Polyamine uptake transporter 2 is essential for systemic acquired resistance establishment in Arabidopsis.

Polyamine uptake transporter 2 is essential for systemic acquired resistance establishment in Arabidopsis Emmanuel Flores-Hern´ andez a , María Elisa Gonzalez b,* , Paulina Alvarado-Guitron c , Francisco I. Jasso-Robles d , Cesar´ e Ovando-V´ azquez e , Juan Francisco Jim´ enez-Bremont f , Sanja ´ Cavar Zeljkovi´ c d,g , Mark´ eta Ulbrichov´ a d , Nuria De Diego d,* , Margarita Rodríguez-Kessler c,* a Facultad de Ciencias Químicas, Universidad Aut´ onoma de San Luis Potosí (UASLP), Av. Dr. Manuel Nava 6, Zona Universitaria, 78240 San Luis Potosí, Mexico b Instituto Tecnol´ ogico de Chascomús (INTECH), Universidad Nacional de San Martín (UNSAM), Consejo Nacional de Investigaciones Científicas y T´ ecnicas (CONICET), Av. Intendente Marino Km 8.2, 7130 Chascomús, Provincia de Buenos Aires, Argentina c Facultad de Ciencias, Universidad Aut´ onoma de San Luis Potosí (UASLP), Av. Chapultepec 1570, Priv. del Pedregal, 78295 San Luis Potosí, Mexico d Czech Advanced Technology and Research Institute (CATRIN), Palacký University Olomouc, ˇ Slechtitelů 29, 78371 Olomouc, Czech Republic e Centro Nacional de Superc´ omputo, Instituto Potosino de Investigaci´ on Científica y Tecnol´ ogica A.C. (IPICYT), Camino a la Presa de San Jos´ e 2055, 78216 San Luis Potosí, Mexico f Divisi´ on de Biología Molecular, Instituto Potosino de Investigaci´ on Científica y Tecnol´ ogica A.C. (IPICYT), Camino a la Presa de San Jos´ e 2055, 78216 San Luis Potosí, Mexico g Czech Agrifood Research Center, ˇ Slechtitelů 29, 78371 Olomouc, Czech Republic ARTICLE INFO Keywords: Putrescine Polyamine transport Reactive oxygen species Salicylic acid Systemic acquired resistance ABSTRACT The study of polyamine transport in plants has become increasingly important due to the central role of these amines in regulating growth, development, adaptation, and stress responses. This research focused on the Arabidopsis thaliana Polyamine Uptake Transporters gene family under conditions of systemic acquired resistance. We evaluated all single mutants of this gene family and found that the put2-1 mutant abolished systemic acquired resistance while enhancing basal resistance to Pseudomonas syringae pv. tomato DC3000. In contrast, the 35S:: PUT2 overexpression lines showed improved resistance and reduced bacterial titers compared to wild-type plants. RNA-seq analysis revealed that the put2-1 mutant had deregulated expression of genes involved in the biosynthesis, signaling, and inactivation of salicylic acid and N-hydroxypipecolic acid. Most of these genes were transcriptionally upregulated by putrescine in wild-type plants, but not in the put2-1 mutant. Putrescine supplementation increased endogenous putrescine and salicylic acid levels in wild-type plants but not in put2-1, highlighting the essential role of this transporter in facilitating putrescine mobilization and regulating salicylic acid in distal tissues. We found that the defective systemic acquired resistance phenotype in the put2-1 mutant was linked to changes in the timing of polyamines, ROS, phenolic compound accumulation, and alterations in stomatal immunity. Our study emphasizes the key role of the Polyamine Uptake Transporter 2 (PUT2/LAT4) in establishing systemic acquired resistance in Arabidopsis, while also maintaining the plant’s intrinsic basal resistance mechanisms. These findings offer valuable insights into the complex mechanisms of plant resistance, positioning polyamine transport as a central hub in systemic responses. 1. Introduction Plants have evolved a sophisticated and highly regulated immune system capable of responding rapidly to pathogen threats through mechanisms activated by pathogen-associated molecular patterns (PAMPs), producing a cascade of signals that culminate in PAMPtriggered immunity (PTI). However, specific pathogens have adapted by deploying virulence factors known as effectors to suppress these innate immune responses. In response, plants have evolved the capacity to recognize these effectors through resistance proteins that activate effector-triggered immunity (ETI) (van der Burgh and Joosten, 2019). Following the initial contact with a pathogen, plants fortify their * Corresponding authors. E-mail addresses: [email protected] (M.E. Gonzalez), [email protected] (N. De Diego), [email protected] (M. Rodríguez-Kessler). Contents lists available at ScienceDirect Plant Stress journal homepage: www.sciencedirect.com/journal/plant-stress https://doi.org/10.1016/j.stress.2025.101046 Received 25 July 2025; Received in revised form 29 August 2025; Accepted 16 September 2025 Plant Stress 18 (2025) 101046 Available online 23 September 2025 2667-064X/© 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ). local defenses and develop systemic acquired resistance (SAR), a state of heightened defensive readiness that confers long-lasting protection against a broad range of pathogens (Vlot et al., 2021). This systemic immunity is mediated by a complex network of signaling molecules like reactive oxygen species (ROS), Ca 2+ , and "mobile signals" such as methyl salicylate (MeSA), azelaic acid (AzA), glycerol-3-phosphate (G3P), dehydroabietinal (DA), nitric oxide (NO), extracellular nicotinamide adenine dinucleotide phosphate [eNAD(P)] trans-acting siRNA-like RNAs (tasi-ARFs), and pinene monoterpenes (Guerra et al., 2020; Kachroo and Kachroo, 2020; Li et al., 2023; Vlot et al., 2021; Shine et al., 2022). SAR establishment leads to the production of salicylic acid (SA) and pipecolic acid (Pip), which facilitate communication between infected and distal tissues, effectively establishing an immune memory that primes the plant to respond more swiftly and robustly to subsequent infections (Lim, 2023). Polyamines, aliphatic compounds with two or more amino groups, are usually protonated at physiological pH and play essential roles across a plant’s life cycle, from embryogenesis and seed germination to fruit ripening and senescence (Bl´ azquez, 2024). The most studied plant polyamines are the diamine putrescine (Put), the triamine spermidine (Spd), the tetraamines spermine (Spm), and thermospermine (tSpm) (Bl´ azquez, 2024). However, their abundance depends on the plant species (´ Cavar Zeljkovi´ c et al., 2024). Polyamines are crucial mediators of the plant defense response (Jim´ enez-Bremont et al., 2014; Gonzalez et al., 2021). For instance, their catabolism, particularly through the action of polyamine oxidases (PAO), generates hydrogen peroxide (H 2 O 2 ), a reactive oxygen species (ROS) compound that inhibits pathogen growth, strengthens cell walls, induces stomata closure, and acts as a second messenger in the signaling network regulating defense gene expression (Wang et al., 2019). The Atpao1-1 x Atpao2-1 double mutant, susceptible to Pseudomonas syringae pv. tomato DC3000 (Pst), has altered ROS levels (Jasso-Robles et al., 2020). Contrarily, overexpression of apoplastic ZmPAO in Nicotiana tabacum var. Xanthi increased tolerance to P. syringae pv. tabaci and the oomycete Phytophthora parasitica var. nicotianae (Moschou et al., 2009). Furthermore, endogenous Spm accumulation in Arabidopsis thaliana also confers resistance to Pseudomonas viridiflava (Gonzalez et al., 2011). However, polyamine catabolism is not always detrimental to pathogens, as the H 2 O 2 produced by the ZmPAO1 enzyme is essential for tumor development during the Zea mays-Ustilago maydis interaction, which favors pathogen survival (Jasso-Robles et al., 2016). The conjugation of polyamines with hydroxycinnamic acids produces compounds with antimicrobial activity. For instance, p-coumaroylputrescine bolsters the defense mechanisms of A. thaliana against the pathogen Alternaria brassicicola (Muroi et al., 2009). While the intricate role of polyamine biosynthesis, conjugation, and catabolism in plant-pathogen interactions is partially known, our understanding of the implications of polyamine transport under stress conditions remains limited, especially regarding plant defense mechanisms. The A. thaliana genome encodes five genes for Polyamine Uptake Transporters (PUT1-PUT5), which belong to the L-type amino acid transporter (LAT) family of proteins. Structurally, these proteins have 10 to 12 transmembrane domains with cytoplasmic aminoand carboxyterminal ends (Fujita and Shinozaki, 2014). In addition to polyamines, some PUT/LAT family members can transport amino acids (such as leucine), vitamin B1, and the herbicide paraquat (Mulangi et al., 2012; Li et al., 2013; Martinis et al., 2016; Begam and Good, 2017; Begam et al., 2020). The localization of PUTs in various cellular compartments, such as the endoplasmic reticulum (PUT1 and PUT5), Golgi apparatus (PUT2), chloroplast (PUT2 and PUT3), and plasma membrane (PUT3), suggests that these transporters play a significant role in the intracellular mobilization of polyamines in plants (Li et al., 2013; Fujita and Shinozaki, 2014; Ahmed et al., 2017). Experimental evidence suggests that mobilizing plant polyamines under pathogen attack can promote plant resistance and, in some cases, pathogen virulence (Lowe-Power et al., 2018; Vilas et al., 2018). The recent observation that Put or its derivatives could serve as a signaling molecule to activate ETI and SAR in Arabidopsis, particularly in a process largely dependent on H 2 O 2 (Liu et al., 2020), leads us to hypothesize that the transport of polyamines or their derived metabolites via PUT/LAT transporters could significantly contribute to systemic defense responses. This study aimed to identify and functionally characterize PUT transporter(s) associated with SAR in Arabidopsis. Single mutants of the PUT gene family were assessed under SAR-inducing conditions to investigate how altered polyamine transport influences the plant’s immune response, using the Arabidopsis-Pseudomonas pathosystem as a model. Using transcriptomic and metabolic approaches, we characterized the put2-1 mutant to understand the basis of its SAR deficiency. Our findings provide key insights into the role of Put transport, highlighting its essential function in plant immunity. 2. Materials and methods 2.1. Plant material and growth conditions Arabidopsis thaliana ecotype Columbia-0 (WT) and T-DNA mutant lines for members of the polyamine uptake transporter family in Arabidopsis [put1-1 (GABI_890c10), put2-1 (SALK_119707c), put3-1 (SALK_206472c), put4-1 (SAIL_1275_c06), and put5-1 (SALK_007135)] were acquired from Salk Institute Genomic Analysis Laboratory (www. signal.salk.edu/cgi-bin/tdnaexpress). Homozygous lines were identified by PCR. The absence of the PUT gene expression in the corresponding T-DNA mutant line was confirmed by qPCR (Fig. S1). Specific primers used for typing, cloning, and gene expression analysis are listed in Table S1. For the experiments, seeds were stratified for 2 days in distilled water at 4 ◦C before being germinated in pots containing a sterile commercial substrate composed of sunshine#3: vermiculite: perlite (3:1:1). Plants were grown in a controlled growth chamber at 22 ±2 ◦C under shortday photoperiod (8 h light/16 h dark) for 6 weeks for assessing bacterial titers in SAR conditions, transcriptomic and metabolomic analysis as described below. Additionally, plants were grown under a long-day photoperiod (16 h light/8 h dark regime) for 4 weeks to assess basal resistance. 2.2. Generation of the AtPUT2 overexpression lines The AtPUT2 ORF sequence (1485 bp) was PCR amplified and cloned into the pENTER-D-TOPO entry vector (Invitrogen, Carlsbad, CA, USA) and recombined into the pEarley103 expression vector (Earley et al., 2006) using the Gateway LR clonase enzyme mix (Invitrogen). The expression clone (35S::PUT2) was transformed into Rhizobium radiobacter (formerly Agrobacterium tumefaciens) strain GV3101 by heat shock and then introduced into A. thaliana by floral dip. Transformed seeds were selected based on their resistance to glufosinate (Finale Ultra, BASF), following standard protocols (Harrison et al., 2006). Three independent overexpression lines were chosen for further analysis, 35S:: PUT2-2, -18, and -27 (Fig. S1). 2.3. Bacterial strain and plant inoculation for SAR assays Pseudomonas syringae pv. tomato DC3000 (Pst) and Pseudomonas syringae avrRpt2 strains were used to induce SAR in Arabidopsis (Macho et al., 2010; Rufi´ an et al., 2019). The strains were grown in King’s B medium with rifampicin (50 μ g/mL) at 28 ◦C. The SAR assay was carried out as Rufi´ an et al. (2019) described. Briefly, the lower rosette leaves (8, 9, and 10) of six-week-old plants were inoculated with bacteria (OD 600 =0.005) to induce local priming (SAR) or with the Mock (MgCl 2 10 mM, pH 7.0) as the control (native) condition. Then, 48 h after primary infection, upper leaves (13, 14, and 15) were systemically challenged with Pst (OD 600 =0.0005). After a specific time, the upper leaves were collected for further analysis, assuming a native plant status or a E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 2 SAR condition has been established. 2.4. Polyamine infiltration for studying SAR-like responses Validation experiments were conducted to elucidate further the role of specific polyamines in regulating SAR-like responses. For this, the lower leaves of six-week-old plants were infiltrated with 30 μ M Put, Spd, Spm or Mock. Then, 6 h after polyamine infiltration, the upper leaves were collected to quantify the gene expression of specific genes related to the SA and Pip pathways. Another set of plants, 48 h after Put infiltration, the upper leaves were challenged with Pst and collected at 72 h post-inoculation (hpi) for the estimation of bacterial titers. The upper leaves of Put-infiltrated plants were also collected at 6 and 24 h for further metabolic analysis. 2.5. Estimation of bacterial titers Bacterial titers were determined in the upper leaves at 72 hpi. Sixleaf disks (∅ 0.5 cm) from each plant (n =5) were homogenized in 0.2 mL of MgCl 2 (10 mM, pH 7.0) and serially diluted (1:10 to 1:1 × 10 9 ). Then, 10 µL of each dilution was plated on solid King’s B agar supplemented with rifampicin (50 µg/mL). Colony-forming units (CFU) were counted 24 h after incubation at 28 ◦C. 2.6. Fungal strain, spore collection, and plant inoculation The Botrytis cinerea B05.10 strain was grown on Potato Dextrose Agar (PDA) for two weeks in the dark at 25 ◦C. The mycelium was scraped from the Petri dish, placed in a Tween 20 solution (0.02 %, v/v), filtered through a mesh, and centrifuged to obtain spores. After washing with sterile distilled water, the spores were resuspended in Potato Dextrose Broth (PDB) medium supplemented with sucrose (10 mM) and KH 2 PO 4 (10 mM) and adjusted to a final concentration of 1 ×10 5 spores/mL. For broad-spectrum SAR assays, six-week-old WT or put2-1 mutant plants were locally primed with Pst (OD 600 =0.005) or Mock (10 mM MgCl 2 ) on the lower leaves and then systemically challenged with B. cinerea by inoculating a drop (5 μ L) of spore suspension on the distal upper leaves. Inoculated leaves were collected at 24 and 48 hpi and stained with a 2.6 M Evans blue solution, following the protocol described by Vijayaraghavareddy et al. (2017). For tissue clarification, leaves were placed in an ethanol glycerol [90:10 (v/v)] solution and heated at 70 ◦C for 10 min or until no chlorophyll was visible. Clarified leaves were mounted on slides using a lactic acid:phenol:water [1:1:1 (v/v/v)] solution and photographed using a smartphone camera adapted to a stereoscope. Representative images were selected for each line and treatment, and lesion size was quantified using Image J Pro Plus 4.5 analysis software. 2.7. RNA isolation, Illumina sequencing, and data analysis Total RNA was isolated using the TRI Reagent® method (Merck, Darmstadt, Germany) following SAR assays. The lower leaves were inoculated with Pst to induce local priming (SAR) or Mock treatment. At 24 hpi, the uninoculated upper leaves were collected for RNA extraction. In a second group of plants, 48 h after primary infection, upper leaves were systemically challenged with Pst and collected at 24 hpi for RNA extraction (see Fig. 2a and b). Three biological replicates, each containing over 20 µg total RNA, were submitted to GENEWIZ® (https://www.genewiz.com/) for standard mRNA sequencing (by poly-A selection) using the Illumina HiSeq platform with a 2 ×150 bp configuration. RNA-seq quality was analyzed using the FastQC v0.11.9 tool (Andrews, 2010), and the minimum read Phred score for the reads was 33. All reports from FastQC were collected using MultiQC v1.14. Neither adapter bias nor poor quality at the 3 ′ end was evident in the RNA-seq data. There was no need to process the fragments. The Hisat v2.1.0 tool mapped the fastq files to the Arabidopsis genome. R internal scripts were used for the Hisat2 mapping statistics process (R core team, 2022). The featureCounts tool from the SubRead package was used to quantify the mapped fragments (Liao et al., 2019). An internal R script (R core team, 2022) produced a counts matrix using these quantifications. Differential expression analysis was performed using the edgeR R package (Robinson et al., 2010); the calcNormFactors function was used to calculate the normalization factors, and the estimatedDisp function was used with default parameters to calculate the dispersion. The glmFit function fits the data to the Negative Binomial density distribution. The glmLRT function defined and performed the proposed contrast between conditions. Differentially expressed genes were defined as those with a fold change value of ≥2 and a p-value ≤0.05, and an FDR of ≤0.1. Genes of interest with significant differential expression were validated by qPCR. Gene Ontology (GO) term enrichment was performed using a custom R script with a logistic regression model. The glm function with the Binomial density distribution family and the logit link was used to fit the logistic regression model y =f(x), defining the classes y as class 1transcripts in the GO term and class 0transcripts not in the GO term. The score x was defined as x=-log 10 (FDR)sign(logFC). The RNAseq data were deposited in the Gene Expression Omnibus database under the GEO accession GSE275478. 2.8. Gene expression analysis by RT-qPCR Total isolated RNA was treated with DNAse I (Thermo Fisher Scientific, Massachusetts, USA) to eliminate gDNA. First-strand cDNA synthesis was performed using the RevertAid Reverse Transcriptase Kit (Thermo Fisher Scientific, Massachusetts, USA). Gene expression levels were quantified by qPCR using the Maxima SYBR green qPCR Master Mix (2x) (Thermo Scientific). Primers used are listed in Table S1. qPCR thermal cycling conditions consisted of 30 s at 95 ◦C (initial denaturation), 40 PCR cycles of 10 s at 95 ◦C (denaturation), and 30 s at 60 ◦C (annealing/extension). Melting curves started at 65 ◦C and gradually increased the temperature every 0.5 ◦C up to 95 ◦C. The 2 -ΔΔCt method (Livak and Schmittgen, 2001) was used to calculate the change in gene expression relative to the control samples, with AtEF1 α (AT5G60390) as the reference gene. 2.9. Quantification of free polyamines Six-week-old Arabidopsis plants were used to quantify the levels of free polyamines in the upper leaves after the different SAR treatments at 6 and 24 hpi. Briefly, lower leaves were inoculated with Pst to induce local priming (SAR) or Mock, and at 6 and 24 hpi the upper leaves were collected. In another set of plants, 48 h after the inoculation of the local leaves, the upper leaves were challenged with Pst, and samples were collected at 6 and 24 hpi. Leaves were snap-frozen in liquid nitrogen and stored at −80 ◦C. The samples were lyophilized, and the resulting dry weight (DW) was used for the targeted metabolic analysis. Free polyamines were analyzed according to the method described by ´ Cavar Zeljkovi´ c et al. (2024). 200 μ L of 2 M NaOH was added to 200 μ L of the supernatant of the extract described above, followed by 2.5 μ L of benzoyl chloride in MeOH (50:50, v/v). The reaction mixture was vortexed for 5 s and then stirred for 40 min at 25 ◦C. After the reaction, 500 μ L of saturated NaCl was added, and benzoylated polyamines were extracted with 2 ×500 μ L of diethyl ether. The solvent was evaporated under a vacuum at 40 ◦C. Dry samples were dissolved in 200 μ L of mobile phase and analyzed according to the protocol described by ´ Cavar Zeljkovi´ c et al. (2024), with minor modifications to include additional target compounds. The analysis was performed in multiple reaction monitoring (MRM) mode, and transitions of the target compounds were as follows: Put (297.10>105.10, 297.10>77.05, 297.10>176.00), Dap (282.95>104.95, 282.95>77.00, 282.95>162.05), Dap-d 6 (288.95>112.95, 288.95>82.00, 288.95>170.05), Cad E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 3 (311.10>104.95, 311.10>77.05, 311.10>190.20), nSpd (444.15>105.05, 444.15>162.00, 444.15>322.20), Spd (458.20>105.10, 458.20>162.15, 458.20>336.30), hSpd (472.20>247.20, 472.20>105.05, 472.20>176.05), nSpm (605.00>162.20, 605.00>105.20, 605.00>323.30), tSpm (619.25>105.00, 619.25>162.00, 619.25>337.20), Spm (619.25>497.30, 619.25>162.00, 619.25>105.00), and Agm (443.00>104.85, 443.00>375.00). 2.10. Quantification of free phenolic compounds Analysis of phenolic compounds was performed according to the protocol described in Sedl´ akov´ a et al. (2023). The UHPLC-MS/MS measurements were carried out on an Ultra Performance LC-MS 8050 system (Shimadzu, Kyoto, Japan) with a triple quadrupole mass spectrometer equipped with an electrospray ionization (ESI) source operating in negative mode. A 5 µL sample was injected into an Acquity UPLC BEH C18 column (1.7 µm, 2.1 ×100 mm, Waters, Milford, MA, USA), connected to the corresponding pre-column. The mobile phase consisted of a mixture of 15 mM formic acid (pH 3, adjusted with NH 4 OH) (solvent A) and ACN (solvent B) at a flow rate of 0.4 mL/min. The linear gradient consisted of 10 % B for 1 min, 10–13 % B for 2 min, isocratic 13 % B for 4 min, 13–25 % B for 3 min, 25–70 % B for 1.2 min, isocratic 75 % B for 0.8 min, back to 10 % B within 0.5 min, and equilibration for 3.5 min. The analysis was performed in multiple reaction monitoring (MRM) mode, and transitions of the target compounds were as follows: SAG (297.70>137.10, 297.70>93.10), pCA-d 6 (169.10>124.85, 169.10>97.15, 169.10>98.10), pCA (163.00>119.10, 163.00>93.00, 163.00>117.10), SiA (227.70>208.30, 222.70>192.20, 222.70>164.30), FA (193.10>134.25, 193.10>178.25), SA-d 4 (141.10>96.80, 141.10>69.10, 141.10>78.10), and SA (137.10>92.70, 137.10>65.00, 137.10>75.05). All standards and reagents were of the highest available purity and purchased from Sigma Aldrich Company (Prague, Czech Republic). 2.11. Stomatal aperture analysis The stomatal aperture was assessed following Pantaleno et al. (2024). Epidermal peels were obtained from the abaxial side of leaves from six-week-old plants and placed in the opening buffer (5 mM MES, pH 6.1, 50 mM KCl) for 3 h under light to encourage the optimal opening of most stomata. Then, the peels were treated with or without 1 µM flagellin 22 (flg22) for 0-, 15-, 30-, and 60-min periods. Stomata were observed under a microscope using a 40x objective and documented with a digital camera. The stomatal aperture was analyzed by Image J Pro Plus 4.5 analysis software. 2.12. Luminol assay Luminol assays were conducted as outlined Bisceglia et al. (2015) with minor modifications. The lower leaves of six-week-old plants were infiltrated with Mock or Pst (as described above) to induce local priming, and the upper leaves were used for the luminol assay. Discs were obtained from the midrib level using a sharp 4 mm biopsy punch from at least three leaves per plant and carefully transferred to a Petri dish containing ddH2O. Using a flat toothpick, one leaf disc was placed in each well of a 96-well luminometer plate, containing 150 µL ddH 2 O with the adaxial side facing upward. To minimize the impact of wounding, the plates were kept under the same growth conditions as the original plants for 20 h. Before measurement, water was removed from each well, and 100 μ L of reaction solution (100 μ M luminol, 10 μ g/mL horseradish peroxidase, and 1 μ M flg22) was added. Luminescence of the disc reaction mixture without the elicitor was monitored as the blank. Luminol luminescence was measured for one hour using the multimode reader Synergy H4 from BioTek, at 2-min intervals with an integration time of 1000 ms. 2.13. Statistical analysis The results of each representative experiment are shown as the mean ±SE. Statistical differences (p ≤0.05) were determined by Student’s ttest using GraphPad Prism version 10.0.0; by Generalized Linear Mixed Models (GLMMs) with negative binomial distribution or by two-way, three-way, or four-way ANOVA with LSD Fisher comparison as appropriate using the InfoStat v2020e (https://www.infostat.com.ar/index. php?mod=page&id=15) statistical package. Graphs were obtained using GraphPad Prism version 10.0.0. Asterisks and different letters indicate statistically significant differences between the means. The changes in the metabolic profile between lines and treatments were also analyzed using multivariate statistical analysis, specifically principal component analysis (PCA) and correlation matrices performed in RStudio (Version 1.1.463 – © 2009–2018 RStudio, Inc.) using the packages factoextra, ggplot2, grid, ggrepel, ggnewscale and corrplot. 3. Results 3.1. The AtPUT2 polyamine uptake transporter is essential for SAR establishment but not for basal resistance in Arabidopsis SAR was induced in WT plants and single mutant lines of the A. thaliana PUT family (put1-1, put2-1, put3-1, put4-1, and put5-1). CFUs were estimated at 72 hpi following systemic challenge with Pst in sixweek-old plants. In WT plants, bacterial titers were significantly lower in systemic leaves of locally challenged (primed) compared to the Mocktreated controls, indicating successful SAR establishment, as reported in previous studies (Rufi´ an et al., 2019). We first analyzed bacterial titers in WT and mutant lines after Mock-infiltration. The put1-1 behaved like WT, while the other mutants increased basal resistance (Fig. 1a). Under SAR-induced conditions, put1-1 and put3-1 mutants reduced bacterial titers after priming as the WT (Fig. 1a). In contrast, the put2-1, put4-1, and put5-1 mutant lines displayed a defective SAR. Notably, put4-1 and put5-1 mutants showed similar bacterial titers in primed plants as in the Mock-infiltrated ones (Fig. 1a). The put2-1 mutant exhibited the most pronounced SAR deficiency, with higher bacterial titers in primed plants than in the Mock-infiltrated ones, suggesting a key role for AtPUT2 in SAR (Fig. 1a). To further study the role of AtPUT2 in SAR, we generated three Arabidopsis PUT2 overexpression lines (35S::PUT2-2, -18, and -27) and challenged them with Pst. All 35S::PUT2 overexpression lines were resistant to Pst inoculation, inducing SAR, and exhibited similar bacterial titers to the WT (Fig. 1a). Following inoculation with the avirulent strain P. syringae avrRpt2, the put2-1 mutant failed to establish SAR, as evidenced by increased bacterial titers compared to the native plant status (Fig. 1b). Interestingly, the put2-1 mutant line also exhibited enhanced basal resistance (Fig. 1a and b). Specifically, put2-1 plants inoculated with the Mock on the lower leaves and challenged on the upper leaves with Pst had lower bacterial titers than WT, a phenotype consistent even in four-week-old put2-1 mutant plants (Fig. S2). This suggests a dual phenotype for the put2-1 mutant, in which SAR is compromised, but basal resistance is enhanced. 3.2. Broad-spectrum SAR is lost in the Arabidopsis put2-1 mutant SAR provides broad-spectrum protection against various pathogens. We examined whether AtPUT2 influences this protection by testing SAR induced by Pst against an unrelated pathogen, Botrytis cinerea, in the WT and the put2-1 mutant line (Fig. 1c and d). Plants in native or SAR status were systemically inoculated with B. cinerea, and the infected leaves were stained with Evans blue. In WT plants, local priming with Pst significantly reduced lesion sizes caused by B. cinerea at 48 hpi, demonstrating effective broad-spectrum SAR (Fig. 1c). However, the put2-1 mutant showed larger fungal lesions in Pst-primed plants (Fig. 1c and d), indicating impaired broad-spectrum SAR. This result suggests E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 4 that while the loss of AtPUT2 function does not affect basal resistance to Pst in Arabidopsis, this transporter is crucial for managing SAR, even against unrelated pathogens. 3.3. Transcriptomic profiling reveals that the put2-1 mutant exhibits altered expression of genes associated with defense and SAR To further investigate the role of the AtPUT2 gene in plant defense, we conducted a transcriptome analysis of WT and put2-1 mutant plants Fig. 1. Evaluation of SAR and broad-spectrum SAR in Arabidopsis polyamine uptake transporter mutants and overexpression lines. a) Bacterial titers in systemic leaves of WT and polyamine uptake transport mutants (put1–1, put2–1, put3–1, put4–1, and put5–1) and AtPUT2 overexpression lines (35S::PUT2–2, −18, and −27) which were locally infiltrated with Mock, maintaining a native plant status, or challenged with Pseudomonas syringae pv. tomato DC3000 (Pst) to induce SAR. b) Bacterial titers in systemic leaves of WT and put2–1. Plants were locally infiltrated with Mock or challenged with the avirulent strain P. syringae avrRpt2. CFU, colonyforming units. Experiments were repeated twice with similar results. Values show the mean of five or six biological replicates ±SE. Different letters indicate significant differences (p ≤0.05) between treatments according to two-way ANOVA and LSD Fisher’s post-hoc test. c) Lesion size in WT and put2–1 mutant plants, locally infiltrated with Mock or challenged with Pst, was assessed in systemic leaves after inoculation with B. cinerea (Bc). Values are the mean of four biological replicates (n =12 leaves) ±SE. Lesion size (cm 2 ) induced by Bc was quantified using ImageJ® software. Different letters denote significant differences (p ≤0.05) between treatments via three-way ANOVA followed by LSD Fisher’s post-hoc test. d) Evans blue staining at 24 and 48 hpi with Bc. Representative image of 12 leaves. Scale bar (0.5 cm). Each image displays a 2x digital zoom. E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 5 under native and SAR conditions at 24 hpi (Fig. 2a and b; complete gene list available at File S1). For the native condition, the lower leaves of a set of plants were infiltrated with Mock solution, while the upper leaves were either kept in their native state or challenged with Pst (Fig. 2a). For the SAR condition, the lower leaves were infiltrated with Pst, while the upper leaves were either maintained in their native state or challenged with Pst (Fig. 2a). Samples were collected at 24 hpi as indicated (Fig. 2b). RNA-seq analysis revealed 28.8 ±2.1 million fragments per library with high quality (minimum Phred score of 33) (Fig. S3). In the considered comparisons, 1160 genes showed increased gene expression, and 3857 showed decreased expression (Fig. 2c and d). In the put2-1 mutant, the comparison of SAR (1 ◦ Pst / 2 ◦ Pst) vs. native (1 ◦ Mock / 2 ◦ Pst) had Fig. 2. Transcriptomic analysis of put2–1 mutant under native and SAR conditions. a) Experimental design and b) sampling. WT and put2–1 plants were inoculated with Pst to establish the following conditions: native plant status and SAR. The lower leaves (8, 9, and 10) were inoculated with Pst at OD 600 =0.005 to induce local priming (SAR) or treated with a Mock solution (MgCl 2 10 mM) to maintain a native plant status. At 24 hpi, the uninoculated upper leaves (13, 14, and 15) were collected for RNA extraction. In a second group of plants, 48 h after primary infection, the upper leaves were systemically challenged with Pst at OD 600 =0.0005 and then collected 24 hpi for RNA extraction. For each condition, at least six plants were used. Scissors indicate the upper leaves that were harvested for the experiments. Venn diagrams representing the common and specific number of c) upregulated genes and d) down-regulated genes between the considered contrasts. e) Heatmap summarizing the Gene Ontology (GO) enrichment for selected terms based on the contrasts. The scale color represents the enrichment score. E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 6 the highest number of differentially expressed genes (DE), with 1107 increased and 3811 decreased (Fig. 2c and d). Furthermore, there were only 9 genes with increased and 3 with reduced expression shared between put2-1 [SAR (1 ◦ Pst / 2 ◦ Pst) vs. native (1 ◦ Mock / 2 ◦ Pst) ] and WT [SAR (1 ◦ Pst / 2 ◦ Native) vs. native (1 ◦ Mock / 2 ◦ Native) ] conditions (Table S2). Gene Ontology (GO) enrichment analysis, based on the Differential Expression results, revealed deregulated terms associated with SAR (GO: 0009627), response to hydrogen peroxide (GO:0042542), regulation of defense response (GO:0031347), response to fungus (GO:0009620), plant-type hypersensitive response (GO:0009626), fatty acid biosynthetic process (GO:0006633), thylakoid membrane organization (GO:0010027) and plant-type cell wall organization (GO:0009664) in the put2-1 mutant compared to WT (Fig. S4). A heatmap summarizing the GO enrichment analysis of all contrasts is shown in Fig. 2e. Representative deregulated genes associated with SAR and defense in put2-1 under SAR (1 ◦ Pst / 2 ◦ Pst) condition are listed in Table 1, with many linked to SA and Pip metabolism. 3.4. The put2-1 mutant displays deregulation in the SA and SAR marker genes Expression of SAR and defense marker genes was evaluated in the upper (systemic) leaves of the WT and put2-1 plants under native or SAR conditions (Fig. 3). The key examined genes included: SA synthesis and response (PAD4, SARD1, ICS1, and PR1), Pip and NHP biosynthesis (ALD1, SARD4, and FMO1), SAR signaling (AZI1), negative regulation of NPR1 (NIMIN1), glycosylation of NHP and SA (UGT76B1), the ethyleneand jasmonate-responsive plant defensin (PDF1.2) and a Spm responsive gene (NHL10) (Fig. 3). The expression of most genes was influenced by the interaction among local priming, systemic challenge and genotype according to ANOVA (File S2). Under native (1 ◦ Mock / 2 ◦ Native) conditions, put2-1 exhibited increased expression of most genes related to SA synthesis and response (PAD4, SARD1, ICS1, PR1), Pip, and NHP biosynthesis (ALD1 and FMO1), as well as AZI1 and PDF1.2 compared to WT (Fig. 3a-e, g, j and k), consistent with its basal resistance phenotype (Fig. 1a). After local priming with Pst (1 ◦ Pst / 2 ◦ Native) , expression of these marker genes showed slight changes in WT plants regarding the native uninoculated (1 ◦ Mock / 2 ◦ Native) condition (Fig. 3). At the same time, put21 increased the expression of PAD4, SARD4, NIMIN1, UGT76B1, AZI1, and NHL10 (Fig. 3a, f, h-j, and l), but decreased PR1, ALD1, and FMO1, as well as PDF1.2 (Fig. 3d, e, g and k), compared to the native uninoculated condition. In systemically challenged plants without priming (1 ◦ Mock / 2 ◦ Pst) , both WT and put2-1 upregulated most marker genes, particularly SARD1 and PR1 in the mutant (Fig. 3b and d). Interestingly, genes related to SA and NHP biosynthesis (SARD1, ICS1, SARD4, and FMO1), as well as the PR1 Table 1 Up and down-regulated genes in the put2-1 mutant in the SAR (1ºPst / 2ºPst) vs. native (1ºMock / 2ºPst) comparison. GeneID Description Involved process logFC p value FDR AT3G30775 Earley responsive to dehydration 5 (ERD5) Defense 5.237 7.10E-13 2.22E-10 AT5G42380 Calmodulin like 37 (CML37) Defense 4.262 6.11E-06 1.11E-04 AT2G19190 FLG22-induced receptor-like kinase 1 (FRK1) Defense 3.451 1.23E-02 4.74E-02 AT3G22600 Glycosylphosphatidylinositol-anchored lipid protein transfer 5 (LTPG5) Defense 3.244 4.17E-03 2.02E-02 AT3G23250 MYB domain protein 15 (MYB15) Defense 3.137 6.26E-03 2.79E-02 AT1G19020 Small defense-associated protein 1 (SDA1) Defense 3.046 1.28E-06 3.12E-05 AT1G22890 PROSCOOP14 Defense 3.017 1.75E-07 6.07E-06 AT2G39660 Botrytis-induced kinase 1 (BIK1) Defense 2.865 2.25E-07 7.41E-06 AT1G74710 Isochorismate synthase 1 (ICS1) Defense 2.854 3.49E-06 6.98E-05 AT1G28330 Dormancy-associated protein 1 (DYL1) Defense 2.552 8.07E-04 5.54E-03 AT4G23810 WRKY transcription factor 53 (WRKY53) Defense 2.203 9.64E-03 3.92E-02 AT2G43790 Mitogen-activated protein kinase 6 (MPK6) Defense 1.326 3.04E-05 4.02E-04 AT1G64280 Nonexpressor of pathogenesis-related genes 1 (NPR1) Defense 1.017 4.21E-03 2.03E-02 AT5G44420 Plant defensine 1.2 (PDF1.2) Defense -3.509 1.21E-03 7.68E-03 AT5G05300 Peptide IDL6 Defense*3.788 1.17E-07 4.39E-06 AT5G05190 Enhanced disease resistance 4 (EDR4) Defense*2.863 1.42E-09 1.05E-07 AT3G52400 Syntaxin of plants 122 (SYP122) Defense*2.667 1.34E-05 2.08E-04 AT2G39030 L-ornithine N5-acetyltransferase (NATA1) Defense*-2.646 7.70E-03 3.28e-02 AT1G16420 Metacaspase-8 (MC8) HR 3.263 1.14E-02 4.46E-02 AT1G66090 Disease resistance protein (TIR-NBS class) HR 3.177 7.42E-07 1.98E-05 AT4G25110 Metacaspase-2 (MC2) HR 3.141 3.32E-05 4.33E-04 AT3G01290 Hypersensitive induced reaction 2 (HIR2) HR 2.702 3.30E-04 2.72E-03 AT2G45170 Autophagy-related protein 8e (ATG8E) HR 2.547 1.86E-05 2.72E-04 AT4G12720 Nudix hydrolase homolog 7 (NUDT7) ROS 2.677 7.92E-08 3.21E-06 AT2G13810 AGD2-like defense response protein 1 (ALD1) SAR 6.227 2.21E-05 3.11E-04 AT1G19250 Flavin dependent monooxygenase 1 (FMO1) SAR 5.157 2.94E-03 1.54E-02 AT4G12470 Azelaic acid induced 1 (AZI1) SAR 5.024 9.27E-06 1.57E-04 AT4G12480 Earley Arabidopsis aluminum induced 1 (EARLI1) SAR 3.820 4.39E.05 5.44E-04 AT2G35980 NDR1/HIN1-like protein 10 (NHL10) SAR 3.711 5.49E-03 2.52E-02 AT1G73805 SAR deficient 1 (SARD1) SAR 2.508 8.16E-04 5.59E-03 AT5G26920 CAM-binding protein 60-like G (CBP60G) SAR 2.349 7.67E-03 3.27E-02 AT5G52810 SAR deficient 4 (SARD4) SAR 2.338 1.45E-05 2.21E-04 AT4G33430 BRI1-associated receptor kinase 1 (BAK1) SAR 1.977 3.06E-08 1.44E-06 AT3G52430 Phytoalexin deficient 4 (PAD4) SAR 1.575 1.23E-04 1.23E-03 AT1G80460 Nonhost resistance to P. S. Phaseolicola 1 (NHO1) SAR 1.312 5.32E-03 2.45E-02 AT5G14760 Flagellin-insensitive 4 (FIN4) SAR 1.092 1.16E-02 4.52E-02 AT4G31780 Monogalactosyl diacylglycerol synthase 1 (MGD1) SAR -1.058 4.17E-03 2.02E-02 AT4G27030 Fatty acid desaturase 4 (FAD4) SAR -1.263 2.20E-02 7.40E-02 AT3G11170 Fatty acid desaturase 7 (FAD7) SAR -1.418 2.66E-04 2.29E-03 AT2G40690 Suppressor of fatty acid desaturase deficiency 1 (SFD1 or GLY1) SAR -1.565 6.51E-04 4.65E-03 AT2G05990 Mosaic death 1 (MOD1) SAR -2.403 3.63E-04 2.94E-03 AT1G49430 Long-chain acyl-CoA synthetase 2 (LACS2) SAR -3.575 6.30E-06 8.34E-09 AT1G02450 NIM1-interacting 1 (NIMIN1) SAR*4.966 1.12E-06 2.79E-05 AT3G25882 NIM1-interacting 2 (NIMIN2) SAR*4.434 1.39E-10 1.55E-08 AT3G11340 UDP-glycosyltransferase 76B1 SAR*3.646 1.58E-02 5.73E-02 * Asterisks indicate a negative role in the respective process. E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 7 gene, showed higher expression in the put2-1 mutant compared to WT under the locally primed and systemically challenged (1 ◦ Pst / 2 ◦ Pst) condition (Fig. 3b, c, f, and g). In the same conditions, negative regulators (NIMIN1 and UGT76B1) and NHL10 were strongly induced in put2-1 compared to WT (Fig. 3h, i, and l). Notably, NIMIN1, UGT76B1, and NHL10 displayed a consistent expression pattern in put2-1 across all tested conditions, differing markedly from WT (Fig. 3h, i, and l). Overall, the simultaneous strong induction of both positive and negative SAR regulators in put2-1 likely disrupts the balance between induction and attenuation of SAR, leading to an impaired systemic response. The stronger expression of SA and SAR marker genes in put2-1 under SAR (1 ◦ Pst / 2 ◦ Pst) condition compared to WT suggested a delayed response to secondary infection. To test this, we examined the expression of SARrelated genes (ICS1, PR1, FMO1, SARD4, NHL10, and UGT76B1) at an earlier time point (6 hpi) (Fig. S5). ANOVA revealed that, except for ICS1, the expression of all genes was influenced by the interaction among local priming, systemic challenge, and genotype (File S2). Our results confirmed that the WT responded more rapidly to systemic Fig. 3. Gene expression analysis of SAR markers in the put2–1 mutant line. Gene expression of a) PAD4, b) SARD1, c) ICS1, d) PR1, e) ALD1, f) SARD4, g) FMO1, h) NIMIN1, i) UGT76B1, j) AZI1, k) PDF1.2, and l) NHL10 in the different plant status (native or SAR) at 24 hpi. Gene expression values were normalized to the EF1 α reference gene and relative to WT plants in native status (1 ◦ Mock / 2 ◦ Native) using the 2 -ΔΔCt method. Values are the mean of three replicates ±SE. Different letters denote significant differences (p ≤0.05) between treatments according to three-way ANOVA and LSD Fisher’s post-hoc test. E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 8 challenge without priming (1 ◦ Mock / 2 ◦ Pst) , whereas put2-1 exhibited a delayed response (Fig. S5). The exception was SARD4, which behaved similarly in both lines (Fig. S5c). Interestingly, in the SAR and systemically challenged condition (1 ◦ Pst / 2 ◦ Pst) , most analyzed genes were less expressed in WT than in put2-1, except for PR1 and UGT76B1. In WT, priming likely triggers a rapid response after the challenge of systemic leaves with Pst, and by 6 hpi, the expression levels of marker genes may have already decreased. This suggests that plant status differentially affects gene expression in the WT and the put2-1 mutant. 3.5. AtPUT2 is crucial for the proper expression of SAR marker genes relying on putrescine To investigate the role of free polyamines and their transport in SAR, we locally infiltrated the lower leaves of six-week-old WT and put2-1 mutant plants with Mock (MgCl 2 ) or 30 µM of selected polyamines (Put, Spd, Spm). Then, we measured the expression of SAR marker genes in the upper leaves at 24 hpi. ANOVA revealed that the interaction between polyamine type and genotype influenced gene expression (File S2). In WT, Put treatment significantly increased the expression of all marker genes, but the systemic effect of Put was impaired in the put2-1 mutant (Fig. 4). Spd strongly induced PR1, SARD4, FMO1, and NIMIN1 expression in WT, but had little effect on the other marker genes analyzed (Fig. 4b-d, and h). In put2-1, Spd treatment reduced marker gene expression (Fig. 4). Finally, Spm increased the expression of negative regulators of SAR (UGT76B1 and NIMIN1) in put2-1, and to a lesser extent, UGT76B1 expression in WT (Fig. 4e and h). These results align with previous findings that local Put treatment triggers a SAR-like response in Arabidopsis (Liu et al., 2020), and demonstrate the crucial role of the AtPUT2 transporter for relaying systemic signal(s) to distal leaves for proper SAR gene expression. 3.6. Local infiltration of Put results in a reduction of bacterial titers in systemic tissues Since Put infiltration triggered the expression of SAR marker genes, we evaluated its impact on Pst systemic resistance. Six-week-old WT, put2-1, and 35S::PUT2 overexpression lines were locally infiltrated with 30 μ M Put or Mock, followed by Pst inoculation of the upper leaves 48 h later. At 72 hpi, Put-treated WT plants showed significantly lower bacterial titers than the Mock-treated plants, indicating SAR activation (Fig. 5). Conversely, the put2-1 consistently maintained low bacterial titers, with no significant differences between Mock and Put treatments (Fig. 5). Interestingly, the 35S::PUT2 overexpression lines exhibited low bacterial titers even in the Mock-treated plants, similar to the put2-1 mutant, suggesting basal resistance. Furthermore, the 35S::PUT2 lines Fig. 4. Regulation of SAR marker genes by polyamines. Gene expression of a) ICS1, b) PR1, c) SARD4, d) FMO1, e) UGT76B1, f) AZI1, g) NHL10, and h) NIMIN1 in systemic leaves at 6 h after local infiltration with Mock or 30 μ M Put, Spd, or Spm. Gene expression values were normalized to the EF1 α reference gene and relative to WT Mock plants using the 2 -ΔΔCt method. Values are the mean of three replicates ±SE. Different letters indicate significant differences (p ≤0.05) between treatments according to two-way ANOVA and LSD Fisher’s post-hoc test. E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 9 compromising the systemic immune response. Interestingly, we also found that both Spm treatment and put2-1 under SAR upregulated UGT76B1 expression in Arabidopsis. Moreover, the high Spm levels in the mutant line indicate a clear connection between UGT76B1 transcript levels and Spm. The put2-1 mutant also exhibited elevated levels of other higher polyamines, including tSpm, nSpd, and nSpm, which aligned with increased ADC2, SPMS, and ACL5 expression. Consistent with these findings, Kim et al. (2019) reported Spm overaccumulation in seeds of the put2-1 mutant. This accumulation suggests potential defects in polyamine distribution or metabolic regulation within the cell, reinforcing the idea that AtPUT2 is critical for maintaining polyamine homeostasis and proper compartmentalization. Polyamine supplementation experiments showed that Spd and Spm differently regulate gene expression. Spd treatment induced NIMIN1 expression in WT plants but not in put2-1, while Spm increased NIMIN1 and UGT76B1 expression in put2-1. NIMIN1, a negative regulator of plant immune responses, acts by sequestering the SAR master regulator NPR1 (Mohan et al., 2016). NIMIN1 was highly expressed in the put2-1 mutant under native conditions and was further upregulated in response to local priming (1 ◦ Pst / 2 ◦ Native) , systemic challenge (1 ◦ Mock / 2 ◦ Pst) , and SAR (1 ◦ Pst / 2 ◦ Pst) . Thus, affecting the defense responses in put2-1. Overexpression of NIMIN1 leads to SA intolerance (Mohan et al., 2016), mimicking the npr1 mutant phenotype characterized by reduced expression of SA-induced PR genes, including PR1, and impaired SAR. Interestingly, despite the loss of SAR in put2-1, PR1 expression was not repressed, suggesting that a SA-independent pathway might regulate its expression. ROS are key signaling molecules involved in regulating SAR and stomatal immunity. Previous studies have shown that Put induces RBOH-D and RBOH-F, which generate apoplastic ROS and contribute to SAR-like responses (Liu et al., 2020). In our study, the put2-1 mutant line accumulated superoxide radical ions in response to local Pst inoculation (1 ◦ Mock / 2 ◦ Pst) but not under SAR (1 ◦ Pst / 2 ◦ Pst), suggesting a defect in systemic ROS signaling. Various experimental approaches in this study consistently demonstrated that the put2-1 mutant displays impaired ROS accumulation and systemic signaling. For instance, luminol-based assays revealed that the put2-1 mutant had weaker ROS signals than the WT and the 35S::PUT2-27 line. Following flg22 elicitation, the put2-1 mutant showed no differences in ROS dynamics between Mock-treated and Pst-primed plants, confirming the compromised systemic response. Moreover, stomatal closure assays revealed that put2-1 exhibited attenuated responsiveness to flg22 compared to WT, while the 35S::PUT2-27 showed an enhanced response. While stomatal closure mediated by the FLG22 receptor is known to be SA-dependent, polyamines (Put, Spd, and Spm) also significantly contribute to this process by enhancing nitric oxide and ROS production in guard cells. This polyamine response involves the activity of RBOH and amine oxidase enzymes, contributing to stomatal closure (Zheng et al., 2015; Agurla et al., 2018). Put stimulates NO production, thereby promoting stomatal closure (Agurla et al., 2018), a process that may be impaired in put2-1 due to its reduced Put content under SAR. SA modulates polyamine metabolism in Arabidopsis, increasing Put accumulation via an NPR1-independent but partially MPK6-dependent mechanism, while Pst triggers Put accumulation in a SA-dependent manner (Rossi et al., 2021). Although the polyamines-ROS-SA crosstalk has primarily been studied at the biosynthesis level, our findings indicate that AtPUT2-mediated polyamine transport also regulates SA and ROS levels, thereby modulating plant defense and stomatal immunity. Another key finding of this study was that the put2-1 mutant exhibited altered expression of genes encoding chloroplast enzymes, mainly related to galactolipid biosynthesis, suggesting a metabolic disorder in this organelle. In addition to its role in photosynthesis, the chloroplast is a crucial organelle involved in synthesizing Pip and precursors of SA, and coordinating plant defense responses (Kachroo et al., 2021). The AtPUT2 transporter has been reported to localize to multiple intracellular compartments, including the chloroplast and the Golgi apparatus (Li et al., 2013; Fujita and Shinozaki, 2014; Ahmed et al., 2017), with additional localization predictions to the plasma membrane, vacuole, and mitochondria according to the SUBA4 database (Hooper et al., 2017). In chloroplasts, polyamines are key for stabilizing thylakoid structure, post-translational modifications of antenna proteins, and regulating photosynthesis, photoadaptation, and stress responses (Sobieszczuk-Nowicka and Legocka, 2014). Our findings suggest that AtPUT2 may be involved in chloroplast-associated metabolic processes crucial for immune signaling and systemic resistance. However, other previously described roles for polyamines in the chloroplast may also be dependent on their transport. Although further studies are needed to understand the chloroplastassociated regulation of AtPUT2 in SAR, our assumptions are also supported by the fact that the put2-1 mutant exhibits a similar phenotype to loss-of-function mutants of genes involved in galactolipid biosynthesis, with compromised SAR, while retaining basal resistance to Pst (Maldonado et al., 2002; Nandi et al., 2004; Chaturvedi et al., 2008; Lim et al., 2020). In these mutants, the loss of SAR has been linked to defects in plastid function (Chaturvedi et al., 2008). For example, the MGDL gene, which encodes a chloroplast A-type monogalactosyldiacylglycerol synthase required for galactolipid synthesis, plays a role in generating precursors for mobile signals, such as Aza and G3P, which are essential for SAR (Kachroo et al., 2021). Recently, it has been found that levels of various galactolipids, such as MGDG (18:3, 16:3), MGDG (18:3, 16:2), and MGDG (16:3), which are primary precursors of jasmonic acid (JA), increase in the Spm-deficient spms mutant that is Pst susceptible and Bc resistant (Zhang et al., 2023). Therefore, it is reasonable to suggest that the increased Spm levels in the put2-1 mutant may also influence galactolipid and JA content as well as the defense responses to pathogens. Moreover, the increased susceptibility to Bc in systemic tissues of the put2-1 mutant could also result from alterations in the ethylene-JA pathway, as recently shown by Zhang et al. (2023) and Pe˜ na-Lucio et al. (2025). Our transcriptomic analysis also revealed that many genes associated with photosynthesis and chloroplast function (Table S3), including those involved in galactolipid synthesis in the chloroplast, such as MGD1, FAD4, and FAD7, were down-regulated in the put2-1 mutant line (Table 1, Fig. S9). These findings reinforce the evidence that AtPUT2 impacts chloroplast function, and that the SAR deficiency observed in the put2-1 mutant may also result from disrupted production of galactolipid-derived mobile signals. 5. Conclusion Our findings reveal the crucial role of the Polyamine Uptake Transporter 2 (PUT2/LAT4) in SAR and broad-spectrum SAR establishment in Arabidopsis. Fig. 10 shows a model integrating the main findings related to the function of Put and AtPUT2 in systemic responses. AtPUT2 transporter is required for Put transport to systemic tissues, which regulates the expression of essential genes involved in SA and NHP biosynthesis and modulates SA levels. Under SAR (1 ◦ Pst / 2 ◦ Pst) , the put2-1 mutant exhibits alterations in the expression of SAR-related genes, SA, ROS, and Put content, indicating that the proper timing of accumulation of each actor is crucial for SAR establishment. Particularly, ROS signaling is compromised in the put2-1 mutant, affecting other key defense responses such as stomatal immunity. The downregulation of crucial genes involved in galactolipid synthesis in the put2-1 mutant points to future research regarding the importance of polyamine transport in chloroplast-mediated SAR responses. Understanding how polyamine transport mechanisms contribute to plant defense could significantly enhance our understanding of plant stress resilience. Funding This work was supported by Secretaría de Ciencia, Humanidades, E. Flores-Hern´ andez et al. Plant Stress 18 (2025) 101046 16 Tecnología e Innovaci´ on (SECIHTI) - Mexico (Ciencia de Frontera 20191564453), the Ministry of Agriculture, Czech Republic (MZE-RO0423), and by the European Regional Development Fund (ERDF) Programme Johannes Amos Comenius (CZ.02.01.01/00/23_021/0008909). CRediT authorship contribution statement Emmanuel Flores-Hern´ andez: Writing – review & editing, Writing – original draft, Visualization, Investigation, Formal analysis. María Elisa Gonzalez: Writing – review & editing, Validation, Formal analysis, Conceptualization. Paulina Alvarado-Guitron: Writing – review & editing, Validation, Formal analysis. Francisco I. Jasso-Robles: Resources, Funding acquisition, Formal analysis. Cesar´ e OvandoV´ azquez: Software, Formal analysis, Data curation. Juan Francisco Jim´ enez-Bremont: Writing – review & editing, Resources, Funding acquisition. Sanja ´ Cavar Zeljkovi´ c: Investigation. Mark´ eta Ulbrichov´ a: Investigation, Formal analysis. Nuria De Diego: Writing – review & editing, Writing – original draft, Visualization, Resources, Funding acquisition, Formal analysis, Data curation. Margarita Rodríguez-Kessler: Writing – review & editing, Writing – original draft, Visualization, Supervision, Resources, Funding acquisition, Formal analysis, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments Emmanuel Flores Hern´ andez is a doctoral student in the Programa de Posgrado en Ciencias en Bioprocesos, Universidad Aut´ onoma de San Luis Potosí (UASLP), and has received a fellowship (778715; CVU: 935284) from Secretaría de Ciencia, Humanidades, Tecnología e Innovaci´ on (SECIHTI), former Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCYT)-M´ exico. Paulina Alvarado Guitron is a doctoral student in the Programa de Posgrado en Ciencias de la Vida, Universidad Aut´ onoma de San Luis Potosí (UASLP), and has received a fellowship (4038882; CVU: 1177830) from SECIHTI. 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