Recent research demonstrates that undermining interactions between pathogen effectors and their host target proteins can reduce infection. As more effector–target pairs are identified, their structures and interaction surfaces exposed, and there is the possibility of making multiple edits to diverse plant genomes, the desire to convert crops to nonhosts could become reality.</p

Birch, Paul R. J.

Boevink, Petra C.

McLellan, Hazel

English

Discovery Research Portal

                                                                    University of DundeeHow to convert host plants into nonhostsMcLellan, Hazel; Boevink, Petra C.; Birch, Paul R. J.Published in:Trends in Plant ScienceDOI:10.1016/j.tplants.2023.05.008Publication date:2023Licence:CC BYDocument VersionPublisher's PDF, also known as Version of recordLink to publication in Discovery Research PortalCitation for published version (APA):McLellan, H., Boevink, P. C., & Birch, P. R. J. (2023). How to convert host plants into nonhosts. Trends in PlantScience, 28(8), 876-879. https://doi.org/10.1016/j.tplants.2023.05.008General rightsCopyright and moral rights for the publications made accessible in Discovery Research Portal are retained by the authors and/or othercopyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated withthese rights. • Users may download and print one copy of any publication from Discovery Research Portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain. • You may freely distribute the URL identifying the publication in the public portal.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 31. Jul. 2023Trends inPlant ScienceGlossaryAlphaFold2 (AF2): a computer program usingartificial intelligence to predict protein structuralinformation from amino acid sequences.Apoplast: the intercellular area between plant cells.CRISPR-Cas9: a gene editing tool, derived fromForumHow to convert hostplants into nonhostsHazel McLellan ,1Petra C. Boevink ,2 and bacteria, which uses RNA to guide a nuclease tocreate breaks in target DNA; this can either knock outthe gene or be repaired to encode a specificsequence.Effectors: proteins secreted by plant pathogenswhich act inside or outside plant cells to promotepathogenesis.Effector-triggered immunity (ETI): the second layerof plant defence, a stronger response triggered by therecognition of effectors or effector activity by plantnucleotide-binding, leucine-rich repeat receptors.Gene editing: the insertion, deletion, or replacementof DNA in the genome of an organism.Orthologue: genes from different species originatingfrom a common ancestral gene.Pattern-triggered immunity: the first layer of plantdefence triggered by the perception of pathogenassociated molecular patterns by pattern recognitionreceptors.Paul R.J. Birch 1,2,*Recent research demonstrates thatundermining interactions betweenpathogen effectors and their hosttarget proteins can reduce infec-tion. As more effector–target pairsare identified, their structures andinteraction surfaces exposed, andthere is the possibility of makingmultiple edits to diverse plant ge-nomes, the desire to convert cropsto nonhosts could become reality.Nonhost resistance (NHR) prevents infec-tion of a plant by most microbial speciesand, as such, is anticipated to be broad-spectrum and durable. The molecularbasis of NHR is poorly understood, al-though anticipated to be composed ofthe same mechanisms as host resistance[1]. Infection of plants by pathogenic mi-croorganisms involves the deployment ofvirulence proteins called effectors (seeGlossary) that act either on the outside ofplant cells (apoplastic effectors) or aredelivered inside living plant cells (cytoplas-mic effectors) to suppress immunity [2].More than a decade ago, Schulze-Lefertand Panstruga [3] hypothesised thatNHR in plants that are closely relatedto the host plant would be mainly drivenby perception of effector activities bynucleotide-binding, leucine-rich-repeatreceptors (NLRs), resulting in effector-triggered immunity (ETI). By contrast,in distantly related plants NHR would bemore likely due to failure of effectors tointeract with or properly manipulate theirtarget proteins, due to not being appropri-ately adapted to do so at the protein876 Trends in Plant Science, August 2023, Vol. 28, No. 8sequence or structural level. The conse-quence would be a greater likelihood ofNHR being driven by pattern-triggeredimmunity.Biochemical evidence of the latter wassupported by Dong et al. [4], who revealedthat the apoplastic effector EPIC1 frompotato late blight pathogen Phytophthorainfestans, which inhibits the defence pro-tease RCR3 in potato, poorly inhibits pro-tease activity of an RCR3 homologue,MRP2, in the nonhost plant Mirabilisjalapa. By contrast, the pathogen effectororthologue PmEPIC1 in the sister spe-cies Phytophthora mirabilis, which infectsM. jalapa, strongly inhibits MRP2 but onlypoorly inhibits RCR3 from potato. Struc-tural comparisons to the tarocystatin in-hibitor interaction with papain proteaserevealed a polymorphic site, Gln111Arg,between EPIC1 from P. infestans andPmEPIC1 of P. mirabilis, mutation ofwhich recapitulated inhibitor activitiesagainst RCR3 and MRP2 [4]. The studyprovided strong evidence supporting aneed for pathogen effectors to coevolvewith their targets to appropriately manipu-late them but fell short of demonstratingthat this can determine host range. Towhat extent does failure of effectors tointeract with targets, or to modulatetheir activities, contribute to NHR? Weexamine this question from the viewpointof biotrophic and hemi-biotrophic filamen-tous (oomycete and fungal) pathogens,but note that it may apply to other patho-gens where effector manipulation of hosttargets is essential to create a susceptibleenvironment.Breakdown in nonhost effector–target interactions boosts diseaseresistanceA recent paper [5] demonstrated thatcytoplasmic RxLR effectors from twooomycetes, potato pathogen P. infestansand Arabidopsis (Arabidopsis thaliana)pathogenHyaloperonospora arabidopsidis,enhanced susceptibility when expressed intheir host plants but generally performedpoorly when expressed in the nonhostpathosystem. Given that there was no evi-dence of effector recognition leading toETI, likely explanations for this failure topromote colonisation are: (i) that the effec-tors fail to appropriately suppress immunityin the nonhost plant, or (ii) that the require-ments for infection of these two pathogensare quite different, one of which is ahemibiotroph and the other an obligatebiotroph.Following yeast-2-hybrid (Y2H) screenswith 64 P. infestans RXLR effectors, poten-tial target proteins from potato were identi-fied for 40 of them. Candidate orthologuesof these (cAtOrths) were cloned fromarabidopsis, which is a nonhost forP. infestans. A matrix Y2H screen was per-formed of the cAtOrths with the 64 RXLReffectors from P. infestans and 169 fromH. arabidopsidis.Whereas few P. infestanseffector–target interactions were conservedfrom potato to arabidopsis, there wasenrichment of RXLR effectors fromH. arabidopsidis interacting with cAtOrths[5]. The failure of many P. infestans RXLRsTrends in Plant ScienceFigure 1. A pathway from host to nonhost. We suggest that the steps that could result in the conversion oa host plant into a nonhost can include: (1) selecting effectors that are conservedbetween all isolates of the pathogen(core effectors) and are fully or partially essential for infection. (2) For each effector, identify the host target protein(blue shape; interaction represented by dashed lines) using methods such as yeast-2-hybrid (Y2H)coimmunoprecipitation, or proximity labelling. (3) Narrow down the critical interacting region, which could be doneusing Y2H analysis with truncations (red lines) of the target protein. (4) To focus further into the critical regionidentify noninteracting nonhost orthologue(s) (purple shape). (5) Use modelling tools such as AlphaFold2 to identifysurface-exposed residues in the putative interface between effector and target and how they differ in the nonhosorthologue (purple spots for residues in the interacting host target, yellow spots for equivalent residues in thenoninteracting orthologue). (6) Mutate these potential key residues to the equivalent residues in the nonhosorthologue (yellow spots) and determine whether this breaks the interaction with the effector. The order of steps (3to (5) can be diversified. (7) Express the noninteracting mutants of the target in host plants and determine whethethis reduces infection (brown patches represent infection). (8) Mutations in host target proteins that reduceinfection in the overexpression experiments can be recapitulated using CRISPR gene editing (GE) in the host plantsTrends in Plant Scienceto interact with cAtOrths, including severalwhose potato targets have been function-ally verified, is consistent with the hypothe-sis that there may be sequence/structuraldiversity in the equivalent proteins indistant nonhost plants, at least in theregions of effector interaction [3]. As anexample, the effector Pi06087/PiSFI3from P. infestans, which targets a potatoprotein StUBK/StPUB33, fails to inter-act with the arabidopsis orthologue,AtPUB33. Expression of Pi06087 in hostplants, such as Nicotiana benthamiana,enhances P. infestans colonisation. How-ever, no such increased susceptibility toH. arabidopsidis was observed when ex-pressing Pi06087 in arabidopsis, consistentwith it failing to interact with, and thus ma-nipulate, AtPUB33 [5].Critically, transgenic expression ofAtPUB33 in the host plants potato andN. benthamiana resulted in a small butsignificant reduction in P. infestans coloni-sation. Moreover, effector Pi06087 no lon-ger enhanced P. infestans colonisation intransgenic N. benthamiana expressingAtPUB33 [5]. These observations suggestthat breakdown in effector–target interac-tions can be exploited to provide diseaseresistance. This supports a hypothesisthat, if we know the precise points ofinteraction between effector and targetproteins, we may alter the latter to under-mine effector activity and reduce infection.What factors need to be considered toconvert a host plant into a nonhost byaltering effector targets?Using knowledge of effectoressentiality, targets, and activitiesto design nonhost plantsAn initial key question to address is: whicheffector–target interactions to focus on?Addressing the effectors first, we arguethat it is important to identify those thatare partially or entirely essential for infec-tion (Figure 1, step 1). It should be notedthat the activities of some essential effec-tors may be monitored by NLRs andbreakdown in the effector–target interac-tion could prevent that ETI. Nevertheless,effector essentiality implies that failure toTrends in Plant Science, August 2023, Vol. 28, No. 8 877f,,tt)r.appropriately manipulate their targetswould attenuate infection regardless ofNLR monitoring activity. FilamentousTrends in Plant Sciencepathogens such as fungi and oomycetespotentially secrete hundreds of effectors,many of which are likely to be functionallyredundant, and yet essential effectors, orgroups of effectors, are often observed[6]. Recently, 27 ‘core’ effectors wereidentified in Colletotrichum orbiculare,based on conservation of sequence andin planta expression across pathogenisolates. C. orbiculare has a broad hostrange and infects members of the distantlyrelated Solanaceae and Cucurbitaceae.Five effectors were identified that,when collectively knocked out usingCRISPR-Cas9, reduced infection on cu-cumber and melon (Cucurbitaceae) andN. benthamiana (Solanaceae), suggestingthat they acted redundantly to perform anessential function(s) for infection. Interest-ingly, independent knockouts of four differ-ent effectors, singly or in combination,compromised infection of cucumber andmelon, but not N. benthamiana [7]. This re-inforces the notion that effectors whichpromote susceptibility in one host plantdo not necessarily function in a distantly re-lated plant, even one that is a host. Host-specific effectors in fungal plant pathogenshave also been described in associationwith conditionally dispensable (CD) chro-mosomes. A recent example reports twohost-specific SIX-like effectors in Fusariumoxysporum f. sp. conglutinans that residein CD chromosomes and suppressarabidopsis-specific phytoalexin produc-tion [8]. Collectively, these are examplessupporting the observation that effectoractivities may be attuned to some hostsand not others; undermining them can re-duce host range. The next challenge is toidentify their targets (Figure 1, step 2).Once targets have been discovered, theconsideration is how best to prevent inter-action between a pathogen effector andits host target whilst retaining the functionof the latter. A potential next step is to nar-row down interacting regions of effectorswithin their targets, which could, for exam-ple, be done using Y2H with host protein878 Trends in Plant Science, August 2023, Vol. 28, No. 8truncations (Figure 1, step 3). Cautionmust be taken to avoid truncations thatfail to interact due to protein misfolding.Which amino acids in the interactingregion need to be changed to prevent ef-fector interaction? In the aforementionedexample [5], orthologues of host effectortargets were selected from the nonhostplant arabidopsis (cAtOrths) that didnot interact with P. infestans effectors(Figure 1, step 4). Transgenic host potatoor N. benthamiana plants were generatedexpressing the effector-noninteractingnonhost protein AtPUB33, leading to re-duced host susceptibility. However, givencontinued challenges of using transgenicplants, we propose that the precise pointsof contact between effectors and theirhost targets need to be determined and al-tered by alternative means, such as geneediting [9,10]. Having defined the interac-tion region, the sequence differences inthis region between the host protein andnoninteracting orthologues from nonhostswill guide how and where to make aminoacid changes to undermine effector inter-action, confident in the assumption thatsuch changes may not prevent the endog-enous function of the host protein, asthese differences are tolerated in thenonhost equivalent (Figure 1, step 4).To identify more precise changes to makein the effector-interacting regions of hosttarget proteins, structural predictions mayreveal exposed amino acids that representeffector docking sites at the interface be-tween the proteins. The development ofAlphaFold2 (AF2) for accurate predictionof protein structures [11] is revolutionisingour understanding of effector protein evo-lution [12] and accelerating studies of pro-tein–protein interactions. Recently AF2-multimer was used to accurately identifyboth validated and previously unknownATG8-interaction motifs in interactingproteins in plants and animals and inpathogen effectors that target ATG8[13]. Whilst it is preferable to generate co-complex effector–target structures tobiochemically verify interaction sites, theartificial intelligence-driven understandingof protein structures promises to greatlyaccelerate the resolution of precise inter-action points between effectors andtheir targets (Figure 1, step 5). Mutanttarget forms can be tested in medium-throughput methods such as Y2H to iden-tify those that fail to interact with effectors(Figure 1, step 6). If transient expressionsystems are available multiple mutated tar-gets can be tested, singly or in combina-tion, to identify those that reduce hostsusceptibility [5] (Figure 1, step 7).How many essential effector–target inter-actions need to be compromised toconvert a host plant into a nonhost?This is difficult to predict, given the evolu-tionary potential of many pathogens, butsafer to assume that attenuating multipleinteractions would create an enduring bar-rier to infection. Single-site alterationswould best be done using CRISPR-Cassystems based on minimal changesneeded to break effector–target interac-tions (Figure 1, step 8). Potentially, multiplegene-editing changes can be made simul-taneously, as demonstrated for a range ofcrops [9,10].Given the advances in identifying filamen-tous pathogen effectors and their tar-gets, the development of powerful toolsto predict protein structure, and thepotential to precisely edit multiple siteswithin plant genomes, it is timely to con-sider how to convert host plants intononhosts by undermining effector–targetinteractions.AcknowledgmentsP.R.J.B., H.M., and P.C.B are supported by theBiotechnology and Biological Sciences ResearchCouncil grant BB/S003096/1; European ResearchCouncil (ERC)-Advanced grant PathEVome (787764);and Scottish Government Rural and EnvironmentScience and Analytical Services Division (RESAS).Declaration of interestsNo interests are declared.Trends in Plant Science1Division of Plant Science, School of Life Sciences, University ofDundee, @James Hutton Institute, Errol Road, Invergowrie,Dundee DD2 5DA, UK2Cell and Molecular Sciences, James Hutton Institute, ErrolRoad, Invergowrie, Dundee DD2 5DA, UK*Correspondence:paul.birch@hutton.ac.uk; P.Birch@dundee.ac.uk (P.R.J. Birch).https://doi.org/10.1016/j.tplants.2023.05.008Crown Copyright © 2023 Published by Elsevier Ltd. This is anopen access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).References1. Panstruga, R. and Moscou, M.J. (2020) What is the molecu-lar basis of nonhost resistance?Mol. Plant-Microbe Interact.33, 1253–12642. Jones, J.D. and Dangl, J.L. (2006) The plant immunesystem. Nature 444, 323–3293. Schulze-Lefert, P. and Panstruga, R. (2011) A molecularevolutionary concept connecting nonhost resistance, path-ogen host range, and pathogen speciation. Trends PlantSci. 16, 117–1254. Dong, S. et al. (2014) Effector specialization in a lineageof the Irish potato famine pathogen. Science 343,552–5555. McLellan, H. et al. (2022) Exploiting breakdown in nonhosteffector–target interactions to boost host disease resis-tance. Proc. Natl. Acad. Sci. U. S. A. 119, e21140641196. Thordal-Christensen, H. et al. (2018) Why did filamentousplant pathogens evolve the potential to secrete hundredsof effectors to enable disease? Mol. Plant Pathol. 19, 7817. Inoue, Y. et al. (2023) Selective deployment of virulence ef-fectors correlates with host specificity in a fungal plantpathogen. New Phytol. 238, 1578–15928. Ayukawa, Y. et al. (2021) A pair of effectors encodedon a conditionally dispensable chromosome of Fusariumoxysporum suppress host-specific immunity. Commun.Biol. 4, 7079. Selma, S. et al. (2023) Clustered regularly interspacedshort palindromic repeats tools for plant metabolic engi-neering: achievements and perspectives. Curr. Opin.Biotechnol. 79, 10285610. Gupta, A. et al. (2023) CRISPR-induced miRNA156-recognition element mutations in TaSPL13 improve multi-ple agronomic traits in wheat. Plant Biotechnol. J. 21,536–54811. Jumper, J. et al. (2021) Highly accurate protein structureprediction with AlphaFold. Nature 596, 583–58912. Seong, K. and Krasileva, K.V. (2023) Prediction of effectorprotein structures from fungal phytopathogens enablesevolutionary analyses. Nat. Microbiol. 8, 174–18713. Ibrahim, T. et al. (2023) AlphaFold2-multimer guided high-accuracy prediction of typical and atypical ATG8-bindingmotifs. PLoS Biol. 21, e3001962Trends in Plant Science, August 2023, Vol. 28, No. 8 879

How to convert host plants into nonhosts

Hazel McLellan

Petra C. Boevink

Paul R.J. Birch

Crossref

                                                                    University of DundeeHow to convert host plants into nonhostsMcLellan, Hazel; Boevink, Petra C.; Birch, Paul R. J.Published in:Trends in Plant ScienceDOI:10.1016/j.tplants.2023.05.008Publication date:2023Licence:CC BYDocument VersionPublisher's PDF, also known as Version of recordLink to publication in Discovery Research PortalCitation for published version (APA):McLellan, H., Boevink, P. C., & Birch, P. R. J. (2023). How to convert host plants into nonhosts. Trends in PlantScience, 28(8), 876-879. https://doi.org/10.1016/j.tplants.2023.05.008General rightsCopyright and moral rights for the publications made accessible in Discovery Research Portal are retained by the authors and/or othercopyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated withthese rights.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 25. Sep. 2025ForumHow to convert hostplants into nonhostsHazel McLellan ,1Petra C. Boevink ,2 andPaul R.J. Birch 1,2,*Recent research demonstrates thatundermining interactions betweenpathogen effectors and their hosttarget proteins can reduce infec-tion. As more effector–target pairsare identified, their structures andinteraction surfaces exposed, andthere is the possibility of makingmultiple edits to diverse plant ge-nomes, the desire to convert cropsto nonhosts could become reality.Nonhost resistance (NHR) prevents infec-tion of a plant by most microbial speciesand, as such, is anticipated to be broad-spectrum and durable. The molecularbasis of NHR is poorly understood, al-though anticipated to be composed ofthe same mechanisms as host resistance[1]. Infection of plants by pathogenic mi-croorganisms involves the deployment ofvirulence proteins called effectors (seeGlossary) that act either on the outside ofplant cells (apoplastic effectors) or aredelivered inside living plant cells (cytoplas-mic effectors) to suppress immunity [2].More than a decade ago, Schulze-Lefertand Panstruga [3] hypothesised thatNHR in plants that are closely relatedto the host plant would be mainly drivenby perception of effector activities bynucleotide-binding, leucine-rich-repeatreceptors (NLRs), resulting in effector-triggered immunity (ETI). By contrast,in distantly related plants NHR would bemore likely due to failure of effectors tointeract with or properly manipulate theirtarget proteins, due to not being appropri-ately adapted to do so at the proteinsequence or structural level. The conse-quence would be a greater likelihood ofNHR being driven by pattern-triggeredimmunity.Biochemical evidence of the latter wassupported by Dong et al. [4], who revealedthat the apoplastic effector EPIC1 frompotato late blight pathogen Phytophthorainfestans, which inhibits the defence pro-tease RCR3 in potato, poorly inhibits pro-tease activity of an RCR3 homologue,MRP2, in the nonhost plant Mirabilisjalapa. By contrast, the pathogen effectororthologue PmEPIC1 in the sister spe-cies Phytophthora mirabilis, which infectsM. jalapa, strongly inhibits MRP2 but onlypoorly inhibits RCR3 from potato. Struc-tural comparisons to the tarocystatin in-hibitor interaction with papain proteaserevealed a polymorphic site, Gln111Arg,between EPIC1 from P. infestans andPmEPIC1 of P. mirabilis, mutation ofwhich recapitulated inhibitor activitiesagainst RCR3 and MRP2 [4]. The studyprovided strong evidence supporting aneed for pathogen effectors to coevolvewith their targets to appropriately manipu-late them but fell short of demonstratingthat this can determine host range. Towhat extent does failure of effectors tointeract with targets, or to modulatetheir activities, contribute to NHR? Weexamine this question from the viewpointof biotrophic and hemi-biotrophic filamen-tous (oomycete and fungal) pathogens,but note that it may apply to other patho-gens where effector manipulation of hosttargets is essential to create a susceptibleenvironment.Breakdown in nonhost effector–target interactions boosts diseaseresistanceA recent paper [5] demonstrated thatcytoplasmic RxLR effectors from twooomycetes, potato pathogen P. infestansand Arabidopsis (Arabidopsis thaliana)pathogenHyaloperonospora arabidopsidis,enhanced susceptibility when expressed intheir host plants but generally performedpoorly when expressed in the nonhostpathosystem. Given that there was no evi-dence of effector recognition leading toETI, likely explanations for this failure topromote colonisation are: (i) that the effec-tors fail to appropriately suppress immunityin the nonhost plant, or (ii) that the require-ments for infection of these two pathogensare quite different, one of which is ahemibiotroph and the other an obligatebiotroph.Following yeast-2-hybrid (Y2H) screenswith 64 P. infestans RXLR effectors, poten-tial target proteins from potato were identi-fied for 40 of them. Candidate orthologuesof these (cAtOrths) were cloned fromarabidopsis, which is a nonhost forP. infestans. A matrix Y2H screen was per-formed of the cAtOrths with the 64 RXLReffectors from P. infestans and 169 fromH. arabidopsidis.Whereas few P. infestanseffector–target interactions were conservedfrom potato to arabidopsis, there wasenrichment of RXLR effectors fromH. arabidopsidis interacting with cAtOrths[5]. The failure of many P. infestans RXLRsGlossaryAlphaFold2 (AF2): a computer program usingartificial intelligence to predict protein structuralinformation from amino acid sequences.Apoplast: the intercellular area between plant cells.CRISPR-Cas9: a gene editing tool, derived frombacteria, which uses RNA to guide a nuclease tocreate breaks in target DNA; this can either knock outthe gene or be repaired to encode a specificsequence.Effectors: proteins secreted by plant pathogenswhich act inside or outside plant cells to promotepathogenesis.Effector-triggered immunity (ETI): the second layerof plant defence, a stronger response triggered by therecognition of effectors or effector activity by plantnucleotide-binding, leucine-rich repeat receptors.Gene editing: the insertion, deletion, or replacementof DNA in the genome of an organism.Orthologue: genes from different species originatingfrom a common ancestral gene.Pattern-triggered immunity: the first layer of plantdefence triggered by the perception of pathogenassociated molecular patterns by pattern recognitionreceptors.876 Trends in Plant Science, August 2023, Vol. 28, No. 8Trends inPlant Scienceto interact with cAtOrths, including severalwhose potato targets have been function-ally verified, is consistent with the hypothe-sis that there may be sequence/structuraldiversity in the equivalent proteins indistant nonhost plants, at least in theregions of effector interaction [3]. As anexample, the effector Pi06087/PiSFI3from P. infestans, which targets a potatoprotein StUBK/StPUB33, fails to inter-act with the arabidopsis orthologue,AtPUB33. Expression of Pi06087 in hostplants, such as Nicotiana benthamiana,enhances P. infestans colonisation. How-ever, no such increased susceptibility toH. arabidopsidis was observed when ex-pressing Pi06087 in arabidopsis, consistentwith it failing to interact with, and thus ma-nipulate, AtPUB33 [5].Critically, transgenic expression ofAtPUB33 in the host plants potato andN. benthamiana resulted in a small butsignificant reduction in P. infestans coloni-sation. Moreover, effector Pi06087 no lon-ger enhanced P. infestans colonisation intransgenic N. benthamiana expressingAtPUB33 [5]. These observations suggestthat breakdown in effector–target interac-tions can be exploited to provide diseaseresistance. This supports a hypothesisthat, if we know the precise points ofinteraction between effector and targetproteins, we may alter the latter to under-mine effector activity and reduce infection.What factors need to be considered toconvert a host plant into a nonhost byaltering effector targets?Using knowledge of effectoressentiality, targets, and activitiesto design nonhost plantsAn initial key question to address is: whicheffector–target interactions to focus on?Addressing the effectors first, we arguethat it is important to identify those thatare partially or entirely essential for infec-tion (Figure 1, step 1). It should be notedthat the activities of some essential effec-tors may be monitored by NLRs andbreakdown in the effector–target interac-tion could prevent that ETI. Nevertheless,effector essentiality implies that failure toappropriately manipulate their targetswould attenuate infection regardless ofNLR monitoring activity. FilamentousTrends in Plant ScienceFigure 1. A pathway from host to nonhost. We suggest that the steps that could result in the conversion ofa host plant into a nonhost can include: (1) selecting effectors that are conservedbetween all isolates of the pathogen(core effectors) and are fully or partially essential for infection. (2) For each effector, identify the host target protein(blue shape; interaction represented by dashed lines) using methods such as yeast-2-hybrid (Y2H),coimmunoprecipitation, or proximity labelling. (3) Narrow down the critical interacting region, which could be doneusing Y2H analysis with truncations (red lines) of the target protein. (4) To focus further into the critical region,identify noninteracting nonhost orthologue(s) (purple shape). (5) Use modelling tools such as AlphaFold2 to identifysurface-exposed residues in the putative interface between effector and target and how they differ in the nonhostorthologue (purple spots for residues in the interacting host target, yellow spots for equivalent residues in thenoninteracting orthologue). (6) Mutate these potential key residues to the equivalent residues in the nonhostorthologue (yellow spots) and determine whether this breaks the interaction with the effector. The order of steps (3)to (5) can be diversified. (7) Express the noninteracting mutants of the target in host plants and determine whetherthis reduces infection (brown patches represent infection). (8) Mutations in host target proteins that reduceinfection in the overexpression experiments can be recapitulated using CRISPR gene editing (GE) in the host plants.Trends in Plant ScienceTrends in Plant Science, August 2023, Vol. 28, No. 8 877pathogens such as fungi and oomycetespotentially secrete hundreds of effectors,many of which are likely to be functionallyredundant, and yet essential effectors, orgroups of effectors, are often observed[6]. Recently, 27 ‘core’ effectors wereidentified in Colletotrichum orbiculare,based on conservation of sequence andin planta expression across pathogenisolates. C. orbiculare has a broad hostrange and infects members of the distantlyrelated Solanaceae and Cucurbitaceae.Five effectors were identified that,when collectively knocked out usingCRISPR-Cas9, reduced infection on cu-cumber and melon (Cucurbitaceae) andN. benthamiana (Solanaceae), suggestingthat they acted redundantly to perform anessential function(s) for infection. Interest-ingly, independent knockouts of four differ-ent effectors, singly or in combination,compromised infection of cucumber andmelon, but not N. benthamiana [7]. This re-inforces the notion that effectors whichpromote susceptibility in one host plantdo not necessarily function in a distantly re-lated plant, even one that is a host. Host-specific effectors in fungal plant pathogenshave also been described in associationwith conditionally dispensable (CD) chro-mosomes. A recent example reports twohost-specific SIX-like effectors in Fusariumoxysporum f. sp. conglutinans that residein CD chromosomes and suppressarabidopsis-specific phytoalexin produc-tion [8]. Collectively, these are examplessupporting the observation that effectoractivities may be attuned to some hostsand not others; undermining them can re-duce host range. The next challenge is toidentify their targets (Figure 1, step 2).Once targets have been discovered, theconsideration is how best to prevent inter-action between a pathogen effector andits host target whilst retaining the functionof the latter. A potential next step is to nar-row down interacting regions of effectorswithin their targets, which could, for exam-ple, be done using Y2H with host proteintruncations (Figure 1, step 3). Cautionmust be taken to avoid truncations thatfail to interact due to protein misfolding.Which amino acids in the interactingregion need to be changed to prevent ef-fector interaction? In the aforementionedexample [5], orthologues of host effectortargets were selected from the nonhostplant arabidopsis (cAtOrths) that didnot interact with P. infestans effectors(Figure 1, step 4). Transgenic host potatoor N. benthamiana plants were generatedexpressing the effector-noninteractingnonhost protein AtPUB33, leading to re-duced host susceptibility. However, givencontinued challenges of using transgenicplants, we propose that the precise pointsof contact between effectors and theirhost targets need to be determined and al-tered by alternative means, such as geneediting [9,10]. Having defined the interac-tion region, the sequence differences inthis region between the host protein andnoninteracting orthologues from nonhostswill guide how and where to make aminoacid changes to undermine effector inter-action, confident in the assumption thatsuch changes may not prevent the endog-enous function of the host protein, asthese differences are tolerated in thenonhost equivalent (Figure 1, step 4).To identify more precise changes to makein the effector-interacting regions of hosttarget proteins, structural predictions mayreveal exposed amino acids that representeffector docking sites at the interface be-tween the proteins. The development ofAlphaFold2 (AF2) for accurate predictionof protein structures [11] is revolutionisingour understanding of effector protein evo-lution [12] and accelerating studies of pro-tein–protein interactions. Recently AF2-multimer was used to accurately identifyboth validated and previously unknownATG8-interaction motifs in interactingproteins in plants and animals and inpathogen effectors that target ATG8[13]. Whilst it is preferable to generate co-complex effector–target structures tobiochemically verify interaction sites, theartificial intelligence-driven understandingof protein structures promises to greatlyaccelerate the resolution of precise inter-action points between effectors andtheir targets (Figure 1, step 5). Mutanttarget forms can be tested in medium-throughput methods such as Y2H to iden-tify those that fail to interact with effectors(Figure 1, step 6). If transient expressionsystems are available multiple mutated tar-gets can be tested, singly or in combina-tion, to identify those that reduce hostsusceptibility [5] (Figure 1, step 7).How many essential effector–target inter-actions need to be compromised toconvert a host plant into a nonhost?This is difficult to predict, given the evolu-tionary potential of many pathogens, butsafer to assume that attenuating multipleinteractions would create an enduring bar-rier to infection. Single-site alterationswould best be done using CRISPR-Cassystems based on minimal changesneeded to break effector–target interac-tions (Figure 1, step 8). Potentially, multiplegene-editing changes can be made simul-taneously, as demonstrated for a range ofcrops [9,10].Given the advances in identifying filamen-tous pathogen effectors and their tar-gets, the development of powerful toolsto predict protein structure, and thepotential to precisely edit multiple siteswithin plant genomes, it is timely to con-sider how to convert host plants intononhosts by undermining effector–targetinteractions.AcknowledgmentsP.R.J.B., H.M., and P.C.B are supported by theBiotechnology and Biological Sciences ResearchCouncil grant BB/S003096/1; European ResearchCouncil (ERC)-Advanced grant PathEVome (787764);and Scottish Government Rural and EnvironmentScience and Analytical Services Division (RESAS).Declaration of interestsNo interests are declared.Trends in Plant Science878 Trends in Plant Science, August 2023, Vol. 28, No. 81Division of Plant Science, School of Life Sciences, University ofDundee, @James Hutton Institute, Errol Road, Invergowrie,Dundee DD2 5DA, UK2Cell and Molecular Sciences, James Hutton Institute, ErrolRoad, Invergowrie, Dundee DD2 5DA, UK*Correspondence:paul.birch@hutton.ac.uk; P.Birch@dundee.ac.uk (P.R.J. Birch).https://doi.org/10.1016/j.tplants.2023.05.008Crown Copyright © 2023 Published by Elsevier Ltd. This is anopen access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).References1. Panstruga, R. and Moscou, M.J. (2020) What is the molecu-lar basis of nonhost resistance?Mol. Plant-Microbe Interact.33, 1253–12642. Jones, J.D. and Dangl, J.L. (2006) The plant immunesystem. Nature 444, 323–3293. Schulze-Lefert, P. and Panstruga, R. (2011) A molecularevolutionary concept connecting nonhost resistance, path-ogen host range, and pathogen speciation. Trends PlantSci. 16, 117–1254. Dong, S. et al. (2014) Effector specialization in a lineageof the Irish potato famine pathogen. Science 343,552–5555. McLellan, H. et al. (2022) Exploiting breakdown in nonhosteffector–target interactions to boost host disease resis-tance. Proc. Natl. Acad. Sci. U. S. A. 119, e21140641196. Thordal-Christensen, H. et al. (2018) Why did filamentousplant pathogens evolve the potential to secrete hundredsof effectors to enable disease? Mol. Plant Pathol. 19, 7817. Inoue, Y. et al. (2023) Selective deployment of virulence ef-fectors correlates with host specificity in a fungal plantpathogen. New Phytol. 238, 1578–15928. Ayukawa, Y. et al. (2021) A pair of effectors encodedon a conditionally dispensable chromosome of Fusariumoxysporum suppress host-specific immunity. Commun.Biol. 4, 7079. Selma, S. et al. (2023) Clustered regularly interspacedshort palindromic repeats tools for plant metabolic engi-neering: achievements and perspectives. Curr. Opin.Biotechnol. 79, 10285610. Gupta, A. et al. (2023) CRISPR-induced miRNA156-recognition element mutations in TaSPL13 improve multi-ple agronomic traits in wheat. Plant Biotechnol. J. 21,536–54811. Jumper, J. et al. (2021) Highly accurate protein structureprediction with AlphaFold. Nature 596, 583–58912. Seong, K. and Krasileva, K.V. (2023) Prediction of effectorprotein structures from fungal phytopathogens enablesevolutionary analyses. Nat. Microbiol. 8, 174–18713. Ibrahim, T. et al. (2023) AlphaFold2-multimer guided high-accuracy prediction of typical and atypical ATG8-bindingmotifs. PLoS Biol. 21, e3001962Trends in Plant ScienceTrends in Plant Science, August 2023, Vol. 28, No. 8 879

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How to convert host plants into nonhosts

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