, Citation1983), but they seldom germinate or germinate sparingly (Kröber, Citation1969; Heist et al., Citation2002). This is in sharp contrast to the oospores of P. viciae f. sp. pisi that germinate easily when provided the proper environmental conditions (van der Gaag and Frinking, Citation1996). The role that sexual reproduction plays in maintaining genetic diversity and producing survival propagules of P. tabacina remains uncertain. However, Kröber (Citation1969) working with diseased tissue from Europe and the Soviet Union thought that oospores probably did not play an impactful role in the disease cycle, especially in establishing infection after overwintering. Nevertheless, LaMondia (Citation2010) speculated, with great reservations, that abundant oospores may be able to overwinter in infected tissues and serve as inoculum the following growing season. Sunko et al. (Citation2002b) also concluded that sexual reproduction is not the primary determinant of genetic diversity and population structure. Furthermore, there are no reports of blue mold initiated by oospore germination. However, it is possible the oospores play an important role in establishing and maintaining infections of host plants in the subtropics, but this hypothesis has not been investigated. Therefore, P. tabacina is most likely a clonal oomycete in temperate climates, which is similar to Ps. humuli (Wallace and Quesada-Ocampo, Citation2017).
P. tabacina was first reported infecting tobacco in the United States of America (USA) in 1921 (Smith and McKenney, Citation1921), and a herbarium sample provided evidence that the disease was present in Italy in 1934 (Carrieri et al., Citation2017) although this was probably an isolated incidence. Since 1921, the disease has spread to almost all of the tobacco growing regions of the world except for Eastern Asia including the People’s Republic of China (Thines and Choi, Citation2016). Prior to 1979, blue mold was primarily a foliar disease of transplants (Davis et al., Citation1981), which seldom translated to field infections. Instances of field diseases were usually alleviated by use of conventional contact, multisite mode of action fungicides (e.g. mancozeb, ferbam, copper, and sulfur) (Pfeufer and Pearce, Citation2015) or the heat of the summer (Spurr and Todd, Citation1982). However, a disease epidemic, which began in the Caribbean (Jamaica and Cuba) during the 1979 growing season, quickly spread to North America. This caused an estimated 14.5% reduction in crop value in the US and Canada (Nesmith, Citation1984) worth more than 250 million dollars (Lucas, Citation1980; Nesmith, Citation1984). This “new” form of the disease was characterized by a change in oospore morphology, high sustained disease incidence in the field, and systemic infections of plants not previously seen (Spurr and Todd, Citation1982).
Sporangia that incited the 1979 and 1980 epidemics were thought to have been transported by wind currents from Cuba to Florida (USA), and from there, northward to infect new plants (Todd, Citation1981). Aylor et al. (Citation1982) indicated that sporangia may be aerially transported for hundreds of km in 12–24 h, presumably before they lose viability. Spore viability is dramatically decreased by high sunlight (reduced to 0 in 6 h), to a lesser extent by low relative humidity (Bashi and Aylor, Citation1983), and by short term exposure to 254 nm UV light (Sukanya and Spring, Citation2013). Therefore, movement of sporangia via wind currents over longer distances is favored by cloudy days, but dry sunny days do not preclude local spread of the disease (Bashi and Aylor, Citation1983). Additionally, the disease may instigated by infected transplants (Moss and Main, Citation1988) as verified during the 1979 epidemic in Ontario, Canada (Gayed, Citation1985), and with the 2002 and 2003 epidemics in Germany (Keil and Spring, Citation2005).
Since the initial epidemics of 1979 and 1980 with the “new form” of P. tabacina, the disease became established throughout the tobacco growing regions of the world (Sukno et al., Citation2002a; Ristaino et al., Citation2007) including Europe where it causes regular epidemics in Germany with high economic losses (Zipper et al., Citation2009). Control of the disease at this time essentially relied on single-site of action fungicides (e.g. metalaxyl) in the USA and elsewhere. As predicted (Lucas, Citation1980), isolates resistant to metalaxyl were identified early in the 1980s in the USA where over 70% of the tobacco was treated with pre-plant metalaxyl (Nesmith, Citation1984). Bruck et al. (Citation1982) determined that three of the fourteen isolates tested from North Carolina (USA) were resistant to metalaxyl. Isolates resistance to this fungicide were later identified from Texas (USA) in 1983 and Mexico in 1985 (Wiglesworth et al., Citation1988), as well as in Germany in 2002 (Krauthausen et al., Citation2003), and France and Italy (Zipper et al., Citation2009). In fact, the predictions of Lucas (Citation1980) were accurate: the “overuse” of metalaxyl, which is a site-specific acylanaline fungicide, selected for naturally occurring resistant individuals that had temporarily become the dominant genotype in the field. However, with reduced-to-eliminated use of this class of fungicides, the sensitive strains occurred more frequently because of lack of selection pressure, stronger virulence, and were generally thought to be more fit than the metalaxyl tolerant strains (Spring et al., Citation2013). The development of less sensitive isolates to dimethomorph (DMM) fungicides was reported after repeated usages over years in Connecticut (USA) (LaMondia, Citation2013).
B. Current control measures
One method to control diseases caused by biotrophic pathogens is to develop resistant cultivars, and this has been the long-term challenge in combating blue mold. Natural, durable resistance in N. tabacum to blue mold is rarely identified (Rufty, Citation1989). To mitigate that issue, 15 Randomly Amplification of Polymorphic DNA (RAPD) markers were identified and statistically associated with a gene for resistance to blue mold. Two of these RAPD markers were converted to Sequence Characterized Amplified Regions (SCARs), which flanked a Quantitative Trait Locus (QTL) and potentially could be utilized in developing resistant varieties (Milla et al., Citation2005). Clayton (Citation1945) also stated that all tobacco (N. tabacum) varieties grown in the USA were susceptible; since 1933, he endeavored to identify sources of resistance from wild species of Nicotiana (e.g. N. debneyi (e.g. Patel et al., Citation2011 and others)), and transfer this resistance to tobacco. Clayton (Citation1968, Citation1967; see also a review by Rufty (Citation1989)) successfully transferred resistance from N. debneyi to N. tabacum. Furthermore, Wark (Citation1970) succeeded in introgressing resistance genes from N. goodspeedii into tobacco to develop the cultivars Sirogo and Sirone, which were registered in Australia. Wu et al. (Citation2015) introgressed a gene (RBM1) from N. debneyi into N. tabacum that conferred complete resistance to blue mold via a hypersensitive response. There are some reports of blue mold resistant cultivars of N. tabacum, including a broadleaf cigar wrapper variety “B2,” developed by LaMondia (Citation2012), and partial resistance by in a flue-cured breeding line, NC-BMR 90 (Rufty, Citation1989). According to Ristaino et al. (Citation2007), there is only one resistant burley tobacco cultivar, NC 2000 (USA Patent 6965062B2: Rufty, Citation2005); however, cultivar NC 2002 also has moderate-to-high resistance to blue mold (Johnson et al. Citation2017).
Because there are very few N. tabacum tobacco cultivars with high resistance to blue mold, fungicides are used to control disease outbreaks. The decision to employ fungicides to control blue mold is linked to disease forecasts and weather conditions. In the USA, a program, which was initially developed in the 1940s to report blue mold incidences and to make this information available to growers, is used. In Kentucky (USA), during the early 1980s, blue mold reports included disease incidences, meteorological information (winds) that might favor the spread of the disease, and advice as when to use preventive fungicides although no specific recommendation as to usage was made at the time (Nesmith, Citation1984). Currently, the North American Plant Disease Forecast Center (NAPDFC) provides the geographic presence of disease and potential spread of blue mold (and cucurbit downy mildew) using aerobiology and biometeorology (Main et al., Citation2001). Growers can then make an informed decision about preventive fungicide use and/or cultural practices. A similar system operated by CORESTA (Cooperation Centre for Scientific Research Relative to Tobacco) in Europe also reports and predicts incidences. There are many fungicides available to treat blue mold although none of them will provide complete disease control. Most extension publications advise growers to rotate fungicides to prevent potential development of widespread resistance, as seen with metalaxyl-based products (see e.g. Johnson et al., Citation2017; Peterson, Citation2017; Pfeufer and Pearce, Citation2015 for details of fungicides and application programs).
C. Infection/resistance mechanisms
Two main avenues for investigating infection and resistance to colonization by blue mold have been explored: leaf surface compounds that influence sporangial germination and induced systemic resistance. Sporangia of P. tabacina have an auto-inhibitor (5-isobutyroxy-β-ionone; Leppik et al., Citation1971) that is easily removed by washing the spores in water (Shepherd and Mandryk, Citation1962) and presumably by free water on the leaf surfaces. Inhibition of germination of sporangia by compounds on susceptible N. tabacum leaf surfaces, but not resistant species, N. debneyi, were noted by Shepherd and Mandryk (Citation1963), and first isolated and chemically identified by Cruickshank et al. (Citation1977). The inhibitory compounds were identified as α and β isomers of 4,8,13-duvatriene-1,3 diol and produced in glandular trichomes (Keene and Wagner, Citation1985). The α isomer inhibited germination more than the β isomer, but interestingly, dilutions of these compounds significantly stimulated germination (Menetrez et al., Citation1990). Cis-abienol, another terpene found on the leaf surface, significantly thwarted germination also, but not to the extent of α and β isomers of 4,8,13-duvatriene-1,3 diol. Therefore, a number of compounds may influence germination of sporangia, and thus, affect resistance to infection (Kennedy et al., Citation1992). Because these are all water soluble compounds, rainfall or even high humidity and dew could dilute the inhibitory compounds and allow or stimulate germination (Menetrez et al., Citation1990).
Induced or systemic acquired resistance (SAR) has been investigated in the P. tabacina – N. tabacum pathosystem. Studies from the late 1950s and early 1960s hinted that when diseased tobacco plants were either naturally infected or inoculated with stem injections of blue mold (Cruickshank and Mandryk, Citation1960), subsequent infections and disease severity on the same plant were dramatically reduced (see Tuzun and Kúc, Citation1989 for details). Later these observations of induced resistance or SAR were confirmed by Cohen and Kúc (Citation1981) who inoculated the base of tobacco plants with sporangia. Although the secondary phloem and vascular cambium tissues became necrotic at the inoculation site, the foliage was afforded some protection but did develop lesions. However, the number and size of lesions, as well as the number of spores produced per unit area of lesion were all significantly reduced on protected plants compared to plants that had no prior exposure to blue mold. Furthermore, protection against blue mold could be developed by inoculating plants with viruses, fungi, and bacteria, and this response was due primarily to a signal transduction from the site of infection to the foliage (see Kúc, Citation1987) where defensive pathogenesis proteins (PR) (e.g. β-1,3–glucanases and chitinases) were produced (Tuzun et al., Citation1989; Ye et al., Citation1989). A simple, but elegant, proof of this concept was demonstrated by grafting and girdling experiments in which the resistant response was transmitted to the scion by grafting and the signal was disrupted by girdling (Kúc, Citation1987; Kúc and Tuzun, Citation1983). Salicylic acid and derivatives such as acetylsalicylic acid (Ye et al., Citation1989), appeared to be the messenger compound to produce the PR proteins (e.g. Malamy et al., Citation1990; Horvath and Chua, Citation1994; Zhang et al., Citation2010; Innes, Citation2018). Phytoalexins probably do not play a role in the SAR in tobacco (Stolle et al., Citation1988).
The interface between P. tabacina and susceptible N. tabacum is quite interesting and resembles more of a resistant reaction by the host to the invader. Haustoria were completely encased by callose and probably later with cellulose but not lignin (Trigiano et al., Citation1983). Encasements as well as papillae are generally thought to be defensive responses (Aist, Citation1976) but are found in the susceptible reactions in P. tabacina (see Svircev et al., Citation1989 for details). However, Svircev and McKeen (Citation1982) did not observe papillae and appositions and reported that haustoria were not always completely encased in their study. Different cultivars and races of the pathogen were used in these studies and could account for the discrepancies between the two reports (Svircev et al., Citation1989). Therefore, the function(s) of these host responses in susceptibility/resistance remains largely unresolved.
D. Methods for identifying diversity and monitoring of pathotypes and races
Before the advent of molecular-based techniques, diversity of the pathogen was assessed on host differential panels, e.g. the reaction of specific hosts to the pathogen and was termed pathotypes. For example, three pathotypes (APT1, APT2, and APT3) were described from Australia based on host resistance, the growth of the pathogen (lesion size) and sporulation (Hill, Citation1963; Hill, Citation1966; also see Rufty (Citation1989) for details). Shepherd (Citation1970) classified four forma specialis of P. hyoscyami (hyoscyami, tabacina, hybrida, and velutina) based on the ability of the pathogen to sporulate on different hosts that included Hyoscyamus niger, N. langsdorfii, and N. tabacum x N. debneyi (). These pathotypes would probably be elevated to species using modern molecular assessment tools. Wigelsworth et al. (Citation1994b) also described pathotypes based on germination percentages of sporangia from Mexico, the USA, and Bulgaria on leaf surfaces of various cultivars of tobacco. In Europe, Tuboly (Citation1966) and Jankowski (Citation1972) reported a physiological race (PT2) that infected N. debneyi, whereas the previous race (presumably PT1) did not. During the 1979 and 1980 blue mold epidemics, Spurr and Todd (Citation1982) reported a new physiological race designated OPT-1, and Cohen and Kúc (Citation1981) designated a physiological race KPT-1 of blue mold that caused systemic infections, which had different size oospores than previously described, e.g. BPT from 1963 (see Trigiano and Spurr, Citation1987). Reuveni et al. (Citation1988) described physiological races of P. tabacina from Texas (USA) with metalaxyl resistance and compared it to the metalaxyl sensitive KY79 isolated from N. tabacum in Kentucky (USA), and demonstrated differences in virulence, symptom development and sporulation expressed on cultivar K14. Based on a molecular marker associated with resistance to metalaxyl and using genetically defined homogeneous molecular races of metalaxyl M—tolerant and—sensitive sporangia, Spring et al. (Citation2013) determined that the sensitive race was more virulent, but more fit in the absence of fungicide than the tolerant race. However, most of the metalaxyl-resistant P. tabacina “isolates” described (e.g. Bruck et al., Citation1982) would better meet the physiological race designation.
Table 11. Classification of Peronospora tabacina accessions from various locations.
Genetic characterization and detection of diversity and population structure is extremely difficult to investigate in obligate pathogens. Their identification and therefore early detection was largely lacking before the introduction of molecular methods for analyzing DNA. Early diagnostic of this disease is the most useful for planning preventive treatments of field plants and regulation and certification of blue mold free transplants, which is of paramount importance in the establishment of the disease in the field and subsequent spread to other healthy plantings. To utilize these molecular tools, genomic DNA can be isolated directly from carefully gathered sporangia that excluded host materials (Sukno et al., Citation2002a) or from diseased tissue (Trigiano and Ownley, Citation2017) depending on the molecular application being used. The internal transcribed spacer (ITS) region of ribosomal DNA of most eukaryotic organisms (White et al., Citation1990) was used to characterize isolates of P. tabacina (Wiglesworth et al., Citation1991). There have been several studies that have utilized ITS for positive identification and early detection of P. tabacina in tobacco tissues. Tsay et al. (Citation2006) designed specific primers for blue mold from ITS1/ITS4 primers (White et al., Citation1990), and in a nested reaction with other primers, amplified a 243 base pair (bp) segment, which was specific for all blue mold samples tested. A derived primer (PTAB) used with the ITS4 primer was utilized to generate a 764-bp amplicon that was specific to P. tabacina among all other fungi and oomycetes tested (Ristaino et al., Citation2007). Both of the methods based on ITS are very sensitive and specific for blue mold and therefore aided in the detection of the disease. More recently, a real-time polymerase chain reaction assay was developed and is based on primers derived from the ITS region (Blanco-Meneses and Ristaino, Citation2011). This technique detected blue mold in as little as four days-post-inoculation in medium-resistant and susceptible tobacco cultivars. Early detection of P. tabacina also has been achieved with a 232-bp characterized RAPD (SCAR) marker in which specific primers were designed (Wigelworth et al., Citation1994b).
Assessment of genetic diversity and population genetics awaited the development of more advanced molecular techniques. One of the early investigations of the genetics of P. tabacina used Restriction Fragment Length Polymorphisms (RFLPs) (Sukno et al., Citation2002b). Their results indicated very few polymorphisms among the observed samples from which they identified 10 different haplotypes. The authors concluded that although the technique was useful, the genetic variability of their samples was low. RFLPs are not very robust and typically do not have the resolving power to determine closely related individuals and population structure. However, Inter-Simple Sequence Repeats (ISSRs), a technique that targets multiple anonymous amplification sites were used to examine isolates differing in fungicide sensitivity (Zipper et al., Citation2009). Two of these amplicons were characterized (specific primers developed for these regions) and reliably differentiate between metalaxyl-sensitive and -tolerant phenotypes of the pathogen. A specific and accurate genetic marker of fungicide sensitivity permitted monitoring for the presence and frequency of the phenotypes from year-to-year, as well as selecting isolates for studies on virulence and pathogen fitness. Significant changes of sporangia size and shape of the metalaxyl-tolerant strain coincided with the molecular difference (Spring et al., Citation2013).
Microsatellite markers or Simple Sequence Repeats (SSRs) are repeated DNA motifs that are abundant in eukaryotic organisms (e.g. Powell et al., Citation1996). These markers are co-dominant, and thus, can explore heterozygosity at various loci. Additionally, once the markers are developed, DNA of diseased tissue may be isolated and amplified with primers specific for P. tabacina without amplifying host DNA. These attributes make microsatellites ideal for identifying individuals and conducting population studies (e.g. Tautz, Citation1989; Gupta and Varshney, Citation2000). Because obligate oomycete pathogens are difficult to work with, very few microsatellite marker systems have been developed for the downy mildews (e.g. Wallace and Quesada-Ocampo, Citation2017; Taylor et al., Citation2018). Microsatellite markers were developed for P. tabacinia using a small insert library approach (Trigiano et al., Citation2012). The number of microsatellites and their motifs was defined for the genome and 10 were selected to characterize the genetic diversity of 44 isolates from various geographical locations in the world. In this P. tabacina population study, the authors identified nearly four unique genotypes per locus, and 32 multilocus genotypes (MLGs) within the study population (Trigiano et al. Citation2012). The genetic diversity was considered low-to-moderate but certainly more than revealed by RFLPs (Sunko et al., Citation2002b). These markers were also used to characterize the population structure of worldwide isolates in which at least two preliminary distinct populations were identified (Hadziabdic et al., Citation2015). Genomic sequencing, exploration of microsatellites, and identification of genes of interest have become very inexpensive, and the laborious technique of discovering markers via insert libraries is now obsolete.
E. Outlook
The population structure and global migration pattern of blue mold were also characterized by sequencing two nuclear and one mitochondrial gene of 54 isolates of P. tabacina (Blanco-Meneses et al., Citation2018). These results supported the idea of long-distance migration of the pathogen from the Caribbean, Florida, and Texas to other northern US states. Although this study included a very limited sampling of isolates, the findings supported historical accounts of migration/distribution of the P. tabacina in Europe and the Middle East.
In conclusion, research related to P. tabacina, which causes significant economic damages in tobacco growing regions worldwide, is challenging and limited in scope. There are very few rigorously defined pathotypes and races of P. tabacina and most were described using morphological characteristics, host differential ranges, and differences in disease severity before robust molecular techniques were available. In many of the reports available from this period, variances in virulence were either missing or had ill-defined host differentials. Molecular tools and availability of different markers to evaluate genetic diversity, migration patterns, spatial distribution, and decline or expansions of existing populations provided invaluable research resources in the past three decades. Recently sequenced and annotated genome of P. tabacina (Derevnina et al., Citation2015) will further our understanding of virulence and genes associated with disease severity, physiology, and other biologically interesting processes. Comparative genomics between and among the downy mildews and other closely related oomycetes is also now possible.
VII. Bremia lactucae
A. Biological features
The genus Bremia (Regel 1843) (Peronosporaceae; Oomycete) is distinguished morphologically from other genera of the Peronosporales by its asexual conidiophores (Savulescu, Citation1962). In the taxonomic designation within the genus Bremia, there has been much confusion as to the species division. For rather long time there were only two species distinguished (B. graminicola and B. lactucae), and they differed in parasitism of various host families (Lebeda et al., Citation2002). Bremia lactucae Regel, causal agent of lettuce downy mildew, was considered as a parasite of some tribes of the Asteraceae, particularly in the subfamily Cichorioideae and B. graminicola Naumov as a pathogen of grass species of Arthraxon Beauv. (Poaceae). This species is characterized by small conidia and was easily distinguished from B. lactucae (Crute and Dixon, Citation1981). According to the host genera specialization, Skidmore and Ingram (Citation1985) distinguished many formae speciales (f.sp.) of B. lactucae (e.g. f.sp. centaureae, f.sp. cirsii, f.sp. lactucae, f.sp. lapsanae, f.sp. senecionis, f.sp. taraxaci, etc.), whereas other authors expected the existence of more independent Bremia species (Dick, Citation2000).
More recently, B. graminicola was shown to be unrelated to the type species (B. lactucae) and transferred to the new genus Graminivora, thus leaving Bremia transiently as a monotypic genus (Thines et al., Citation2006a, Citation2010). Meanwhile, molecular phylogenetic data confirmed the diversity of B. lactucae sensu lato and contributed to the separation of more than 10 distinct species (e.g. Choi and Thines, Citation2015) with mostly narrow host spectra. As a consequence, B. lactucae sensu stricto should be limited to the pathogen causing lettuce downy mildew (LDM) on Lactuca sativa and closely-related Lactuca species (see Lebeda et al., Citation2007b).
Lettuce downy mildew is a major and most devastating disease of lettuce with world-wide distribution (Crute and Dixon, Citation1981; Lebeda et al., Citation2002; Michelmore and Wong, Citation2008; Subbarao et al., Citation2017) and very high economic impact (Crute, Citation1992a;Citationb). LDM especially occurs in regions with temperate climate and may attack the plant throughout its crop cycle (Crute and Dixon, Citation1981). However, there is very incomplete information about the distribution of the oomycete on wild Lactuca species (Lebeda, Citation1984a; Lebeda and Syrovátko, Citation1988; Lebeda et al., Citation2002). From recent field studies made in the Czech Republic, it is evident that the most common weedy growing host species of B. lactucae is L. serriola (Lebeda et al., Citation2008a). The epidemiological impact of B. lactucae on wild Lactuca spp. is not very well known. The first quantitative results from Czech Republic showed that LDM on L. serriola was rather common and affected 75–80% of the natural host populations, but the degree of infection and severity of symptoms expression on infected plants and their populations was rather low (Lebeda et al., Citation2008a; Mieslerová et al., Citation2013). Migration and gene flow between wild (L. serriola) and crop (L. sativa) pathosystems are expected and this is likely to be a continous threat for cultivated lettuce (Lebeda et al., Citation2008a).
The morphology of B. lactucae (and some related Bremia spp.) was described in details in some previous (Crute and Dixon, Citation1981; Skidmore and Ingram, Citation1985) and most recent papers (Choi et al., Citation2011). Two basic infection modes are known for B. lactucae: first, direct penetration of the epidermis is the most frequent mechanism of infection, and second, rarely (1–5%) an indirect (stomatal) penetration occurs (Lebeda and Reinink, Citation1991, Citation1994; Lebeda et al., Citation2001). Asexual reproduction and sporulation are influenced by many environmental, host and genetic factors (Lebeda and Schwinn, Citation1994). Sexual reproduction, resulting in oospore formation inside the host tissue, is well known in B. lactucae. Both heterothallism and homothallism are known, however, heterothallism is prevalent in B. lactucae s. str. (Michelmore, Citation1981), and two compatibility (mating) types designated B1 and B2 were distinguished (Michelmore and Ingram, Citation1980). Heterothallism seems to be determined by two haplotypes at a single locus with the B1 compatibility type being conferred by a homozygous recessive condition and the B2 mating type by a heterozygous condition (Michelmore and Wong, Citation2008). It is generally accepted that oospores have an important role in overwintering and epidemiology of B. lactucae, but environmental factors can markedly influence the numbers of spores produced during both sexual and asexual reproduction (Michelmore, Citation1981; Scherm and van Bruggen, Citation1994).
B. Geographic distribution and economic relevance
The main distribution area of B. lactucae is in temperate and subtropical zones of both hemispheres and all continents, where lettuce is cultivated (Crute and Dixon, Citation1981). However, LDM also occurs in more dry areas (e.g. California and Arizona in the USA; and in Israel) where lettuce is grown under irrigation (Netzer, Citation1973; Simko et al., Citation2014; Subbarao et al., Citation2017). LDM occurs on field cultures as well as on protected (glasshouse) lettuce crops. However, substantial differences among geographic areas of one continent and country may be observed in the occurrence of B. lactucae, and the level of damage it causes to various Lactuca species, including wild Lactuca spp. (Petrželová and Lebeda, Citation2004a, Citation2011; Lebeda et al., Citation2008a). It appears that, under natural conditions, disease prevalence of B. lactucae infection mostly does not reach high levels (Lebeda et al., Citation2008a), but the opposite situation is known in lettuce cultivation (Simko et al., Citation2014b).
The pathogen can infect lettuce in any developmental stage. Early infections can cause irreversible damage and subsequent rotting of young plants. On infected leaves of adult lettuce plants, light green or yellow lesions with pathogen sporulation predominantly appear on abaxial part of the leaves. Heavily infected leaves can get necrotic and open for secondary infection, and thus are not suitable for marketing (Crute and Dixon, Citation1981; Simko, Citation2013). Enormous variation in symptom development was recorded in naturally infected weedy growing L. serriola (Lebeda et al., Citation2008a). The main reason for this difference may be the broad genetic diversity of L. serriola populations, characterized by the occurrence of a large number of race-specific resistance genes and/or factors (Lebeda et al., Citation2002, Citation2014b).
LDM is considered as one of the economically most important diseases on lettuce (Subbarao et al., Citation2017). In regions with high lettuce production (e.g. California, USA), disease reduced yield by decreasing plant survival, plant vigor, and mature plant weight, and increased the number of leaves that must be removed at harvest, or disfiguring the plant to render it unmarketable.
Devastating epidemics of B. lactucae occasionally occur, however mostly on local or regional level, not on the level of the whole continent. It is evident that the main cause of these epidemics is the occurrence of new virulence phenotypes of the pathogen that are able to overcome recently used resistances (Lebeda and Zinkernagel, Citation2003a,Citationb). The virulence structure of B. lactucae populations is highly specific for particular growing areas as a result of different history of usage of Dm genes or R-factors (Lebeda and Schwinn, Citation1994; Lebeda and Zinkernagel, Citation2003b).
C. Current control mechanisms
In comparison to many other vegetable crops, lettuce is a short-time growing crop with 10-12 (max. 18) weeks cultivation cycles. Lettuce cultivars for commercial production are designed for specific seasonal planting slots (Simko et al., Citation2014), thus rendering control measures for various diseases and pests, including LDM, rather difficult (Subbarao et al., Citation2017). Protection is achieved mostly by preventive applications of pesticides with various number of treatments (five to eight) per cultivation cycle. However, due to pesticide impact on environment and human health, emerging pesticide resistance, and stricter policies on levels of pesticide residues in agricultural products, new sustainable control strategies are needed (Barrière et al., Citation2014).
For successful lettuce resistance breeding the availability of sources of resistance and appropriate methods for resistance screening is required (Lebeda et al., Citation2009, Citation2014b). Recently, efficient in vivo screening methods for laboratory and growth chamber experiments (Lebeda and Petrželová, Citation2010), as well as marker-assisted selection (MAS) methods (Simko, Citation2013) were applied and should be supplemented with tests under field conditions.
During the last five decades, enormous progress in our knowledge and availability of sources among cultivated lettuce and wild Lactuca species with resistance against B. lactucae was achieved. In current lettuce breeding, at least four different strategies are used to control LDM. These approaches are based on utilization of vertical (race-specific) resistance, quantitative (race-nonspecific) resistance, field resistance and non-host resistance (Crute, Citation1992a Lebeda and Jendrulek, Citation1988; Lebeda et al., Citation2002, Citation2014b; Simko, Citation2013; Parra et al., Citation2016; Petrželová et al., Citation2011).
Vertical resistance is based on monogenic traits and has been used for nearly a century to improve cultivated lettuce against LDM. A classification system based on single dominant resistance genes or resistance factors was proposed and developed (Crute and Johnson, Citation1976), but meanwhile, 28 so-called Dm genes and 23 resistance factors (R) have been reported (Parra et al., Citation2016). In addition, there are also resistance genes of minor effect that confer incomplete or field resistance. Many of these genes will probably be identified in the future by quantitative trait locus (QTL), and analysis using molecular markers (Michelmore and Wong, Citation2008; Simko et al., Citation2015; Parra et al., Citation2016). However, thanks to enormous pathogen virulence variability, the durability of resistance based on individual Dm genes/R-factors is very short-lived (Lebeda and Schwinn, Citation1994; Lebeda and Zinkernagel, Citation2003b). For this reason, there is a continuous search for new sources of race-specific resistance to B. lactucae (Lebeda et al., Citation2014b).
Recent strategies for control of LDM include the combined use of resistant cultivars and fungicides as well as agronomic practices that reduce foliar humidity (Barrière et al., Citation2014). The use of fungicides is constrained by high costs and the development of fungicide-resistant strains (Crute, Citation1987; Schettini et al., Citation1991), as well as human health problems. There are increasingly restrictive regulations aimed at reducing pesticide applications in lettuce production (Subbarao et al., Citation2017). In Europe, several chemicals that are effective against B. lactucae are and/or will be withdrawn from the market (Barrière et al., Citation2014). Nevertheless, fungicide application, especially at a young plant stage, could give additional protection to B. lactucae.
D. Knowledge on infection/resistance mechanisms
Host-parasite specificity in pathosystem Lactuca spp. – B. lactucae is determined by many different factors (external and internal). The recognition between a host plant and B. lactucae starts shortly after the first surface contact and seems to be influenced by characteristics of leaf surfaces (indumentum) (Lebeda et al., Citation2008b). Conidia germinate on both non-host and host plants. On host plants, the frequency of germination and germ tubes formation is significantly influenced by the host genotype (Lebeda et al., Citation2001). After penetration, the development of internal infection structures (primary and secondary vesicles, intra- and inter-cellular hyphae, and haustoria) is variable and very much depend on type of resistance (e.g. vertical, horizontal, field, non-host) (Lebeda et al., Citation2001, Citation2002, Citation2008b).
Histological and cytological studies have demonstrated large variations in tissue and cell response. Expression of resistance in Lactuca spp. is frequently accompanied with the hypersensitive response (HR), however in very variable extent (Lebeda and Reinink, Citation1991, Citation1994; Lebeda and Pink, Citation1998; Lebeda et al., Citation2006b). In non-host resistance of L. saligna, HR is not considered as a primary mechanism of resistance (Lebeda and Reinink, Citation1994; Lebeda and Pink, Citation1998; Lebeda et al., Citation2006b). Prior to HR, irreversible membrane damage (IMD) occurs, and is a crucial point in cell metabolism and directly associated with a HR expression (Bennett et al., Citation1997). IMD or HR expression is specifically linked to various Dm genes (Mansfield et al., Citation1997) and related to changes of cytoskeleton, phenolic compounds, reactive oxygen (ROS), nitrogen (RNS) and sulfur (RSS) species intermediates (Lebeda et al., Citation2008b; Sedlářová et al., Citation2016; Tichá et al., Citation2018). The expression of some Dm genes of Lactuca spp. was reported to be temperature-dependent (Judelson and Michelmore, Citation1992).
The interaction between B. lactucae and lettuce (L. sativa) is determined by an extensively characterized gene-for-gene relationship (Christopoulou et al., Citation2015a, Citation2015b; Parra et al., Citation2016; Giesbers et al., Citation2017). It is expected that current developments in genetic and genomic research of lettuce (e.g. Reyes-Chin-Wo et al., Citation2017) will substantially contribute to the breeding progress and development of varieties with new, more diverse and most durable resistances (Lebeda et al., Citation2014b). New and promising approaches to control B. lactucae in lettuce based on host-induced gene silencing (Govindarajulu et al., Citation2015) and interfamily transfer of pattern-recognition receptors (Van Hese et al., Citation2016) were recently discussed. These approaches would move the lettuce breeding into a new sphere, which could be independent from resistance genes.
E. Methods to monitor virulence diversity
B. lactucae very frequently forms physiologically specialized entities (physiological races) characterized by certain types of pathogenicity (i.e. virulence patterns) that enables them to overcome the resistance of different host lettuce and wild Lactuca spp. genotypes (e.g. Lebeda and Zinkernagel, Citation2003a, Citation2003b). The display of compatibility/incompatibility in the interactions between host Lactuca spp. and B. lactucae is well-differentiated (Lebeda et al., Citation2002; Lebeda and Petrželová, Citation2010). The knowledge of genetics of host-pathogen interactions and the classification of Dm resistance genes (Parra et al., Citation2016) provides the possibility to identify the complementary virulence factors (v-factors) of B. lactucae. The first study in this direction was made on microevolutionary shift in the occurrence of v-factors (Lebeda and Zavadil, Citation1979) based on temporal changes of lettuce cultivars with different resistances, or Dm genes. Direct relationship between the introduction of new Dm resistance genes and the occurrence of specific B. lactucae v-factors (i.e. new pathogen pathotype and/or races) in the Netherlands during the period 1960–1990 was demonstrated (Lebeda and Schwinn, Citation1994; ). Afterward, changes in the genetic structure of the lettuce crop (Lactuca sativa) and populations of B. lactucae in Germany from 1974 to 1997 were studied. Substantial changes in the frequencies of R-genes were recorded over the period as a reaction to the occurrence of new virulence phenotypes in the pathogen population (Lebeda and Zinkernagel, Citation2003b).
Table 12. Evolution of B. lactucae virulence on lettuce in the period 1964–1988.
The term pathotype was repeatably used in various papers on B. lactucae virulence variation (e.g. Ilott et al., Citation1987; Schettini et al., Citation1991; Datnoff et al., Citation1994; Brown et al., Citation2004; Trimboli, Citation2004), however, in this case, must be considered as a synonymous to the term “race.” The system of characterization and denomination of B. lactucae pathotypes was developed in the US (University of California, Davis) in the laboratory of R. W. Michelmore. The pathotypes were described as Pathotype I, Pathotype II, Pathotype III, etc. (Ilott et al., Citation1987), later the denomination was changed for Pathotype CA I (California/CA/), CA II, CA III, …. and most recently CA IX (Bl: 9US) (Anonymous, Citation2018a). During the last decades, the differential sets of lettuce cultivars were continuously changing, according to the expanding knowledge of race-specific resistance genes (Parra et al., Citation2016). The details about history and virulence of B. lactucae isolates (pathotypes) in the Western US can be found at http://bremia.ucdavis.edu/bremia_database.php/. The International Bremia Evaluation Board – US (IBEB – US; previously the American Bremia Evaluation Board) was constituted in 2015 to formalize the nomination of new B. lactucae pathotypes (Michelmore and Truco, Citation2016). Currently, the US system of pathotype denomination is changing and implemented to IBEB – Global (International Bremia Evaluation Board; http://www.worldseed.org/our-work/plant-health/other-initiatives/ibeb/), i.e. global system, where US pathotypes (races) are described as Bl: 1US – Bl: 9US, …. (Anonymous, Citation2018a, Citation2018b, Citation2018c). However, most recently the US system is moving from term pathotype to term race (Anonymous, Citation2018c) and is contributing to better international communication and standardization of races nomenclature.
The virulence variation in B. lactucae is considered and known for about 100 years, and probably Schweizer (Citation1919) was the first who hypothesized existence of virulence phenotypes (physiological races) in B. lactucae. However, the first experimental evidence based on infection experiments originate from the 1920s to 1940s (Jagger, Citation1926; Jagger and Chandler, Citation1933; Ogilvie, Citation1944, Citation1946). Later on, intensified screening of B. lactucae virulence variation unraveled a high degree of pathogenic diversity of LDM, but the use of various differential sets of lettuce cultivars in the infection bioassays hampered comparison of the results from different countries (Crute and Dixon, Citation1981; Lebeda, Citation1982a). Therefore, a more advanced system for differentiation and denomination of B. lactucae virulence phenotypes was established by Crute and Johnson (Citation1976) who based their classification on known resistance genes (Dm genes or R-factors) in lettuce cultivars. This work created the first opportunity for an international system to describe LDM variation on the level of specific virulence phenotypes (v-phenotypes) and/or virulence factors (v-factors) (Wolfe et al., Citation1976). This conception also gave the opportunity to move from concept of individual v-phenotypes (e.g. Lebeda, Citation1979a, Citation1979b) to the population level and introduce for virulence surveying the population genetic approach and to express most critical v-factors in pathogen population (Lebeda, Citation1981; Wolfe and Knott, Citation1982).
The determination of v-factors in the LDM population of a geographic region became important information for lettuce growers to estimate infection risk and to implement preventive control measures. This fueled LDM virulence monitoring studies in many countries (e.g. Lebeda, Citation1979a, Citation1979b, Citation1982b; Jönsson et al., Citation2005; Sharaf et al., Citation2007; Maisonneuve et al., Citation2011; Souza et al., Citation2011; Trimboli and Nieuwenhuis, Citation2011; Petrželová et al., Citation2013; Nordskog et al., Citation2014; Van Hese et al., Citation2016).
This approach also gave the possibility for more detailed pathogen population analyses based on the background of virulence complexity of individual isolates (Lebeda, Citation1982b), frequency of individual v-factors and their complexes (pairs, triplets, etc.) (Lebeda, Citation1981, Citation1982c), expression of v-factors and v-phenotypes diversity (Lebeda, Citation1982d), and genetic similarity or dissimilarity (Lebeda and Jendrulek, Citation1987a, Citation1987b), and application of the Virulence Analysis Tools (VAT) software (Kosman et al., Citation2008; Schachtel et al., Citation2012; Petrželová et al., Citation2013), as well as detailed microevolutionary spatiotemporal studies (Lebeda and Zinkernagel, Citation2003b).
A practicable problem for comparability of the bioassay-based classification of LDM virulence phenotypes is the necessity of uniform test conditions. This starts with the access to the unified and genetically defined host differentials and requires identical inoculation and incubation conditions, as well as evaluation of infection symptoms. The most commonly used technique is inoculation of cotyledons or leaf dics of Lactuca spp. (Lebeda and Petrželová, Citation2010).
On the way to standardize the bioassay-based LDM classification, an international initiative named IBEB (International Bremia Evaluation Board) proposed guidelines for defining and correct denomination of new virulence phenotypes (van Ettekoven and van der Arend, Citation1999).
For this purpose, a lettuce differential set EU-A (1999) was defined for testing B. lactucae isolates, which later on was amended by replacing and adding some genotypes in the set EU-B (2010) (). The results of LDM screening on this set are translated into sextet codes, i.e. that per six results (+ or −) the six values (1, 2, 4, 8, 16, 32) are given if the reaction is susceptible (+). Values in each group (in the set EU-A were three full groups, ) are summed, the result is a unique value (sextet code) that specifically characterizes each isolate (). With the introduction of the sextet code, the denomination of previous virulence phenotypes (e.g. NL1 to NL15) has been changed as well, and are now named BL followed by number and sextet code (e.g. BL-16 (EU-A 63/31/02/00)).
Table 13. Original differential sets EU-A and EU-B of lettuce cultivars/lines for testing virulence of B. lactucae isolates (van Ettekoven and van der Arend, Citation1999; IBEB, 2010; Parra et al., Citation2016).
Table 14. Recent differential set EU-C of lettuce cultivars/lines for testing virulence of B. lactucae isolates (IBEB, 2016; Parra et al., Citation2016).
Table 15. Example of coding B. lactucae virulence phenotypes (physiological races) according to a sextet code produced in differential lettuce set EU-A (van Ettekoven & van der Arend,Citation1999).
In 2016, this system was replaced by a new differential set EU-C, where many previous genotypes were omitted (). Because of the existence of different systems in Europe and the US, in 2015, it was decided to unify this system and was recently implemented by IBEB–Global (see above and ).
Table 16. Sporulation behavior of Bremia lactucae virulence phenotypes from US (Bl: 5-9US) and Europe (Bl: 16-33EU) to the IBEB C differential set of lettuce (IBEB, 2018).
All the virulence surveys reported above were made with B. lactucae isolates and their populations from cultivated lettuce (L. sativa). However, B. lactucae is also, at least in some European countries, common on L. serriola (Lebeda, Citation1984a; Lebeda and Syrovátko, Citation1988; Petrželová and Lebeda, Citation2004a; Lebeda et al., Citation2008a; Mieslerová et al., Citation2013). Structural and temporal changes in virulence variation of B. lactucae populations on L. serriola are very dynamic an diverse (Lebeda, Citation1984; Lebeda and Petrželová, Citation2004; Petrželová and Lebeda, Citation2004b; Lebeda et al., Citation2008a). The highest frequency was recorded by v-factors v7, v11, v15–17, and v24–30, matching Dm genes from L. serriola. In contrast, v-factors (e.g. v1–4, 6, and 10) matching Dm genes originating from L. sativa were very rare. This demonstrates the close adaptation of B. lactucae virulence to the host (L. serriola) genetic background.
F. Attempts to correlate virulence classification with molecular markers
Currently, there is only limited information available on the molecular genetic diversity of B. lactucae on lettuce and closely related Lactuca spp. (Michelmore and Wong, Citation2008) in relationship to geographic distribution, the host specificity, virulence variation of isolates and pathogen populations, coevolution, and gene flow between populations. Early attempts to identify and classify the virulence variation between B. lactucae races were made on the level of inter-simple sequence repeats (ISSR) (Wagner and Idczak, Citation2004); however, there was no direct relationship between v-phenotypes and molecular markers established. Although other methods such as AFLP and RFLP analysis were employed to search for mapping avirulence genes in the B. lactucae genome (Sicard et al., Citation2003), no use of these fingerprint techniques for virulence classification has been reported so far.
Defined genomic regions with high potential for differentiation on the infraspecific level were tested for phylogenetic investigations and the noncoding parts of the nrITS proved to be suitable to distinguish LDM isolates of lettuce from those pathogenic to L. indica and less related hosts (Choi et al. Citation2007a). A currently ongoing studies of B. lactucae from L. sativa and L. serriola, based on nrITS sequences, showed high haplotype diversity among and within pathogen populations. It is expected that the populations are linked only by very low levels of gene flow, and it is likely that the populations evolved in relative isolation from each other, which is supported by comparative virulence surveys (Lebeda et al., Citation2008a). It seems that B. lactucae on L. sativa emerged from several host jumps from L. serriola, whereas geneflow between both pathosystems is only weakly pronounced. Multiple host jumps can probably cause the periodical occurrence of downy mildew epidemics in lettuce based on the breakdown of resistance genes introduced from L. serriola.
Several proteomic approaches were applied to identify protein markers providing typical signals from intact spore (IS) MALDI-TOF MS of B. lactucae. Ribosomal proteins and histones could be employed as markers in biotyping analyses for pathogen identification (Chalupova et al., Citation2012; Beinhauer et al., Citation2016). However, these markers are not directly linked with pathogen virulence behavior. Oomycetes use a diverse arsenal of secreted proteins (effectors) to manipulate their hosts (Stassen and Van den Ackervecken, Citation2011). Thus, 34 potential RxLR(-like) effector proteins of B. lactucae (Stassen et al., Citation2012) were identified and later tested for specific recognition within a collection of 129 B. lactucae-resistant Lactuca lines (Stassen et al., Citation2013). These results provided an insight into the transcriptome of B. lactucae and its encoded effector arsenal (Stassen et al., Citation2012), which could be potentially exploited in virulence studies if their secretion is relevant for pathogenicity. However, not all identified putative effectors seem to play such a role in the pathogenicity of LDM. So, very recently, Choi et al. (Citation2017) reported that BrRxLR11 is a useful phylogenetic marker for Bremia but shows very low expression. This suggests that BrRxLR11 is not under positive selection and may not be useful for virulence studies.
G. Outlook
Currently, we need more detailed and comprehensive studies of B. lactucae populations around the globe and to be able to compare those from more complex view. It must be based on more efficient cooperation and coordination between researchers, breeders, and some authorities (e.g. IBEB). Because we basically understand the biological basis of B. lactucae virulence variation (Michelmore and Wong, Citation2008), it could be good prerequisite for exploitation a new techniques in this area like molecular genetic and genomic approaches for races identification and characterization.
During the last years, some new approaches for B. lactucae race and population genetic studies have been developed. Draft genomes of B. lactucae (The Bremia Genome Project, UC, Davis, CA, USA; http://www.bremia.ucdavis.edu/) have been published and could be used to perform comparative genomic analysis and develop tools such as microsatellites to characterize individual pathogen isolates and genetic population structure. The most recent strategy in this area, i.e. genome sequencing of B. lactucae, is summarized on site of above mentioned Bremia Genome Project (http://bremia.ucdavis.edu/): “The data will enable the efficient discovery of genes encoding virulence effectors and the dissection of the co-evolution of phytopathogenic oomycetes and their plant hosts. The genome sequence will enable the identification of genes involved in virulence and chemical insensitivity.”
VIII. White blister rusts
A. Specific biological features
Unlike downy mildews, white blister rusts do not depend on high humidity for sporulation as the formation of spores is from sporogenous hyphae below the plant epidermis (Heller and Thines, Citation2009). In addition, it is noteworthy that the white blister rusts have evolved independently from the downy mildews (Hudspeth et al., Citation2003; Riethmüller et al., Citation2002). Hence, they have been separated from the Peronosporales and classified into an order of their own, the Albuginales (Thines and Spring, Citation2005). The spores are liberated from the pustule-like sori when the epidermis is lytically dissolved by the primary sporangia (Heller and Thines, Citation2009). Sporangia tolerate desiccation better than in case of downy mildews. In the genus Pustula and the genus white blister pathogens of morning glories (Convolvulaceae), which are currently still placed in the genus Albugo, sporangia are often thick-walled to avoid collapsing upon desiccation. Germination by zoospores is the primary mode of sporangium germination, rendering the infection process dependent on at least limited amounts of water. Similar to the downy mildews, white blister rust species sexually form thick-walled oospores, which outlast unfavorable conditions. In sunflower white blister rust, Pustula helianthicola, oospores are formed homothallically and can also be found in achenes of the host, so they are easily distributed by seeds (Lava and Spring, Citation2012; Lava et al., Citation2013). Unlike in downy mildews, oospores are also used for discriminating species in white blister rusts (Choi et al. Citation2007b, Citation2008; Thines et al. Citation2009a; Ploch et al. Citation2010; Rost and Thines, Citation2012; Mirzaee et al. Citation2013). Apart from a generalist species, A. candida, species within white blister rusts seem to be highly host specific, either on the genus level (Ploch et al., Citation2011) or even on the species level (Ploch et al. Citation2010). At the same time, there are several Brassicaceae species that are affected by both the generalist and a specialized species (Choi et al. Citation2006; Thines et al. Citation2009b).
B. Economic impact
White blister rusts are economically relevant in the production of cruciferous crops, such as rapeseed, mustard, and broccoli (Petrie, 1963; Bains and Jhooty, Citation1979) but losses can be significant also in commercially or ornamentally grown sunflowers (Allen and Brown, Citation1980; Thines et al., Citation2006b; Rost and Thines, Citation2012). Apart from white blister rust on crucifers and sunflower, caused by A. candida and P. helianthicola, respectively, there are some other species with economic impact. These are Wilsoniana bliti and W. amaranthi on foxtails, the white blister rust pathogen of spinach A. occidentalis, which based on molecular phylogenetic data will need to be transferred from Albugo to a new genus and A. lepidii on common cress. Some outbreaks by uncharacterized species on ornamentals are occasionally reported, but their monetary impact is often limited.
C. Current control mechanisms
White blister rusts can be controlled by various fungicides and oomyceticides, but are generally able to tolerate higher doses of dimetomorph than the downy mildews of the Peronosporaceae. In the agricultural practice, resistance breeding is a widely used strategy (e.g. Liu et al., Citation1996; Bansal et al., Citation1999), although varieties regarded as resistant might allow infections to a degree that they can be passed on to the next generation of plants (Allan, Citation1975). This transmission is probably due to the endophytic nature of the pathogen that has also been found in natural host populations (Ploch and Thines, Citation2011).
D. Knowledge on infection/resistance mechanisms
Knowledge on virulence and avirulence mechanisms is rather poor in white blister rusts. So far, only few QTL conferring resistance to white blister rust have been found (e.g. Ferreira et al., Citation1995; Kole et al., Citation2002; Borhan et al., Citation2004, Citation2008). Even less is known on avirulence factors in white blister rusts, which still need to be identified. However, white blister rusts are able to effectively shut down plant immune responses (Cooper et al., Citation2008), thereby also letting some unadapted pathogens to colonize pre-infected host plants (Belhaj et al., Citation2017). Apart from the research that has been done on A. candida (Links et al., Citation2011) and A. laibachii (Thines et al., 2009; Kemen et al., Citation2011), nothing has been published yet about the molecular mechanisms leading to infection of resistance in white blister rust pathosystems.
E. Methods to monitor the genetic or virulence diversity
So far, less effort has been put into monitoring infection diversity in white blister rusts. This is also owing to the fact that pure spore preparations for ALFP or ISSR fingerprinting are not easily obtained from the field plants and that other typing methods that are not influenced by contaminant DNA, e.g. microsatellites, have not been developed. In addition, standardized cultivation of white blister rusts is currently limited to A. candida, A. laibachii, and P. helianthicola. Thus, there are only few examples and limited to crucifer-infecting white blister rust species where field isolates have been screened for their infectivity in various crops (e.g. Rimmer et al., Citation2000). Similarly, there have been few studies that have systematically addressed the infectivity of natural pathogen strains on various lineages of the model plant, Arabidopsis thaliana and its relatives (Holub, Citation2008; Thines et al., 2009; Hoebe et al., Citation2011).
F. Attempts to correlate pathotyping and race classification
There have been some attempts to classify isolates of Albugo into various races. Of these, race 1 corresponds to A. laibachii, whereas races 2-9 are different lineages of A. candida isolated from various hosts (Pound and Williams, Citation1963; Verma et al., Citation1975; Petrie, Citation1988; Borhan et al., Citation2008; Holub, Citation2008; Thines et al., 2009). A major issue is that the designation of such physiological races is done primarily on the basis of the host plant from which the strain is isolated, e.g. race 4 designates isolates from the type host of A. candida, Capsella bursa-pastoris. In addition, a limited set of other Brassicaceae is often used for further characterization (Petrie, Citation1988; Holub, Citation2008). However, this might be highly misleading as it is conceivable that there is infrequent admixture on hosts overlapping in the host spectrum of two distinct strains of A. candida. In explanation, each strain of Albugo has just a limited amount of compatible hosts, which can, however, be phylogenetically very divergent (Khunt et al., Citation2000). If these strains mate, the new combination of pathogenicity effectors might lead to new mosaic genotypes with new host spectra (Adhikari et al., Citation2003; Thines, Citation2010, Citation2014; McMullan et al., Citation2015). This means that there can be multiple genetic lineages affecting Capsella bursa-pastoris, with divergent host spectra, but overlapping only in terms of pathogenicity to C. bursa-pastoris. Their other potential hosts might be highly divergent, depending on which additional virulence factors they are carrying, which might also be hosts that are seen as typical for other races, e.g. A. thaliana or Brassica oleracea. Thus, there is an urgent need for a revised race/pathotypes designation scheme for A. candida taken into consideration the recent findings regarding the evolutionary history and strategies of this generalist pathogen.
IX. Final remarks
The current status in virulence classification of the different biotrophic oomycete pathogens treated here differs significantly. The reason for that is quite variable and may depend on deficits in the knowledge of individual biological peculiarities, taxonomic uncertainties, as well as on economic aspects such as the necessary research funding. The latter, for instance, seems to be responsible for the lack of resistance screening in tobacco against P. tabacina. Research for this crop is largely dependent on corporate or private funds as many world governments will not permit the use of public money for this purpose. Thus, there is yet no virulence testing at all in this pathosystem, and most likely will not. Thus, the population of tobaco blue mold is so far only classified in two groups, a metalaxyl-sensitive and a tolerant race, both of which show differences in the infection behavior (Spring et al., Citation2013) and can be identified by molecular markers (Zipper et al., Citation2009).
The lack of progress in the white blister rusts is similar. The economic losses, caused by Albugo spp., Pustula spp., or Wilsoniana spp. is currently regarded as not severe enough to spend much research efforts in developing suitable methods for bioassay-based virulence testings in individual pathosystems.
In P. cubensis (and partly in B. lactucae), the taxonomic species concept is still not fully accepted so that the methodology for virulence phenotyping is not yet clear. Pathogen isolates from a seemingly broad host spectra (e.g. Cucumis spp., Cucurbita spp., Citrullus spp., or Lagenaria spp.) can hardly be classified on resistance differentials of a single crop species.
The situation is completely different for P. viticola, where the host range in Vitis ssp. is clearly defined. However, despite significant progress in identifying resistance markers in the host, there is yet no common set of differentials for bioassay-based pathotyping, which would be the prerequisite for classification of virulence phenotypes and subsequent search for correlating molecular markers. An additional obstacle, in this case, is the perennial nature of the host plant which restricts bioassays to certain periods of the year and requests significant logistic efforts in host cultivation.
This leaves P. halstedii as the only example for which the methodology of pathotyping is employed uniformly world-wide and where the requirements for the development of a molecular-based virulence classification are accomplished and may be published in the near future (see INRA Sunflower Bioinformatics Resources, Citation2018).
Acknowledgements
The authors thank Dr. Yigel Cohen for the critical review of the manuscript before submission. A. Lebeda work was supported by projects MSM 6198959215 (Ministry of Education, Youth and Sports), QH 71254 and QH 71229 (Czech Ministry of Agriculture), and by the Internal Grant Agency of Palacky University in Olomouc (IGA_PrF_2019_04). R. N. Trigiano's contribution was supported by USDA Grant NACA 58-6062-6.
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