Arabidopsis thaliana Iron Superoxide Dismutase FeSOD1 Protects ARGONAUTE 1 in a Copper-Dependent Manner

Arabidopsis thaliana Iron Superoxide Dismutase FeSOD1 Protects ARGONAUTE 1 in a Copper-Dependent Manner | 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 Arabidopsis thaliana Iron Superoxide Dismutase FeSOD1 Protects ARGONAUTE 1 in a Copper-Dependent Manner View ORCID Profile Ariel H. Tomassi , View ORCID Profile Ana Perea-García , View ORCID Profile Guillermo Rodrigo , View ORCID Profile Javier Sánchez-Vicente , View ORCID Profile Adriana E. Cisneros , Marta Olmos , Amparo Andrés-Bordería , View ORCID Profile Lucio López-Dolz , View ORCID Profile José- Antonio Daròs , View ORCID Profile Lola Peñarrubia , View ORCID Profile Alberto Carbonell doi: https://doi.org/10.1101/2025.02.26.640378 Ariel H. Tomassi 2 Instituto de Biología Molecular y Celular de Plantas (Consejo Superior de Investigaciones Científicas–Universitat Politècnica de València) , Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ariel H. Tomassi Ana Perea-García 3 Departament de Bioquímica i Biología Molecular, Universitat de València , Burjassot, Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ana Perea-García Guillermo Rodrigo 4 Institute for Integrative Systems Biology (I2SysBio), CSIC – University of Valencia , Paterna 46980, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Guillermo Rodrigo Javier Sánchez-Vicente 2 Instituto de Biología Molecular y Celular de Plantas (Consejo Superior de Investigaciones Científicas–Universitat Politècnica de València) , Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Javier Sánchez-Vicente Adriana E. Cisneros 2 Instituto de Biología Molecular y Celular de Plantas (Consejo Superior de Investigaciones Científicas–Universitat Politècnica de València) , Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Adriana E. Cisneros Marta Olmos 3 Departament de Bioquímica i Biología Molecular, Universitat de València , Burjassot, Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Amparo Andrés-Bordería 3 Departament de Bioquímica i Biología Molecular, Universitat de València , Burjassot, Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lucio López-Dolz 2 Instituto de Biología Molecular y Celular de Plantas (Consejo Superior de Investigaciones Científicas–Universitat Politècnica de València) , Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lucio López-Dolz José- Antonio Daròs 2 Instituto de Biología Molecular y Celular de Plantas (Consejo Superior de Investigaciones Científicas–Universitat Politècnica de València) , Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for José- Antonio Daròs Lola Peñarrubia 3 Departament de Bioquímica i Biología Molecular, Universitat de València , Burjassot, Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lola Peñarrubia For correspondence: acarbonell{at}ibmcp.upv.es Alberto Carbonell 2 Instituto de Biología Molecular y Celular de Plantas (Consejo Superior de Investigaciones Científicas–Universitat Politècnica de València) , Valencia, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alberto Carbonell For correspondence: acarbonell{at}ibmcp.upv.es Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT Copper (Cu) deficiency compromises plant growth and limits crop productivity. Plants respond to Cu scarcity by activating the expression of several microRNAs, known as Cu-miRNAs, which degrade mRNAs from various cuproproteins to conserve Cu. Cu-miRNAs, like most plant miRNAs, associate with ARGONAUTE 1 (AGO1), the primary effector protein of miRNA-mediated gene silencing pathways, whose function is typically modulated by interacting proteins acting as cofactors. However, how AGO1 is regulated and functions under Cu deficiency remains unknown. Here, we searched for AGO1 interactors in Arabidopsis thaliana plants expressing a functional AGO1 protein tagged with the Twin-Strep-tag (TST) polypeptide, grown under Cu-sufficient or Cu-deficient conditions. TST-AGO1 complexes were affinity-purified, and proteins were identified using tandem mass spectrometry. Interestingly, the iron superoxide dismutase 1 (FeSOD1) encoded by FSD1 , was enriched in TST-AGO1 complexes purified from plants grown under Cu deficiency. Moreover, fsd1-2 mutant plants showed reduced levels of AGO1 compared to wild-type plants under Cu sufficiency, while both Cu-miRNA-specific and general AGO1 target mRNAs accumulated to higher levels in fsd1-2 plants under both Cu-deficient and Cu-sufficient conditions compared to wild-type plants. These findings suggest that FeSOD1 is essential for proper AGO1 function, and that its superoxide dismutase activity, which mitigates oxidative stress, enhances AGO1 stability, particularly under Cu deficiency. HIGHLIGHT AGO1 is essential for Cu-deficiency responses but is sensitive to oxidative stress. FeSOD1 interacts with AGO1 and protects it from superoxide radical-induced degradation, thereby preserving miRNA-mediated gene silencing pathways. INTRODUCTION Plants require rapid and flexible responses to changing environmental conditions throughout their developmental stages, particularly under stress. MicroRNAs (miRNAs) are a class of small RNAs (sRNAs) that regulate gene expression post-transcriptionally and function as key players in the interplay between development and stress responses ( Borges and Martienssen, 2015 ; Song et al ., 2019 ). miRNAs regulate a wide range of developmental processes including hypocotyl elongation, root development and the transition from vegetative to reproductive phases ( Schwab et al ., 2005 ; Meng et al ., 2010 ). Conversely, certain miRNAs are integral to stress responses, modulating plant adaptation to a multitude of environmental conditions such as nutrient availability, low temperatures and drought ( Patel et al ., 2017 ; Martin et al ., 2010 ; Buhtz et al ., 2010 ). For instance, miRNAs involved in nutrient stress, including transition metal deficiencies, play significant roles in plant adaptation ( Patel et al ., 2017 ) by regulating processes like metal uptake, chelation, antioxidant response and hormone signaling ( Ding et al ., 2020 ). The availability of essential transition metals, such as copper (Cu) and iron (Fe), often limit agricultural productivity ( Broadley et al ., 2012 ). These metals, essentials as cofactors in metalloproteins central to life, can also cause toxicity when in excess, leading to increased reactive oxidative species (ROS) production ( Farooq et al ., 2019 ). Due to their dual nature as essential and toxic elements, plants have developed complex homeostatic networks to assure their uptake and distribution while preventing toxicity ( Puig and Peñarrubia, 2009 ; Pilon, 2011 ; Kobayashi et al ., 2019 ; Kumar et al ., 2021 ). ROS are also produced under metal scarcity, as the malfunctioning of key redox metalloproteins in respiratory and photosynthetic electron transport chains causes oxidative stress ( Shahbaz and Pilon, 2019 ). Among ROS, the superoxide radical is one of the most harmful species, capable of damaging macromolecules. ROS detoxification involves superoxide dismutases (SODs), which in plants use different metals as cofactors, functioning in various cellular compartments under diverse conditions. Plant SODs include FeSODs, Cu and zinc (Zn)SODs (Cu/ZnSODs) and manganese (Mn) MnSODs ( Ravet and Pilon, 2013 ). In Arabidopsis thaliana (Arabidopsis), the denoted as Cu-miRNAs play crucial roles in plant responses under Cu deficiency, orchestrating metal redistribution and substituting Cu/ZnSODs with FeSODs ( Yamasaki et al ., 2007 ; Pilon, 2017 ). Cu-miRNAs are proposed to modulate metalloprotein mRNAs post-transcriptionally, establishing a metal prioritization hierarchy and preventing interference with metal-sensitive processes ( Perea-García et al ., 2022 ; Shahbaz and Pilon, 2019 ). Cu-miRNAs, including miR397, miR398, miR408 and miR857, are induced under Cu deficiency and primarily target mRNAs encoding Cu/ZnSODs ( CSD1 and CSD2 ), plantacyanin and laccases ( Pilon, 2017 ). Cu-miRNAs containing cis - regulatory domains in their promoters, recognized by a SQUAMOSA BINDING PROTEIN- LIKE (SPL) family member, SPL7, the master transcription factor driving Cu-deficiency responses ( Yamasaki et al ., 2009 ; Bernal et al ., 2012 ). In addition to Cu-miRNAs, plasma membrane Cu transporters genes ( COPT1 , COPT2 and COPT6 ) as well as FSD1 (encoding FeSOD1) are regulated similarly ( Yamasaki et al ., 2007 ; Bernal et al ., 2012 ; Garcia-Molina et al ., 2013 ). These processes enhance high affinity Cu uptake and metalloprotein substitution as primary responses to nutrient scarcity. Importantly, SPL7 belongs to a large family of transcription factors mainly involved in the control of developmental phase transitions and reproduction ( Huijser and Schmid, 2011 ). Based on their sizes and similarities, the Arabidopsis SPL family can be grouped in two subfamilies: large SPLs (including SPL1, SPL7, SPL12, SPL14 and SPL16) and small SPLs (the remaining 11 SPLs) ( Guo et al ., 2008 ; Xing et al ., 2010 ). The small SPLs, with the exception of SPL8, share a miRNA response element that is complementary to miR156 responsive in the timing of the vegetative and reproductive phase transitions ( Rhoades et al ., 2002 ; Schwab et al ., 2005 ; Wu and Poethig, 2006 ; Gandikota et al ., 2007 ). SPL3 overexpressing plants, resistant to miR156 regulation, display a strong reduction in SPL7- mediated Cu-deficiency responses, probably due to competition between SPL7 and miR156- regulated SPL3 for cis element binding in target promoters ( Perea-García et al ., 2021 ). Therefore, the balance of miR156 SPL targets and non-targets is essential for SPL7-mediated Cu-deficiency adaptation at different levels, underscoring that the effect of miRNA on its targets could serve to reinforce the miRNA non-target function. Thus, while Cu-miRNAs function as post-transcriptional modulators of metalloproteins, allowing flexible Cu redistribution, other miRNAs, such as miR156, operate upstream, balancing the relative abundance of SPL transcription factors to integrate Cu-deficiency responses with developmental processes. ARGONAUTE (AGO) proteins act as the effector proteins in sRNA-mediated RNA silencing pathways in eukaryotes ( Meister, 2013 ). In plants, AGOs regulate essential biological processes such as development, stress responses, genome stability and defense against pathogens, particularly to viruses ( Carbonell, 2017 ; Fang and Qi, 2016 ; Carbonell and Carrington, 2015 ). They associate with sRNAs such as miRNAs and siRNAs to form the RNA- induced silencing complex (RISC), which directs the endonucleolytic cleavage or translational repression of sequence-complementary target RNAs ( Huntzinger and Izaurralde, 2011 ). Arabidopsis has 10 AGO members that have functionally diverged during the specialization of sRNA-based RNA silencing pathways ( Chapman and Carrington, 2007 ). AGO1 is the principal miRNA-associating AGO ( Vaucheret et al ., 2004 ) and, consequently, ago1 mutants show severe growth defects ( Morel et al ., 2002 ). AGO1 protein levels, are regulated at different transcriptional and posttranscriptional levels ( Molinier, 2020 ). For instance, AGO1 can be ubiquitinated and degraded through the ubiquitin-proteasome pathway that tags AGOs with ubiquitin molecules for their degradation by the 26S proteasome ( Earley et al ., 2010 ), or through autophagy by sequestration of AGO1 proteins in autophagosomes ( Derrien et al ., 2012 ). In contrast, AGO1 protein is stabilized by its binding to sRNAs ( Vaucheret et al ., 2006 ; Hacquard et al ., 2022 ), as unloaded AGO1 is more prone to degradation, by its sequestration into stress granules ( Leung et al ., 2006 ) or through its association with co-factors. AGO1 physically interacts with several proteins, including chaperones involved in RISC loading such as HEAT SHOCK PROTEIN 70 (HSP70), HSP90 and CYCLOPHILLIN 40/SQUINT (CYP40/SQN), which facilitate the conformational opening of AGO1 during sRNA loading ( Iki et al ., 2010 ; Iwasaki et al ., 2010 ; Iki et al ., 2012 ). Moreover, TRANSPORTIN 1 (TRN1), ENHANCED MiRNA ACTIVITY 1 (EMA1) β and CONSTITUTIVE ALTERATIONS IN THE SMALL RNAS PATHWAYS 9 (CARP9) proteins interact with AGO1 to modulate miRNA loading ( Wang et al ., 2011 ; Cui et al ., 2016 ; Tomassi et al ., 2020 ), while PROTEIN ARGININE METHYLTRANSFERASE 5 (PRMT5) associate with AGO1 to promote its methylation ( Martín-Merchán et al ., 2024 ). Finally, proteins known to interact with AGO1 in response to stress are limited to DAMAGE-SPECIFIC DNA BINDING PROTEIN 2 (DDB2), TUDOR DOMAN-CONTAINING PROTEIN 1 (TSN1) and TSN2 and SWI/SNF complexes in response to UV, general stress and hormone or cold stress, respectively ( Liu et al ., 2018 ; Gutierrez-Beltran et al ., 2021; Schalk et al ., 2017 ). However, proteins specifically interacting with AGO1 during the metal stress response have not been identified. To better understand AGO1’s role in response to Cu deficiency, we searched for AGO1 interactors in Arabidopsis transgenic lines expressing a functional AGO1 protein tagged with the bidentate polypeptide Twin-Strep-tag (TST), grown under Cu-sufficient or Cu-deficient conditions. AGO1 complexes were affinity-purified, and proteins were identified by tandem mass spectrometry (AP-MS or affinity purification mass spectrometry). Interestingly, FSD1 - encoded FeSOD1, recently proposed as an AGO1 interactor as a result of a yeast two-hybrid screening ( Bressendorff et al ., 2023 ), was enriched in AGO1 complexes purified from plants grown under Cu deficiency. fsd1-2 mutant plants accumulated lower levels of AGO1 compared to Col-0 plants under Cu sufficiency, and both Cu-miRNA-specific and general AGO1 target mRNAs accumulated to higher levels in fsd1-2 plants grown under Cu deficiency and sufficiency, respectively, compared to Col-0. These results underscore the role of FeSOD1 in protecting AGO1 stability, especially under Cu deficiency, where its function in miRNA- mediated gene silencing pathways becomes particularly important. RESULTS Generation and functional characterization of Arabidopsis transgenic lines expressing TST-tagged AGO1 TST is an advanced affinity tag used for the purification and detection of recombinant proteins under non-denaturing, mild conditions ( Schmidt et al ., 2013 ). It consists of a tandem arrangement of two Strep-tag II sequences, designed to enhance binding affinity to Strep-Tactin, a derivative of streptavidin. The TST coding sequence was inserted after AGO1 start codon to tag the N-terminus of AGO1, a previously done with hemagglutinin (HA) or FLAG peptides ( Baumberger and Baulcombe, 2005 ; Carbonell et al ., 2012 ), in the pAGO1:TST-AGO1 construct, which includes authentic AGO1 regulatory sequences ( Figure 1A ). As a control, the pAGO1:TST-GFP construct, designed to express TST-tagged GFP under the same AGO1 regulatory sequences, was also generated ( Figure 1A ). To test the functionality of TST-AGO1, pAGO1:TST-AGO1 and pAGO1:TST-GFP constructs were transformed in both Col-0 and ago1-25 genetic backgrounds. At least, 24 independent T1 transgenic lines were recovered for each construct in both backgrounds. Interestingly, ago1-25 phenotypic defects, such as slow growth or delayed flowering, were suppressed in plants expressing pAGO1:TST-AGO1 , but not in plants expressing pAGO1:TST-GFP ( Figure 1B and 1C ). In contrast, plants expressing either construct in the Col-0 background were phenotypically similar to non-transformed Col-0 plants ( Figure 1B and 1C ). Importantly, plants expressing pAGO1:TST-AGO1 or pAGO1-TST-GFP constructs accumulated high levels of TST-AGO1 and TST-GFP proteins, respectively, as observed in the western blot analysis ( Figure 1D ). To further investigate TST-AGO1 functionality, AGO1-dependent TAS1c tasiRNA 255 (tasiR255) formation was analyzed in T1 transgenic plants. TasiR255 accumulation levels were restored to Col-0 levels in ago1-25 plants transformed with pAGO1:TST-AGO1 but not in ago1-25 plants transformed with pAGO1:TST-GFP ( Figure 1D ). Finally, tasiR255 levels in transgenic lines expressing either construct in the Col-0 background were similar than those of non-transformed Col-0 plants. Overall, these results indicate that the addition of a TST tag at the 5’ terminus of Arabidopsis AGO1 does not affect AGO1 functionality. They also suggest that the expression of TST-AGO1 in a Col-0 background does not impair plant growth or AGO1 functionality. Download figure Open in new tab Figure 1. Phenotypic and molecular analyses of Arabidopsis Col-0 and ago1-25 transgenic plants expressing TST-tagged AGO1 or GFP. A , Diagram of the constructs. TST, GFP and AGO1 sequences are shown in orange, green and dark blue boxes, respectively. AGO1 endogenous promoter and 3’ UTR regulatory sequences are shown in a light blue arrow and box, respectively. B , Pictures of 21-day-old Col-0 (top panel) and ago1-25 (bottom panel) T1 transgenic plants, homozygous for the transgene. Col-0 and ago1-25 non-transgenic controls (NTCs) are included. C , Box plot representing the mean flowering time of Col-0 and ago1-25 NTC and T1 transgenic plants ( n = 24). Pairwise Student’s t -test comparisons are represented with an * if significantly different ( P < 0.05) compared to Col-0 NTC. D , Accumulation of TAS1c -dependent tasiRNA (tasiR255) and TST-AGO1 in T1 transgenic lines. The graph at the top shows the mean ( n = 3) relative to tasiR255 levels + standard deviation (Col-0 = 1.0). One blot from three biological replicates is shown. Each biological replicate is a pool of at least eight independent lines that were randomly selected. U6 and L-Rubisco (ribulose-1,5-bisphosphate carboxylase/oxygenase) blots are shown as loading controls. Other details are as in C. AP-MS analysis of AGO1 protein complexes in response to Cu deficiency stress Given the previously described key role of miRNA-mediate gene regulation in response to Cu deficiency ( Pilon, 2017 ; Perea-García et al ., 2022 ), we analyzed the AGO1 protein interactome under Cu deficiency compared to Cu sufficiency, using three independent T4 pAGO1:TST-AGO1 transgenic lines to study AGO1 function in both conditions: lines 1, 2 and 3. As a negative control, one T4 pAGO1:TST-GFP transgenic line was also grown in parallel under the same conditions. Seedlings of each transgenic line were grown for 10 days under Cu sufficiency (1 μM CuSO4) or under Cu deficiency (100 μM bathocuproine disulphonate, BCS) conditions. AGO1 and GFP protein complexes were purified by affinity chromatography in native conditions. Proteins from the purified complexes were resolved using denaturing polyacrylamide gel electrophoresis (PAGE) and subsequently subjected to in-gel digestion with trypsin. The resulting peptides were extracted from the gel and analyzed by liquid chromatography coupled with tandem mass spectrometry to identify the proteins in the purified complexes. Data S1 shows all hits resulting from proteomic analysis of complexes purified from seedlings of each transgenic line grown under Cu sufficiency and Cu deficiency. Next, we examined the dynamics of the AGO1 protein interactome in response to Cu deficiency. Proteins from purified samples were processed using the ProteinPilot ( Shilov et al ., 2007 ) and Mascot ( Perkins et al ., 1999 ) software tools, and the identified proteins were matched against the Viridiplantae protein database to filter for plant-specific proteins ( Figure 2A ). These plant proteins were further analyzed using the BLAST tool ( Altschul et al ., 1990 ) against the NCBI Genomes to identify Arabidopsis-specific proteins. The total number of proteins identified in the three pAGO1:TST-AGO1 lines under Cu deficiency were similar (2185, 2099 and 2002 for lines 1, 2 and 3, respectively), although higher than the number observed in all lines under Cu sufficiency (1565, 1680 and 1749 for lines 1, 2 and 3, respectively) ( Figure 2B ). The total number of proteins identified in the pAGO1:TST-GFP line under Cu deficiency and sufficiency was rather similar (2080 and 1975, respectively) ( Figure 2B ).We then quantified the change in the abundance of AP-MS interactors under these two conditions (Data S2), discarding those proteins present in the pAGO1:TST-GFP control purifications. A log2 fold change value was assigned for each protein comparison, with log2 fold > 0 indicating that the protein is more abundant in Cu deficiency and log2 fold < 0 indicating higher abundance in Cu sufficiency, respectively. A Venn diagram showed that 89 proteins were more abundant in Cu deficiency than in Cu sufficiency in the three lines ( Figure 2C , Data S3). Among these proteins, we considered the Fe superoxide dismutase 1 protein (FeSOD1) for our subsequent analyses, as it was recently identified as an AGO1 interactor in yeast two hybrid assays ( Bressendorff et al ., 2023 ) and was also known to participate in oxidative stress responses in a Cu-dependent manner ( Melicher et al ., 2022 ). Download figure Open in new tab Figure 2. Protein analyses in TST-AGO1 complexes purified by AP-MS . A , Flowchart of the process for plant protein identification. Proteins from purified samples are processed through ProteinPilot and Mascot software tools, and identified proteins are matched against the Viridiplantae protein database to filter for plant proteins. The plant proteins are further analyzed using the Blast tool against the NCBI Genomes database to identify Arabidopsis-specific proteins. B , Bar chart showing the total number of proteins identified by AP-MS in the three different pAGO1-TST-AGO1 transgenic lines grown under copper (Cu) deficiency (light grey bars) or Cu sufficiency (dark grey bars). C , Venn diagram comparing the total number of proteins in Cu deficiency versus Cu sufficiency identified in the three pAGO1:TST-AGO1 transgenic lines. The cutoff value for significant fold change is set at log2 fold = 1, meaning that only proteins enriched in Cu deficiency versus Cu sufficiency are represented. Overlapping section indicates the proteins identified in purified samples from independent transgenic lines. AGO1 and FeSOD1 fine-tune Cu-responsive SOD gene expression To assess the impact of Cu deficiency on plant growth, Arabidopsis Col-0, fsd1-2 (loss-of-function mutant for FSD1 ), and ago1-25 (mutant for AGO1 ) seedlings were grown under Cu-sufficient and Cu-deficient conditions ( Figure 3A ), and their root lengths were quantified ( Figure 3B ). Under Cu sufficiency, all genotypes displayed healthy growth, with fsd1-2 seedlings showing a slight but statistically significant increase in root length compared to Col-0 ( P < 0.05), while ago1-25 seedlings exhibiting a pronounced decrease as observed before in other ago1 mutants ( Trolet et al ., 2019 ). Under Cu deficiency, root growth was significantly inhibited across all genotypes ( Figure 3A , 3B). Download figure Open in new tab Figure 3. Analysis of Arabidopsis superoxide dismutase genes under copper sufficiency and deficiency conditions in Col-0, fsd1-2 and ago1-25 seedlings. A , Photographs of 10-day-old of Col-0, fsd1-2 and ago1-25 seedlings grown on plates with MS medium in Cu sufficiency (1 µM Cu) or deficiency (100 µM BCS). B , Quantification of root length of Col-0, fsd1-2 and ago1-25 seedlings grown in the same conditions than in A. Mean relative level ( n = 40-45) + standard error of root length. Pairwise Student’s t -test comparisons are represented with an * if significantly different ( P < 0.05) compared to Col-0 in each condition. C , Relative expression of CSD1, CSD2, FSD1 and MSD1 mRNAs determined by RT-qPCR in 10-day-old Col-0, fsd1-2 and ago1-25 seedlings, grown under control (Cu sufficiency, 1 μM CuSO4) and Cu deficiency (100 μM BCS). Mean relative level ( n = 3) + standard error of mRNAs after normalization to ACTIN2 . Bars with an * are significantly different from that of the Col-0 control sample ( P < 0.05 in all pairwise Student’s t -test comparisons). Other t -test comparisons are also shown. Each biological replicate is a pool of at least twenty independent lines that were randomly selected. Expression of SOD genes is an excellent marker for Cu status in plant cells ( Yamasaki et al ., 2009 ; Andrés-Colás et al ., 2013 ). To examine SOD expression under our experimental conditions, mRNA accumulation of CSD1 , CSD2 , FSD1 and MSD1 was measured by RT-qPCR ( Figure 3C ) in Col-0, fsd1-2 and ago1-25 seedlings. As previously reported ( Yamasaki et al ., 2009 ), expression of Cu/Zn SODs encoded by CSD1 and CSD2 in Col-0 seedlings was high under Cu sufficiency but remained low under Cu deficiency ( Figure 3A ). Although the expression pattern in ago1-25 was similar, CSD expression was significantly higher in most cases ( Figure 3C ). Since CSD expression is regulated by miR398 , the impaired AGO1 function in ago1-25 could explain this difference. On the other hand, expression of FeSOD1, encoded by FSD1, remained low under Cu sufficiency and was higher under Cu deficiency in both genotypes, although it was significantly lower in ago1-25 under Cu deficiency ( Figure 3C ). This suggests an indirect effect of AGO1 function on FSD1 transcription under Cu deficiency, potentially due to miR156 influencing the ratio of different SPL members and thereby affecting SPL7’s occupancy of Cu deficiency target promoters ( Perea-García et al ., 2021 ). Finally, expression of MnSOD, encoded by MSD1, remained approximately constant across both genotypes and conditions ( Figure 3C ). FeSOD1 is essential for AGO1 stability and functionality, particularly under Cu deficiency Next, we investigated whether FeSOD1 function was required for proper AGO1 expression. To do so, AGO1 protein levels were measured by western blot in 10-day-old Col-0, fsd1-2 and ago1-25 seedlings grown under Cu sufficiency and Cu deficiency conditions ( Figure 4A ). Surprisingly, AGO1 protein levels in Col-0 plants drastically dropped (around 90%) in Cu deficiency compared to Cu sufficiency. This decrease was similar to that observed in ago1-25 plants grown under both Cu conditions. Additionally, AGO1 protein levels also decreased by about 80% in fsd1-2 seedlings compared to Col-0 plants under Cu sufficiency ( Figure 4A ). These results indicate an important decrease in AGO1 protein in Col-0 plants grown content under Cu deficiency, and in fsd1-2 seedlings grown under both Cu conditions. Download figure Open in new tab Figure 4. Accumulation of AGO1 protein and mRNA in Arabidopsis Col-0 , fsd1-2 and ago1-25 seedlings. A , Accumulation of endogenous AGO1 protein in 10-day-old Col-0, fsd1-2 and ago1-25 seedlings, grown under control (Cu sufficiency) and Cu deficiency. The graph at the top shows the mean ( n = 3) relative to endogenous AGO1 levels + standard deviation (Col-0 = 1.0). One blot from three biological replicates is shown. Each biological replicate is a pool of at least twenty independent lines that were randomly selected. HISTONE H3 (H3) blot is shown as loading control. B , Relative expression of AGO1 determined by RT-qPCR in 10-day-old Col-0, fsd1-2 and ago1-25 seedlings, grown under control and Cu deficiency. Mean relative level ( n = 3) + standard error of mRNA after normalization to ACTIN2 (Col-0 = 1.0). Bars with an * are significantly different from that of the Col-0 control sample ( P < 0.05 in all pairwise Student’s t -test comparisons). Each biological replicate is a pool of at least twenty independent lines that were randomly selected. To further investigate whether the reduction in AGO1 protein levels was due to transcriptional regulation, we analyzed AGO1 mRNA levels by RT-qPCR ( Figure 4B ) in the same samples used for AGO1 protein analysis ( Figure 4A ). Under Cu sufficiency, AGO1 transcript levels were significantly higher in fsd1-2 compared to Col-0, suggesting that FeSOD1 function may influence AGO1 expression. Additionally, ago1-25 mutants exhibited a significant increase in AGO1 mRNA levels relative to Col-0, likely due to impaired miR168-mediated AGO1 mRNA regulation caused by reduced AGO1 activity ( Vaucheret et al ., 2006 ). Under Cu deficiency, AGO1 transcript accumulation markedly increased in Col-0, fsd1-2 and ago1-25 seedlings compared to Cu sufficiency, with ago1-25 displaying the highest expression levels ( Figure 4B ). These results indicate that the reduction in AGO1 protein levels under Cu deficiency is not due to decreased AGO1 transcript accumulation. To further assess the relationship between AGO1 mRNA and protein levels, we calculated the relative ratio of AGO1 mRNA to AGO1 protein accumulation in the same samples ( Figure 4C ). Under Cu sufficiency, this ratio (R) was much higher in fsd1-2 (R=4.9) and ago1-25 (R=40.6) mutants compared to Col-0 (R=1), indicating that despite increased AGO1 transcript levels, AGO1 protein accumulation remained low in these mutants. Under Cu deficiency, the AGO1 mRNA/protein ratio increased more drastically across all genotypes, particularly in ago1-25 , which exhibited the highest ratio (R=50.2) among the conditions tested. To determine whether the decrease in AGO1 protein content also affected its functionality under Cu deficiency, the expression of several Cu-miRNA targets ( ARPN, miR160 target; CCS, CSD1, CSD2, miR398 targets; GST25, miR396 target; LAC3 , miR397 target) was analyzed by RT-qPCR in 10-day-old Col-0, fsd1-2 and ago1-25 seedlings ( Figure 5A ). As expected, the expression of all Cu-miRNA targets (except for GSTU25 ) significantly increased in ago1-25 compared to Col-0. Similarly, all miRNA targets were induced to varying degrees in fsd1-2 compared to Col-0, with the increase in CSD1 being statistically significant ( Figure 5A ). These findings confirm that AGO1 functionality requires the presence of FeSOD1 under Cu deficiency. Download figure Open in new tab Figure 5. Accumulation of miRNA target genes in Arabidopsis Col-0 , fsd1-2 and ago1-25 seedlings. A , Relative expression of Cu-miRNA targets ARPN , CCS , LAC3 and GSTU25 determined by RT-qPCR in 10-day-old Col-0, fsd1-2 and ago1-25 seedlings, grown under Cu deficiency. Mean relative level ( n = 3) + standard error of mRNAs after normalization to ACTIN2 (Col-0 = 1.0). Bars with an * are significantly different from that of the Col-0 control sample ( P < 0.05 in all pairwise Student’s t -test comparisons). Each biological replicate is a pool of at least twenty independent lines that were randomly selected. B, Relative expression of miRNA targets ARF8 , NF-YA9, SPL3 , SPL9 and TCP4 determined by RT-qPCR in 10-day-old Col-0, fsd1-2 and ago1-25 seedlings, grown under Cu sufficiency (1 μM CuSO4). Other details are as in A. Next, we wondered whether FeSOD1 activity was also required for general AGO1 function under Cu sufficiency and for regulating other non-Cu-miRNA targets. The expression of different well-known miRNA targets ( ARF8 , miR167 target; NF-YA9 , miR169 target; SPL3 and SPL9 , miR156 targets; TCP4 , miR159 target) was analyzed by RT-qPCR in 10-day-old Col-0, fsd1-2 and ago1-25 seedlings grown under Cu sufficiency ( Figure 5B ). As expected, the expression of all miRNA targets was significantly higher in ago1-25 compared to Col-0. Interestingly, the expression of all miRNA targets also increased in fsd1-2 compared to Col-0, with a statistically significant increase observed for four out of five miRNA targets ( ARF8 , SPL3 , SPL9 and TCP4 ). Notably, the increased expression of miR156 targets ( SPL3 and SPL9 ) is relevant, as these targets compete with SPL7 in Cu-deficiency responses ( Perea-García et al ., 2021 ). Finally, the expression of the miRNA targets mentioned above was also analyzed in seedlings of the different genotypes grown under Cu deficiency (Figure S1). The expression of all miRNA targets was higher in both fsd1-2 and ago1-25 compared to Col-0, although this increase was significant only for NF-YA9 and SPL3 in ago1-25 (Figure S1). In conclusion, our results indicate that FeSOD1 is necessary for proper AGO1 function in miRNA-mediated gene silencing. We propose a model ( Figure 6 ) in which FeSOD1’s superoxide dismutase activity protects against oxidative stress, contributing to the increased stability of the AGO1 protein. This protective role of FeSOD1 is especially important under Cu deficiency due to the elevated oxidative stress and the critical role played by Cu-miRNAs in the plant’s response to this nutrient deficit. Absence of FeSOD1 in fsd1-2 mutants results in AGO1 degradation independently of the Cu levels ( Figure 6 ). Download figure Open in new tab Figure 6. Model for the anti-superoxide protection of the AGO1 function by the FeSOD1 dome under Cu deficiency. Top, under Cu sufficiency Cu-miRNA and FSD1 expression are essentially blocked. A basal level of iron superoxide dismutase FeSOD1 allows the protection of AGO1 from reactive oxygen species (ROS) derived from normal cellular metabolism. Middle, under Cu deficiency, the increase presence of ROS, including superoxide anion, induces a certain level of AGO1 degradation. However, in these conditions SPL7 outcompetes SPL3 and SPL9 for binding to cis-regulatory transcriptional elements (GTACs) present in promoters of Cu-miRNA genes and FeSOD1-encoding FSD1, inducing their expression. Increased levels of FeSOD1 play a protective role of the effector complex of RNAi by detoxifying superoxide anion. By directly interacting with AGO1 and/or associated RNA Binding Proteins (RBP), FeSOD1 promotes AGO1 stability contributing to Cu-miRNA and general AGO1 functions. Bottom, in fsd1 mutants, the lack of FeSOD impedes proper detoxification of ROS and leads to AGO1 degradation in both Cu sufficiency (left) and Cu deficiency (right) conditions. DISCUSSION This study investigates plant responses under Cu deficiency conditions, where Cu-miRNAs regulate the mRNAs encoding cuproproteins. Different studies have reported that numerous miRNAs are induced by a variety of environmental stresses, suggesting the existence of shared signaling pathways ( Martin et al ., 2010 ). Plants face a conflictive situation when responding to adverse conditions, give the extensive role of miRNAs in stress responses and the instability of the key protein AGO1 within RISC under suboptimal conditions ( Fang and Qi, 2016 ). To solve this conflict, providing a protective environment to preserve AGO1 function could be crucial for an effective stress response. Here, we explored how Cu deficiency influences the regulation of miRNA targets mediated by AGO1. We analyzed the AGO1 protein interactome in pAGO1:TST-AGO1 Arabidopsis transgenic plants grown under both normal and Cu-deficient conditions. Due to the adverse effects of Cu deficiency on AGO1 function, we searched for interactor proteins with a protective effect on AGO1. Notably, a well-documented response to Cu deficiency is the substitution of Cu/ZnSODs with FeSODs to support antioxidative defense ( Yamasaki et al ., 2009 ). In this context, FeSOD1 was enriched in TST-AGO1 complexes purified from all three pAGO1:TST-AGO1 lines grown in Cu deficiency. Since FeSOD1 was recently identified as an AGO1 interactor in yeast two-hybrid assays ( Bressendorff et al ., 2023 ), the role of FeSOD1-AGO1 interaction became the main focus of our study. Particularly striking is the opposite pattern observed between AGO1 mRNA and protein levels, suggesting that either AGO1 translation or stability is severely compromised under Cu deficiency. This is evidenced by the significant decrease in endogenous AGO1 protein levels in Col-0 plants grown under Cu-deficient conditions compared to Cu-sufficient conditions. A similar opposite pattern is also observed in fsd1-2 and, more drastically, in the ago1-25 mutant, possibly indicating a compensatory increase in AGO1 mRNA synthesis in response to low AGO1 protein levels ( Figure 4 ). The elevated ROS levels induced by Cu deficiency appear to be a key factor explaining AGO1 degradation, as the presence of FeSOD1 detoxifies the cellular oxidative state and safeguards AGO1 function in regulating Cu-miRNA genes or other known targets ( Figure 5A , Figure 6 , Figure S1). Consistently, as peroxide is the reaction product of SODs, the peroxidase PRX32 is also identified as antioxidant molecules interacting with AGO1 under Cu deficiency (Data S3). Whether ROS-induced AGO1 degradation occurs via the ubiquitin-proteasome system, the autophagy pathway or simultaneously through both remains unknown. It is possible that specific proteins target AGO1 for degradation, as reported for the F-box protein FBW2 that assembles an SCF complex that selectively targets for proteolysis AGO1 when it is unloaded ( Hacquard et al ., 2022 ). Alongside Cu-miRNAs, SPL7 can also induce FSD1 expression ( Yamasaki et al ., 2009 ). Our results indicate that defects in AGO1 function impact Cu-miRNAs and FSD1 expression ( Figure 3C ). The reduced expression of FSD1 in ago1-25 likely results from defective miR156 targeting. Indirectly, FSD1 expression is affected by miR156, which main function is to inhibit the gene expression of some members of the SPL protein family (especially SPL3), while it does not affect other members such as SPL7. The purpose seems to be reducing competition between SPL factors for target promoter binding ( Perea-García et al ., 2021 ). Consequently, the defective targeting of miR156 in ago1-25 explains the increased expression of non-SPL7 members (SPL3 and SPL9), potentially disrupting SPL7 responses, including FSD1 expression ( Figure 5 ). Additionally, the expression of miR398 targets, CSDs and CCS , is also reduced in ago1-25 ( Figure 3C ). To test whether the FeSOD1-AGO1 interaction functions reciprocally, we examined the role of FeSOD1 in AGO1 function. FeSOD1 is essential for ROS response, specifically in eliminating superoxide radicals ( Ravet and Pilon, 2013 ). In this sense, the interaction between AGO1 and FeSOD1 suggests that antioxidant protection is necessary for AGO1 function. To check this, we studied the AGO1 protein content in fsd1-2 mutants. Homozygous fsd1-2 seedlings grown under Cu-deficient and Cu-excess conditions exhibit reduced ROS neutralization, affecting phenotypes like increased chlorosis ( Melicher et al ., 2022 ). Moreover, this capacity depends on Cu availability, as FSD1 expression is regulated by Cu status. AGO1 levels depend on Cu status and the presence of FeSOD1, supporting the hypothesis that Cu deficiency and FeSOD1 have a protective role against oxidative damage to AGO1 ( Figure 3B ). Furthermore, the effects on different Cu-miRNA targets ( ARPN , CCS , CSD2 , GSTU25 , LAC3 ) ( Figure 5A ) highlights the defect in AGO1 function in the absence of this protective barrier. Taken together, our findings reveal the challenges plants face under Cu deficiency in maintaining RNA interference efficiency, given the essential role of Cu-miRNAs and the stability of AGO1 protein under these conditions. The substitution of Cu/ZnSOD with FeSOD1 serves as a solution to this compromise ( Figure 6 ). Increased Fe demand for FeSOD1 highlights the interaction between Cu and Fe homeostasis ( Perea-García et al ., 2021 ; Waters et al ., 2012 ). Notably, IRT1, the main Fe transporter, was enriched in TST-AGO1 complexes purified under Cu deficiency. Further studies are needed to clarify the role of the AGO1-IRT1 interaction, although an indirect association via IRT1-RNA binding proteins with the RISC may be plausible. While stress conditions often reveal molecular imbalances, such as RNA interference functioning with unstable AGO1, these balances could also exist under normal conditions, as observed here for AGO1 under Cu sufficiency. Despite low FSD1 levels under Cu sufficiency, the expression of non-Cu-miRNAs, such as miR167 ( ARF8 ) ( Wu et al ., 2006 ), miR169 ( NF-YA9 ) ( Sorin et al ., 2014 ), miR156 ( SPL3 and SPL9 ) ( Kim et al ., 2012 ) and miR159 ( TCP4 ) ( Palatnik et al ., 2007 ) was also affected in fsd1-2 ( Figure 5B ). These findings suggest a broader scenario ( Figure 6 ) where maintaining an antioxidant environment around AGO1 is crucial for proper RNA interference function, particularly under Cu deficiency. MATERIALS AND METHODS Plant materials, growth conditions and plant phenotyping ago1-25 is a hypomorphic mutant obtained in an EMS mutagenesis and described before ( Morel et al ., 2002 ). fsd1-2 (GABI_740E11) is a mutant line derived from a T-DNA insertion and described before ( Melicher et al ., 2022 ). Wild-type Arabidopsis cv Columbia 0 (Col-0), ago1-25 and fsd1-2 seeds were grown on plates where Cu concentration was 1 mM, considered as Cu sufficiency, as previously described ( Perea-García et al ., 2020 ). For severe Cu deficiency condition, 100 μM of (BCS) was added to the growth medium. Seedlings were grown for 10 days at neutral photoperiodic conditions (12 h light, 23°C/12 h darkness, 16°C). Root length of 10-day old seedlings was measured using ImageJ ( Abramoff et al ., 2004 ). Transgene constructs pENTR-pAGO1-3xHA-AGO1 ( Carbonell et al ., 2012 ) was digested with Hind III and Kpn I, and the two fragments (7812 bp and 1425 bp) were gel-purified. The 1425 bp fragment was ligated into Hind III/ Kpn I-digested pBSIIKS + to generate pBS-pAGO1-3xHA . A 4266 bp linear pBS-pAGO1 fragment lacking the 3xHA tag was amplified using pBS-pAGO1-3xHA as template and oligonucleotide pair D2475/D2476, gel purified and assembled with a 136 bp TST-AGO1 fragment using a plasmid containing a TST-GFP cassette and oligonucleotide pair D2477/2478 in the presence of GeneArt Gibson Assembly HiFi Master Mix (Invitrogen) to generate pBS-pAGO1-TST . pBS-pAGO1-TST was digested with Hind III- Kpn I, and the resulting 1437 bp fragment was ligated to the 7812 bp mentioned before, to generate pENTR-pAGO1-TST-AGO1 . Finally, the pAGO1-TST-AGO1 cassette was cloned by LR recombination into pMDC99 , a Gateway-compatible plant transformation vector ( Curtis and Grossniklaus, 2003 ), to generate pMDC99-pAGO1-TST-AGO1 . Nucleotide and amino acid sequences of TST-AGO1 and TST- GFP are listed in Text S1. A 6003 bp and an 863 bp fragment was amplified from pENTR-pAGO1-3xHA-AGO1 ( Carbonell et al ., 2012 ) and TST-GFP plasmid with oligonucleotide pair AC-22/AC-23 and AC-20/AC-21, respectively. Both fragments were assembled in the presence of GeneArt Gibson Assembly HiFi Master Mix (Invitrogen) to generate pENTR-pAGO1-TST-GFP . The pAGO1-TST-GFP was transferred by LR recombination into pMDC99 to generate pMDC99- pAGO1-TST-GFP . RNA and protein preparation Total RNA form Arabidopsis seedlings or inflorescences was isolated as before ( Cisneros et al ., 2023 ). Triplicate samples from pools of Arabidopsis seedlings or inflorescences were analyzed. Total protein extracts were prepared in 2X PDB buffer (0.0625 M Tris pH 6.8, 2% SDS, 10% glycerol, 10% mercaptoethanol, 0.02% bromophenol blue) in a 1:5 tissue:buffer ratio. Real-time RT-qPCR cDNA synthesis and qPCR analysis were performed essentially as before ( Cisneros et al ., 2025 ). Briefly, five hundred ng of DNaseI-treated total RNA was used to produce cDNA from 10-day-old Arabidopsis seedlings with the PrimeScript RT Reagent Kit (Perfect Real Time, Takara) according to manufacturer’s instructions. RT-qPCR was done on optical 96-well plates in a QuantStudio 3 Real-Time PCR system (Thermo Fisher Scientific, Waltham, MA, USA) following these conditions: 20 s at 95°C, followed by 40 cycles of 95°C for 3 s and 60°C for 30 s, with an additional melt curve stage consisting of 15 s at 95°C, 1 min at 60°C and 15 s at 95°C. The 20-μl reaction included 10 μl of 2× TB Green Premix Ex Taq (Takara), 2 μl of diluted complementary DNA (1:5), 0.4 μl of ROX II Reference Dye (50X) and 300 nM of each gene-specific primer. Oligonucleotides used for RT-qPCR are listed in Table S1. Target mRNA expression levels were calculated relative to reference genes ACT2 and UBQ10 , using the delta delta cycle threshold comparative method of QuantStudio Design and Analysis software, version 1.5.1 (Thermo Fisher Scientific). Three independent biological replicates, and two technical replicates for each biological replicate were analyzed. Small RNA blot assays Small RNA blot assays and band quantification from radioactive membranes were done as described ( Cisneros et al ., 2022 ). Oligonucleotides used as probes for sRNA blots are listed in Table S1. Protein blot assays Proteins were separated in NuPAGE Novex 4-12% Bis-Tris gels (Invitrogen), transferred to Protran nitrocellulose membranes (Amersham) and detected by chemiluminescence using specific antibodies and SuperSignal West Pico PLUS chemiluminescent substrate (ThermoFisher Scientific) as before ( Cisneros et al ., 2025 ). Here, for detection of TST-tagged proteins, StrepMAB-Classic HRP Twin-Strep-Tag antibody (IBA) at a 1:10000 dilution was used. For detection of endogenous AGO1 and HISTONE3 (H3), anti-AGO1 (Agrisera) and anti-Histone 3 (Abcam) were used at 1:10000 and 1:4000 dilutions, respectively, and conjugated with 1:20000 of goat anti-rabbit IgG horseradish peroxidase secondary antibody (ThermoFisher Scientific). Images were acquired with an ImageQuant 800 CCD imager (Cytiva) and analyzed with ImageQuantTL v10.2 (Cytiva). Ponceau red S solution (Thermo Fisher Scientific) staining of membranes was used to verify the global protein content of the samples. Statistical analysis Statistical tests are described in the figure legends. Significant differences were determined with two-tailed Student’s t- test ( P < 0.05). Affinity purification of protein complexes Protein complexes containing TST-tagged protein products were purified from 1.5 g of 12-day-old seedlings by affinity chromatography in native conditions using a 1-ml Strep-Tactin XT spin column (IBA) as previously described ( Martinez et al ., 2016 ). Protein identification by liquid chromatography coupled with tandem mass spectrometry Protein preparations were separated by SDS-PAGE using 4% and 10% acrylamide for stacking and resolving gel, respectively. Electrophoresis was stopped when the front entered 1 cm into the resolving gel, and the gel was stained with Coomassie. The bands were cut for subsequent in-gel digestion with trypsin (12.5 ng/ul). The digest was acidified with 0.5% TFA to stop digestion. The peptides were desalted using C18 columns according to the manufacturer’s protocol (Pierce C18 Spin Columns, Thermo Scientific). The peptides were dried in a speedvac and resuspended in 15 µL of mobile phase (2% ACN, 0.05% TFA) for injection into HPLC. The mixture of tryptic peptides was analyzed by high-resolution mass spectrometry using an Orbitrap Fusion (Thermo Scientific) in “Data Dependent Acquisition” mode, equipped with a nanoESi ion source. The peptide extract, diluted in 2% acetonitrile (ACN) and 0.05% trifluoroacetic acid (TFA), was first separated in an Ultimate 3000 Dionex UHPLC (Thermo Scientific) under the following chromatographic conditions: preconcentration on a C18 pre-column (PepMap100, 5 µm, 300 µm x 5 mm, Thermo Scientific) at a flow rate of 5 µL/min for 3 minutes in 98% acetonitrile and 0.1% TFA. The chromatographic gradient of 4–40% acetonitrile was applied at a flow rate of 300 nL/min on a C18 nano-column (Acclaim PepMap RSLC 75 µm x 50 cm, Thermo Scientific) over 60 minutes. The total chromatography time was 85 minutes. The Orbitrap Fusion operated in positive mode with a voltage of 2 kV. The mass range in “full scan” mode was 400–1500 m/z in the Orbitrap at a resolution of 120,000, with an AGC target of 4×10⁵ and a dynamic “injection time.” Peptide analysis was performed in “data dependent acquisition” mode, operating in MS/MS Top 50 mode, fragmenting as many high-intensity ions as possible per “full scan” within a cycle time of 3 seconds. Fragmentation spectra were acquired in the linear trap by CID fragmentation at a collision energy of 35%, with a dynamic injection time and an AGC target of 1×10². A dynamic exclusion time of 15 seconds was included for each ion to avoid repetitive ion fragmentation. Protein identification was done using Proteome Discoverer 2.1 (PD2.1, Thermo Fisher Scientific). Proteins were identified with the following conditions: database, Uniprot_Arabidopsis-thaliana + AGO-sequences; tolerance, 10 ppm for Orbitrap and 0.02 Da for Ion Trap; maximum of 1 missed cleavages; *b-ions weight 1 (CID) and 0.3 (HCD); *y-ions weigh: 1 (CID-HCD); dynamic modifications, oxidation (Met); fixed modifications, carbamidomethylation (Cys) (*depends on the fragmentation type: CID or HCD); acceptance criteria, Percolator (Delta CN<0.05); FDR of 1% against decoy database. Resulting Excel sheets contain the identifications at the peptide and protein levels (Data S1). The data included in the report are filtered by a 1% FDR based on the probability values obtained by Percolator. The minimum number of peptides per protein is 1. Computational analysis A previously developed bioinformatic pipeline ( Ambrós et al ., 2021 )was used to process all information obtained via proteomics. From the raw proteomic lists, all plant proteins were identified and mapped to Arabidopsis genes (proteins), keeping the normalized MS peak area as a quantitative measure. Specifically, we identified proteins from green plants by GenInfo Identifier (GI) through Mascot analysis and conducted sequence alignments using BLAST to identify individual genes in A. thaliana , using data from The Arabidopsis Information Resource (TAIR) version 10 ( Lamesch et al ., 2012 ). For each hit, the associated amino acid sequence was retrieved from the NCBI database in FASTA format using the Biopython Entrez module. Only alignments with e-values < 0.0001 were considered, and any redundant elements were excluded. The protein list obtained from the Cu deficiency condition was compared against the list obtained from the Cu sufficiency condition in a quantitative manner ( i.e. , by subtracting the MS peak areas) for each transgenic line, discarding those proteins present in control pAGO1-TST-GFP lists for each condition. After the control filtering, if a protein was in one list but not in the other, we considered |log2 fold| = 100 (arbitrary value, denoted by Inf in the figures); positive for proteins detected in Cu deficiency but not in sufficiency and negative for proteins detected in Cu sufficiency but not in deficiency. All genes (proteins) in the lists were functionally annotated according to the information from TAIR10. Gene and virus identifiers Arabidopsis gene identifiers are: ACT2 (AT3G18780), AGO1 (AT1G48410), ARF8 (AT5G37020), ARPN (AT2G02850), CCS (AT1G12520), CSD1 (AT1G08830), CSD2 (AT2G28190), FSD1 (AT4G25100), GSTU25 (AT1G17180), LAC3 (AT2G30210), MSD1 (AT3G10920) NF-YA9 (AT3G20910), SPL3 (AT2G33810), SPL9 (AT2G42200), TCP4 (AT3G15030), UBQ10 (AT4G05320). CONFLICTS OF INTEREST The authors declare no conflict of interest. AUTHOR CONTRIBUTIONS A.C. and L.P. planned and designed the research. A.H.T., A.P.G., A.C., A.E.C., L.L.D., A.A.B. and M.O. performed most of the experiments. J.S.V. and J.A.D. performed AGO1 affinity purifications. G.R. did the computational analysis of AP-MS samples. A.H.T., A.P.G, L.P and A.C. analyzed data. A.C. and L.P. wrote the manuscript with input from rest of the authors. DATA AVAILABILITY STATEMENT All data relating to this manuscript can be found within the manuscript and its supplementary files. Data that support the findings of this study are available from the corresponding authors upon reasonable request. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE ( Perez-Riverol et al ., 2022 ) partner repository with the dataset identifier PXD057108. SUPPLEMENTAL DATA Data S1 . Proteins identified by AP-MS in pAGO1:TST-AGO1 and pAGO1:TST-GFP transgenic lines grown under Cu deficiency and Cu sufficiency. Data S2. Proteins identified by AP-MS in each of the three pAGO1:TST-AGO1 transgenic lines grown under Cu deficiency versus Cu sufficiency, and not present in pAGO1:TST-GFP AP- MS samples for each condition. Data S3. Proteins identified by AP-MS in all three pAGO1:TST-AGO1 transgenic lines grown under Cu deficiency versus Cu sufficiency, and not present in pAGO1:TST-GFP AP-MS samples for each condition. Figure S1. Accumulation of miRNA target mRNAs in different Arabidopsis genotypes under Cu deficiency. Table S1. Name, sequence and use of oligonucleotides used in the present study. Text S1 . Nucleotide and amino acid sequences of TST-based inserts. ACKOWLEDGEMENTS This work was supported by grants or fellowships from MCIN/AEI/10.13039/501100011033 (co-financed by the European Regional Development Fund) [RTI2018-095118-A-I00, PID2021-122186OB-I00 and RYC-2017-21648 to A.C.; PID2021-127671NB-I00 to G.R.; PID2020-116940RB-I00 to L.P. and A.P.G.; BIO2017-83184-R and PID2020-114691RB-I00 to J.A.D.; PRE2019-088439 to A.E.C.], and from the Generalitat Valenciana (CIPROM/2022/21 to G.R. and J.A.D.) We thank Dr. Tomás Takác for sharing fsd1-2 seeds and Carlos Fuentes from the Proteomics Unit of University of Córdoba for the assistance in preparing and analyzing purified proteins. Footnotes ahtomas1{at}ibmcp.upv.es , ana.perea{at}uv.es , guillermo.rodrigo{at}csic.es , jsanchez{at}madeinplant.com , adgoncis{at}ibmcp.upv.es , marta.olmos{at}uv.es , Amparo.Andres-Borderia{at}uv.es , lulodolz{at}gmail.com , jadaros{at}ibmcp.upv.es , Lola.Penarrubia{at}uv.es This version of the manuscript has been revised to inbclude the supplementary material. REFERENCES ↵ Abramoff , M. , Magalhaes , P. and Ram , S . ( 2004 ) Image processing with ImageJ . Biophotonics International , 11 , 36 – 42 . OpenUrl CrossRef ↵ Altschul , S.F. , Gish , W. , Miller , W. , Myers , E.W. and Lipman , D.J . ( 1990 ) Basic local alignment search tool . J Mol Biol , 215 , 403 – 10 . OpenUrl CrossRef PubMed Web of Science ↵ Ambrós , S. , Gómez-Muñoz , N. , Giménez-Santamarina , S. , Sánchez-Vicente , J. , Navarro-López , J. , Martínez , F. , Daròs , J.-A. and Rodrigo , G . ( 2021 ) Molecular signatures of silencing suppression degeneracy from a complex RNA virus . 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( 2009 ) SQUAMOSA Promoter Binding Protein–Like7 Is a Central Regulator for Copper Homeostasis in Arabidopsis . The Plant Cell , 21 , 347 – 361 . OpenUrl Abstract / FREE Full Text View the discussion thread. Back to top Previous Next Posted March 01, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Arabidopsis thaliana Iron Superoxide Dismutase FeSOD1 Protects ARGONAUTE 1 in a Copper-Dependent Manner Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. 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