Plants and other living organisms can survive stress and starvation by digesting and recycling parts of their own cells. This process is known as autophagy and it involves engulfing cellular material inside spherical structures called autophagosomes, before delivering it to sites in the cell where digestive enzymes can break the material down. A form of autophagy, known as selective autophagy, can specifically degrade toxic substances such as disease-causing microbes. Selective autophagy works through proteins called autophagy cargo receptors that define which molecules are targeted for degradation. However, it was not clear whether autophagy protects plants from infections, or how much disease-causing microbes interfere with this process for their own benefit.

The microbe that causes late blight of potatoes (called Phytophthora infestans) is infamous for triggering widespread famines in Ireland in the 19^th century. This disease-causing microbe continues to pose a serious threat to food security today, and parasitizes plant tissues by releasing proteins called effectors that enter the plant’s cells to subvert the plant’s physiology and counteract its defenses.

Dagdas, Belhaj et al. now report that an effector from P. infestans, called PexRD54, can bind to autophagy-related protein from potato, called ATG8CL, and stimulate the formation of autophagosomes. Further experiments revealed that the PexRD54 effector could outcompete a plant autophagy cargo receptor that would otherwise bind to ATG8CL. This plant cargo receptor contributes to the plant’s defences, and by preventing it from interacting with ATG8CL, PexRD54 makes the plant more susceptible to infection by P. infestans.

These findings show that the PexRD54 effector has evolved to interact with an autophagy-related protein to counteract the plant’s defences. Dagdas, Belhaj et al. suggest that PexRD54 might do this by activating autophagy to selectively eliminate some of the molecules that the plant use to defend itself. Furthermore, P. infestans might also benefit from the nutrients that are released when cellular material is broken down via autophagy. Future work could test these two hypotheses and explore whether other effectors from disease-causing microbes work in a similar way.

Autophagy is conserved catabolic pathway that sequesters unwanted cytosolic components into newly formed double membrane vesicles, autophagosomes, to direct them to the cell’s lytic compartment (He and Klionsky, 2009). The process plays a vital role in survival of the organism by improving cellular adaptation to environmental and stress conditions (Shintani and Klionsky, 2004). Autophagy provides building blocks and energy for elementary cellular processes by degrading dysfunctional or unnecessary cellular components during nutrient deprivation (Shintani and Klionsky, 2004). However, even though autophagy was initially thought to be a bulk degradation process activated during starvation, recent studies showed that it can act selectively, capturing specific substrates through specialized cargo receptors to respond to a variety of environmental and stress conditions (Stolz et al., 2014).

Autophagy is executed through coordinated action of more than 30 core proteins known as the ATG (autophagy-related) proteins (Lamb et al., 2013). Selective autophagy is regulated through specific interactions of autophagy cargo receptors and ATG8 proteins (Stolz et al., 2014). Autophagy cargo receptors carry a short sequence motif called ATG8-interaction motif (AIM) that binds lipidated ATG8 proteins anchored on autophagosomal membranes. Cargo receptors mediate recognition of a diverse set of cargo (Stolz et al., 2014). For instance, mammalian autophagy cargo receptors NDP52 and optineurin can recognize intracellular pathogenic bacteria and mediate their autophagic removal by sorting the captured bacteria inside the ATG8-coated autophagosomes (Boyle and Randow, 2013). Nevertheless, the precise molecular mechanisms of selective autophagy and the components that regulate it remain unknown (Huang and Brumell, 2014; Mostowy, 2013; Randow, 2011).

In plants, autophagy plays important roles in stress tolerance, senescence, development, and defense against invading pathogens (Patel and Dinesh-Kumar, 2008; Lenz et al., 2011; Vanhee and Batoko, 2011; Li and Vierstra, 2012; Lv et al., 2014; Teh and Hofius, 2014). Specifically, autophagy is implicated in the accumulation of defense hormones and the hypersensitive response, a form of plant cell death that prevents spread of microbial infection (Yoshimoto et al., 2009). However, the molecular mechanisms that mediate defense-related autophagy and the selective nature of this process are poorly understood. Furthermore, how adapted plant pathogens manipulate defense-related autophagy and/or subvert autophagy for nutrient uptake is unknown.

In this study, we investigated how a pathogen interferes with and coopts a plant autophagy pathway. The potato blight pathogen, Phytophthora infestans, is a serious threat to food security, causing crop losses that, if alleviated, could feed hundreds of millions of people (Fisher et al., 2012). This pathogen delivers RXLR-type effector proteins inside plant cells to enable parasitism (Morgan and Kamoun, 2007). RXLR effectors form a diverse family of modular proteins that alter a variety of host processes and therefore serve as useful probes to dissect key pathways for pathogen invasion (Morgan and Kamoun, 2007; Bozkurt et al., 2012). Here, we show that the RXLR effector PexRD54 has evolved to bind host autophagy protein ATG8CL to stimulate autophagosome formation. In addition, PexRD54 depletes the autophagy cargo receptor Joka2 out of ATG8CL complexes to counteract host defenses against P. infestans.

As part of an in plantascreen for host interactors of RXLR effectors, we discovered that the P. infestans effector PexRD54 associates with ATG8CL, a member of the ATG8 family (Materials and methods, Supplementary files 1,2). The association between PexRD54 and ATG8CL was retained under stringent binding conditions in contrast to other candidate interactors (Supplementary file 1). We validated the association with reverse coimmunoprecipitation after co-expressing the potato ATG8CL protein with the C-terminal effector domain of PexRD54 in planta (Figure 1A,B). In addition, PexRD54 expressed and purified from Escherichia coli directly bound ATG8CL in vitro with high affinity and in a one to one ratio (K_D = 383 nM based on isothermal titration calorimetry) (Figure 1C). PexRD54 has two predicted ATG8 Interacting Motifs (AIMs) that match the consensus amino acid sequence W/F/Y-x-x-L/I/V (AIM1 and AIM2, Figure 1A). In planta coimmunoprecipitations of single and double AIM mutants of PexRD54 revealed that AIM2, which spans the last four amino acids of the protein (positions 378–381), is required for association with ATG8CL (Figure 1D). PexRD54^AIM2 mutant also failed to bind ATG8CL in vitro (Figure 1E). In addition, ATG8CL bound with high affinity to a synthetic peptide (KPLDFDWEIV) that matches the last 10 C-terminal amino acids of PexRD54 (K_D = 220 nM) (Figure 1—figure supplement 1). We conclude that the C-terminal AIM of PexRD54 is necessary and sufficient to bind ATG8CL.

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ATG8 occurs as a family of nine proteins in potato (Figure 2—figure supplements 1–2). PexRD54 bound ATG8CL with ~10 times higher affinity than another ATG8 family member, ATG8IL, in both in planta and in vitro assays (Figure 2). These findings prompted us to use ATG8IL as a negative control in the subsequent experiments.

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We then investigated the subcellular localization of PexRD54 within plant cells. N-terminal fusions of PexRD54 to the green fluorescent protein (GFP) or red fluorescent protein (RFP) labelled the nucleo-cytoplasm and mobile punctate structures (Figure 3—figure supplement 1 and Video 1). Immunogold labelling in transmission electron micrographs of cells expressing GFP:PexRD54 revealed a strong signal in electron dense structures that are not peroxisomes (Figure 3—figure supplements 2–3, Dagdas et al., 2016). To determine whether these structures are ATG8CL autophagosomes, we transiently co-expressed RFP:PexRD54 with GFP:ATG8CL in plant cells and observed an overlap between the two fluorescent signals in sharp contrast to RFP:PexRD54^AIM2 and RFP:EV negative controls (Figure 3 and Video 2). This indicates that PexRD54 localizes to ATG8CL-marked autophagosomes and its C-terminal AIM is necessary for autophagosome localization. In contrast, RFP:PexRD54 signal overlapped with GFP:ATG8IL-labelled autophagosomes in only 15–20% of observations consistent with its weaker binding affinity to ATG8IL (Figure 3—figure supplement 4).

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To further confirm that PexRD54-labelled endomembrane compartments are indeed autophagosomes, we investigated the effect of the autophagy inhibitor 3-methyl adenine (3-MA) (Hanamata et al., 2013) on PexRD54 localization. Compared to water, 3-MA treatment reduced the number of PexRD54 and ATG8CL puncta but did not reduce the number of puncta of the trans-Golgi network (TGN) marker VTI12 (Geldner et al., 2009) (Figure 3—figure supplement 5).

Phospholipid modification of a conserved glycine residue at the C-terminus of ATG8 proteins is required for autophagosome formation, and deletion of this terminal glycine yields a dominant negative ATG8 (Hanamata et al., 2013). We deployed a terminal glycine deletion mutant of ATG8CL (ATG8CLΔ) to determine its effect on subcellular distribution of PexRD54 (Figure 3—figure supplement 6). As expected, deletion of the terminal glycine did not affect binding of ATG8CL to PexRD54 (Figure 3—figure supplement 7A). However, GFP:ATG8CLΔ led to the depletion of RFP:PexRD54 labelled puncta presumably because the dominant negative effect of ATG8CLΔ prevented accumulation of RFP:PexRD54 in ATG8CL-labelled autophagosomes (Figure 3—figure supplement 7B–D). In contrast, GFP:ATG8ILΔ, a terminal glycine deletion mutant of ATG8IL, had no effect on the punctate localization of RFP:PexRD54 (Figure 3—figure supplement 7C–D). These experiments independently support the finding that PexRD54 accumulates in ATG8CL autophagosomes.

Increase in ATG8 labelled puncta is widely used as a functional readout of autophagic activity (Hanamata et al., 2013; Bassham, 2015). In samples expressing PexRD54, we noticed a ~fivefold increase in the number of ATG8CL marked autophagosomes compared to control samples expressing PexRD54^AIM2 or empty vector control (Figure 4, Video 3). In contrast, PexRD54 did not alter the number of ATG8IL autophagosomes consistent with the weak binding noted between these two proteins (Figure 4A). This indicates that PexRD54 stimulates the formation of ATG8CL autophagosomes.

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Next, we set out to determine the effect of PexRD54 on autophagic flux. Treatment of RFP:ATG8CL expressing leaves with the specific vacuolar ATPase inhibitor concanamycin-A (Bassham, 2015) increased the number of ATG8CL-labelled puncta both in the presence of PexRD54 or controls (PexRD54^AIM2 or vector control) indicating that PexRD54 does not block autophagic flux (Figure 5A–B). We also confirmed these observations using western blot analyses. PexRD54, but neither PexRD54^AIM2 or vector control, increased the levels of GFP:ATG8CL protein 3 days after co-expression in planta (Figure 5C). Treatment of three-day samples with E64d, an inhibitor of vacuolar cysteine proteases (Bassham, 2015), further increased protein levels of GFP:ATG8CL. This further confirms that PexRD54 stimulates autophagy rather than blocking autophagic flux (Figure 5C). PexRD54 did not alter the accumulation of GFP:ATG8IL or control GFP protein, confirming that PexRD54 increases ATG8CL protein accumulation specifically (Figure 5C). Consistent with these observations, we noted an increase in GFP:ATG8CL levels, but not in control GFP, during P. infestans infection relative to the mock infection (Figure 5—figure supplement 1).

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The presence of a functional AIM in PexRD54 prompted us to hypothesize that this effector perturbs the autophagy cargo receptors of its host plants. Recently, Joka2 was reported as a selective autophagy cargo receptor of Solanaceous plants that also binds ATG8 via an AIM (Svenning et al., 2011; Zientara-Rytter et al., 2011) (Figure 6A). Indeed, in planta coimmunoprecipitation assays confirmed that potato Joka2, but not the AIM mutant, Joka2^AIM, associated with ATG8CL (Figure 6—figure supplement 1). Joka2 association with ATG8CL was somewhat specific given that this cargo receptor failed to coimmunoprecipitate with ATG8IL (Figure 6—figure supplement 2). Joka2, but not Joka2^AIM, also markedly increased the number of GFP:ATG8CL autophagosomes (Figure 6—figure supplement 3, Video 4), and enhanced ATG8CL protein levels (Figure 6—figure supplement 4). This indicates that Joka2 also activates ATG8CL-mediated selective autophagy.

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Given that both PexRD54 and Joka2 bind ATG8CL via their respective AIMs, we hypothesized that PexRD54 interferes with the Joka2-ATG8CL complex. We tested our hypothesis by performing coimmunoprecipitation experiments between Joka2:RFP and GFP:ATG8CL in the presence or absence of PexRD54. Remarkably, ATG8CL complexes were depleted in Joka2 in the presence of PexRD54 relative to the PexRD54^AIM2 and vector control (Figure 6—figure supplement 5). Consistently, Joka2 binding to ATG8CL decreased with increasing PexRD54 concentrations (Figure 6B). The distinct AIMs of PexRD54 and Joka2 presumably determine the effect observed in these competition experiments. To further test this, we replaced the functional PexRD54 AIM with two sequences that cover the Joka2 AIM:GVAEWDPI (PexRD54^J2AIM1) and GVAEWDPILEELKEMG (PexRD54^J2AIM2) (Figure 6C). Both PexRD54^J2AIM1 and PexRD54^J2AIM2 associated with ATG8CL to a lesser extent than wild-type PexRD54 (Figure 6D), and were less effective than PexRD54 in depleting Joka2 out of ATG8CL complexes (Figure 6—figure supplement 6). These findings reveal that PexRD54 antagonizes Joka2 for ATG8CL binding.

Finally, we investigated the degree to which activation of Joka2-ATG8CL-mediated autophagy contributes to pathogen defense. Overexpression of Joka2, but not Joka2^AIM, significantly restricted the size of the disease lesions caused by P. infestans (Figure 7A–B). Conversely, virus-induced gene silencing of Joka2 resulted in increased disease lesions (Figure 7—figure supplement 1). This indicates that Joka2-mediated selective autophagy contributes to defense against this pathogen. Remarkably, PexRD54 counteracted the enhanced resistance conferred by Joka2 whereas PexRD54^AIM2 failed to reverse this effect (Figure 7C–D). We conclude that PexRD54 counteracts the positive role of Joka2-mediated selective autophagy in pathogen defense.

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As demonstrated in mammalian systems, eukaryotic cells employ autophagy to defend against invading pathogens (Boyle and Randow, 2013; Randow and Youle, 2014). In turn, pathogens can deploy effectors to avoid autophagy and enable parasitic infection (Baxt et al., 2013). For instance, to counteract antimicrobial autophagy, intracellular bacterial pathogen Legionella pneumophila secretes a type IV effector protein RavZ that impedes autophagy by uncoupling ATG8-lipid linkage (Choy et al., 2012). In this study, we show that a plant pathogen effector has evolved an ATG8 interacting motif to bind with high affinity to the autophagy protein ATG8CL and stimulate the formation of ATG8CL-marked autophagosomes. Unlike the Legionella effector RavZ, PexRD54 activates selective autophagy possibly to eliminate defense-related compounds or to reattribute cellular resources by promoting nutrient recycling. Our results show that, in addition to disrupting, pathogens can also activate autophagy for their own benefit (Figure 8).

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Additionally, we show that the effector competes with the host cargo receptor Joka2 and depletes it out of ATG8CL autophagosomes to promote disease susceptibility. Thus P. infestans coopts the host cell’s endomembrane compartment to promote its own growth at the cost of the cell’s physiology (Bozkurt et al., 2015). Joka2 could contribute to immunity by inducing autophagic removal of plant or pathogen molecules that negatively affect host defenses. It will be interesting in the future to determine the identity of potential defense-related cargo carried by Joka2 (Figure 8).

The physiological roles of selective autophagy and the molecular mechanisms involved remain to be determined both in plants and animals. Characterization of additional host cargo receptors and interactome analysis of particular ATG8 proteins should improve our understanding of how selective autophagy operates in response to a variety of stress conditions including immunity. In the potato genome, we identified nine ATG8 genes. Both Joka2 and the effector showed higher affinity to ATG8CL compared to ATG8IL (Figure 2 and Figure 6—figure supplement 2). This indicates that variation between plant ATG8 proteins may contribute to the selective nature of autophagy.

This work further highlights the intricate changes in endomembrane compartment formation that take place during plant-microbe interactions (Bozkurt et al., 2015; Lipka and Panstruga, 2005; Kwon et al., 2008; Ivanov et al., 2010; Wang et al., 2010). Future studies will need to consider pathogen-directed modulation of the spatio-temporal dynamics of autophagy and subcellular trafficking during host infection. It will be interesting to determine whether other plant pathogens also secrete effectors that evolved an ATG8 interacting motif or target autophagy in other ways. These effectors would serve as valuable tools to dissect the mechanisms of defense-related selective autophagy.

1. 1. Nusbaum C
   2. Haas B
   3. Kamoun S
   4. Fry W
   5. Judelson H
   6. Ristaino J
   7. Govers F
   8. Whis- son S
   9. Birch P
   10. Birren B
   11. Lander E
   12. Gala- gan J
   13. Zody M
   14. De- von K
   15. O’Neil K
   16. Zembek L
   17. Ander- son S
   18. Jaffe D
   19. But- ler J
   20. Alvarez P
   21. Gnerre S
   22. Grabherr M
   23. Mauceli E
   24. Brockman W
   25. Young S
   26. LaButti K
   27. Sykes S
   28. DeCaprio D
   29. Craw- ford M
   30. Koehrsen M
   31. Engels R
   32. Mon- tgomery P
   33. Pearson M
   34. Howarth C
   35. Lar- son L
   36. White J
   37. O’Leary S
   38. Kodira C
   39. Zeng Q
   40. Yandava C
   41. Alvarado L

   (2006) Phytophthora infestans T30-4 secreted RxLR effector peptide protein, putative (PITG_09316) mRNA, complete cds

   Publicly available at NCBI Nucleotide (Accession no: XM_002903553.1).

   http://www.ncbi.nlm.nih.gov/nuccore/XM_002903553.1
2. 1. Fernandez-Pozo et al

   (2014) Solanum tuberosum polypeptide PGSC0003DMP400038670

   Publicly available at SolGenomics Database (Accession no: PGSC0003 DMP400038670).

   https://solgenomics.net/
3. 1. Fernandez-Pozo et al

   (2014) Solanum tuberosum polypeptide PGSC0003DMP400009229

   Publicly available at SolGenomics Database (Accession no: PGSC0003 DMP400009229).

   https://solgenomics.net/
4. 1. Fernandez-Pozo et al

   (2010) Tomato locus Solyc10g006270

   Publicly available at SolGenomics Database (Accession no: Solyc10g006270).

   https://solgenomics.net/
5. 1. Fernandez-Pozo et al

   (2010) Tomato locus Solyc07g064680

   Publicly available at SolGenomics Database (Accession no: Solyc07g064680).

   https://solgenomics.net/
6. 1. Fernandez-Pozo et al

   (2010) Tomato locus Solyc01g068060

   Publicly available at SolGenomics Database (Accession no: Solyc01g068060).

   https://solgenomics.net/
7. 1. Dagdas YF
   2. Belhaj K
   3. Maqbool A
   4. Chaparro-Garcia A
   5. Pandey P
   6. Petre B
   7. Tabassum N
   8. Cruz-Mireles N
   9. Hughes RK
   10. Sklenar J
   11. Win J
   12. Menke F
   13. Findlay K
   14. Banfield MJ
   15. Kamoun S
   16. Bozkurt TO

   (2016) An effector of the Irish potato famine pathogen antagonizes a host autophagy cargo receptor

   Publicly available at NCBI (Accession no: KR021366).

   https://www.ncbi.nlm.nih.gov/nuccore/976151098/
8. 1. Dagdas YF
   2. Belhaj K
   3. Maqbool A
   4. Chaparro-Garcia A
   5. Pandey P
   6. Petre B
   7. Tabassum N
   8. Cruz-Mireles N
   9. Hughes RK
   10. Sklenar J
   11. Win J
   12. Menke F
   13. Findlay K
   14. Banfield MJ
   15. Kamoun S
   16. Bozkurt TO

   (2015) An effector of the Irish potato famine pathogen antagonizes a host autophagy cargo receptor

   Publicly available at NCBI (Accession no: KR021365).

   https://www.ncbi.nlm.nih.gov/nuccore/976151096/
9. 1. Dagdas YF
   2. Belhaj K
   3. Maqbool A
   4. Chaparro-Garcia A
   5. Pandey P
   6. Petre B
   7. Tabassum N
   8. Cruz-Mireles N
   9. Hughes RK
   10. Sklenar J
   11. Win J
   12. Menke F
   13. Findlay K
   14. Banfield MJ
   15. Kamoun S
   16. Bozkurt TO

   (2016) PREDICTED: Solanum tuberosum protein NBR1 homolog (LOC102582603), transcript variant X2, mRNA

   Publicly available at NCBI nucleotide (Accession no: XM_006344410.2).

   https://www.ncbi.nlm.nih.gov/nuccore/971545348/
10. 1. Dagdas YF
    2. Belhaj K
    3. Maqbool A
    4. Cha- parro-Garcia A
    5. Pandey P
    6. Petre B
    7. Tabassum N
    8. Cruz- Mireles N
    9. Hughes RK
    10. Sklenar J
    11. Win J
    12. Menke F
    13. Findlay K
    14. Banfield MJ
    15. Ka- moun S
    16. Bozkurt TO

    (2016) Data from: An effector of the Irish potato famine pathogen antagonizes a host autophagy cargo receptor

    Available at Dryad Digital Repository under a CC0 Public Domain Dedication.

    http://dx.doi.org/10.5061/dryad.dv56j

1. 1. Altschul SF
   2. Gish W
   3. Miller W
   4. Myers EW
   5. Lipman DJ

   (1990) Basic local alignment search tool

   Journal of Molecular Biology 215:403–410.

   https://doi.org/10.1016/S0022-2836(05)80360-2

   • PubMed
   • Google Scholar
2. 1. Bassham DC

   (2015) Methods for analysis of autophagy in plants

   Methods 75:181–188.

   https://doi.org/10.1016/j.ymeth.2014.09.003

   • PubMed
   • Google Scholar
3. 1. Baxt LA
   2. Garza-Mayers AC
   3. Goldberg MB

   (2013) Bacterial subversion of host innate immune pathways

   Science 340:697–701.

   https://doi.org/10.1126/science.1235771

   • PubMed
   • Google Scholar
4. 1. Berrow NS
   2. Alderton D
   3. Sainsbury S
   4. Nettleship J
   5. Assenberg R
   6. Rahman N
   7. Stuart DI
   8. Owens RJ

   (2007) A versatile ligation-independent cloning method suitable for high-throughput expression screening applications

   Nucleic Acids Research 35:e45.

   https://doi.org/10.1093/nar/gkm047

   • PubMed
   • Google Scholar
5. 1. Birgisdottir ÅB
   2. Lamark T
   3. Johansen T

   (2013) The LIR motif - crucial for selective autophagy

   Journal of Cell Science 126:3237–3247.

   https://doi.org/10.1242/jcs.126128

   • PubMed
   • Google Scholar
6. 1. Boyle KB
   2. Randow F

   (2013) The role of ‘eat-me’ signals and autophagy cargo receptors in innate immunity

   Current Opinion in Microbiology 16:339–348.

   https://doi.org/10.1016/j.mib.2013.03.010

   • PubMed
   • Google Scholar
7. 1. Bozkurt TO
   2. Belhaj K
   3. Dagdas YF
   4. Chaparro-Garcia A
   5. Wu C-H
   6. Cano LM
   7. Kamoun S

   (2015) Rerouting of plant late endocytic trafficking toward a pathogen interface

   Traffic 16:204–226.

   https://doi.org/10.1111/tra.12245

   • PubMed
   • Google Scholar
8. 1. Bozkurt TO
   2. Schornack S
   3. Banfield MJ
   4. Kamoun S

   (2012) Oomycetes, effectors, and all that jazz

   Current Opinion in Plant Biology 15:483–492.

   https://doi.org/10.1016/j.pbi.2012.03.008

   • PubMed
   • Google Scholar
9. 1. Bozkurt TO
   2. Schornack S
   3. Win J
   4. Shindo T
   5. Ilyas M
   6. Oliva R
   7. Cano LM
   8. Jones AME
   9. Huitema E
   10. van der Hoorn RAL
   11. Kamoun S

   (2011) Phytophthora infestans effector AVRblb2 prevents secretion of a plant immune protease at the haustorial interface

   Proceedings of the National Academy of Sciences of the United States of America 108:20832–20837.

   https://doi.org/10.1073/pnas.1112708109

   • PubMed
   • Google Scholar
10. 1. Caillaud M-C
    2. Wirthmueller L
    3. Sklenar J
    4. Findlay K
    5. Piquerez SJM
    6. Jones AME
    7. Robatzek S
    8. Jones JDG
    9. Faulkner C
    10. Birch P

    (2014) The plasmodesmal protein PDLP1 localises to haustoria-associated membranes during downy mildew infection and regulates callose deposition

    PLoS Pathogens 10:e1004496.

    https://doi.org/10.1371/journal.ppat.1004496

    • PubMed
    • Google Scholar
11. 1. Chaparro-Garcia A
    2. Schwizer S
    3. Sklenar J
    4. Yoshida K
    5. Petre B
    6. Bos JIB
    7. Schornack S
    8. Jones AME
    9. Bozkurt TO
    10. Kamoun S
    11. Vinatzer BA

    (2015) Phytophthora infestans RXLR-WY effector AVR3a associates with dynamin-related protein 2 required for endocytosis of the plant pattern recognition receptor FLS2

    PLOS ONE 10:e0137071.

    https://doi.org/10.1371/journal.pone.0137071

    • PubMed
    • Google Scholar
12. 1. Choy A
    2. Dancourt J
    3. Mugo B
    4. O'Connor TJ
    5. Isberg RR
    6. Melia TJ
    7. Roy CR

    (2012) The legionella effector RavZ inhibits host autophagy through irreversible Atg8 deconjugation

    Science 338:1072–1076.

    https://doi.org/10.1126/science.1227026

    • PubMed
    • Google Scholar
13. Data

    1. Dagdas YF
    2. Belhaj K
    3. Maqbool A
    4. Chaparro-Garcia A
    5. Pandey P
    6. Petre B
    7. Tabassum N
    8. Cruz-Mireles N
    9. Hughes RK
    10. Sklenar J
    11. Win J
    12. Menke F
    13. Findlay K
    14. Banfield MJ
    15. Kamoun S
    16. Bozkurt TO

    (authors) (2016) Data from: an effector of the irish potato famine pathogen antagonizes a host autophagy cargo receptor

    Dryad Digital Repository.

    https://doi.org/10.5061/dryad.dv56j
14. 1. Fisher MC
    2. Henk DA
    3. Briggs CJ
    4. Brownstein JS
    5. Madoff LC
    6. McCraw SL
    7. Gurr SJ

    (2012) Emerging fungal threats to animal, plant and ecosystem health

    Nature 484:186–194.

    https://doi.org/10.1038/nature10947

    • PubMed
    • Google Scholar
15. 1. Geldner N
    2. Dénervaud-Tendon V
    3. Hyman DL
    4. Mayer U
    5. Stierhof Y-D
    6. Chory J

    (2009) Rapid, combinatorial analysis of membrane compartments in intact plants with a multicolor marker set

    The Plant Journal 59:169–178.

    https://doi.org/10.1111/j.1365-313X.2009.03851.x

    • PubMed
    • Google Scholar
16. 1. Hanamata S
    2. Kurusu T
    3. Okada M
    4. Suda A
    5. Kawamura K
    6. Tsukada E
    7. Kuchitsu K

    (2013) In vivo imaging and quantitative monitoring of autophagic flux in tobacco by-2 cells

    Plant Signaling & Behavior 8:e22510.

    https://doi.org/10.4161/psb.22510

    • PubMed
    • Google Scholar
17. 1. He C
    2. Klionsky DJ

    (2009) Regulation mechanisms and signaling pathways of autophagy

    Annual Review of Genetics 43:67–93.

    https://doi.org/10.1146/annurev-genet-102808-114910

    • PubMed
    • Google Scholar
18. 1. Huang J
    2. Brumell JH

    (2014) Bacteria–autophagy interplay: a battle for survival

    Nature Reviews Microbiology 12:101–114.

    https://doi.org/10.1038/nrmicro3160

    • PubMed
    • Google Scholar
19. 1. Ivanov S
    2. Fedorova E
    3. Bisseling T

    (2010) Intracellular plant microbe associations: secretory pathways and the formation of perimicrobial compartments

    Current Opinion in Plant Biology 13:372–377.

    https://doi.org/10.1016/j.pbi.2010.04.005

    • PubMed
    • Google Scholar
20. 1. Kalvari I
    2. Tsompanis S
    3. Mulakkal NC
    4. Osgood R
    5. Johansen T
    6. Nezis IP
    7. Promponas VJ

    (2014) ILIR

    Autophagy 10:913–925.

    https://doi.org/10.4161/auto.28260

    • PubMed
    • Google Scholar
21. 1. Karimi M
    2. Inzé D
    3. Depicker A

    (2002) GATEWAY vectors for agrobacterium-mediated plant transformation

    Trends in Plant Science 7:193–195.

    https://doi.org/10.1016/S1360-1385(02)02251-3

    • PubMed
    • Google Scholar
22. 1. Kumar S
    2. Tamura K
    3. Jakobsen IB
    4. Nei M

    (2001) MEGA2: molecular evolutionary genetics analysis software

    Bioinformatics 17:1244–1245.

    https://doi.org/10.1093/bioinformatics/17.12.1244

    • PubMed
    • Google Scholar
23. 1. Kwon C
    2. Neu C
    3. Pajonk S
    4. Yun HS
    5. Lipka U
    6. Humphry M
    7. Bau S
    8. Straus M
    9. Kwaaitaal M
    10. Rampelt H
    11. Kasmi FE
    12. Jürgens G
    13. Parker J
    14. Panstruga R
    15. Lipka V
    16. Schulze-Lefert P

    (2008) Co-option of a default secretory pathway for plant immune responses

    Nature 451:835–840.

    https://doi.org/10.1038/nature06545

    • PubMed
    • Google Scholar
24. 1. Lamb CA
    2. Yoshimori T
    3. Tooze SA

    (2013) The autophagosome: origins unknown, biogenesis complex

    Nature Reviews Molecular Cell Biology 14:759–774.

    https://doi.org/10.1038/nrm3696

    • PubMed
    • Google Scholar
25. 1. Larkin MA
    2. Blackshields G
    3. Brown NP
    4. Chenna R
    5. McGettigan PA
    6. McWilliam H
    7. Valentin F
    8. Wallace IM
    9. Wilm A
    10. Lopez R
    11. Thompson JD
    12. Gibson TJ
    13. Higgins DG

    (2007) Clustal w and clustal x version 2.0

    Bioinformatics 23:2947–2948.

    https://doi.org/10.1093/bioinformatics/btm404

    • PubMed
    • Google Scholar
26. 1. Lenz HD
    2. Haller E
    3. Melzer E
    4. Gust AA
    5. Nürnberger T

    (2011) Autophagy controls plant basal immunity in a pathogenic lifestyle-dependent manner

    Autophagy 7:773–774.

    https://doi.org/10.4161/auto.7.7.15535

    • PubMed
    • Google Scholar
27. 1. Li F
    2. Vierstra RD

    (2012) Autophagy: a multifaceted intracellular system for bulk and selective recycling

    Trends in Plant Science 17:526–537.

    https://doi.org/10.1016/j.tplants.2012.05.006

    • PubMed
    • Google Scholar
28. 1. Lipka V
    2. Panstruga R

    (2005) Dynamic cellular responses in plant–microbe interactions

    Current Opinion in Plant Biology 8:625–631.

    https://doi.org/10.1016/j.pbi.2005.09.006

    • PubMed
    • Google Scholar
29. 1. Liu Y
    2. Schiff M
    3. Dinesh-Kumar SP

    (2002) Virus-induced gene silencing in tomato

    The Plant Journal 31:777–786.

    https://doi.org/10.1046/j.1365-313X.2002.01394.x

    • PubMed
    • Google Scholar
30. 1. Lv X
    2. Pu X
    3. Qin G
    4. Zhu T
    5. Lin H

    (2014) The roles of autophagy in development and stress responses in arabidopsis thaliana

    Apoptosis 19:905–921.

    https://doi.org/10.1007/s10495-014-0981-4

    • PubMed
    • Google Scholar
31. 1. Morgan W
    2. Kamoun S

    (2007) RXLR effectors of plant pathogenic oomycetes

    Current Opinion in Microbiology 10:332–338.

    https://doi.org/10.1016/j.mib.2007.04.005

    • PubMed
    • Google Scholar
32. 1. Mostowy S

    (2013) Autophagy and bacterial clearance: a not so clear picture

    Cellular Microbiology 15:395–402.

    https://doi.org/10.1111/cmi.12063

    • PubMed
    • Google Scholar
33. 1. Oh S-K
    2. Young C
    3. Lee M
    4. Oliva R
    5. Bozkurt TO
    6. Cano LM
    7. Win J
    8. Bos JIB
    9. Liu H-Y
    10. van Damme M
    11. Morgan W
    12. Choi D
    13. Van der Vossen EAG
    14. Vleeshouwers VGAA
    15. Kamoun S

    (2009) In planta expression screens of phytophthora infestans RXLR effectors reveal diverse phenotypes, including activation of the solanum bulbocastanum disease resistance protein rpi-blb2

    The Plant Cell Online 21:2928–2947.

    https://doi.org/10.1105/tpc.109.068247

    • PubMed
    • Google Scholar
34. 1. Patel S
    2. Dinesh-Kumar SP

    (2008) Arabidopsis ATG6 is required to limit the pathogen-associated cell death response

    Autophagy 4:20–27.

    https://doi.org/10.4161/auto.5056

    • PubMed
    • Google Scholar
35. 1. Petre B
    2. Saunders DGO
    3. Sklenar J
    4. Lorrain C
    5. Win J
    6. Duplessis S
    7. Kamoun S

    (2015) Candidate effector proteins of the rust pathogen melampsora larici-populina target diverse plant cell compartments

    Molecular Plant-Microbe Interactions 28:689–700.

    https://doi.org/10.1094/MPMI-01-15-0003-R

    • PubMed
    • Google Scholar
36. 1. Randow F
    2. Youle RJ

    (2014) Self and nonself: how autophagy targets mitochondria and bacteria

    Cell Host & Microbe 15:403–411.

    https://doi.org/10.1016/j.chom.2014.03.012

    • PubMed
    • Google Scholar
37. 1. Randow F

    (2011) How cells deploy ubiquitin and autophagy to defend their cytosol from bacterial invasion

    Autophagy 7:304–309.

    https://doi.org/10.4161/auto.7.3.14539

    • PubMed
    • Google Scholar
38. 1. Saunders DGO
    2. Breen S
    3. Win J
    4. Schornack S
    5. Hein I
    6. Bozkurt TO
    7. Champouret N
    8. Vleeshouwers VGAA
    9. Birch PRJ
    10. Gilroy EM
    11. Kamoun S

    (2012) Host protein BSL1 associates with phytophthora infestans RXLR effector AVR2 and the solanum demissum immune receptor R2 to mediate disease resistance

    The Plant Cell 24:3420–3434.

    https://doi.org/10.1105/tpc.112.099861

    • PubMed
    • Google Scholar
39. 1. Segonzac C
    2. Feike D
    3. Gimenez-Ibanez S
    4. Hann DR
    5. Zipfel C
    6. Rathjen JP

    (2011) Hierarchy and roles of pathogen-associated molecular pattern-induced responses in nicotiana benthamiana

    Plant Physiology 156:687–699.

    https://doi.org/10.1104/pp.110.171249

    • PubMed
    • Google Scholar
40. 1. Shintani T
    2. Klionsky DJ

    (2004) Autophagy in health and disease: a double-edged sword

    Science 306:990–995.

    https://doi.org/10.1126/science.1099993

    • PubMed
    • Google Scholar
41. 1. Song J
    2. Win J
    3. Tian M
    4. Schornack S
    5. Kaschani F
    6. Ilyas M
    7. van der Hoorn RAL
    8. Kamoun S

    (2009) Apoplastic effectors secreted by two unrelated eukaryotic plant pathogens target the tomato defense protease Rcr3

    Proceedings of the National Academy of Sciences of the United States of America 106:1654–1659.

    https://doi.org/10.1073/pnas.0809201106

    • PubMed
    • Google Scholar
42. 1. Stolz A
    2. Ernst A
    3. Dikic I

    (2014) Cargo recognition and trafficking in selective autophagy

    Nature Cell Biology 16:495–501.

    https://doi.org/10.1038/ncb2979

    • PubMed
    • Google Scholar
43. 1. Svenning S
    2. Lamark T
    3. Krause K
    4. Johansen T

    (2011) Plant NBR1 is a selective autophagy substrate and a functional hybrid of the mammalian autophagic adapters NBR1 and p62/SQSTM1

    Autophagy 7:993–1010.

    https://doi.org/10.4161/auto.7.9.16389

    • PubMed
    • Google Scholar
44. 1. Teh O-K
    2. Hofius D

    (2014) Membrane trafficking and autophagy in pathogen-triggered cell death and immunity

    Journal of Experimental Botany 65:1297–1312.

    https://doi.org/10.1093/jxb/ert441

    • PubMed
    • Google Scholar
45. 1. Vanhee C
    2. Batoko H

    (2011) Autophagy involvement in responses to abscisic acid by plant cells

    Autophagy 7:655–656.

    https://doi.org/10.4161/auto.7.6.15307

    • PubMed
    • Google Scholar
46. 1. Wang D
    2. Griffitts J
    3. Starker C
    4. Fedorova E
    5. Limpens E
    6. Ivanov S
    7. Bisseling T
    8. Long S

    (2010) A nodule-specific protein secretory pathway required for nitrogen-fixing symbiosis

    Science 327:1126–1129.

    https://doi.org/10.1126/science.1184096

    • PubMed
    • Google Scholar
47. 1. Win J
    2. Krasileva KV
    3. Kamoun S
    4. Shirasu K
    5. Staskawicz BJ
    6. Banfield MJ
    7. Heitman J

    (2012) Sequence divergent RXLR effectors share a structural fold conserved across plant pathogenic oomycete species

    PLoS Pathogens 8:e1002400.

    https://doi.org/10.1371/journal.ppat.1002400

    • PubMed
    • Google Scholar
48. 1. Yoshimoto K
    2. Jikumaru Y
    3. Kamiya Y
    4. Kusano M
    5. Consonni C
    6. Panstruga R
    7. Ohsumi Y
    8. Shirasu K

    (2009) Autophagy negatively regulates cell death by controlling NPR1-dependent salicylic acid signaling during senescence and the innate immune response in arabidopsis

    The Plant Cell Online 21:2914–2927.

    https://doi.org/10.1105/tpc.109.068635

    • PubMed
    • Google Scholar
49. 1. Zientara-Rytter K
    2. Łukomska J
    3. Moniuszko G
    4. Gwozdecki R
    5. Surowiecki P
    6. Lewandowska M
    7. Liszewska F
    8. Wawrzyńska A
    9. Sirko A

    (2011) Identification and functional analysis of Joka2, a tobacco member of the family of selective autophagy cargo receptors

    Autophagy 7:1145–1158.

    https://doi.org/10.4161/auto.7.10.16617

    • PubMed
    • Google Scholar

Author details

1. Yasin F Dagdas

   The Sainsbury Laboratory, Norwich, United Kingdom

   Contribution

   YFD, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Contributed equally with

   Khaoula Belhaj

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-9502-355X

2. Khaoula Belhaj

   The Sainsbury Laboratory, Norwich, United Kingdom

   Contribution

   KB, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Contributed equally with

   Yasin F Dagdas

   Competing interests

   The authors declare that no competing interests exist.

3. Abbas Maqbool

   Department of Biological Chemistry, John Innes Centre, Norwich, United Kingdom

   Contribution

   AM, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

4. Angela Chaparro-Garcia

   The Sainsbury Laboratory, Norwich, United Kingdom

   Contribution

   AC-G, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

5. Pooja Pandey

   Department of Life Sciences, Imperial College London, London, United Kingdom

   Contribution

   PP, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

6. Benjamin Petre

   The Sainsbury Laboratory, Norwich, United Kingdom

   Contribution

   BP, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

7. Nadra Tabassum

   Department of Life Sciences, Imperial College London, London, United Kingdom

   Contribution

   NT, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-2722-9441

8. Neftaly Cruz-Mireles

   The Sainsbury Laboratory, Norwich, United Kingdom

   Contribution

   NC-M, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

9. Richard K Hughes

   Department of Biological Chemistry, John Innes Centre, Norwich, United Kingdom

   Contribution

   RKH, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

10. Jan Sklenar

    The Sainsbury Laboratory, Norwich, United Kingdom

    Contribution

    JS, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

11. Joe Win

    The Sainsbury Laboratory, Norwich, United Kingdom

    Contribution

    JW, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

12. Frank Menke

    The Sainsbury Laboratory, Norwich, United Kingdom

    Contribution

    FM, Conception and design, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

13. Kim Findlay

    Department of Cell and Developmental Biology, John Innes Centre, Norwich, United Kingdom

    Contribution

    KF, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

14. Mark J Banfield

    Department of Biological Chemistry, John Innes Centre, Norwich, United Kingdom

    Contribution

    MJB, Conception and design, Analysis and interpretation of data, Drafting or revising the article

    Competing interests

    The authors declare that no competing interests exist.

    "This ORCID iD identifies the author of this article:" 0000-0001-8921-3835

15. Sophien Kamoun

    The Sainsbury Laboratory, Norwich, United Kingdom

    Contribution

    SK, Conception and design, Analysis and interpretation of data, Drafting or revising the article

    For correspondence

    sophien.kamoun@tsl.ac.uk

    Competing interests

    The authors declare that no competing interests exist.

    "This ORCID iD identifies the author of this article:" 0000-0002-0290-0315

16. Tolga O Bozkurt

    1. The Sainsbury Laboratory, Norwich, United Kingdom
    2. Department of Life Sciences, Imperial College London, London, United Kingdom

    Contribution

    TOB, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

    For correspondence

    o.bozkurt@imperial.ac.uk

    Competing interests

    The authors declare that no competing interests exist.

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