Identifying and Characterizing Yellow Rust Effectors
Info: 8365 words (33 pages) Dissertation
Published: 16th Dec 2019
1. Yellow Rust of Wheat
Despite being a major staple crop worldwide, wheat remains susceptible to biotic limitations that have a devastating impact on production. One of the major biotic limitations to the growth of wheat is yellow rust, caused by the fungus Puccinia striiformis f. sp. tritici (PST). Up to 70% yield loss can be observed at times in all major wheat producing areas, depending on the cultivars present (Chen et al., 2005). In recent years, new PST races have emerged that are adapted to warmer temperatures, have expanded virulence profiles, and are more aggressive than previously characterized races leading to wide scale losses (Hovmoller et al., 2010). For example, two new atypical races of PST called Warrior and Kranich were detected on both wheat and triticale in 2011 (Sørensen et al., 2014). In comparison to the typical isolates present in Europe at the time, both Warrior and Kranich caused more disease on wheat lines that previously provided long-term effective adult plant resistance (Sørensen et al., 2014).
To control yellow rust disease, farmers rely heavily on fungicides that are deployed to keep the pathogen in check. However, chemical solutions are often costly and can be detrimental to the environment. In addition, breeders deploy resistance genes into the wheat germplasm in attempt to keep yellow rust infection under control. However, PST races are capable of overcoming these resistances and so it is important to study the genetic determinants of pathogenicity, in order to exploit this knowledge to develop better informed management and breeding strategies.
2. General Features of Plant immunity
At the molecular level, pathogens such as stripe rust secrete proteins called effectors into the apoplast or symplast of the plant (Win et al., 2012). If not detected by the host plant, these proteins can alter plant function to encourage disease development through a process known as effector triggered susceptibility (ETS) (Win et al., 2012). Conversely, resistance genes (R genes) in plants encode intracellular receptor proteins (R proteins) that can detect symplastic effectors. This detection can either be direct or indirect, and requires compatibility in binding between the plant receptor and the effector or its target. This in turn triggers the plants second line of defence, which is known as effector triggered immunity (ETI) (Win et al., 2012). This robust immune response usually leads to localized cell death, reactive oxidative species burst, and callose deposition (Dodds & Rathjen 2010). When a plant has an R protein that can detect effectors or their interaction with specific host targets, the pathogen is said to be avirulent due to the success of ETI (Win et al., 2012). Conversely, when a pathogen’s effector evades detection by plant intracellular R proteins, the pathogen is termed virulent, and the plant is called a compatible host (Win et al., 2012).
3. Rust/Fungal infection on host plants
3.1 Infection of Rust Fungi on Plant Hosts
Rust fungi encompass multiple plant pathogenic species within the order Pucciniales, and share common features of infection. Rust fungi infect hosts during the asexual phase of the pathogen life cycle and produce specialized infection structures to carry out this process. Dikaryotic (n+n) urediniospores produce a germ tube around 3 hours post inoculation (hpi), which subsequently enters wheat leaf tissue via the stoma around 6-8 hpi (Chen et al. 2014). Primary infection hyphae emerge around 12-18 hpi and grow within the apoplast towards plant mesophyll cells. Once a mesophyll cell is contacted, a haustorial mother cell produces a slender neck which invaginates the host cell plasma membrane and produces a specialized balloon shaped structure called the haustorium (Chen et al. 2014). The fungal haustorium stays in close contact with the host cytoplasm, but remains separated by the extra-haustorial matrix and the extra-haustorial membrane, thus producing a dynamic host-pathogen interface. The haustorium not only draws nutrients from host cells, but also secretes effector proteins required for infection into the host cytoplasm (Fig 1a). Infection hyphae within the apoplast may also secrete effectors that must pass through the host cell wall and plasma membrane to reach the host cytoplasm (Fig 1b).
Fig. 1. Effectors Cross Multiple Different Biological Interfaces To Enter The Host Cytoplasm. Petre & Kamoun 2014b.
3.2 Basic Fungal Effector Components
As a result of the haustorium and invasive hyphae remaining outside the host cytoplasm, fungal effector proteins must pass through multiple membranes in order to translocate from the fungus into the host plant cell. The current paradigm suggests fungal effectors contain three main components: a general secretory signal peptide, a translocation domain located at the N terminus of the protein, and the C-terminal region (Figure 2). The signal peptide is required for the effector protein to exit the fungus, and enter either the extrahaustorial matrix or the apoplast. Translocation domains, on the other hand, are thought to play a role in transporting effector proteins across the extrahaustorial matrix or plant cell wall and plasma membrane into the host cytoplasm. In oomycetes, these translocation domains contain conserved motifs such as the RXLR amino acid sequence (Jiang et al., 2008). These conserved domains are often used as input to search for other oomycete effectors. However, fungal effectors do not have a consensus host cell entry motif. Thus, effector mining in fungi is largely based on predicted N-terminal signal peptides.
Figure 2. Fungal and Oomycete effector domains required for host cell entry. Petre & Kamoun 2014b.
3.3 Previously Described Rust Effectors
Only a handful of effectors from rust fungi have been previously characterized (Table 1). This is most likely due to the fact rust fungi are obligate biotrophs and cannot be cultured in the lab (Petre et al., 2014a). Further, both pathogen and host are generally not amenable to molecular genetics (Petre et al., 2014a). For example, yellow rust cannot be transformed in the lab, nor can cereal hosts be transformed via Agrobacterium mediated transient expression.
The majority of rust effectors that have been identified to date are from the well-studied flax rust pathosystem. This system has the advantage of the host responding well to Agrobacterium mediated transient expression (Duplessis et al., 2012). Properties of these effectors provide insight into the identification of additional effectors from the rust fungi.
3.3.1 Rust effectors are translocated into the host cytoplasm
Most rust effectors have been identified on the basis of ability to cause HR in hosts containing cognate R genes (Table 1). This provides indirect evidence that these proteins are entering the host cell. Agrobacterium mediated transient expression of AvrL567, AvrM, AvrP4, and AvrP123 in flax induce an R gene dependent cell death response. Since all corresponding R genes are cytoplasmic, this implies recognition occurs inside the host plant cell, and that these Avrs are being translocated into the host cytoplasm during infection (Dodds et al., 2004, Catanzariti et al., 2006).
The first direct evidence of effector proteins translocating into the host cytoplasm comes from immunolocalization studies of RTP1 from the bean rust fungus Uromyces fabae. Using this method, RTP1 was found to accumulate in the extra-haustorial matrix, and was found in the host plant cytoplasm at later stages of haustorial development (Kemen et al., 2005). Also using immunolocalization, Rafiqi et al. (2010) demonstrate AvrM is directly trafficked from haustoria to plant cells during infection.
3.3.2 Rust effectors are highly polymorphic and often interact directly with their cognate R proteins
The pioneering work done on AvrL567 and AvrM from flax rust has established these Avrs as models for effector recognition by immune receptors. Both effectors are delivered into the host plant cytoplasm and are recognized by specific immune receptors via a direct interaction (Dodds et al., 2004, Catanzariti et al., 2006).
Dodds et al., (2006) found 12 sequence variants of AvrL567 from six rust strains. The six variants that were shown to be avirulent in planta were co-expressed in a Yeast two-hyrbid system to test their interaction specificity to the associated R genes L5, L6, and L7. AvrL567 variants A, B, F, J, and L are recognized by both L5 and L6, whereas AvrL567-D is L6 specific. The alleles found to be virulent in planta did not associate with either L6 or L7 in yeast. Similarly, Cantanzariti et al. (2010) found avirulent alleles of AvrM directly interact with the associated M resistance protein in a yeast two hybrid assay. These results suggest recognition is based on a direct R-Avr protein interaction. The authors posit recognition by direct interaction may be overcome through sequence diversification, as seen in AvrL567 and AvrM, rather than loss of function (Dodds et al., 2006).
Both AvrM and AvrL567 are also characterized by high levels of polymorphism as a result of diversifying selection. For example, there are 35 polymorphic positions in the 12 sequence variants of AvrL567, even though this gene is only 127 amino acids in length. Similarly, AvrM variants have 14 polymorphic positions including deletions, showing elevated sequence variation in comparison to the flanking sequence (Catanzariti et al., 2006).
It is often suggested that highly polymorphic effector genes are a result of an arms race between these effectors are their interacting receptors. Indeed, structural analysis of AvrL567 alleles A and D revealed polymorphisms in residues that interact with the associated R protein (Wang et al., 2007).
Table 1. Previously Characterized Rust Effectors and Their Avirulence Property
|Effector Protein||Rust Fungus||Avirulence property|
|AvrM||Melampsora lini (Flax Rust)||Yes|
|RTP1||Uromyces fabae (Bean Rust)||Not Determined|
|PGTAUSPE 10-1||Puccinia graminis (Stem Rust)||Yes|
4. Identification of Candidate Effectors
4.1 Positional Cloning
Most of the ground-breaking work on rust effectors has come from studies on the flax rust fungus, Melampsora lini. Indeed, the first rust effectors identified came from studying the M. lini – flax pathosystem. In the absence of sophisticated in silico technology, these effectors, for example AvrL567, were identified using traditional map based cloning combined with expressed sequence tag libraries from infected materials as probes (Dodds et. al, 2004).
Map based cloning involves following a phenotype of interest in a breeding population and looking for linkage to established genomic markers. AvrL567 was identified by crossing flax rust strain H (L5, L6, L7 avirulent) with strain C (L5, L6, and L7 virulent) to produce the hybrid CH5 strain. This strain was selfed, producing an F2 mapping population (Dodds et. al, 2004).
A subset of a clones from a cDNA library enriched for transcripts present in flax leaves during infection with the avirulent H strain were used as probes. These cDNA clones were used as DNA probes to detect RFLPs segregating in the flax rust mapping family. One cDNA probe called IU2F2 detected RFLPs that cosegregated with the avirulence locus corresponding to the L5, L6, and L7 resistance genes in flax. Clones of this locus were isolated, and were narrowed down to a single gene that caused HR when transiently expressed in flax lines containing L5, L6, or L7, confirming its identity as AvrL567 (Dodds et. al, 2004).
The flax rust system has been studied in depth since the 1970’s when Flor established the gene-for-gene hypothesis defining interplay between host resistance (R) and rust avirulence (Avr) genes (Duplessis et al., 2012). Therefore, this system has had much more time for the development of good genetic stocks, and a well-characterized mapping population with families segregating for multiple Avr loci (Duplessis et al., 2012). Unfortunately, in other systems lacking these components, map based cloning remains quite labour intensive and time consuming (Stergiopoulos & de Wit 2009). Additionally, establishing a breeding population for map based cloning has proven to be difficult for rust species with alternate hosts during the sexual cycle, including Puccinia striiformis. Fortunately, advances in next generation sequencing over the past few years have paved the way for a new era in effector discovery.
4.2Genome wide effector mining using fungal effector protein features
Previously, genomic resources for identifying rust effectors has been limited to transcriptomic studies of isolated haustoria. Thus, other stages in the infection cycle have been ignored, suggesting a gap in knowledge in the full effector gene repertoire (Duplessis et al., 2012). In the new genomics era, the release of full sequenced genomes of rust fungi has revolutionised effector discovery. High throughput computational methods of mining candidate effectors from full genomes has proven to be a valuable resource (Duplessis et al., 2012). A characteristic profile of plant pathogen effectors has emerged over the past few years (Petre et al., 2014a). The following section describes common features typically used to mine effector candidates in genome wide studies.
4.2.1 Signal peptides and Transmembrane Domains
In order for effectors to target host components and modulate plant immunity, they must first be secreted from the fungal pathogen. Thus, a common first step in mining fungal proteomes for effectors is identifying proteins which have signal peptides. These N terminal peptides, usually 20-30 amino acids in length, target proteins to the secretory pathway (Sonah et al., 2016). Generally, signal peptides are positively charged at the N-terminus and are subsequently followed by a hydrophobic region and cleavage site at the C terminus (Sonah et al., 2016). Programs such as SignalP predict signal peptide cleavage sites in proteins with high accuracy using sophisticated analytical algorithms including several artificial neural networks (Petersen et al., 2011).
Not all proteins with signal peptides are secreted outside of the fungus. Signal peptides may also contain hydrophobic segments, usually longer than those in secretory proteins, that target proteins to a membrane (Sonah et al., 2016). Therefore, in order to delimit secreted proteins from transmembrane (TM) proteins, it is necessary to identify TM domains within the secretome. TMHMM, a commonly used program to identify transmembrane domains, uses a hidden Markov model to predict TM proteins, and has been used in many effector prediction pipelines (Cantu et al., 2013, Saunders et al., 2012).
4.2.2 Small and Cysteine Rich Proteins
Effectors that remain in the apoplast, and some that pass through the apoplast and into the host cytoplasm, often contain multiple cysteine residues. These effectors are deemed small cysteine rich proteins, or SCRs. These cysteine residues are involved in disulphide bridge formation that likely contribute to protein stability in the protease rich environment of the plant apoplast. For example, Avr4 and Avr9, effectors from the tomato leaf mould pathogen Cladosporum fulvum, contain disulphide bonds between cysteine residues that are required for stability and activity (Van Den Hooven et al., 2001, Van Den Burg et al., 2003) . For cytoplasmic effectors, disulphide-bridge formation may contribute to proper tertiary folding required for the protein to be taken up by the host (Stergiopoulos & de Wit 2009).
4.2.3 Effectors Often Occupy Unstable Regions of the Genome
Previous analyses of fungal and oomycete pathogen genomes have revealed the presence of expanded genomes partially due to transposon invasions and repetitive elements (Raffaele & Kamoun 2012). Rust fungi are no exception, with the poplar rust and stem rust genomes comprising of nearly 50% repeats and transposable elements (Duplessis et al., 2014). Such unstable repeat rich regions are often enriched with effector genes (Raffaele & Kamoun 2012).
For example, the 49.3% of Phytophora infestans secreted proteins, or secretome, are located within repeat rich, gene sparse regions despite the fact secreted proteins represent only 22.1% of total genes (Raffaele et al., 2010). Further, analysis of the phytopathogenic ascomycete Leptosphaeria maculans genome revealed AT-rich blocks that are gene poor and transposable element rich. These particular regions are enriched in genes likely to have a role in pathogeneicity (Rouxel et al., 2011). 20% of genes located in these AT rich blocks encode small secreted prtoteins (SSPs), most of which have features indicative of effectors, whereas only 4.2% of genes located in GC blocks encode SSPs, most of which lack features of known effectors of L. maculans (Rouxel et al., 2011).
These studies suggest genomic plasticity plays a large role in the development and diversification of virulence traits and effector repertoires (Raffaele & Kamoun 2012). Thus, location within repeat regions of the genome can be used as a requirement to rank the likelihood of a fungal secreted protein being an effector.
4.2.4 Other Features of Previously Described Fungal Effectors
Since only few rust effectors have been characterized, no general features have been identified that may be used in the computational prediction of other effectors from fungi in the Pucciniales. Despite this, rust secretomes may be mined for candidate effectors by searching for other features of known effectors from filamentous pathogens in general. Other than possessing a signal peptide, multiple cysteine residues, and residing in repeat rich genomic regions, such features include the presence of internal repeats, in planta induced genes, similarity to haustorial proteins, and the absence of PFAM domains, except for those associated with pathogenicity. For example, Saunders et al. (2012) designed an in silico pipeline to identify the putative effector repertoire from the genomes of poplar leaf rust and wheat stem rust. Using the aforementioned criterion, Markov clustering and hierarchical clustering were used to rank protein families of these two rust pathogens for their likelihood of being effectors.
4.3 Comparative genomics
In combination with general candidate effector mining, comparative genomics has emerged as a powerful tool for effector identification. This approach involves comparing the genomes of multiple sequenced isolates with distinct virulence profiles. Non synonymous SNPs, and other changes in protein coding genes between sequenced isolates may reveal effector genes required for (a)virulence on particular wheat lines and not others.
4.3.1 Integration of comparative genomics and transcriptomics
For example, Cantu et al. (2013) utilized comparative genomics to identify five Pst effector candidates within the 2,999 predicted secreted proteins that were highly expressed in haustoria and are polymorphic between two UK isolates that differ in virulence to only two wheat varieties (YrRob and YrSol).
After genome sequencing of the isolates, non-synonymous SNPs were called, and RNAseq data identified transcripts specifically enriched in haustoria. Proteins with a high likelihood as candidate effectors were determined by a scoring system, which involved annotating and ranking proteins based on known effector features. One candidate effector from this analysis, PST130_05023, has four amino acid substitutions between four sequenced isolates (UK isolates: PST-87/7, PST-08/21, US isolates: PST-21, PST-43, PST-130). The one specific substitution between the two UK isolates may explain the differential virulence of these two isolates seen on YrRob and YrSol. This gene, along with the other four candidates, are now of high priority for functional validation as virulence/avirulence factors in the wheat varieites Robigus and Solstice.
Furthermore, following a field pathogenomics study of 2013 UK isolates of Pst, Hubbard et al. (2015) were able to identify polymorphic and differentially expressed effector candidates which could be linked to the differential virulence profiles of PST 2013 field isolates (Hubbard et al., 2015). Thirty-nine PST field isolates collected in the UK from 2013 were sequenced and aligned to the PST-130 genome. These field isolates were separated into four distinct population clusters using multivariate discriminant analysis of principal components (DAPC). Non-synonymous SNPs where the amino acid residue was conserved among all members of a single population cluster, but differed from the amino acid encoded by all members of at least one other population cluster were identified. Next, proteins that had detectable secretion signals, displayed features typical of characterized effector proteins, and that were significantly down or up regulated in comparison to genes in other population clusters were detected. These analyses revealed 10 upregulated and 9 down regulated genes among the most highly ranked PST effector candidates from a previous study (Hubbard et al., 2015). One effector candidate in particular, PST130_08031, was specifically down-regulated by isolates in cluster III, and had two amino acid substitutions that were specific among cluster I isolates.
4.3.2 Comparative Genomics of Spontaneous Mutants
Although comparing the genomes of field isolates with different virulence profiles has proven useful in identifying candidate effectors, one challenge regarding this approach is not knowing which polymorphisms are associated with changes in virulence, rather than divergent evolutionary origins of the isolates. This can be a problem even in closely related isolates. Further, comparing isolates with multiple differences in virulence profiles makes it difficult to associate polymorphisms with the ability to infect specific wheat varieties.
One way to mitigate this problem is to isolate a spontaneous gain of virulence mutant from an avirulent strain. Since the isolates share a common evolutionary background, any changes seen in protein coding regions may be associated with a single resistance gene, and are less likely to be a result of evolutionary divergence. Chen et al. (2017) used this method to identify the first confirmed avirulence effector from Puccinia graminis f. sp. tritici (Pgt), AvrSr50. By sequencing a spontaneous mutant of Pgt virulent to Sr50, the authors were able to identify a 2.5Mbp loss of heterozygosity event. Within this region, Chen et al. (2017) found 24 genes annotated as haustorially secreted proteins. Allelic variants of these genes missing in the spontaneous gain of virulence mutant, but present in the avirulent progenitor were candidates of AvrSr50. One of these candidates, when co-infiltrated in N. benthamiana via Agrobacterium mediated transient expression induced HR, confirming its identity as AvrSr50. To date, this is the first example of functional validation of a candidate effector from rust identified via genome wide comparative genomics, uncovering the potential of this approach in identifying effectors from rust fungi.
5.1 Functional Validation of Candidate Effectors: Avirulence
Recognition of avirulent fungal effectors by their associated R protein in host plants leads to a hypersensitive response (HR) whereby localized cell death prevents the spread of biotrophic pathogens (Win et al., 2012). Such effectors are deemed avirulent. One of the most direct ways to validate candidate proteins as effectors is characterization of avirulence function. However, although large numbers of candidate effectors from PST have been identified, none of them have been confirmed as avirulence factors in the lab.
Unlike other rust hosts such as flax, cereal leaves cannot be transformed via Agrobacterium mediated transient expression. Therefore, this traditional method of high-throughput functional analysis of effectors in dicot plants cannot be used for yellow rust. To make matters worse, only one resistance gene for yellow rust, YR10, has been cloned (Liu et al., 2014). Co-delivery of candidate Avrs with cloned R genes in N. Benthamiana via Agrobacterium is also not possible. Additionally, there is currently no method for culturing and transforming yellow rust. Alternative systems have been developed in attempt to heterlogously express candidate effectors in wheat to study function in planta. The following section describes multiple methods for assessing avirulence function of candidate effectors, each of which have pros and cons.
5.1.1 Bacterial Delivery
Bacterial pathogens deliver effector proteins directly into the host cytoplasm via a type III secretion system (T3SS) whereby a specialized needle passes through host membranes to release (a)virulence factors. The T3SS approach of delivering candidate rust effectors in planta has high potential for high-throughput screening. This is mostly due to the well-studied nature of this system, and the ease of culturing bacteria in the lab (Upadhyaya et al., 2014).
Sohn et al. (2007) were able to deliver effector proteins ATR1 and ATR13 from the downy mildew fungus Hyaloperonospora parasitica into host Arabidopsis leaves via the type III secretion system of Pseudomonas syringae pv tomato DC3000. Both effectors were fused to the N terminal type three secretion signal of a known P. syringae effector protein, AvrRPS4. P syringae strains expressing these fusion constructs triggered HR in Arabidopsis carrying the associated R genes of ATR1 and ATR13.
Unfortunately, P.syringae DC3000 causes strong HR on wheat on its own (Yin & Hulbert 2011). A variant P. syringae strain CUCPB5500, which has 18 effector genes deleted from its genome, also causes HR on wheat, although less severe than the DC3000 strain (Yin & Hulbert 2011).
In attempt to harness the T3SS system for the delivery of effector proteins in cereal plants, Upadhyaya et al. (2014) used a modified P. fourescens strain called EtHan (effector to host analyser). This strain has the hrp-hrc region of P. syringae (required machinery for the T3SS) stably integrated into the non-pathogenic strain P. flourescens. The EtHan strain does not cause HR on wheat on its own, providing potential for delivering candidate effectors in wheat and assessing subsequent cell death associated with avirulence. To demonstrate this strain can effectively deliver proteins in wheat, EtHan was transformed with a construct containing the T3SS of a known Avr gene from P. syringae (AvrRPM1) fused to a calmodulin-dependent adenylate cyclase (Cya). The Cya protein domain is inactive in in prokaryotes, but becomes active and produces cAMP in eukaryotes in the presence of calmodulin. When the Ethan strain containing the T3SS Cya fusion was infiltrated into wheat leaves, significantly higher cAMP was detected in comparison to the empty vector control. Further, when a candidate Puccinia graminis f. sp. tritici. effector (PGTAUSPE-10-1) was inoculated on differential wheat lines containing 24 different stem rust resistance genes, an HR response was detected on wheat line W3534. These data suggest the EtHan system can deliver proteins into wheat leaves, and can subsequently be used for screening avirulence function.
Sharma et al. (2013) similarlysought out to develop a high throughput system to deliver effectors into monocot plants. Two known cytoplasmic Avr proteins from the rice pathogen Magnaporthe oryzae, Avr-Pik and Avr-pii, were cloned into the effector detector vector (pEDV) which has the type three secretion signal from AvrRps4 that is necessary and sufficient for T3SS-dependent delivery into plants. Subsequently, B. glumae (a bacterial crop pathogen) was transformed with the pEDV-Avr-Pik-NLS or pEDV-Avr-Pii-NLS constructs and translocation of fluorescently tagged effectors were determined via microscopy after leaf sheath assays on wheat. At 3 DPI, clear fluorescent mCherry signals could be detected in the nuclei of leaf sheaths, suggesting the B.glumae pEDV system is also effective in delivering effector proteins in wheat.
Although bacterial delivery remains a promising option for effector delivery in wheat, there have been no proper Avr controls from cereal rusts to confirm this system. To date PGTAUSPE-10-1 has not been followed up for further confirmation of avirulence function. Recently, the first Avr effector from stem rust, AvrSr50, has been thoroughly studied and confirmed via an HR response after Agrobacterium mediated transient co-expression with the corresponding R gene SR50 in N. benthamiana (Chen et al., 2017). Unfortunately, using the Ethan system, AvrSR50 did not cause HR on wheat lines carrying the associated R gene SR50 (Diane Saunders, Personal Communication). The lack of reproducibility in this system may be due to inconsistent and low levels of protein being delivered into the wheat cells. Indeed, in comparison to a known pathogenic bacteria of wheat, Xanthamonas translucens, P. flourescens EtHan proliferated five log fold CFUs/unit leaf area lower after 96 hours post infiltration. Additionally, in a Cya assay X. translucens delivered enough reporter construct such that cAMP accumulation increased several fold in comparison to Cya delivered by EtHAn. Unfortunately, X. translucens causes severe HR on wheat on its own, and is not suitable for avirulence screening of candidate effectors. To mitigate these problems, a strain compatible for infection in wheat that can proliferate to high levels without causing HR on its own must be used. Additionally, using a constitutive promoter may increase the levels of protein production and thus delivery.
5.1.2 Viral Delivery
Recently, the first confirmed avirulence effector of brown rust, AvrSr50, was confirmed via co-expression with the corresponding R gene SR50 in N. benthamiana using mediated Agrobacterium mediated transient expression. This data was supported by a viral delivery system in wheat (Chen et al., 2017). The Barley stripe mosaic virus (BSMV) overexpression vectors including the coding sequence of AvrSR50 were proliferated in N. benthamiana via Agrobacterium. Sap from infiltrated N. benth leaves were mechanically inoculated onto wheat leaf seedlings. Wheat leaves with SR50 did not show any signs of BSMV disease symptoms, suggesting AvrSR50 recognition by SR50. Although this assay does not demonstrate aviurlence directly via an HR response, lack of BSMV disease symptoms suggests the plant defence system is indeed being triggered by the presence of an effector (Chen et al., 2017).
Another approach to deliver effectors in planta is transient expression via particle bombardment/biolistic transformation. In this method, the reduced expression of a reporter gene can be used as an indicator of HR. This system has been used in rice, whereby delivery of the Avr-Pita effector from Magnaporthe Oryzae was co-delivered with a GUS reporter gene into rice seedlings with the corresponding R gene Pi-ta. Reduced GUS activity was only observed when Avr-Pita was delivered in leaves of resistant Pi-ta (Jia et al., 2000). These results suggest a biolistics approach to avirulence assays can be applicable to other monocots such as wheat.
However, due to the labour intensive nature of particle bombardment, it may not be viable for high-throughput screening (Upadhyaya et al., 2014). Further, not all cells in the targeted region are transformed in this method, resulting in individual transformed cells scattered among untransformed ones (Yin & Hulbert 2011). Depending on the efficiency of transformation, a clear pattern in reporter activity levels may be lost.
5.1.4 Protoplast Transformation
Avirulence function of effectors has also been studied using protoplast transformation. In this method, plant host protoplasts from lines containing associated R genes are transformed with effectors alongside a reporter gene. Similarly to the biolistic method, a decrease in reporter gene signal suggests a hypersensitive response, and thus avirulence function. Although there have been no examples from a rust fungus/cereal crop pathosystem, this method has been employed in barley and rice (Ribot et al., 2013, Lu et al., 2016). Lu et al. (2016) transformed barley protoplasts containing MLA-1 or MLA13 with AVRa1 and AVRa13 from Blumeria graminis f. sp. hordei respectively. In this case, luciferase activity was quantified as a proxy for cell death. A significant reduction of luciferase signal was detected in a Mla1-AVRa1 and Mla13-AVRa13 specific manner.
5.2 Functional Validation of Candidate Effectors: Virulence
Currently, all rust effectors that have been characterized are based on aviurlence phenotypes. This does not represent the actual biological function these effectors have on promoting biotrophic disease on host plants. Two major setbacks in studying virulence function include high functional redundancy in effector repertoires, and a lack of high-throughput cell biological assays in crop hosts (Petre et al., 2014a). Functional redundancy is demonstrated in the flax rust effector AvrL567, whereby flax lines silencing this effector did not show any reduced growth of the pathogen (Lawrence et al., 2010). This suggests AvrL567 alone is not required for full virulence, and might be expendable in the infection process due to functional redundancy (Lawrence et al., 2010). Despite this, some progress has been made in dissecting function in virulence, particularly using localization and biochemical studies in wheat and surrogate plants like N. Benthamiana.
5.2.1 Localization and Biochemical studies in Wheat
To study the virulence role of RTP1p, an effector from the bean rust fungus Uromyces fabae, Kemen et al. (2013) used a combination of immunocytological loclaization and biochemical approaches. Using anti-RTP1p anitbiodies, combined with electron microscopy, cryo-scanning electron microscopy, and live cell imaging, Kemen et al. (2013) were able to see RTP1p localizes in protuberances of the extra huastorial matrix, and throughout the host cytoplasm in later stages of infection. Further, they detected RTP1p in close proximity to microfilaments, suggesting close association with these structures, or the ability to form filamentous structures itself. Using a biochemical approach, the authors were able to demonstrate the latter. RTP1p was heterologously expressed in the yeast Pichia pastoris, and purified protein was successfully converted into filaments, suggesting RTP1 is able to form filaments without the presence of other proteins. The authors posit the filamentous structure of RTP1 is transferred into the host to stabilize the host cell and haustorium from degradation during the infection process.
5.2.2 Localization and Biochemical studies in surrogate systems
Unfortunately, there are no well-developed antibodies to assess localization of YR candidate effectors. Producing antibodies for screening multiple candidates is time consuming and not a viable option. A more high throughput method for assessing localization is expression of fluorescently tagged candidate effectors in the model plant N. benthamiana. Petre et al. (2016) screened multiple candidates in this way, and found nine candidates were targeted to specific plant subcellular components or protein complexes. In particular, one candidate PST02549 was found to accumulate in P bodies, which are protein complexes involved in mRNA processing and storage. Further, using CoIP tandtem mass spectrometry, Petre et al. (2016) found this same effector associates with EDC4, a protein involved in mRNA decapping. The authors suggest this candidate effector may target P bodies to manipulate host plant RNA metabolism potentially to suppress immune responses.
Although this method is useful as a first step in screening multiple candidates, P. striiformis does not naturally infect N. benthamiana, and further studies in wheat should be used to verify localization and plant interactors. Further, this method is prone to false negatives, as effector candidates may target natural host components that are too divergent in N. benthamiana to interact with (Petre et al., 2016).
Catanzariti, A. M., Dodds, P. N., Lawrence, G. J., Ayliffe, M. A., & Ellis, J. G. (2006). Haustorially Expressed Secreted Proteins from Flax Rust Are Highly Enriched for Avirulence Elicitors. The Plant Cell, 18(1), 243–256.
Catanzariti, A.-M., Dodds, P. N., Ve, T., Kobe, B., Ellis, J. G., & Staskawicz, B. J. (2010). The AvrM effector from flax rust has a structured C-terminal domain and interacts directly with the M resistance protein. Molecular Plant-Microbe Interactions, 23(1), 49–57.
Cantu, D., Segovia, V., MacLean, D., Bayles, R., Chen, X., Kamoun, S., Dubcovsky,.
J., Saunders, D. GO., & Uauy, C. (2013). Genome analyses of the wheat yellow
(stripe) rust pathogen Puccinia striiformis f. sp. tritici reveal polymorphic and
haustorial expressed secreted proteins as candidate effectors. BMC Genomics,
Chen, X. M. (2005). Review / Synthèse Epidemiology and control of stripe rust [ Puccinia striiformis f . sp . tritici ] on wheat. Canadian Journal of Botany, 27, 314–337.
Chen, W., Wellings, C., Chen, X., Kang, Z., & Liu, T. (2014). Wheat stripe (yellow) rust caused by Puccinia striiformis f. sp. tritici. Molecular Plant Pathology, 15(5), 433–446.
Chen, J., Upadhyaya, N. M., Ortiz, D., Sperschneider, J., Li, F., Bouton, C., … Dodds, P. N. (2017). Loss of AvrSr50 by somatic exchange in stem rust leads to virulence for Sr50 resistance in wheat. Science, 358(6370), 1607–1610.
Dodds, P.N., Lawrence, G.J., Catanzariti, A.M., Ayliffe, M. A., & Ellis, J. G. (2004).
The Melampsora lini AvrL567 avirulence genes are expressed in haustoria and
their products are recognized inside plant cells. The Plant Cell, 16, 755–768.
Dodds, P. N., Lawrence, G. J., Catanzariti, A.-M., Teh, T., Wang, C.-I. A., Ayliffe, M. A., … Ellis, J. G. (2006). Direct protein interaction underlies gene-for-gene specificity and coevolution of the flax resistance genes and flax rust avirulence genes. Proceedings of the National Academy of Sciences, 103(23), 8888–8893.
Dodds, P. N., & Rathjen, J. P. (2010). Plant immunity: towards an integrated view of plant–pathogen interactions. Nature Reviews Genetics, 11(8), 539–548.
Duplessis, S., Joly, D. L., & Dodds, P. N. (2012) ‘Rust Effectors’, in Martin, F., & Kamoun, S. (eds.) Effectors in Plant-Microbe Interactions. West Sussex: John Wiley & Sons, pp. 155 – 193.
Duplessis, S., Bakkeren, G. & Hamelin, R. Advancing knowledge on biology of rust
fungi through genomics. Advances in Botanical Research 70, (Elsevier Ltd.,
Hovmoller, M. S., Walter, S., & Justesen, A. F. (2010). Escalating Threat of Wheat Rusts. Science, 329(5990), 369–369.
Hubbard, A., Lewis, C. M., Yoshida, K., Ramirez-Gonzalez, R. H., de Vallavieille-Pope, C., Thomas, J., … Saunders, D. G. O. (2015). Field pathogenomics reveals the emergence of a diverse wheat yellow rust population. Genome Biology, 16(1), 23.
Jia, Y., Mcadams, S. A., Bryan, G. T., Hershey, H. P., & Valent, B. (2000). Direct interaction of resistance gene and avirulence gene products confers rice blast resistance. The EMBO Journal, 19(15), 4004-4014.
Jiang, R. H. Y., Tripathy, S., Govers, F., & Tyler, B. M. (2008). RXLR effector reservoir in two Phytophthora species is dominated by a single rapidly evolving superfamily with more than 700 members. Proceedings of the National Academy of Sciences, 105(12), 4874–4879.
Kemen, E., Kemen, A. C., Rafiqi, M., Hempel, U., Mendgen, K., Hahn, M., & Voegele, R. T. (2005). Identification of a Protein from Rust Fungi Transferred from Haustoria into Infected Plant Cells. Molecular Plant-Microbe Interactions, 18(11), 1130–1139.
Kemen, E., Kemen, A., Ehlers, A., Voegele, R., & Mendgen, K. (2013). A novel structural effector from rust fungi is capable of fibril formation. Plant Journal, 75(5), 767–780.
Lawrence, G. J., Dodds, P. N., & Ellis, J. G. (2010). Transformation of the flax rust fungus, Melampsora lini: Selection via silencing of an avirulence gene. Plant Journal, 61(2), 364–369.
Liu, W., Frick, M., Huel, R., Nykiforuk, C. L., Wang, X., Gaudet, D. A., … Laroche, A. (2014). The Stripe Rust Resistance Gene Yr10 Encodes an Evolutionary-Conserved and Unique CC-NBS-LRR Sequence in Wheat. Molecular Plant, 7(12), 1740–1755.
Lu, X., Kracher, B., Saur, I. M. L., Bauer, S., Ellwood, S. R., Wise, R., & Yaeno, T. (2016). Allelic barley MLA immune receptors recognize sequence-unrelated avirulence effectors of the powdery mildew pathogen. Proceedings of the National Academy of Sciences, 113(42).
Petersen, T. N., Brunak, S., Von Heijne, G., & Nielsen, H. (2011). SignalP 4.0: Discriminating signal peptides from transmembrane regions. Nature Methods, 8(10), 785–786.
Petre, B., Joly, D. L., & Duplessis, S. (2014a). Effector proteins of rust fungi. Frontiers in Plant Science, 5(416), 1–7.
Petre, B., & Kamoun, S. (2014b). How Do Filamentous Pathogens Deliver Effector Proteins into Plant Cells? PLoS Biology, 12(2).
Petre, B., Saunders, D. G. O., Sklenar, J., Lorrain, C., Krasileva, K. V., Win, J., … Kamoun, S. (2016). Heterologous Expression Screens in Nicotiana benthamiana Identify a Candidate Effector of the Wheat Yellow Rust Pathogen that Associates with Processing Bodies. Plos One, 11(2).
Raffaele, S., Win, J., Cano, L. M., & Kamoun, S. (2010). Analyses of genome architecture and gene expression reveal novel candidate virulence factors in the secretome of Phytophthora infestans. BMC Genomics, 11(637), 1-18.
Raffaele, S., & Kamoun, S. (2012). Genome evolution in filamentous plant pathogens : why bigger can be better. Nature Reviews Microbiology, 10, 417-430.
Rafiqi, M., Gan, P. H. P., Ravensdale, M., Lawrence, G. J., Ellis, J. G., Jones, D. A., … Dodds, P. N. (2010). Internalization of Flax Rust Avirulence Proteins into Flax and Tobacco Cells Can Occur in the Absence of the Pathogen. The Plant Cell, 22(6), 2017–2032.
Ribot, C., Césari, S., Abidi, I., Chalvon, V., Bournaud, C., Vallet, J., … Kroj, T. (2013). The Magnaporthe oryzae effector AVR1-CO39 is translocated into rice cells independently of a fungal-derived machinery. Plant Journal, 74(1), 1–12.
Rouxel, T., Grandaubert, J., Hane, J. K., Hoede, C., Van De Wouw, A. P., Couloux, A., … Howlett, B. J. (2011). Effector diversification within compartments of the Leptosphaeria maculans genome affected by repeat-induced point mutations. Nature Communications, 2(202), 1-10.
Saunders, D. G. O., Win, J., Cano, L. M., Szabo, L. J., Kamoun, S., & Raffaele, S. (2012). Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi. PLoS One, 7(1).
Sharma, S., Sharma, S., Hirabuchi, A., Yoshida, K., Fujisaki, K., Ito, A., … Saitoh, H. (2013). Deployment of the Burkholderia glumae type III secretion system as an efficient tool for translocating pathogen effectors to monocot cells. Plant Journal, 74(4), 701–712.
Sohn, K. H., Lei, R., Nemri, A., & Jones, J. D. G. (2007). The Downy Mildew Effector Proteins ATR1 and ATR13 Promote Disease Susceptibility in Arabidopsis thaliana. The Plant Cell Online, 19(12), 4077–4090.
Sonah, H., Deshmukh, R. K., & Bélanger, R. R. (2016). Computational Prediction of Effector Proteins in Fungi: Opportunities and Challenges. Frontiers in Plant Science, 7(126), 1–14.
Sørensen, C. K., Hovmøller, M. S., Leconte, M., Dedryver, F., & de Vallavieille-Pope, C. (2014). New Races of Puccinia striiformis Found in Europe Reveal Race Specificity of Long-Term Effective Adult Plant Resistance in Wheat. Phytopathology, 104(10), 1042–1051.
Stergiopoulos, I., & de Wit, P. J. G. M. (2009). Fungal Effector Proteins. Annual Review of Phytopathology, 47(1), 233–263.
Upadhyaya, N. M., Mago, R., Staskawicz, B. J., Ayliffe, M. a, Ellis, J. G., & Dodds, P. N. (2014). A bacterial type III secretion assay for delivery of fungal effector proteins into wheat. MPMI, 27(3), 255–264.
Van den Burg, H. A., Westerink, N., Francoijs, K. J., Roth, R., Woestenenk, E., Boeren, S., … Vervoort, J. (2003). Natural disulfide bond-disrupted mutants of AVR4 of the tomato pathogen Cladosporium fulvum are sensitive to proteolysis, circumvent Cf-4-mediated resistance, but retain their chitin binding ability. Journal of Biological Chemistry, 278(30), 27340–27346.
Van den Hooven, H. W., Van den Burg, H. A., Vossen, P., Boeren, S., De Wit, P. J. G. M., & Vervoort, J. (2001). Disulfide bond structure of the AVR9 elicitor of the fungal tomato pathogen Cladosporium fulvum: Evidence for a cystine knot. Biochemistry, 40(12), 3458–3466.
Wang, C.-I. A., Guncar, G., Forwood, J. K., Teh, T., Catanzariti, A.-M., Lawrence, G. J., … Kobe, B. (2007). Crystal Structures of Flax Rust Avirulence Proteins AvrL567-A and -D Reveal Details of the Structural Basis for Flax Disease Resistance Specificity. The Plant Cell Online, 19(9), 2898–2912.
Win, J., Chaparro- Garcia, A., Belhaj, K., Saunders, D. G., Yoshida, K., Dong, S., Schornack, S., Zipfel, C., Robatzek, S., Hogenhout, S.A., & Kamoun, S. (2012). Effector Biology of Plant-Associated Organisms : Concepts and Perspectives. Cold Spring Harbor Symposia on Quantitative Biology, 77, 235–247.
Yin, C., & Hulbert, S. (2011). Prospects for functional analysis of effectors from cereal rust fungi. Euphytica, 179, 57–67.
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