Fungicide resistance is a form of selection that describes a fungus’s ability to survive and reproduce in the presence of a fungicide Due to issues of length, brevity and complexity, this review will only deal with fungicides that are for the control of true fungi, and not fungicides for the management of Chromista.
Due to issues of length, brevity and complexity, this review will only deal with fungicides that are for the control of true fungi, and not fungicides for the management of Chromista.
the biology of the pathogen,
the mechanism(s) of action of the fungicide,
the rate and frequency of fungicide application.
It is important to note that most fungi show a broad range of sensitivities to the spectrum of different fungicides. For example, most fungicides for the control of Chromista (e.g., mefenoxam, fluopicolide, dimethomorph) do not control true fungi; some fungicides are specific for ascomycete (e.g., thiophanate-methyl) or basidiomycete fungi (flutolanil), and species within the same genus of fungi may respond differently to certain fungicides (Leroux et al. 2012). Additionally, different genotypes exist within a spectrum of sensitive to resistant (Albertini et al. 1999). The relationship between the frequency of fungicide application and resistance has been established (King and Griffin, 1985; Suzuki et al. 2010), and the role of rate or dose in this process is deserving of further study (Genet et al. 2006; van den Bosche et al. 2011).
In 2006, the world market consumed approximately 520 million pounds of fungicide (Grube et al. 2011), a number that is expected to increase as the consumption of other pesticides declines (Troy, 2011). The discovery, development, and registration of a new pesticide comes at a cost (not including the capital costs or production). In 2006, this price was estimated to exceed $180 million (Whitford et al. 2006). With fewer fungicides available (particularly with new modes of action) and increasing consumption, risk of fungicide resistance is even greater, and failures will more profoundly impact cropping systems. All of these factors increase the need for rapid detection of fungicide resistance. Historically, the detection of fungicide resistance in the field has been difficult because disease control failures can be caused by factors other than resistance, including improper fungicide selection, improper timing, reduction of recommended rate, and erroneous sprayer calibration (Latin, 2011).
Rarely, are molecular proofs of fungicide resistance ever fulfilled with plant pathogenic fungi, although many of the genes involved in fungicide resistance are studied in model systems to elucidate mechanisms (Zhang et al. 2002). Usually, resistant individuals are detected using bioassays (sensitivity tests or poison plate assays) and those resistant isolates may be correlated with molecular markers, many of which are based upon previous studies (Koernraadt et al. 1992; Albertini et al. 1999; Schnabel and Jones, 1991; Lesniak et al. 2011). In some instances, segregation analysis between crosses of sensitive and resistance phenotypes is often used to strengthen this correlation (Faretra and Pollastro 1993; Orth et al. 1995; Dyer et al., 2000); however, the ultimate mechanism of resistance is often lacking. Ultimately, the success of molecular detection is only useful if the expected genetic profile that is being screened correlates to the phenotype of resistance. Laboratory tests are required to determine the level of resistance in numerous suspect isolates of the pathogen before an assessment of the status of the orchard, plantation, vineyard or field can be determined. Traditionally, this meant direct-plating of single-spore isolates or mycelial plugs on medium amended with various concentrations of fungicides under specified growth conditions, and then determining inhibition of growth and/or spore germination (Koller et al. 1997). Many fungi, including the economically important downy mildews, powdery mildews, and rust, cannot be cultured. Other fungi, like
Molecular methods have the potential to provide a more rapid and reliable assessment of fungicide resistance, and there are many examples of the successful use of these methods in applied plant pathology (for a review, see Vincelli and Tisserat, 2008). Genetic testing of potentially resistant isolates can be performed directly from disease lesions, obviating the need for isolation, and subsequent growth of the fungus
As a paradigm, nucleic acid-based detection systems offer rapid (within hours) and sensitive (to picograms) methods to detect the presence of alleles known to confer resistance. First used by Koenraadt et al. (1992b) to detect benomyl resistance in
However, it is impossible to review the developing paradigm and not question how we implement these detection systems to provide the end-user, in this instance, the farmer, with the information necessary to make the appropriate management decision. The objective of this review is to briefly discuss the current fundamental approaches of nucleic acid based systems, and the currently known targets for the molecular detection of fungicide resistance. The paper concludes with the limitation of these techniques, the impact detection has had on the management of fungicide resistance, and future directions.
2. Nucleic acid based detection techniques
The molecular detection of fungicide resistance can be boiled down into three fundamental techniques: Hybridization, amplification, and sequencing. It is important to stress though, that most amplification technologies used today are also partly based on hybridization technology, and that all sequencing technology is based upon amplification. This article is not designed to review the preponderance of available techniques; for that information, the reader is encouraged to review the current literature, as new application technologies are produced every year. Instead, this article focuses on certain paradigms that have developed between laboratories for the detection of fungicide resistance, and to provide both structure and context as to where we are currently positioned.
Hybridization is one of the oldest molecular techniques: Sample DNA is denatured into single strands and allowed to anneal with a single-stranded probe labeled with some type of signal (radioactive isotopes, antibodies, enzymes or chemiluminescent compounds) to permit detection. Target DNA is bound to solid support (historically nitrocellulose then nylon, although today numerous substrates are available, including magnetic beads and polystyrene microspheres). Direct hybridization is the simplest assay for single nucleotide discrimination. For 15 to 20-base oligonucleotides, the approximate melting temperature for hybridization of a perfectly matched template compared to one with a single base mismatch can differ by several degrees (Ikuta et al. 1987)—a fact that can be exploited to create a variety of multiplex detection techniques, and discriminate within samples or between samples to a single nucleotide polymorphism.
Briefly, polymerase chain reaction (PCR) is the basis for all amplification-type reactions and involves the heating of the sample DNA for denaturing, followed by the annealing of the small, oligonucleotides that serve as primers for DNA polymerase, followed by the extension of the primers by a thermostable, DNA polymerase. Numerous books and laboratory manuals exist as references for PCR operation and optimization (Sambrook et al, 1989). PCR based detection of fungicide resistance depends upon the ability of the reaction to selectively amplify specific regions of DNA, and usually require several post-PCR steps, including agarose gel electrophoresis for either confirmation of amplicon presence or size, or restriction enzyme analysis (Lesniak et al. 2011; Fontaine et al. 2009; Quello et al. 2009; and reviewed by Ma and Michailides 2005). The development of new fluorescent techniques (LAMP, etc) has led to novel assay formats that greatly simplify the protocols used for the detection of specific nucleic acid sequences (Nurmi et al 2000) and allow for the detection of a specific PCR product in a homogeneous solution without the need to open the amplification tubes after PCR or gel electrophoresis (Tomlinson et al. 2012). In these techniques and their variations, PCR products are monitored as they are generated during the course of the reaction via one of two ways: By fluorescent or chemiluminescent dyes that bind to double-stranded DNA in a nonspecific fashion, or by fluorescence-labeled probes that bind to specific sequences. As a result, PCR amplification, amplicon detection and analysis are all achieved in a single reaction (Figure 1). If this is not enough detection power, multiple, sequence-specific probes with unique fluorescent reporters can be added to the reaction, allowing for additional, and simultaneous, determination of multiple products. Techniques such as this are ideally suited for the detection of fungicide resistance, particularly if multiple alleles are involved. Furthermore, the results can be read in real time as the PCR product accumulates or at the end of the thermal cycling protocol directly from the amplification wells. Although many scientists believe that the choice between real time or “standard” PCR (and gel electrophoresis) depends on whether a quantitative or qualitative assay is desired (Nurmi et al. 2000), the reality is that equipment expense and laboratory expertise limits most “applied” labs, resulting in a preponderance of scientifically dazzling techniques that may be used in a human clinical setting, or a plant pathology laboratory focused on basic science, but are rarely, if ever, subsequently tested using isolates from a field failure.
5. Hybrid technologies
Technologies such as Luminex Xmap powerfully combine hybridization and PCR to create a technique that is capable of discriminating and reporting up to 500 different reactions in a single reaction vessel in just a few seconds per sample (Dunbar 2005; Luminex 2011). The approximate melting temperature for 15 to 20-base oligonucleotides can differ by several degrees compared to a “perfectly matched” hybridization (Ikuta et al. 1987). By exploiting and combining this discriminatory hybridization temperature with PCR and microarrays systems and digital imaging, the user can screen up to several hundred thousands of DNA probes (either PCR products or synthetic oligonucleotides) per square centimeter of a solid matrix. Multiple readings per beadset provide built-in internal controls (Luminex 2011). For medically relevant human pathogens, whole genome arrays have been developed; it is hardly a stretch to imagine development of arrays for a few dozen alleles for important genes, or even genes important for fungicide resistance. Although financially out of reach for most labs, few could envision the sequencing of entire genomes for a few thousand dollars as we do today, and it is hopefully only a matter of time before microarrays to detect fungicide resistance in agriculturally important crops are widely available. Today, and certainly for the next few years, both cost and accessibility also remain obstacles to the development of such arrays. Within reason and immediate reach is a 96-well format that provides fast, simple, and highly reproducible analyses of up to 96 PCR products—which still translates into an assortment of alleles for a variety of fungicide resistance genes.
For most, smaller laboratories, a more realistic approach concerns the use of polymerase chain reaction coupled with cleaved amplified polymorphic sequences (PCR-CAPS). Restriction-fragment length polymorphisms due to small nucleotide polymorphisms (SNP) that co-segregate or are caused by fungicide resistance create or abolish restriction sites in PCR products, and can be exploited for detection of fungicide resistance through the careful selection of locus-specific oligonucleotide primers (Banno et al. 2008; Lesemann et al. 2007, Quello et al. 2009, Fontaine et al. 2009; others).
Assuming that a SNP is present and can be used, oligonucleotide primers with unique sequences are used to amplify a defined locus, followed by the use of a restriction enzyme that can discriminate between resistant and sensitive isolates (Figure 2). An alternative to PCR-CAPS is allele specific (AS-PCR), in which the mutation that confers resistance is used to design primers that specifically amplify the mutated allele, but not the wild-type one (Fontaine et al. 2009, Lesniak et al. 2011, others). This approach is more sensitive, and does not require a RFLP to detect resistance, but also does not detect any heteroplasmy or heterozygosity.
6. DNA sequencing
DNA sequencing, as performed for the last 30 years, has been done via the Sanger method and is the most commonly used sequencing technique available. Genome-sequencing efforts have resulted in technological advances in DNA sequencing and led to the improvement of longer sequencing length, done faster and with less expense. It has also permitted the rapid sequencing of isolates (in part or into total) that did not conform to expected genotype: phenotype relationships (Lesniak et al. 2011; Quello et al. 2010;Leroux et al. 1999, and many others).
Metzker (2009) provides an excellent review of ‘next generation sequencing’ technology, although the rapid pace of technology marches on. One of the newer sequencing technologies that have immediate application to the detection of fungicide resistance is pyrosequencing. DNA pyrosequencing, a method of sequencing by synthesis, was first introduced in 1996, and is faster and less expensive than traditional Sanger (dideoxy sequencing) DNA sequencing methodologies. Unlike the Sanger method, DNA pyrosequencing utilize a cascade of enzymatic reactions that yield detectable light proportional to incorporated nucleotides. As a result, pyrosequencing yields relatively short read lengths and limited amounts of sequence data per pathogen or microbe. However, with careful target selection and primer placement, DNA pyrosequencing has been used for genotyping, SNP detection, and identification of microbes (Petrosino et al. 2009). Most importantly, pyrosequencing has been used to detect point mutations in antimicrobial resistance genes as a means of molecular resistance testing, including antifungal resistance in clinically important fungi (Wiederhold et al. 2008).
Pyrosequencing offers comparable accuracy to conventional DNA sequencing via the Sanger method, but provides greater opportunity for large sample numbers to be processed in parallel. The reaction is performed in real-time, obviating the need for electrophoresis, labeled nucleotides and primers. This is a technique that can be multiplexed, which economically enables rapid and accurate screening of a large number of samples, however, the prohibitive cost of equipment [$200,000-$1million per machine (Metzker 2009)], and technical expertise limits the use of this technology to research universities and industry.
Finally, a review of the variety of molecular techniques used for diagnostic applications (and the constant development of ‘new’ techniques) demonstrates that no universal technique exists which is optimal for detection of nucleic acids. The choice of a particular technique is also dependent on the information required, the targets under consideration, and obviously, cost. Regardless of any given or “popular” technique, new techniques continue to be developed which involve new approaches to amplification, hybridization, formats, imaging, and labels.
7. Detection of fungicide resistance
Regardless of the techniques used, the primary targets of fungicide activity (and thus fungicide resistance) have remained remarkably constant, and include mitosis and cell division; sterol biosynthesis; respiration; nucleic acid synthesis; and signal transduction. The widespread use of fungicides has also resulted in resistance in non-target genes, namely drug transporters, which are included in this review due to the role they play in fungicide resistance. The mechanisms of fungicide resistance that have been identified to date, include: i) a mutation in the target site of the antimicrobial agent that reduces the binding of the fungicide; ii) overproduction of the gene that is the target of the fungicide; (iii) reduced uptake of the antimicrobial agent, and (iv) active efflux of the fungicide. Other mechanisms that may have roles in fungicide resistance (based upon host-pathogen interactions, or basic fungal and other microbe biology) include, the possible presence of an enzyme that inactivates the antimicrobial agent (e.g., pisatin-pisatin demethylase) or even mutations that result in the posttranscriptional or posttranslational modification of the target enzyme or other regulatory factor (Mann and Jenson, 2003), resulting in reduced binding of the antimicrobial. Resistance may also be caused by unrecognized mechanisms—a problem for scientists trying to understand mefenoxam, phosphorous acid, or dodine resistance, to name a few of the fungicides where resistance is known, but the primary mechanism of resistance has not yet been identified.
7.1. Mitosis and cell division: Beta-tubulin assembly inhibitors
Introduced in the 1960s, benzimidazoles were the first penetrant fungicides. Compared to their predecessors, the carbamates, dithiocarbarmates and pthalimides, they were a revolutionary change in fungicides, in that they were noncontact, and extremely effective at low rates. First introduced as benomyl (other MBC fungicides include thiabendazole, and thiophanate-methyl, to name a few), once inside the plant it is metabolized to form methyl benidimidazole carbamate (MBC), which inhibits fungal mitosis via binding to tubulin, the subunit of microtubules essential to forming the mitotic spindle (Ma and Michailides, 2005).
As one of the first noncontact fungicides, it is not surprising that it was one of the first instances of resistance reported, to powdery mildew in greenhouse cucumbers (Schroeder et al. 1969). Since that time, resistance to the benzimidazole class of fungicides has been detected in many fungal species (Ma and Michelides, 2005). Resistance is correlated with point mutations in the β -tubulin gene, with different mutations resulting in altered amino acid changes at the benzimidazole-binding site. These various mutations at different codon sites also result in different levels of resistance: In
PCR-CAPS was used to determine thiophanate-methyl resistance
Detection of specific types of benzimidazole resistance also identifies any negative cross-resistance with diethofencarb (Leroux et al. 1999). The phenylcarbamate diethofencarb was introduced in 1984, and has a similar mode of action to the MBC class of fungicides. In fact, single base pair mutations in codons 198 and 200 result in a readily detectable, negative cross-resistance to diethofencarb (Faretra and Pollastro, 1991; Yarden and Katan, 1993). Negative cross-resistance (NCR) occurs when a novel allele that confers resistance to one toxic chemical results in hyper-sensitivity to another. This mutation therefore results in efficacy to benzimidazole-resistant isolates that possess that allele, but not wild-type isolates. In
8. Signal transduction: Dicarboximides and phenylpyrroles
The dicarboximides are composed of three major products: Iprodione, vinclozolin, and procymidone. The introduction of this class of fungicides coincided with the failure of the benzimidazoles in control of Botrytis in grape. As with benzimidizoles, resistance developed rapidly, due to a combination of concurrent applications of this class without rotation or tank-mixing with other products, coupled with a limited understanding of the process of fungicide resistance. This class of fungicides was primarily used for the control
The molecular mechanisms of dicarboximide resistance involve two separate signal transduction pathways: The two-component histidine kinase and mitogen-activated protein (MAP) kinase cascades. Both MAP kinase and two-component histidine kinase are involved with regulating a diversity of cellular responses including differentiation, cell division, gene expression, heat shock and osmotic response. The first molecular mechanism of dicarboximide resistance was identified in
Studies by Leroux et al. (1999) in
Similar observations regarding the complexity of resistance profiles were observed in
1992; Faretra and Pollastro, 1993; Lyr, 1995). Instead, only moderately resistant, osmotically-stable strains were recovered from the field, and these field isolates of
Many fungi accumulate glycerol to increase osmotic pressure to contend with osmotic stress, or for pathogenicity. Studies done by Fujimura et al., (2000) in
8.1. Sterol biosynthesis inhibitors
This group of fungicides exploits one of, if not the most important mode of action for both antifungals in medicine and fungicides in agriculture. The sterol biosynthesis inhibitor (SBI) fungicides inhibit a precursor of ergosterol that is essential for the development of the fungal membrane (Brent, 1995). These fungicides can be classified based upon their target sites in sterol biosynthesis, with inhibitors of squalene epoxidase (e.g. naftifine, terbinafine, tolnaftate) primarily used for mammalian mycoses. The remaining classes are used for agricultural purposes. ‘Amines’ or ‘morpholines’ (e.g. fenpropidine, piperalin, spiroxamine, tridemorph) act as inhibitors of sterol ∆14-reductase or ∆8->∆7-isomerase, and target the products from the
DMIs were introduced for plant disease management in the 1970s, with resistance and reduced efficacy reported soon after (Brent, 1995). Due to both agricultural and medical importance, the molecular mechanisms of SBI resistance have been highly studied and include (i) mutations in 14-alpha-demethylase (CYP51) structural gene (Delye et al. 1997; 1998; Canas-Gutierrez et al. 2009, and others) and ERG27 gene (Albertini and Leroux, 2004; Fraaije et al. 2007); (ii) overexpression of the CYP51 gene, leading to increased production of the target enzyme (Cools et al. 2012; Luo et al. 2008; Ma et al. 2006; Schnabel and Jones, 2001; Hamamoto et al. 2000), and (iii) overexpression of the ATP-binding cassette (ABC) transporters (Zwiers et al. 2002; Hamamoto et al. 2000; Nakaune et al. 1998) which will be addressed later in the chapter. Several studies, at least in the laboratory, have demonstrated that multiple mechanisms contribute to the variation in azole susceptibility (Stergiopoulis et al. 2003; Zwiers et al. 2002), and genetic analysis of progeny from a cross between
Mutations in the 14-alpha-demethylase (
A second mechanism of DMI resistance involves overexpression of the
A final mechanism of DMI resistance relies upon “drug” transporters, trans-membrane proteins located in the plasma membranes that utilize ATP to translocate compounds, including toxins, out of the cell, preventing the accumulation of these products to toxic levels, as has been shown for
Although fungicide resistance baselines and thresholds have been previously established in many agricultural systems, the primary stumbling block to the rapid identification of DMI fungicide resistance for most fungi is the nature of its quantitative resistance (Koller et al. 1991; Schnabel and Jones, 2001; Ishii, 2009). Unlike qualitative resistance that results from a single gene mutation (e.g.,
8.2. The respiration inhibitors
Respiration is an obvious target for fungicides. The oldest synthetic fungicides still used today include dithiocarbamates (e.g., mancozeb, thiram, ziram) or pthalimide derivatives (e.g., captan), and prevent plant disease by the inhibition of spore germination, and subsequent germ tube elongation. To date, there have been no credible reports of resistance to these older fungicides. Furthermore, older synthetic multi-site fungicides are effective against a wide range of plant-pathogenic fungi, and Chromista. These multisite inhibitors are thio-reactant with those enzymes involved in respiration (Lyr, 1977); Other inhibitors of respiration work at complex II at the succinate dehydrogenase gene, complex III, the cytochrome bc1 (ubiquinol oxidase) at Qo site, or cytochrome bc1 (ubiquinol oxidase) at Qo site; or complex V, where fungicides like fluazinam actually work by uncoupling electron transport and ADP phosphorylation of oxidative phosphorylation (FRAC, 2009). As such, this target is essential to aerobic eukaryotes, and present targets for disruption. The most recently developed group of respiration inhibitors targets mitochondrial complex III (the cytochrome bc1 complex), and targets the outer quinol-oxidizing pocket (Qo site), and complex II at the succinate dehydrogenase gene, which are the areas of most recent and active interest due to their recent release, the nature of fungicide resistance, and potential ease of detection.
8.3. QoI—The quinone outside inhibitors
Fungicides that inhibit the cytochrome bc1 enzyme complex (complex III) at the Qo site (Qo inhibitors, QoIs) were first introduced to the market in 1996. QoI resistance has now been reported in more than 20 pathogens, including the Chromista pathogens, downy mildew of grape and cucurbit, and the fungi that cause apple scab, wheat powdery mildew and Septoria leaf blotch, to name but a few. Resistance has been reported in all major continents: Asia, Australia, Europe, North America, and South America (FRAC 2006; Wilson and Wicks, 2011). The majority of the reports associate the point mutation that results in a change from glutamate to alanine at codon 143 (G143A), followed by the resistance that results from a transition from phenylalanine to leucine at position 129 (F129L) (Pasche et al. 2005; Sierotzki et al. 2007); the least commonly observed mutation involves a change from glycine to arginine at position 137 (G137R) (Sierotzki et al. 2007), and of course, unknown causes (Lesniak et al. 2011). These easily identified mutations allow for the rapid detection for the potential of QoI-resistance in a variety of fungi and Chromista. Furthermore, the degree of resistance is much greater in the G143A allele (referred to as high resistance), and has consistently resulted in a significant reduction in disease control, as compared to resistance associated by F129L and G137R which results in more moderate or partial resistance, and some degree of control at highest rates of fungicide.
A more recent study by Lesniak et al. (2011), found ninety-eight percent of QoI-resistant/shifted isolates screened in Michigan were associated with G143A, consistent with other phytopathogenic fungi resistant to this class of fungicides (Ishii et al., 2009; Ishii et al. 2007). Sequencing the entire
With QoI resistance, allele specific PCR (Lesniak et al. 2011 and many others) and restriction enzyme digest of the amplicon (Leroux et al. 2010 and many others) are both used to detect the presence of the allele. Work by Fontaine et al. (2009), found that the QoI-resistant allele could not be detected after
Succinate dehydrogenase inhibitor (SDHI) fungicides include “first generation” SDHIs, like flutolanil, carboxin, followed by later (and improved) “second generation” compounds, including boscalid, and even “third generation” products like penthiopyrad, and fluopyram. This class of compounds targets and binds to the ubiquinone-binding site (Q-site) of the mitochondrial complex II, specifically the succinate dehydrogenase (SDH) complex in the respiratory chain also referred to as complex II or succinate:ubiquinone oxidoreductase (SQR), inhibiting fungal respiration by blocking electron transport [Kuhn, 1984; reviewed by Avenot and Michailides (2010), including a recent list of resistant organisms and corresponding mutations]. There is no evidence of cross-resistance with other similarly acting chemical classes such as QoI fungicides (which also affect energy production and electron transport) due to their unique mode of action and target site. The primary target of the SDHI fungicides is the SDH complex that consists of four subunits: a flavoprotein (Fp) subunit (SdhA), an iron-sulfur protein (Ip) subunit (SdhB), and two membrane-anchored protein subunits (SdhC and SdhD). Mutations conferring resistance have been found in the SDHB (Avenot et al 2008) and SDHC (Ito et al. 2004) and SDHD subunits (Avenot et al. 2009).
The first widely used SDHI fungicide, carboxin, was used in the late 1960s, and its applications were limited due to its primary activity against basidiomycete pathogens, namely rusts,
Field and laboratory mutants resistant to carboxin and boscalid have been reported in a variety of fungi and cropping systems (For a recent review see Avenot and Michailides 2010). Carboxin and other SDHI fungicide resistances are described as monogenic, and have been identified in both field and laboratory. Sequence analysis of the gene encoding the target protein, the succinate dehydrogenase enzyme (SDHB), revealed that single or double point mutations in the highly conserved regions of gene were associated with resistance. Different levels of resistance are associated with mutations in different alleles: In
Despite the elucidation of the molecular mechanisms of resistance, mycelial growth assay in liquid medium in microtiter plates were developed to monitor fungicide resistance, in
8.5. MDR-efflux pumps and resistance
All living organisms, eukaryote and prokaryotic, are exposed to both food and toxins in their natural environments. To quote Pao (1998), “Transport systems allow the uptake of essential nutrients and ions, excretion of end products of metabolism and deleterious substances, and communication between cells and the environment.” Some of these deleterious substances may be antibiotics produced by bacteria and actinomycetes, antifungals [e.g., strobilurin A produced by
In the human pathogen
Detection of this type of fungicide resistance has proven to be more difficult, or at least less published, in plant pathogens. Numerous reports exist about multiple fungicide resistances in plant pathogens (Leroux et al. 1997, Nakaune et al. 1998; Leroux et al. 1999; Kretchmer et al. 2011; Chapman et al. 2011). It is important to stress that not all of these multiple fungicide resistances are due to MDR, but in fact, are due to other mechanisms (see the section on Dicarboximides for elucidation of one such mechanism) including segregation of separate, multiple resistances (Chapman et al. 2011). One of the first studies (Leroux et al. 1999) that screened multiple fungicide resistances in
The role of MDR in fungicide resistance was further strengthened by work by Kretschmer et al. (2011) who found that fungicide resistant field isolates from France and Germany exhibited three distinct MDR phenotypes of increased fungicide efflux activity and overexpression of efflux transporter genes. In this study, MDR1 strains were found to possess mutations in the transcription factor,
Although the role of MDR genes in fungicide resistance is clear in some pathogens, rapid detection of fungicide resistance due to MDR is not. Some of these difficulties reside in the unclear and multiple mechanisms of DMI and other fungicide resistances discussed above, others in the role and regulation of MDR. To date, most differences identified in fungicide resistance where MDR is implicated have been found to be due to overexpression of ABC transporter genes. Most important to stress is the lack of correlation between expression level specific ABC transporter gene with fungicide resistance, suggesting that multiple transporters may be involved (at least in DMI resistance) or that other mechanisms in addition to upstream transcription factors, have not yet been identified (Cools et al. 2007; Leroux et al. 2011).
Fungicide resistance can be conferred by a variety of mechanisms, and plant pathologists need to recognize that multiple genes may be necessary for this resistance, and that single genes, although easily scored or detected by molecular means, may not be sufficient for determination of resistance. Central to these studies is the recognition of the strengths and the limitations of molecular detection, and the importance of phenotypic versus genotypic resistance. This requires that we recognize that the phenotype of fungicide resistance consists (in many instances) of “major” genes, “minor” genes, the interactions between these genes (epistasis) and the interactions between genes and the environment, and that many of the known mechanisms conferring quantitative fungicide resistance utilize alternative metabolic pathways, exclusion or efflux of fungicides, and hitherto unknown mechanisms (Brent and Holleman 1998; Leroux et al. 1999; Lesniak et al. 2011).
The detection of single gene targets is only the beginning, and understanding the mechanism of resistance does not provide a blueprint as to how to manage the crop in the absence of the fungicide lost. Previous studies labored under an assumption that “a timely detection of resistance levels in populations of phytopathogenic fungi in a field would help growers make proper decisions on resistance management programs to control plant diseases” (Ma and Micheilides 2005). It certainly doesn’t hurt, but few instances are available where this knowledge has been translated for use to growers and resulted in in-season changes of management beyond cessation of use of the fungicide in question. To date, most resistance management consists of abandoning the fungicide that has failed, to use others (Chapman et al. (2011); Lesniak et al. (2011), Avenot et al., others); Chapman et al. (2011) is one of the few instances where fungicide resistance detection was used many years later to confirm that a fungicide could be used with some degree of successful certainty. This was determined by mycelial growth assay as no molecular detection methods currently exist to screen for dodine resistance.
Fungicide sensitivity testing using mycelial growth or germination inhibition (in petri dishes or microtitre plates) lacks the excitement and appeal of the many different molecular approaches to detect fungicide resistance. It is certainly not as fast as any molecular test, although microtiter-based assays combined with Alamar blue (AB), or resazurin provide quantifiable and early detection within days, for fast growing pathogens like
This is not to say that molecular detection of fungicide resistance is without merit. One of, if not the most critical challenges facing applied plant pathologists is the need for the early detection of fungicide resistance in a population. Molecular methods can be used to powerfully detect and monitor the emergence of resistance in those instances where detection is possible, to a degree that phenotypic assays cannot achieve. Unfortunately, there are few studies where this has been done, and most research ends with a proof of concept, and not the implementation of the developed technique to better manage fungicide resistance. Currently, there are few studies monitoring sensitivity and early detection through the use of sentinel plants coupled with molecular detection in those instances where the mechanism can be detected, which could provide powerful information in an early warning system to anticipate the emergence of fungicide resistance in a population and prevent its occurrence. One problem with this approach is that most models for the detection of fungicide resistance emergence should assume an initial resistance mutation frequency from anywhere from as high as 10-4 (Zwiers et al. 2002) to as low as 10-8 (Zheng et al. 2000) based upon laboratory studies.
The developing paradigm that has emerged has been the generation of mutants in the laboratory, followed by their isolation from the field in some instances (but not all), followed by phenotypic screen, and identification of mechanism (Albertini et al. 1999 to Zwiers 2002, and others.) Genotypic screens have been developed, but are rarely evaluated for efficacy and accuracy over time, let alone predictive ability or utility. Furthermore, these developments have still not helped the farmer, nor provided him or her with the information necessary to make the appropriate in-season management decision. The question that remains is if we should be willing to shift the paradigm and use the best technique to adequately address the problem of fungicide failure in the field. As we enter a post-genome period, the technology is available for the detection of even single nucleotide polymorphisms. Whether it is available to rapidly detect fungicide resistance in plant pathogens in a way that is useful for growers remains to be seen.
I would like to thank Drs. Rick Latin and Kiersten Wise for our numerous and ongoing discussions on fungicide resistance, and for their review of this manuscript.
- Due to issues of length, brevity and complexity, this review will only deal with fungicides that are for the control of true fungi, and not fungicides for the management of Chromista.