Helper NLR immune protein NRC3 evolved to evade inhibition by a cyst nematode virulence effector

Helper NLR immune protein NRC3 evolved to evade inhibition by a cyst nematode virulence effector | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Helper NLR immune protein NRC3 evolved to evade inhibition by a cyst nematode virulence effector View ORCID Profile Yu Sugihara , View ORCID Profile Jiorgos Kourelis , View ORCID Profile Mauricio P. Contreras , View ORCID Profile Hsuan Pai , View ORCID Profile Muniyandi Selvaraj , View ORCID Profile AmirAli Toghani , View ORCID Profile Claudia Martínez-Anaya , View ORCID Profile Sophien Kamoun doi: https://doi.org/10.1101/2024.06.16.598756 Yu Sugihara 1 The Sainsbury Laboratory, University of East Anglia , Norwich, United Kingdom 3 Iwate Biotechnology Research Center , Kitakami, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Yu Sugihara Jiorgos Kourelis 1 The Sainsbury Laboratory, University of East Anglia , Norwich, United Kingdom 4 Imperial College London , London, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jiorgos Kourelis Mauricio P. Contreras 1 The Sainsbury Laboratory, University of East Anglia , Norwich, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mauricio P. Contreras Hsuan Pai 1 The Sainsbury Laboratory, University of East Anglia , Norwich, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hsuan Pai Muniyandi Selvaraj 1 The Sainsbury Laboratory, University of East Anglia , Norwich, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Muniyandi Selvaraj AmirAli Toghani 1 The Sainsbury Laboratory, University of East Anglia , Norwich, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for AmirAli Toghani Claudia Martínez-Anaya 1 The Sainsbury Laboratory, University of East Anglia , Norwich, United Kingdom 2 Instituto de Biotecnología, Universidad Nacional Autónoma de México , Cuernavaca, Morelos, México Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Claudia Martínez-Anaya For correspondence: sophien.kamoun{at}tsl.ac.uk claudia.martinez{at}ibt.unam.mx Sophien Kamoun 1 The Sainsbury Laboratory, University of East Anglia , Norwich, United Kingdom Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sophien Kamoun For correspondence: sophien.kamoun{at}tsl.ac.uk claudia.martinez{at}ibt.unam.mx Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF ABSTRACT Parasites can counteract host immunity by suppressing nucleotide binding and leucine-rich repeat (NLR) proteins that function as immune receptors. We previously showed that a cyst nematode virulence effector SPRYSEC15 (SS15) binds and inhibits oligomerisation of helper NLR proteins in the expanded NRC1/2/3 clade by preventing intramolecular rearrangements required for NRC oligomerisation into an activated resistosome. Here we examined the degree to which NRC proteins from multiple Solanaceae species are sensitive to suppression by SS15 and tested hypotheses about adaptive evolution of the binding interface between the SS15 inhibitor and NRC proteins. Whereas all tested orthologs of NRC2 were inhibited by SS15, some natural variants of NRC1 and NRC3 are insensitive to SS15 suppression. Ancestral sequence reconstruction combined with functional assays revealed that NRC3 transitioned from an ancestral suppressed form to an insensitive one over 19 million years ago. Our analyses revealed the evolutionary trajectory of coevolution between a parasite inhibitor and its NLR immune receptor target, identifying key evolutionary transitions in helper NLRs that counteract this inhibition. This work reveals a distinct type of gene-for-gene interaction between parasite or pathogen immunosuppressors and host immune receptors that contrasts with the coevolution between AVR effectors and immune receptors. INTRODUCTION Molecular interactions between plant immune receptors and pathogen effectors drive their coevolution, shaping the dynamics of host-pathogen relationships ( Delaux and Schornack, 2021 ; Jones and Dangl, 2006 ; Ngou et al., 2022 ; Schornack and Kamoun, 2023 ). Harold H. Flor, in 1942, proposed the hypothesis that single genes in plants and pathogens determine the outcome of their interactions; that is, a plant carrying a certain gene displays resistance against a pathogen carrying a corresponding gene ( Flor, 1971 , 1942 ). In plant-pathogen interactions, Flor’s model is generally interpreted as the recognition of pathogen effectors (known as AVR effectors) by plant immune receptors (encoded by disease resistance genes or R genes), triggering a robust resistance mechanism. This gene-for-gene model has provided an invaluable conceptual framework and has significantly influenced both applied and basic research in disease resistance ( Dodds, 2023 ). In particular, this model provided a deep understanding of the principles of coevolution between plant immune receptors, encoded by disease resistance ( R ) genes, and pathogen (or parasite) AVR effectors ( Białas et al., 2018 ; De la Concepcion et al., 2021a ; Dodds et al., 2006 ; Kanzaki et al., 2012 ). Indeed, the plant pathology community has documented numerous examples of adaptive evolution, notably cases where the pathogen AVR effector has evaded detection by its cognate R immune receptor ( Crean et al., 2023 ; Kanzaki et al., 2012 ; Upson et al., 2018 ). Despite advancements in our understanding of R-AVR interactions at the mechanistic and evolutionary level, other types of gene-for-gene interactions, notably coevolution between pathogen immunosuppressors and their host targets, remain less understood ( Contreras et al., 2023a ; Wu and Derevnina, 2023 ) ( S1 Fig ). Nucleotide-binding domain and leucine-rich repeat (NLR) proteins constitute the predominant class of plant disease resistance genes ( Adachi et al., 2019b ; Araújo et al., 2019 ; Kourelis and van der Hoorn, 2018 ). NLRs are intracellular receptors that directly or indirectly recognise pathogen effectors, a molecular event which triggers an immune response ( Cesari, 2018 ; Kourelis and van der Hoorn, 2018 ). A continuous coevolutionary arms race between plants and pathogens has resulted in the diversification and expansion of NLRs in plants ( Barragan and Weigel, 2021 ; Chia and Carella, 2023 ; Contreras et al., 2023a ). NLRs have evolved diverse activation mechanisms. Asterid plants, and notably the Solanaceae, have a complex NLR immune receptor network also known as the NRC network ( Adachi et al., 2019b ; Contreras et al., 2023a ; Wu et al., 2017 ). In this model, a specific phylogenetic clade of coiled-coil (CC)-type NLR proteins, known as NLR REQUIRED FOR CELL DEATH (NRC), function as helper NLRs (NRC-H) genetically downstream of multiple sensor NLRs (NRC-S) to mediate immune responses and to confer disease resistance against diverse pathogens and pests ( Goh et al., 2023 ; Sakai et al., 2024 ; Wu et al., 2017 ). NRC-H and NRC-S are phylogenetically related CC-NLRs that originate from a common ancestor that was present before the split between asterids and Caryophyllales ( Wu et al., 2017 ). Recent studies have shown that the NRC0 sensor/helper gene cluster reflects an ancestral state of the NRC network ( Goh et al., 2023 ; Sakai et al., 2024 ). NRC0 helpers have been genetically and functionally conserved across asterids for more than 100 million years, predating the massive expansion and diversification of NRC-H and NRC-S into lineage- or species-specific NRC networks in lamiids, notably in the Solanaceae family ( Goh et al., 2023 ; Oh et al., 2023 ; Sakai et al., 2024 ). Throughout their expansion and diversification, NRC proteins have subfunctionalised from the larger NRC network, resulting in organ-specialised subnetworks or in partial genetic redundancy as well as evolving specificity to different sensor NLRs ( Huang et al., 2023 ; Lüdke et al., 2023 ). Notably, NRC3 of solanaceous species is required not only by sensor NLRs but also by the tomato cell-surface receptors Cf-2, Cf-4, Cf-5 and Cf-9, which trigger hypersensitive cell death response upon the recognition of the fungal pathogen Cladosporium fulvum (syn. Passalora fulva ) apoplastic effectors ( Kourelis, 2023 ; Kourelis et al., 2022 ; Kourelis and Adachi, 2022 ). Upon perceiving AVR effectors, NRC-S proteins activate their cognate NRC helpers via an ‘activate-and-release’ mechanism, presumably through the NB-ARC (nucleotide-binding adaptor shared by APAF-1, certain R gene products and CED-4) module of the sensor NLR ( Ahn et al., 2023 ; Contreras et al., 2024 , 2022 ; Huang et al., 2023 ). The NB-ARC module consists of three domains: a nucleotide binding domain (NBD), a helical domain (HD1) and a winged helix domain (WHD) ( Bentham et al., 2017 ; Contreras et al., 2023b ; Kourelis et al., 2021 ). The current mechanistic model is that activation by NRC-S converts NRC helpers from a resting state homodimer into resistosomes—oligomeric, pore-like complexes that translocate to the plasma membrane ( Contreras et al., 2022 ; Selvaraj et al., 2023 ). These complexes enable immune responses such as calcium influx and hypersensitive cell death, culminating in disease resistance ( Liu et al., 2024 ). Oligomerisation into resistosomes has been demonstrated in planta for several NRCs using blue native polyacrylamide gel electrophoresis (BN-PAGE) ( Ahn et al., 2023 ; Contreras et al., 2024 , 2023b , 2022 ; Sakai et al., 2024 ). More recently, the cryogenic electron microscopy (cryo-EM) structures of NRC2 and a constitutively active mutant of NRC4 (NRC4 D478V ) revealed hexameric resistosomes ( Liu et al., 2024 ; Ma et al., 2024 ; Madhuprakash et al., 2024 ). We previously showed that SPRYSEC15 (SS15), a small secreted protein of the cyst nematode Globodera rostochiensis , binds and inhibits oligomerisation of NRC2 and NRC3 from the model plant Nicotiana benthamiana , as well as NRC1 from tomato ( Solanum lycopersicum ), by preventing intramolecular rearrangements required for NRC oligomerisation into activated resistosomes ( Ali et al., 2015 ; Contreras et al., 2023b ; Derevnina et al., 2021 ). Conversely, SS15 does not inhibit oligomerisation of N. benthamiana NRC4 protein, a paralog of NRC2 and NRC3 ( Contreras et al., 2023b ). Leveraging NRC4 resilience to SS15 inhibition and the crystal structure of SS15 in complex with the NB-ARC module of NRC1, Contreras et al. (2023) mapped two key residues, E316 and D317, on NRC2 that mediate binding to SS15 and showed that NRC2 variants mutated at these positions can evade SS15 suppression without compromising receptor signalling ( Contreras et al., 2023b ). However, these studies primarily focused on NRC2, NRC3 and NRC4 from a single species N. benthamiana , and didn’t explore the extent to which NRC proteins across the Solanaceae are sensitive to SS15 inhibition. Indeed, Solanaceae species have 7–21 NRC-H paralogs ( Sakai et al., 2024 ), and the phylogenomic analyses of 123 solanaceous genome assemblies from 39 species of the genera Solanum , Physalis , Capsicum and Nicotiana revealed 15 phylogenetic clades ( Selvaraj et al., 2023 ; Sugihara et al., 2023b ). Ten of the 15 clades include orthologs from at least two genera, therefore representing relatively deep NRC lineages. Of interest to this study, SS15 has only been shown to inhibit members of the NRC1, NRC2, NRC3 clade, a well-supported and deep branch in the Solanaceae NRC tree ( Selvaraj et al., 2023 ). The extent to which NLR immune receptors have evolved to counteract pathogen suppressors is unknown. Here we discovered that orthologous NRC proteins from multiple Solanaceae species vary in their sensitivity to suppression by the cyst nematode effector SS15. We found that some natural variants of NRC1 and NRC3 are insensitive to SS15 suppression, whereas all tested NRC2 orthologs are inhibited by SS15. To test hypotheses about adaptive evolution of the NRC-SS15 binding interface, we used ancestral sequence reconstruction to show that NRC3 has transitioned from an ancestral suppressed form to an insensitive one over 19 million years ago. Our analyses reconstructed the evolutionary trajectory of NLR-suppressor coevolution and identified key evolutionary transitions of solanaceous helper NLRs to counteract the SS15 inhibitor. This work reveals a distinct type of gene-for-gene interaction between host immune receptors and pathogen immunosuppressors that contrasts with R-AVR coevolution. RESULTS Natural variants of NRC1 and NRC3 but not NRC2 are insensitive to SS15 inhibition We previously showed that SS15 inhibits NRC1, NRC2 and NRC3 but not NRC4 ( Contreras et al., 2023b ; Derevnina et al., 2021 ). Given that the homologous NRC1, NRC2, NRC3, along with the NLR modulator NRCX, form a well-supported clade in the Solanaceae NRC tree ( Figs 1A and S2 and S3 ) ( Sakai et al., 2024 ; Selvaraj et al., 2023 ), we investigated the degree to which NRC orthologs from multiple Solanaceae species are inhibited by SS15. For this purpose, we cloned 11 representative NRC sequences from Nicotiana benthamiana (NbNRC2 and NbNRC3), Capsicum annuum (pepper; CaNRC1, CaNRC2 and CaNRC3), Solanum tuberosum (potato; StNRC1, StNRC2 and StNRC3) and Solanum lycopersicum (tomato; SlNRC1, SlNRC2 and SlNRC3) from the phylogenetically related NRC1/2/3 clade ( Figs 1A and B and S2 ). To assess cell death due to hypersensitive response (HR) in the presence of SS15, we transiently co-expressed NRCs with the upstream NRC-S sensor NLR, Rx, along with either an empty vector (EV) or SS15 in the leaves of nrc2/3/4 CRISPR knock-out (KO) N. benthamiana plants. We activated the sensor-helper Rx-NRC system by co-expressing the Potato virus X (PVX) coat protein (CP). Whereas all tested NRC2s were inhibited by SS15, some natural variants of NRC1 and NRC3 were insensitive to SS15 inhibition ( Fig 1B ). For NRC1, pepper NRC1 (CaNRC1) and tomato NRC1 (SlNRC1) were inhibited by SS15, while potato NRC1 (StNRC1) was insensitive to SS15 inhibition ( Fig 1B ). For NRC3, N. benthamiana NRC3 (NbNRC3) and potato NRC3 (StNRC3) were inhibited by SS15, while pepper NRC3 (CaNRC3) and tomato NRC3 (SlNRC3) were insensitive ( Fig 1B ). These results indicate that some natural variants of NRC1 and NRC3 are insensitive to SS15 and that they might have acquired mutations affecting SS15 binding to their NB-ARC modules. Download figure Open in new tab Fig 1. Natural variants of NRC1 and NRC3 but not NRC2 are insensitive to SS15 inhibition. (A) Phylogenetic tree of the NRC1/2/3 clade from four different Solanaceae species. We used the full-length NRC sequences of the NRC0, NRC1, NRC2, NRC3 and NRCX clades from four different Solanaceae species ( Nicotiana benthamiana , Capsicum annuum , Solanum tuberosum and Solanum lycopersicum ) to create a phylogenetic tree. The phylogenetic tree was reconstructed by the maximum likelihood method using IQ-TREE with 1,000 bootstrap replicates. The phylogenetic positions of cloned NRCs are indicated in S2 Fig . (B) Representative images of HR cell death assays after transient co-expression of either an empty vector (EV) or SPRYSEC15 (SS15) with the NRC-S sensor NLR, Rx, the Potato virus X (PVX) coat protein (CP) and NRCs in the leaves of N. benthamiana nrc2/3/4 KO plants. Note that, unlike tomato, N. benthamiana lacks nrc1 . Leaves were photographed 5 days after infiltration. NRC3 variants from different Solanaceae species carry key polymorphisms at the SS15 binding interface Contreras et al. (2023) described the structure of SS15 in complex with the NB-ARC module of SlNRC1 (SlNRC1 NB-ARC ) revealing three contact interfaces ( Fig 2A ) ( Contreras et al., 2023b ). To interpret the results of the cell death assay in Fig 1B , we mapped the NRC polymorphisms at these interfaces ( Fig 2B ). Among multiple polymorphisms, we focused on positions D316 and E317 of SlNRC1, which are critical to SS15 inhibition in NbNRC2 ( Contreras et al., 2023b ). In contrast to NRC1 and NRC2, NRC3 is polymorphic at positions matching D316 and E317 (here and below, the position numbers are based on SlNRC1 sequence) ( Fig 2B ). Remarkably, polymorphism E316K in NRC3 correlated with inhibition phenotypes, with CaNRC3 and SlNRC3 orthologs, carrying lysine at position 316 (K316), being insensitive to SS15 inhibition ( Figs 1 and 2B ). We therefore hypothesised that this amino acid substitution at position 316 affects binding and sensitivity to SS15. Download figure Open in new tab Fig 2. NRC3 variants from different Solanaceae species are polymorphic at key residues at SS15 binding interface. (A) Structure of SS15 in complex with the NB-ARC module of SlNRC1 (SlNRC1 NB-ARC ). The NB-ARC module of SlNRC1 has three different interfaces interacting with SS15. The NB-ARC module consists of a nucleotide binding domain (NBD), a helical domain (HD1) and a winged helix domain (WHD), highlighted in different colours. The structure was published in Contreras et al., 2023b (PDB: 8BV0). The boundaries between the domains follow those in Contreras et al., 2023b . (B) Alignment of NRC1, NRC2 and NRC3 interfaces for SS15. The positions of the residues are based on SlNRC1. Whether an NRC is inhibited by SS15 is indicated on the right side of the protein name based on the results in Fig 1B . Two key residues for SS15 inhibition (D316 and E317 of SlNRC1), previously identified in Contreras et al., 2023b , are highlighted with red asterisks. Polymorphisms at NRC3 position 316 determine sensitivity to SS15 suppression Given the findings described in Figs 1 and 2 and since NRC3 is a core helper NLR required not only by sensor NLRs but also by cell surface receptors ( Kourelis, 2023 ; Kourelis et al., 2022 ; Kourelis and Adachi, 2022 ), we focused on NRC3 and tested the effect of E316K substitution on SS15 binding. We generated a single-point mutant for each wild type (WT) NRC3 at position matching SlNRC1 amino acid 316 (E316K in NbNRC3, K314E in CaNRC3, E314K in StNRC3 and K314E in SlNRC3; Figs 2B and 3A ). We then compared the HR cell death between WT NRC3s and single-point mutants in the presence and absence of SS15 ( Figs 3B and C ). The E- to-K substitutions in NbNRC3 and StNRC3 significantly increased the cell death response in the presence of SS15, while the K-to-E substitutions in CaNRC3 and SlNRC3 significantly reduced it ( Figs 3B and C ). SlNRC3 K314E showed reduced HR scores compared with WT SlNRC3, but the difference was not as marked as in the case of other single-point mutants. These results indicate that naturally occurring polymorphisms at position 316 of NRC3 are critical for sensitivity to SS15 in line with our previous study on NbNRC2 ( Contreras et al., 2023b ). Furthermore, our findings indicate that SlNRC3 may contain additional amino acid polymorphisms besides K314 that contribute to its insensitivity to SS15. Download figure Open in new tab Fig 3. Polymorphisms at NRC3 position 316 determine sensitivity to SS15 suppression. (A) Schematic representation of the mutated sites in the multiple sequence alignment of NRC3. The residue matching D316 of SlNRC1 is highlighted with a red asterisk. Whether an NRC is inhibited by SS15 is indicated on the right side of the panel based on Fig 1B . (B) Representative images of HR cell death assays showing the results after transient co-expression of an empty vector (EV) or SS15 with Rx and PVX CP, along with either WT NRC3 or its single-point mutant in the leaves of N. benthamiana nrc2/3/4 KO plants. Mutations were introduced in NRC3 at the residues matching D316 of SlNRC1. The leaves were photographed 5 days after infiltration. (C) Statistical analysis using a two-sided permutation test with 10,000 replicates. Statistically significant differences are indicated (***: p < 0.001; n.s.: not significant). Each column represents an independent experiment. The data underlying Fig 3C can be found in S1 Data. Polymorphisms at position E316 of NbNRC3 determine oligomerisation in the presence of SS15 Contreras et al. (2023) showed that SS15 blocks NRC2 oligomerisation and resistosome formation following activation by the NRC-S protein Rx and PVX CP ( Contreras et al., 2023b ). We extended these experiments to NRC3 orthologs from pepper, potato and tomato to determine the effect of SS15 on their oligomerisation following activation ( Fig 4 ). To this end, we used previously established blue native polyacrylamide gel electrophoresis (BN-PAGE) to assay for NRC resistosome formation ( Contreras et al., 2023b , 2022 ), and NRC3 mutants of the N-terminal MADA motifs (CaNRC3 EEE , StNRC3 EEE and SlNRC3 EEE for C. annuum , S. tuberosum and S. lycopersicum , respectively), which abolish cell death without compromising receptor activation ( Adachi et al., 2019a ; Contreras et al., 2023b ). To activate NRC3s, we co-expressed 4xMyc-tagged NRC3 MADA mutants (NRC3 EEE -4xMyc) with V5-tagged sensor NLR Rx (Rx-V5) and either free GFP or GFP-tagged PVX CP (CP-GFP). These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein (mCherry-6xHA) as a negative control or 4xHA-tagged SS15 (4xHA-SS15) in the leaves of N. benthamiana nrc2/3/4 KO plants ( Figs 4 and S4 – S6 ). High molecular weight bands (arrowheads in Fig 4 ) formed when WT NRC3 EEE were co-expressed with CP, Rx and mCherry, compared with co-expression with the non-activating genes GFP and mCherry in the presence of Rx ( Figs 4 and S4 – S6 ). These results suggest that all tested WT NRC3s oligomerize and form high-order resistosome complexes upon effector-triggered activation mediated by Rx and CP. However, when NRC3 EEE s were co-expressed with SS15 in the presence of Rx and CP, the resistosome band for StNRC3 EEE was considerably reduced in comparison to the absence of SS15, and a smear (also observed in the inactive state) appeared, showing the inhibitory effect of SS15 on StNRC3 EEE . In contrast, SS15 did not prevent resistosome formation for CaNRC3 EEE and SlNRC3 EEE ( Figs 4 and S4 – S6 ). Due to the low level of protein accumulation observed for NbNRC3 in N. benthamiana , we could not analyse the resistosome formation of NbNRC3 ( Derevnina et al., 2021 ). Download figure Open in new tab Fig 4. Polymorphisms at position E316 of NbNRC3 determine oligomerisation in the presence of SS15. Blue native polyacrylamide gel electrophoresis (BN-PAGE) assays were conducted for CaNRC3 EEE (A), StNRC3 EEE (B) and SlNRC3 EEE (C) with their respective single-point mutations at position matching NbNRC3 residue 316. C-terminally 4xMyc-tagged NRC3 EEE mutants were co-expressed with C-terminally V5-tagged Rx and either free GFP or C-terminally GFP-tagged PVX CP in the leaves of N. benthamiana nrc2/3/4 KO plants. These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein or N-terminally 4xHA-tagged SS15. Red arrowheads indicate resistosome bands. Corresponding SDS-PAGE blots are in Figs S4 to S6 . Next, we tested whether mutating NbNRC3 residue 316 (CaNRC3 EEE/K314E , StNRC3 EEE/E314K and SlNRC3 EEE/K314E ) affects SS15 inhibition of NRC3 oligomerization following activation as described in the previous section. Again, high molecular weight bands formed after co-expression of Rx and CP in BN-PAGE assays ( Figs 4 and S4 – S6 ), indicating the capacity of these mutants to form a resistosome ( Figs 4 and S4 – S6 ). In contrast, the resistosome formations of CaNRC3 EEE/K314E and SlNRC3 EEE/K314E were impaired in the presence of SS15. In both cases, the lower molecular weight band of NRC3 exhibited a shift in size, presumably due to NRC3-SS15 complex formation in planta ( Figs 4A and 4C ). Moreover, the anti-HA blots revealed similar migration patterns for SS15 with CaNRC3 EEE/K314E and SlNRC3 EEE/K314E , further suggesting that these mutants are forming a complex with the effector, leading to inhibition. Unlike StNRC3 EEE , the mutant StNRC3 EEE/E314K was capable of oligomerizing in the presence of SS15 ( Fig 4B ). These results indicate that position E316 of NbNRC3 determines the oligomerisation of NRC3 in the presence of SS15, but in tomato SlNRC3, other residues appear to contribute to the insensitivity to SS15. Overall, these results are consistent with our observations in the HR cell death assays ( Figs 1B and 3B and 3C ). Ancestral sequence reconstruction infers that E316 is ancestral in the NRC3 clade We revealed that polymorphisms at position 316 determine SS15 sensitivity in natural variants of NRC3. However, polymorphisms E316 of NbNRC3, K314 of CaNRC3, E314 of StNRC3 and K314 of SlNRC3 are phylogenetically discordant in the NRC3 tree ( Figs 5 and and S2 and S3 ). To clarify the evolutionary history of NRC3, we applied ancestral sequence reconstruction to 314 non-redundant NRC1/2/3/X nucleotide sequences extracted from an NLRome database of 66,665 sequences from 124 genomes in the Solanaceae family ( S3 Fig and S1 Table ) ( Sugihara et al., 2023b ). Ancestral sequence reconstruction inferred five amino acid substitutions from node 1 to node 6 on the three interfaces defined by the crystal structure of SlNRC1 NB-ARC in complex with SS15 ( Fig 2 and 5 ). Node 1, which predates the divergence between the Nicotiana genus and the rest of the taxa, had an ambiguous residue at the position E317 of SlNRC1, resulting in two different ancestral variants anc1.1 and anc1.2 with N317 ( p = 0.45) and D317 ( p = 0.55), respectively ( Figs 5 and S3 and S1 Table ). Both ancestral variants had E316 as the ancestral state, and the E316K polymorphism is inferred to have arisen during the transition from node 1 to 2, which are estimated to date to 24.0 (23.0–25.7) and 19.1 (17.0– 21.0) million years ago (Mya) with 95% confidence intervals, respectively ( Särkinen et al., 2013 ) ( Fig 5 ). These results indicate that the ancestral state of the NRC3 clade at position 316 was most likely E316 with the E316K polymorphism arising over ∼19.1 Mya after the divergence between Nicotiana and the other taxa. Moreover, StNRC3 E314 is likely a regressive mutation that occurred after the divergence between S. lycopersicum and S. tuberosum . Download figure Open in new tab Fig 5. Ancestral sequence reconstruction infers that E316 is ancestral in the NRC3 clade. Schematic illustration of the ancestral sequence reconstruction of the NRC3 clade. The ancestral sequences were inferred from a codon-based alignment of 314 sequences from the NRC1/2/3/X clade ( S3 Fig ). We focused on the three interfaces interacting with SS15 ( Fig 2 ), and five amino acid substitutions were identified from nodes 1 to 6. The ancestral states of remaining residues for the interfaces are identical to the amino acids of SlNRC3. The positions are based on SlNRC1 in the alignment of Fig 2B . A probability value ( p ) greater than 0.3 was considered as an ambiguous residue, and multiple ancestral states were tested from the same node (S1 Table). The correspondence of the inferred ancestral sequences with the nodes is indicated below the phylogeny. We used the calibration time estimated by Särkinen et al., 2013 . Ancestral NRC3 variants with E316 are inhibited by SS15, but those with K316 are not Whereas predicted ancestral sequences at node 1 have E316 (GAA), those at node 2 to node 6 have K316 (AAA) at the key 316 position ( Fig 5 ). We therefore hypothesised that node 1 ancestral NRC3 is suppressed by SS15, whereas subsequent variants with K316 are not. To test this hypothesis, we swapped the SS15 binding interface of SlNRC3 (K at position 316; insensitive to SS15 inhibition) with the ancestral amino acid combinations we previously inferred ( Figs 5 and 6A ). Given that SlNRC3 is identical to anc6.1 at the five SS15 binding interface residues, we cloned the remainder six ancestral NRC3 sequences from node 1 to node 6 in SlNRC3 ( Figs 5 and 6A ), and tested them for SS15 suppression using HR and BN-PAGE assays ( Figs 6 and S7 and S8 ). These experiments revealed that SlNRC3 variants with anc1.1 and anc1.2 amino acid combinations (E316) were suppressed by SS15 for induction of HR and NRC3 oligomerisation, whereas anc2, anc3/4, anc5 and anc6.2 (K316) were not ( Figs 6 and S7 and S8 ). Overall, the difference between the NRC3 treatments with and without SS15 were clear, however, in the case of the HR assays with the anc2 variant, there was statistically significant difference between the empty vector and SS15 ( S7 Fig ). Nonetheless, we conclude that the anc2 variant is insensitive to SS15 given that the effector failed to suppress HR cell death and prevent resistosome formation ( Figs 6 and S7 and S8 ). These results indicate that ancestral NRC3, at the node predating the divergence between Nicotiana and other taxa, was inhibited by SS15. NRC3 evolved to evade SS15 inhibition over 19.1 million years ago through the E316K substitution. Download figure Open in new tab Fig 6. Ancestral NRC3 variants with E316 are inhibited by SS15, but those with K316 are not. (A) Overview of the strategy for resurrecting the ancestral interfaces of NRC3 for SS15. The three interfaces are defined as for SS15 in Fig 2 . Using SlNRC3 as a backbone, we swapped the interface sequences with the ancestral sequences inferred in Fig 5 . (B) Representative images of HR cell death assays showing the results after transient co-expression of either an empty vector (EV) or SS15 with Rx, PVX CP and the ancestral NRC3 variants in the leaves of N. benthamiana nrc2/3/4 KO plants. NbNRC3 and SlNRC3 are used as negative and positive controls, respectively. The ancestral NRC3 variant for anc6.1 was identical to WT SlNRC3. The leaves were photographed 5 days after infiltration. The statistical analysis is in S7 Fig . (C) BN-PAGE assays for ancestral NRC3 variants. C-terminally 4xMyc-tagged ancestral NRC3 EEE variants were co-expressed with C-terminally V5-tagged Rx and C-terminally GFP-tagged PVX CP in the leaves of N. benthamiana nrc2/3/4 KO plants. These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein or N-terminally 4xHA-tagged SS15. A red arrowhead indicates resistosome bands. Corresponding SDS-PAGE blots are in S8 Fig . To further challenge our hypothesis, we compared side-by-side anc1.1 and anc1.2 with SlNRC3 (anc6.1) and its single-point mutant (K314E) in HR cell death assays with and without SS15 ( Figs S9A and S9B ). SlNRC3 variants with anc1.1 and anc1.2 amino acid combinations (E316) were significantly suppressed by SS15 for induction of HR compared to SlNRC3 and the K314E mutant ( Figs S9A and S9B ). In the BN-PAGE assay, SS15 prevented the formation of the resistosome band for the anc1.1 variant whereas SlNRC3 and SlNRC3 K314E were insensitive to SS15 suppression ( Figs S9C and S10 ). These results indicate that SlNRC3 (anc6.1) possesses additional amino acid polymorphisms besides K314, which contribute to its insensitivity to SS15 ( Figs 3 and 6 and S9 and S10 ). DISCUSSION Plant pathogen effectors can function as suppressors of NLR-mediated immunity ( Wu and Derevnina, 2023 ). However, the degree to which NLRs have evolved to evade pathogen immunosuppressors has remained unknown. In this study, we discovered that some natural variants of helper NLRs in the NRC family are insensitive to suppression by the cyst nematode effector SS15. We found that some natural variants of NRC1 and NRC3 are insensitive to SS15 suppression, while all tested NRC2s are suppressed by SS15 ( Fig 1 ). These contrasting SS15 inhibition phenotypes enabled us to determine that a single polymorphic amino acid residue at position E316 of NbNRC2 ( Contreras et al., 2023b ) determines sensitivity to SS15 in the NRC3 clade of solanaceous plants ( Figs 2 – 4 ). We also tested hypotheses about adaptive evolution (from sensitive to insensitive phenotype) of the NRC-SS15 binding interface and used ancestral sequence reconstruction to show that NRC3 has evolved to evade SS15 inhibition over 19 Mya ( Figs 5 – 6 ). These experiments led to an evolutionary model that maps out transitions in the evolution of NRC3 sensitivity to SS15 inhibition ( Fig 7 ) and supports the view that suppressor and their receptor targets are engaged in another layer of gene-for-gene coevolution in addition to classic R-AVR interactions ( S1 Fig ). Intriguingly, the analyses also indicated regressive evolution (from insensitive to sensitive phenotype) in potato StNRC3 ( Figs 5 and 7 ). Collectively, our study indicates adaptive evolution of NLRs to a pathogen immunosuppressor and identified key evolutionary transitions in a Solanaceae helper NLR that counteract this inhibition. Download figure Open in new tab Fig 7. NRC3 has evolved to evade inhibition by the cyst nematode effector SS15 over 19 Mya. Polymorphisms at position E316 of NbNRC3 determine sensitivity to the cyst nematode effector SPRYSEC15 (SS15). The ancestral sequence reconstruction inferred that E316 is an ancestral state of the NRC3 clade and that E316K mutation occurred over 19 million years ago before the divergence of Capsicum and Solanum genus. The E316K mutation has made NRC3 insensitive to SS15, but NRC3 of S. tuberosum (StNRC3) acquired a regressive mutation (K316E) and became inhibited by SS15. Our results indicate that position E316 is critical for SS15 inhibition in both NRC2 and NRC3 clades. On the other hand, the same position is not polymorphic in NRC1 sequences across multiple species, even though they showed varying sensitivities to SS15 ( Fig 1 ). This indicates that another position contributes to insensitivity to SS15 in the NRC1 clade and that the sensitivity to SS15 has evolved independently in different clades of the NRC family. Ancestral sequence reconstruction statistically infers intermediate sequences at phylogenetic nodes, enabling the identification of key evolutionary mutations. It is increasingly being applied to plant-pathogen coevolutionary systems ( Bentham et al., 2021 ; Białas et al., 2021 ; Huang et al., 2023 ; Schornack and Kamoun, 2023 ). For instance, this method was used to explore when the rice sensor NLR Pik-1 evolved to detect the AVR-PikD effector of the pathogenic fungus Magnaporthe oryzae (syn. Pyricularia oryzae ) ( Białas et al., 2021 ). Similarly, ancestral sequence reconstruction was applied to the AVR-Pik effector family to understand the directionality of evolutionary changes, determining whether the effector family expanded host-target binding or host immunity evaded the effector family ( Bentham et al., 2021 ). Moreover, a recent study employed this technique on NRC3 to examine the evolutionary history of sensor-helper compatibility ( Huang et al., 2023 ). In our study, we applied ancestral sequence reconstruction to NRC3 and reconstructed the coevolutionary dynamics between NLRs and pathogen immunosuppressors. We analysed six evolutionarily intermediate sequences of Solanaceae NRC3 to differentiate their evolutionary trajectories and discovered that SS15 sensitivity had shifted due to the E316K polymorphism that arose approximately 19 million years ago. This finding paves the way for further analyses of NLR-suppressor coevolution, particularly whether SS15 has evolved to overcome insensitive NLRs. Ancestral sequence reconstruction revealed the regressive evolution of potato StNRC3 to becoming sensitive to the nematode effector SS15 ( Figs 5 and 7 ). Why did this seemingly counterintuitive evolutionary transition occur in StNRC3? One possible explanation is a trade-off between functional NLR activation and evasion of pathogen immunosuppression. In NLRs, mutations in the NB-ARC module are known to cause autoimmunity, loss-of-function, or sensor-helper incompatibility ( De la Concepcion et al., 2021b ; Huang et al., 2023 ; Sueldo et al., 2015 ; Williams et al., 2011 ). Since E316K is located in the NB-ARC module, this polymorphism could affect NLR activity or autoimmunity, and plants carrying K316 might be subject to negative selection in the absence of parasite pressure. In this scenario, SS15 insensitivity in potato StNRC1 might be a compensating mutation that enhanced the activity of potato StNRC3 ( Fig 1 ). Alternatively, the mutation may reflect a trade-off between SS15 evasion and another, yet unidentified, parasite or pathogen effector that interacts with StNRC3. To address this question, further investigations into the diversity of parasite or pathogen effectors that interact with NRC3 are necessary. NRC helpers have recently been shown to form homodimers in their resting state ( Selvaraj et al., 2023 ). How SS15 prevents a conversion of homodimers into resistosomes remains unclear. Importantly, the SS15-NRC interaction interface does not overlap with the NRC homodimerization interface, and co-expression of NRCs with SS15 does not result in the appearance of lower molecular weight bands of NRCs ( Contreras et al., 2023b ) ( Figs 4 and 6C ). This suggests that SS15 likely to binds to NRC homodimers. Obtaining structural insights into the NRC homodimer together with SS15 will shed more light on the precise molecular mechanism of SS15 inhibition. Recent studies have reported bioengineering plant immune receptors to broaden their recognition repertoire for pathogen effectors ( Bentham et al., 2023 ; Cesari et al., 2022 ; De la Concepcion et al., 2019 ; Kourelis et al., 2023 ; Liu et al., 2021 ; Maidment et al., 2023 ; Marchal et al., 2022 ; Tamborski et al., 2023 ; Zdrzałek et al., 2024 , 2023 ). An alternative bioengineering approach involves designing NLR variants that evade pathogen suppression ( Contreras et al., 2023b ; Karki et al., 2021 ). A previous study utilised the differential SS15 inhibition exhibited by NbNRC2 and NbNRC4 to engineer an SS15-insensitive NRC2 variant. Our study further explored the natural diversity of NRCs within the Solanaceae family, identifying naturally occurring NRC3 variants that have evolved insensitivity to SS15 suppression ( Figs 5 – 7 ). Notably, the tomato SlNRC3 harbours additional mutations at the interface, besides E314K, which confer robust insensitivity to SS15 ( S9 Fig ). Identifying these additional mutations could be useful to bioengineer NRC variants with enhanced robustness against SS15 inhibition. Our findings shed light on a previously overlooked aspect of NLR-suppressor coevolution, underscoring the immune receptors’ capacity to adapt to pathogen-mediated immunosuppression. The suppressor function of the cyst nematode effector SS15 was first identified in N. benthamiana , whereas SS15 elicits a defence response in Nicotiana tabacum (tobacco), a species which also possesses the NRC network ( Ali et al., 2015 ). This observation suggests that SS15 may exhibit AVR activity in different host genetic backgrounds. Similarly, host-dependent AVR/suppressor activities were observed in Avr1 of Fusarium oxysporum f. sp. lycopersici infecting tomatoes ( Houterman et al., 2008 ) and AvrPtoB and AvrPphB of Pseudomonas syringae ( Russell et al., 2015 ; Wang et al., 2023 ). In tomato and its wild relatives, the I gene mediates resistance to Avr1-expressing strains of the fungus, while Avr1 suppresses the resistance mediated by I-2 and I-3 genes ( Catanzariti et al., 2017 , 2015 ; Houterman et al., 2009 , 2008 ; van der Does et al., 2019 ). Notably, I-2 encodes a CC-type NLR, while I and I-3 encode cell-surface receptors ( van der Does et al., 2019 ). Also, while AvrPtoB is recognised by the tomato NLR receptor complex Prf/Pto, in Arabidopsis it acts as a suppressor of the helper NLRs ADR1-L1/L2 ( Sheikh et al., 2023 ; Wang et al., 2023 ; Zhang et al., 2024 ). Interestingly, a recent study showed that this suppression is guarded by the Arabidopsis sensor TIR-NLR SNC1 ( Wang et al., 2023 ; Zhang et al., 2003 ). Additionally, in Arabidopsis , RPS5 indirectly recognises AvrPphB via PBS1 cleavage and triggers HR, while AvrPphB suppresses AvrB-induced activation of RPM1 (resistance to P. syringae pv. maculicola protein 1) ( Pottinger and Innes, 2020 ; Russell et al., 2015 ). In the case of SS15, it remains unclear how it elicits a defence response in N. tabacum . If an NLR recognises SS15 in N. tabacum , it would be interesting to determine whether this NLR binds and detects SS15 through its NB-ARC module, and how evolutionary pressure from SS15 has influenced the evolution of NLR resistance genes. These dual AVR/suppressor activities of effectors add complexity to Flor’s gene-for-gene model, introducing layers of conditional coevolution between the interacting genes ( S1 Fig ). Elucidating evolutionary pathways is crucial for understanding how genes and proteins have evolved to acquire their current functions ( Kamoun, 2024 ; Schornack and Kamoun, 2023 ; Siddiq et al., 2017 ). In plant-pathogen interactions, various modes of gene-for-gene interactions have been proposed ( Brabham et al., 2024 ; Contreras et al., 2023a ; De la Concepcion et al., 2021b ; Huang et al., 2023 ; Sugihara et al., 2023a ; Wu and Derevnina, 2023 ). Deciphering the major evolutionary transitions underlying these gene-for-gene specificities is crucial for understanding the arms race coevolution between plants and pathogens ( Bentham et al., 2021 ; Białas et al., 2021 ; Schornack and Kamoun, 2023 ). This study leveraged natural variants of NLRs that evaded pathogen inhibitors and identified the critical evolutionary transitions that counteract these inhibitors, thereby highlighting the intricate and multilayered coevolutionary dynamics between NLRs and pathogen effectors. A better understanding of NLR-AVR and NLR-suppressor coevolution is critical to inform NLR bioengineering approaches and improve disease resistance. MATERIAL AND METHODS Plant growth conditions N. benthamiana triple nrc2/3/4 CRISPR knock-out (KO) mutant line ‘210.5.5.1’ was grown in a controlled environment growth chamber with a temperature range of 22 to 25°C, 45 to 65% humidity, and a 16/8 h light/dark cycle. Cell death and suppression assays Four-week-old nrc2/3/4 KO N. benthamiana plants were spot-infiltrated with Agrobacterium tumefaciens GV3101 carrying plasmids indicated in S2 Table . Cell death, HR, was photographed 5 days post infiltration and scored according to the 0 (no necrosis) to 7 (confluent necrosis) scale as described in previous studies ( Derevnina et al., 2021 ; Segretin et al., 2014 ). The HR scores were statistically analysed using the “permutation_test” function implemented in “SciPy” python library v1.10.0 with the options “n_resamples=10000, vectorized=False, alternative=two-sided, random_state=0”. In the “permutation_test” function, we used the difference between two group means as a test statistic. Total protein extraction Four-week-old nrc2/3/4 KO N. benthamiana plants were infiltrated with agrobacterial suspensions as indicated in S2 Table . Leaf tissue was collected 72 h after agroinfiltration in liquid nitrogen and was grounded in a Geno/Grinder homogeniser. Proteins were extracted in GTMN buffer [10% glycerol, 50 mM tris-HCl (pH 7.5), 5 mM MgCl2, and 50 mM NaCl] supplemented with 10 mM dithiothreitol (DTT), 1x protease inhibitor cocktail (Sigma-Aldrich), and 0.2% Triton 100-X (Sigma-Aldrich), and incubated on ice for 10 min with short vortex mixing every 2 min. Debris was removed by centrifugation at 5000 xg for 15 min. Supernatant was used for BN-PAGE and SDS-PAGE assays. BN-PAGE assays For BN-PAGE, 25 ul of extracted proteins were combined with NativePAGE 5% G-250 sample additive, NativePAGE 4x sample buffer, and water. Five ul samples were loaded and run on NativePAGE 4 to 16% bis-tris gels alongside SERVA Native Marker (SERVA). Proteins were transferred to PVDF membranes with NuPAGE Transfer Buffer in a Trans-Blot Turbo transfer apparatus (Bio-Rad) as per the manufacturer’s instructions. Proteins were fixed to the membranes incubating with 8% acetic acid for 15 min, washed with water, and left to dry. Activation with ethanol allowed visualising the unstained native protein marker. SDS-PAGE assays Extracted proteins were diluted in SDS loading dye and incubated at 72°C for 10 min and briefly centrifuged. Fifteen ul of supernatant were run on Bio-Rad 4-20% Mini-PROTEAN TGX gels with PageRuler Plus prestained protein ladder (Thermo Fisher Scientific). Proteins were transferred to PVDF difluoride membranes in Trans-Blot Turbo transfer buffer in a Trans-Blot Turbo transfer system (Bio-Rad) as per the manufacturer’s instructions. Immunoblotting and epitope detection BN or SDS blotted membranes were blocked with 5% milk in tris-buffered saline and 0.01% Tween 20 (TBS-T) for an hour at room temperature, and subsequently overnight at 4°C with indicated antibodies ( S2 Table ). Bands were visualised with Pierce ECL Western (32106, Thermo Fisher Scientific), supplementing with up to 50% SuperSignal West Femto Maximum Sensitivity Substrate (34095, Thermo Fisher Scientific) when necessary. Membranes were imaged in an ImageQuant 800 luminescent system (GE Healthcare Life Sciences, Piscataway, NJ). Rubisco loading control was stained using Ponceau S (Sigma-Aldrich). Interface of NRC1 and SS15 The crystal structure of tomato SlNRC1 NB-ARC module (SlNRC1 NB-ARC ) bound to SS15 effector at 4.5 Å resolution (PDB code 8BV0) was previously resolved ( Contreras et al., 2023b ). In this structure, SS15 effector approaches the NRC1 between its NBD and HD1 domains. Molecular interactions between SlNRC1 NB-ARC and SS15 were listed using the CONTACT program of CCP4 ( Winn, 2003 ) with a distance cut-off of 2.5 to 3.6 Å. The interacting residues were clustered in three regions in SlNRC1 ranging 153–170, 306–320 and 348–353 and formed the core of the interface between SlNRC1 NB-ARC and SS15 in the crystal structure. These three regions were named interface 1, 2 and 3, respectively. All the interfaces contain a loop region at their centre together, allowing movement of the NBD with respect to HD1 and WHD. To identify the polymorphisms on these interfaces, 11 NRC protein sequences tested in HR cell death assay were aligned using MAFFT v7.508 with the options “--maxiterate 1000 --localpair” ( Katoh and Standley, 2013 ). The regions corresponding to the interfaces 1, 2 and 3 were extracted from the alignment. Phylogenetic analyses of helper NRC clades A previous study reported NRC helper sequences of N. benthamiana , C. annuum (pepper), S. tuberosum (potato) and S. lycopersicum (tomato) ( Selvaraj et al., 2023 ). The full-length amino acid sequences of the NRC0 (5 sequences), NRC1 (6 sequences), NRC2 (10 sequences), NRC3 (7 sequences) and NRCX (3 sequences) were obtained from this previously published dataset. Exact matches for the NbNRC2, CaNRC3 and StNRC3 sequences used in the HR cell death assay were not found within the dataset. Therefore, they were included in the dataset. The full-length amino acid sequences of helper NRC0/1/2/3/X clades were aligned using MAFFT v7.508 with the options “--maxiterate 1000 --localpair” ( Katoh and Standley, 2013 ). This alignment was then trimmed using ClipKIT v1.3.0 with the options “-c -m gappy -g 0.9” ( Steenwyk et al., 2020 ). Based on the trimmed alignment, a phylogenetic tree was created using IQ-TREE v1.6.12 ( Nguyen et al., 2015 ) with 1,000 ultrafast bootstrap replicates ( Hoang et al., 2018 ). ModelFinder selected the best-fit model for tree reconstruction, “JTT+G4”, according to the Bayesian Information Criterion (BIC) ( Kalyaanamoorthy et al., 2017 ). The resulting tree was visualised using Iroki ( Moore et al., 2020 ), and the bootstrap values for key nodes were shown in the figures. Obtaining codon-based alignment for ancestral sequence reconstruction Sequences of 2,361 helper NRCs were obtained from a previously published dataset ( Huang et al., 2023 ). The dataset was cleaned by removing sequences containing internal stop codons, those lacking a multiple-of-three nucleotide length, and terminal stop codons, resulting in 2,353 sequences. Then, sequences shorter than 2,400 or longer than 2,800 bases were filtered out, resulting in 1,748 sequences. To identify the NRC1/2/3/X clade, the protein sequences of the NB-ARC module were aligned using MAFFT v7.508 with the options “--maxiterate 1000 -- localpair” ( Katoh and Standley, 2013 ). The alignment was trimmed using ClipKIT v1.3.0 with the options “-c -m gappy -g 0.9” ( Steenwyk et al., 2020 ). Based on the trimmed alignment, a phylogenetic tree was created using IQ-TREE v2.2.6 ( Minh et al., 2020 ) with 1,000 ultrafast bootstrap replicates ( Hoang et al., 2018 ). ModelFinder selected the best-fit model for tree reconstruction, “JTT+F+R6”, according to the BIC ( Kalyaanamoorthy et al., 2017 ). Based on this phylogenetic tree, the 591 full-length nucleotide sequences were obtained from the NRC1/2/3/X clade. These 591 sequences were translated using seqkit v2.3.0 “translate” command ( Shen et al., 2016 ) and then re-aligned using MAFFT v7.508 with the options “--maxiterate 1000 -- localpair” ( Katoh and Standley, 2013 ). The position T4 of “Ppr-t_12226” was manually edited in the alignment. To obtain a codon-based nucleotide sequence alignment, the nucleotide sequences were threaded onto the protein alignment using the “thread_dna” command in phykit v1.11.14 ( Steenwyk et al., 2021 ). The alignment was trimmed using ClipKIT v1.3.0 with the options “-c -m gappy -g 0.9” ( Steenwyk et al., 2020 ). Finally, duplicated sequences were removed using seqkit v2.3.0 “rmdup” command ( Shen et al., 2016 ) with the -s and -P options. Some duplicated splicing variants were also filtered out, resulting in 314 non-redundant nucleotide sequences. Ancestral sequence reconstruction Based on the codon-based nucleotide alignment, which contains 314 non-redundant nucleotide sequences from the NRC1/2/3/X clade, a phylogenetic tree was created using IQ-TREE v2.2.6 ( Minh et al., 2020 ) with 1,000 ultrafast bootstrap replicates ( Hoang et al., 2018 ). ModelFinder selected the best-fit model for tree reconstruction, “TIM3+F+I+R4”, according to the BIC ( Kalyaanamoorthy et al., 2017 ). An empirical Bayes method implemented in IQ-TREE was used to infer the ancestral states of the input sequences ( Minh et al., 2020 ; VanAntwerp et al., 2022 ; Yang et al., 1995 ). The previously generated alignment and tree files were input to IQ-TREE, specifying the options “-s DNA -o SlNRCX -m TIM3+F+I+R4”. Since IQ-TREE does not infer the ancestral states of insertion and deletion events (indels), the sequence alignment was converted to a simple binary presence-absence alignment file. In this file, “0” and “1” represent non-gap and gap, respectively. The Jukes-Cantor type binary model (JC2) in IQ-TREE was used to infer the ancestral states of this binary data, similar to how a previous study did with RAxML ( Aadland et al., 2019 ; Stamatakis, 2014 ). For indel reconstruction, the branch lengths of the tree were fixed with the “-blfix” option. Finally, the results of ancestral sequence reconstruction were combined with those of ancestral indel reconstruction, and the probabilities of each codon were calculated by simply multiplying the probabilities of each nucleotide. A probability value ( p ) greater than 0.3 was considered as an ambiguous residue. Focusing on the three interfaces defined by the crystal structure of SlNRC1 NB-ARC in complex with SS15, six different ancestral variants (anc1.1, anc1.2, anc2, anc3/4, anc5, anc6.2) were cloned and tested ( S2 Table ). The ancestral interfaces of anc6.1 were identical to those of WT SlNRC3. This programming pipeline was named “ancseq” and deposited on Github ( https://github.com/YuSugihara/ancseq ). Download figure Open in new tab S1 Fig. Multiple levels of gene-for-gene interactions between pathogens and plants. To date, most studies have focused on coevolution between R (immune receptors or R genes) and AVR effectors, of which there are numerous examples. On the other hand, coevolution between pathogen effectors with immunosuppression activities (suppressors) and their receptor targets are less understood. Download figure Open in new tab S2 Fig. Phylogenetic tree of helper NRC0/1/2/3/X clades and the sequences used in Fig 2B . We used the NRC sequences of the NRC0, NRC1, NRC2, NRC3 and NRCX clades from four different Solanaceae species ( Nicotiana benthamiana , Capsicum annuum , Solanum tuberosum and Solanum lycopersicum ) and created a phylogenetic tree. When a cloned sequence is not identical to any sequences in the dataset, we added them to the dataset. Each cloned NRC sequence is highlighted in red. When a cloned sequence is identical to multiple NRC sequences in the tree, they are indicated in the figure. The phylogenetic tree is reconstructed by the maximum likelihood method using IQ-TREE with 1,000 bootstrap replicates. Download figure Open in new tab S3 Fig. Phylogenetic tree of 314 non-redundant nucleotide sequences from NRC1/2/3/X clade. The 314 non-redundant nucleotide sequences of the NRC1/2/3/X clade were extracted from 124 genomes in the Solanaceae family ( Sugihara et al., 2023b ). The codon-based nucleotide sequence alignment of these sequences was used to reconstruct the phylogenetic tree. The phylogenetic tree was reconstructed by the maximum likelihood method using IQ-TREE with 1,000 bootstrap replicates. If an identical sequence is found in more than one species, all the species names are listed in brackets. Download figure Open in new tab S4 Fig. SDS-PAGE accompanying BN-PAGE shown in Fig 4A . C-terminally 4xMyc-tagged CaNRC3 EEE mutants were co-expressed with C-terminally V5-tagged Rx and either free GFP or C-terminally GFP-tagged PVX CP in the leaves of N. benthamiana nrc2/3/4 KO plants. These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein or N-terminally 4xHA-tagged SS15. Rubisco loading control was carried out using Ponceau staining (PS). Download figure Open in new tab S5 Fig. SDS-PAGE accompanying BN-PAGE shown in Fig 4B . C-terminally 4xMyc-tagged StNRC3 EEE mutants were co-expressed with C-terminally V5-tagged Rx and either free GFP or C-terminally GFP-tagged PVX CP in the leaves of N. benthamiana nrc2/3/4 KO plants. These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein or N-terminally 4xHA-tagged SS15. Rubisco loading control was carried out using Ponceau staining (PS). Download figure Open in new tab S6 Fig. SDS-PAGE accompanying BN-PAGE shown in Fig 4C . C-terminally 4xMyc-tagged SlNRC3 EEE mutants were co-expressed with C-terminally V5-tagged Rx and either free GFP or C-terminally GFP-tagged PVX CP in the leaves of N. benthamiana nrc2/3/4 KO plants. These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein or N-terminally 4xHA-tagged SS15. Rubisco loading control was carried out using Ponceau staining (PS). Download figure Open in new tab S7 Fig. Statistical analysis of Fig 6B . We used a two-sided permutation test with 10,000 replicates. Statistically significant differences are indicated (***: p < 0.001; n.s.: not significant). Each column represents an independent experiment. The data underlying this figure can be found in S1 Data. Download figure Open in new tab S8 Fig. SDS-PAGE accompanying BN-PAGE shown in Fig 6C . C-terminally 4xMyc-tagged ancestral NRC3 EEE variants were co-expressed with C-terminally V5-tagged Rx and C-terminally GFP-tagged PVX CP in the leaves of N. benthamiana nrc2/3/4 KO plants. These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein or N-terminally 4xHA-tagged SS15. Download figure Open in new tab S9 Fig. Tomato NRC3 accumulates mutations that confer robust insensitivity to SS15. (A) Representative images of HR cell death assays showing the results after transient co-expression of either an empty vector (EV) or SS15 with Rx and PVX CP, along with either WT SlNRC3, SlNRC3 K314E or the ancestral NRC3 variants (anc1.1 and anc1.2) in the leaves of N. benthamiana nrc2/3/4 KO plants. The anc1.1 and anc1.2 are the ancestral NRC3 variants tested in Fig 6 . The leaves were photographed 5 days after infiltration. (B) Statistical analysis of S9A Fig using a two-sided permutation test with 10,000 replicates. Statistically significant differences are indicated (***: p < 0.001; n.s.: not significant). Each column represents an independent experiment. (C) BN-PAGE assays for WT SlNRC3, SlNRC3 K314E and anc1.1. C-terminally 4xMyc-tagged NRC3s were co-expressed with C-terminally V5-tagged Rx and C-terminally GFP-tagged PVX CP in the leaves of N. benthamiana nrc2/3/4 KO plants. These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein or N-terminally 4xHA-tagged SS15. A red arrowhead indicates resistosome bands. Corresponding SDS-PAGE blots are in S10 Fig. The data underlying S9B Fig can be found in S1 Data. Download figure Open in new tab S10 Fig. SDS-PAGE accompanying BN-PAGE shown in S9C Fig. C-terminally 4xMyc-tagged ancestral NRC3 variants were co-expressed with C-terminally V5-tagged Rx and either free GFP or C-terminally GFP-tagged PVX CP in the leaves of N. benthamiana nrc2/3/4 KO plants. These effector-sensor-helper combinations were co-expressed either with mCherry-6xHA fusion protein or N-terminally 4xHA-tagged SS15. Rubisco loading control was carried out using Ponceau staining (PS). S1 Table. Summary of ancestral sequence reconstruction probabilities. S2 Table. Cloning details of constructs used in this study. S1 Data. Underlying numerical data for Figs 3C , S7 and S9B . DATA AVAILABILITY The datasets used in this study are archived in Zenodo ( https://doi.org/10.5281/zenodo.10729126 ). The ancestral sequence reconstruction pipeline “anceseq” is available on Github ( https://github.com/YuSugihara/ancseq ) and archived in Zenodo ( https://doi.org/10.5281/zenodo.10808871 ). AUTHOR CONTRIBUTIONS Conceptualisation: Jiorgos Kourelis, Sophien Kamoun Data curation: Claudia Martínez-Anaya, Yu Sugihara, Jiorgos Kourelis, AmirAli Toghani Funding acquisition: Sophien Kamoun Formal analysis: Claudia Martínez-Anaya, Yu Sugihara, Muniyandi Selvaraj Methodology: Yu Sugihara, Mauricio P. Contreras, Hsuan Pai Project administration: Sophien Kamoun Resources: Jiorgos Kourelis Supervision: Claudia Martínez-Anaya, Sophien Kamoun, Jiorgos Kourelis, Mauricio P. 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