Physiological responses of grapevine (Vitis vinifera var. ‘Pinot gris’) affected by different flavescence dorée genotypes: Dynamics through the development of phytoplasma infection

Physiological responses of grapevine (Vitis vinifera var. ‘Pinot gris’) affected by different flavescence dorée genotypes: Dynamics through the development of phytoplasma infection | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Physiological responses of grapevine (Vitis vinifera var. ‘Pinot gris’) affected by different flavescence dorée genotypes: Dynamics through the development of phytoplasma infection Dino DAVOSIR, Ivana ŠOLA, Martina Seruga Music This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3231755/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Phytoplasmas are phytopathogenic bacteria that cause serious damage to agriculture. A quarantine pathogen flavescence dorée phytoplasma (FDp), often associated with grapevine yellows disease, affects viticultural production across Europe. However, the mechanisms of FDp pathogenicity still are not elucidated. In this study, symptomatic and asymptomatic grapevine ( Vitis vinifera L. var. ‘Pinot gris’) were sampled. Two different FDp genotypes (M38 and M54) were identified, and genotype-dependent changes to grapevine physiological responses through the development of FDp infection were analysed. Correlation analyses established a potential linked between measured physiological parameters and relative FDp DNA abundance. Increased malondialdehyde levels pointed to the oxidative stress in infected leaves, and highly correlated with the activation of L -ascorbic acid synthesis. Levels of hydrogen peroxide were reduced in infected leaves, possibly as FDp mechanism to avoid plant-derived oxidative damage. Genotype M54 was associated with a lower accumulation of soluble sugars and lower damage to photosynthetic pigments, while retaining a higher titre than M38. Therefore, pronounced phytoplasma genotype-dependent changes in grapevine physiology, potentially caused by the differences between M54 and M38 on the level of the efficiency of their effectors should be further investigated. Altogether, results provide data on certain targets of FDp in grapevine and could assist the identification of potential specific effectors of this phytoplasma to aid the efforts of FDp management in European vineyards. ascorbic acid biotic stress grapevine yellows hydrogen peroxide oxidative stress photosynthetic pigments Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Phytoplasmas (genus ‘ Candidatus ( Ca. ) Phytoplasma’) are obligate intracellular parasitic bacteria constituting a large monophyletic group within the class Mollicutes, and pathogens of a wide variety of plants. Phytoplasmas are associated with causing diseases in a wide range of plants, including agriculturally important crops, as well as ornamental plants, timber and shade trees. The inability to routinely cultivate phytoplasmas in a pure culture in vitro makes establishing the taxonomic status of phytoplasmas difficult, and also hampers establishing many research models (Namba 2019 ). Phytoplasmas are particularly interesting because despite severe genome reductions due to their parasitic lifestyle, a fair number of (putative) effectors have been recognised in genomes of various phytoplasmas by which they manipulate host physiology. Indeed, transcriptomic, proteomic and other studies of phytoplasma-infected plants confirm a high modification of their normal physiological processes upon phytoplasma infection. Most of the symptoms in phytoplasma-diseased plants are mirrored in specific alterations to gene expression and/or changed protein levels in comparison to uninfected plants. Several genes involved in photosynthesis are downregulated in phytoplasma-infected plants, paralleled by growing evidence that inhibition of photosynthesis is a result of carbohydrate accumulation in source leaves. Increase in concentration of carbohydrates is suggested to be a consequence of phytoplasma manipulation in host plants and severe changes to the expression of genes related to carbohydrate synthesis were observed in several phytoplasma-infected plants (Dermastia et al. 2019 ). Grapevine flavescence dorée phytoplasma (FDp; ribosomal group 16SrV) is associated with grapevine yellows diseases (GY). GY are independently caused by two taxonomically distant phytoplasmas, the other being ‘ Ca . P. solani’ (known as bois noir phytoplasma, BNp; ribosomal group 16SrXII) (Angelini et al. 2018 ). They differ in symptom severity, as FDp is generally more aggressive (Prezelj et al. 2016 ). However, general symptoms of GY include yellowing or reddening of leaves (dependent of the variety), leaf rolling, shrivelled grapes and general plant decline. BNp is present in all viticultural areas worldwide and is mainly spread by the vector Hyalesthes obsoletus Signoret (Homoptera, Cixiidae). On the other hand, FDp is transmitted by the leafhopper vector Scaphoideus titanus Ball (Homoptera, Cicadellidae), and is spread in all main viticultural areas in Europe (Angelini et al. 2018 ), where it is a quarantine pathogen (EPPO Global Database 2002 ). Although FDp has been well characterized, a formal description of FDp as a new phytoplasma species remains to be published (Bertaccini and Lee 2018 ). The first complete genome of FDp ( map genotype M54) was recently published based on dual sequencing approach using both Illumina and Oxford Nanopore Technology. A total of 17 putative secreted proteins based on the presence of the signal peptide were detected. Based on that, these proteins could be potential pathogenicity factors (Debonneville et al. 2022 ). Prior to the publishing of the complete genome sequence, many studies attempted to unravel the mechanisms of FDp pathogenicity by analysing the response of FDp-infected plants using proteomic (Margaria et al. 2013 ), transcriptomic (Abbà et al. 2014 ; Pacifico et al. 2019 ; Teixeira et al. 2020 ) and metabolomic (Ferrandino et al. 2019 ) approaches, or their combinations (Margaria et al. 2014 ; Pagliarani et al. 2020 ; Prezelj et al. 2016 ). Particularly, role of hydrogen peroxide (H 2 O 2 ) has been recognized in recovery against FDp (Gambino et al. 2013 ; Musetti et al. 2007 ). A severe downregulation of genes involved in biosynthesis of photosynthetic pigments (Teixeira et al. 2020 ) and an upregulation of phenolic metabolism (Prezelj et al. 2016 ) was observed in FDp-infected grapevine. Furthermore, varying response of different grapevine varieties to FDp infection was assessed (Pacifico et al. 2019 ; Roggia et al. 2014 ). However, no previous study attempted to analyse the impact of different FDp genotypes on grapevine physiology and observe the changes in the seasonal dynamics of physiological responses through the vegetative season. Therefore, in this study, we analysed the impact of FDp infection in grapevine leaves of variety ‘Pinot gris’ at three time points during the vegetative season. Firstly, FDp was identified using a triplex real-time PCR assay, and the results were used for the relative quantification of FDp DNA. FDp from infected leaves was genotyped by amplification, sequencing and phylogenetic analysis of map gene, conventionally used for the genotyping of FDp. Then, physiological status of infected leaves, as well as the uninfected controls, and potential oxidative stress conditions were assessed by spectrophotometric analyses of the level of lipid peroxidation, H 2 O 2 content and proline content, as well as chromatographic analysis (RP-HPLC) of L -ascorbic acid content. Because of the earlier reports on FDp impact on sugar metabolism, soluble sugars content in infected leaves was assessed. Furthermore, photosynthetic pigment content in grapevine leaves was analysed in samples considering the reported pronounced chlorosis symptoms in FDp-infected leaves to evaluate a potential FDp genotype-dependent effect. Finally, data was statistically analysed using PCA and hierarchical clustering. Correlation analysis was performed for the possible establishment of link between relative FDp DNA abundance and physiological parameters, as well as establishing the potential co-dependency of tested parameters in FDp-infected grapevine to aid the unravelling of FDp pathogenicity mechanisms. 2. Materials and Methods 2. 1. Sampling and plant material Grapevine ( Vitis vinifera L. var. ‘Pinot gris’) leaves of symptomatic and asymptomatic plants were collected from a vineyard in central continental Croatia (Sveti Ivan Žabno, Koprivnica-Križevci County), which was previously under multi-year surveillance for presence of FD and BN phytoplasmas and a sampling location in previous studies (Plavec et al. 2019 ). The vineyard was managed according to integrated pest and disease principles. The leaves of grapevine variety ‘Pinot gris’ with symptoms of yellowing, leaves rolling and fruit drying were collected, as well as the leaves of asymptomatic plants. The leaves were taken randomly from same plants at three time points during the development of infection: at the end of June, at the end of August and at the end of September of 2021. Upon collecting, the samples were stored in a field refrigerator and in the laboratory, the leaves of similar size from the same plant were separated in three replicates for biochemical analyses, frozen under liquid nitrogen and stored at -80°C until freeze-drying. The plant material for biochemical analyses was freeze-dried using the Alpha 1–2 lyophilizer (Martin Christ Gefriertrocknungsanlagen GmbH, Osterode am Harz, Germany) at -55°C and 0.05 mbar for approximately 32 h. Then, the material was grounded to fine powder in a mortar with pestle using liquid nitrogen and stored for later analyses. Each analysis was run in triplicate for each sample with three technical replicates. 2. 2. Phytoplasma detection and identification A CTAB-based method for total nucleic acid extraction was used, according to the previously developed method (Seruga et al. 2003 ). Nucleic acids were extracted from 250 mg of midribs isolated from grapevine leaves. To detect the causative agent of GY in grapevine samples, a triplex real-time PCR assay, which was developed by Pelletier et al. ( 2009 ) was performed for the 10x and 100x dilutions of nucleic acid extracts in duplicates. Amplification was performed using the TaqMan™ Universal PCR Master Mix according to the manufacturer’s instructions using the reported primers and probes (Pelletier et al. 2009 ) as follows: 10 min at 95°C (1 cycle) followed by 45 cycles of 1 min at 94°C and 1.5 min at 59°C. Analyses were carried out using a 7300 Real Time PCR System (Applied Biosystems, Waltham, USA). To quantify the presence of phytoplasma DNA in the samples and compare the quantity of phytoplasma DNA at different analysed time points, cycle threshold (Ct) values from real-time PCR experiment were used as an indicator of relative amount of phytoplasma DNA in samples. All Ct values for FDp map gene reporter were normalized to Ct values of corresponding Vitis sp. chloroplast tRNA L-F spacer reporter (endogenous control). Then, Ct/Ct con values were subtracted from 1 for simplification. For phytoplasma genotyping, nested PCR was used to amplify the phytoplasma map gene fragment with primer pairs FD9f5/MAPr1 for direct and FD9f6/MAPr2 for nested PCR (Arnaud et al. 2007 ). In PCR experiments, GoTaq Flexi DNA Polymerase (Promega) was used. Amplification of map gene fragments was verified by agarose gel-electrophoresis. Amplified DNA fragments were Sanger sequenced in a commercial service (Genewiz, Leipzig, Germany). Sequencing of map gene amplicons was performed using the primers used in the nested PCR (FD9f6/MAPr2). Obtained sequences were edited using the Geneious Prime software (Kearse et al. 2012 ). For phylogenetic analysis, sequence alignment was performed using ClustalX software (Thompson et al. 1997 ). Phylogenetic analysis was performed in MEGA X (Kumar et al. 2018 ) using the neighbour-joining method with model No. of differences and bootstrap with 500 repeats. Reference map gene sequences (LT221949, LT221933, LN850372, LT221945, LT221946) were obtained from NCBI database using the Nucleotide BLAST tool. In order to study the relatedness of detected genotypes, a phylogenetic tree based on concatenated sequences of map was constructed. 2. 3. Analysis of grapevine oxidative stress parameters Samples for the analyses of physiological parameters included three separate replicates of M38-infected leaves, M54-infected leaves and uninfected leaves at three time points during the development of infection, with each of three replicates for each of the three time points analysed in three technical replicates. For the estimation of the level of lipid peroxidation, determination of hydrogen peroxide (H 2 O 2 ) content and proline content, 60 mg of each sample was homogenized in 1.5 mL of 0.1% (w/v) trichloroacetic acid (TCA) using a mortar and pestle. The homogenate was centrifuged at 15000 rpm and 4°C for 15 min, and the supernatant was used for the determination of lipid peroxidation according to the method in Linić et al. ( 2021 ) with some modifications. Briefly, 100 µL of each extract was mixed with 600 µL of 0.5% thiobarbituric acid (TBA) in 20% TCA and the mixture was homogenized and incubated for 30 min at 95°C. Every sample had a separate blank without TBA to minimize the absorbance of other compounds present in the extract. After the incubation, the reaction was stopped by placing the tubes on ice for 10 min. The mixture was centrifuged at 12000 rpm and 4°C for 5 min. After the incubation, colour intensity was quantified by measuring the absorbance at 532 and 600 nm. MDA content in the samples was calculated based on the molar extinction coefficient of 155 mM − 1 cm − 1 , and expressed as ng of MDA per g of dry weight (DW). H 2 O 2 content in grapevine leaves was determined as described in (Junglee et al. 2014 ). Supernatant (250 µL) was mixed with the same volume of potassium phosphate buffer (pH 7.0) and 500 µL of 1 M potassium iodide and the mixture was homogenized. Then, colour intensity was quantified by measuring the absorbance at 390 nm. Content of H 2 O 2 was calculated indirectly based on the calibration curve of standard H 2 O 2 solutions of known concentrations. The results were expressed as µmol of H 2 O 2 per g of DW. Proline content in grapevine leaves was evaluated with a method optimized from Ljubej et al. ( 2021 ). Supernatant (60 µL) was mixed with 600 µL of ninhydrin reagent (1% ninhydrin, 60% acetic acid, 20% ethanol) and the mixture was homogenized and incubated for 20 min at 95°C. Every sample had a separate blank to minimize the absorbance of other compounds present in the extract. After the incubation, colour intensity was quantified by measuring the absorbance at 520 nm. Proline content in the samples was calculated indirectly based on the calibration curve of standard L -proline solutions of known concentrations. The results were expressed as mg of L -proline per g of DW. For the analysis of soluble sugars, extracts were prepared in 70% ethanol as described (Davosir and Šola 2023 ), and their content was evaluated using the method adapted from Dubois et al. ( 1956 ). Volume of 200 µL of each extract diluted to 1 mg DW/mL and was mixed with 100 µL of 5% phenol (v/v) and 500 µL of concentrated H 2 SO 4 . Then, samples were homogenized and incubated for 10 min at RT after which the samples were incubated for 10 min in a water bath at 30°C. After the incubation, colour intensity was quantified by measuring the absorbance at 485 nm. Soluble sugar content in the samples was calculated indirectly as mg of sucrose equivalents (SE) per g of DW based on the calibration curve of standard sucrose solutions of known concentrations. 2. 4. RP-HPLC analysis of L - ascorbic acid content For quantitative analysis of L -ascorbic acid from grapevine leaves extracts prepared in 70% ethanol as for the SS measurement, analysis was carried out using the reversed-phase high-performance liquid chromatography (RP-HPLC). Acidic hydrolysis was carried out prior to the analysis with 1.2 M HCl by incubating the extracts for 2 h at 80°C and 300 rpm. The RP-HPLC analyses were performed using a previously reported and validated method (Šola et al. 2023 ). The analysis of L -ascorbic acid was carried out at 254 nm and L -ascorbic acid was identified based on the comparison with the retention time and UV-spectrum of a commercial standard. For the quantitative analyses, external standard was used, and calibration curve was obtained by injecting the known concentrations (0.25 − 0.01 mg/mL) of standard solutions. The results were expressed as mg/g DW. 2. 5. Determination of grapevine photosynthetic pigments For the spectrophotometric determination of the photosynthetic pigment content, method according to Sumanta et al. ( 2014 ) was used. For this purpose, extracts of photosynthetic pigments were prepared from lyophilized powdered plant tissue using the 80% acetone (v/v) as a solvent. Mass of 15 mg of each sample was mixed with 1 mL of 80% acetone and the solution was mixed for 20 sec. Then, the mixture was centrifuged at 13 000 rpm and 4°C for 5 min, after which the supernatant was transferred to a new tube on ice and the extraction was carried out once again following the same procedure, until the plant material became white. Absorbance of the extracts was monitored at 453, 470, 505, 575, 590, 682, 647 and 663 nm. The content of chlorophyll a and chlorophyll b , total carotenoids, β -carotene, lycopene, and porphyrins was determined from the previously reported equations (Sumanta et al. 2014 ). 2. 6. Statistical analysis Statistical analyses were conducted in Statistica 13.1 (Stat Soft Inc., USA). Analysis of statistically significant differences between the samples was carried out using one-way analysis of variance (ANOVA) and post-hoc Duncan’s Multiple Range Test. Statistically significant differences between the samples at p ≤ 0.05 were marked with different letters. To compare the dynamics of tested parameters during the development of infection, values were normalized to the values of corresponding uninfected controls to eliminate the effect of seasonal dynamics of tested parameters, and the values from different time points for the same sample were compared. Pearson’s correlation coefficients ( r ) were calculated between the absolute values of tested parameters, with statistical significance at p ≤ 0.05. To calculate Pearson’s correlation coefficients between the relative FDp DNA abundance and tested parameters, relative values of tested parameters (compared to control) were used for analysis. Principal component analysis (PCA) and hierarchical clustering analysis based on Euclidian distance were performed to establish the relationship between samples based on tested physiological parameters. 3. Results and Discussion Phytoplasmas cannot be cultivated in a pure culture in vitro and sustaining the phytoplasma infection sometimes appears difficult, as previously shown in in vitro grown grapevine (Eveillard et al. 2016 ). Therefore, studies dealing with investigation of interactions between grapevine and FDp remain almost exclusively based on sampling and analysis of field-grown plants (Abbà et al. 2014 ; Gambino et al. 2013 ; Margaria et al. 2014 ; Prezelj et al. 2016 ; Roggia et al. 2014 ). Initially, it was believed that changes to host physiology are an indirect response to the infection; however, more recent studies revealed that phytoplasma genomes possess a wide variety of effector molecules which enable them to directly modulate host physiology (Tomkins et al. 2018 ). Although whole genomes of some phytoplasmas are extensively studied and many of their effectors recognized, for example for ‘ Ca. P. solani’ (Šeruga Musić et al. 2019 ), detailed whole genome analyses of FDp and functional analyses of putative effectors still await. Although there are some disadvantages of this approach, studying the physiological responses of field-infected grapevine could give an insight into potential targets of FDp effectors, and assist the identification of potential effectors of this phytoplasma. By combining the molecular identification with assessing the impact on grapevine physiology, this study will contribute to unravelling the mechanisms of FDp pathogenicity. Furthermore, to our knowledge, no previous study attempted to investigate the impact of different FDp strains, based on the phylogenetic relationship between relevant genes used in genotyping, on specific targets in grapevine physiology and correlate it with potential differences in pathogenicity. 3. 1. Indications for the epidemiology of FDp FDp was detected in all symptomatic leaves at all three sampling time points. Phylogenetic analysis of map gene amplicons revealed that all the FDp-positive samples were infected by the FD genotypes belonging to the mapFD2 genetic cluster (Fig. 1 a). This is unsurprising, considering previous studies revealed that isolates belonging to the mapFD2 cluster were predominant in Croatian vineyards (Plavec et al. 2019 ). However, two different genotypes within the mapFD2 cluster were detected, M38 and M54. Identified FDp isolates within the mapFD2 genetic cluster comprise two genotypes with map sequences 100% identical to sequences classified as genotypes M38 and M54. The same study (Plavec et al. 2019 ) discussed that M54 genotype within mapFD2 cluster could be the prevalent one in Croatian vineyards and its highly efficient transmission by the vector S. titanus was hypothesised. This genotype was identified as responsible for heavy damage to the viticultural production in Istria region of Croatia (Plavec et al. 2019 ). Prevalence of this genotype was also observed in Italian (Rossi et al. 2019 ) and French vineyards, where this genotype represented 85% of all FD cases in 2000s (Malembic-Maher et al. 2020 ). Present study revealed higher relative FDp DNA abundance in M54-infected grapevine, than in M38-infected grapevine, pointing to a higher phytoplasma titre (Fig. 1 b). This could be linked to higher replicative potential of this genotype within grapevine plants and potentially, easier acquisition by the vector, leading to its higher geographic distribution. Indeed, Galetto et al. ( 2014 ) confirmed that acquisition capability of the FDp by the vector S. titanus correlates with phytoplasma titre in the source plant. Therefore, ability to attain higher titre in infected grapevine could be a potential reason for the higher geographic distribution of M54 genotype. Relative FDp DNA abundance was quantified using a real-time PCR assay (Pelletier et al. 2009 ) through the development of infection at three time points for each identified FDp genotype. The trend of FDp DNA between different time points was similar for samples of both genotypes. As expected, for both M38- and M54-infected samples, the lowest DNA abundance was observed at the first time point in June, earlier in the vegetative season. The peak in FDp DNA abundance was in late summer (August time point) for both M38- and M54-infected samples. A lower DNA abundance at the third time point compared to the August time point was more pronounced in M54-infected grapevine, with a somewhat lower reduction of FDp DNA abundance in M38-infected grapevine. This dynamics is in agreement with the previous results for the FDp titre in field grown grapevine through the vegetative season (Roggia et al. 2014 ), reflecting the similar and conserved seasonal dynamics of FDp replication in grapevine. Interestingly, more effective phytoplasma acquisition by mature S. titanus was observed, rather than S. titanus larvae. Considering that S. titanus matures in July/August (Chuche and Thiéry 2014 ), the highest phytoplasma titre in grapevine at this time point could be the phytoplasma mechanism to maximize the rate of transmission to mature potential vectors who can acquire the phytoplasma more effectively than larvae. 3. 2. Oxidative stress conditions affected by FDp genotypes Both M54- and M38-infected grapevine had characteristic GY symptoms at the first time-point: yellowing, leaf rolling and fruit drying. Morphologically, no difference in disease severity could be observed. However, at the second, and third time point particularly, stronger disease symptoms were observed in M54-infected grapevine. Malondialdehyde (MDA) content, an indicator of the level of membrane lipid peroxidation, is an often-used biomarker of stress conditions in plants, due to the susceptibility of membranes to ROS-induced damage (Hodges et al. 1999 ). Enhanced ROS synthesis is a common defence mechanism against plant pathogens. This increase in ROS synthesis often leads to oxidative stress in infected plants (Suman et al. 2021 ). The level of lipid peroxidation was higher in infected plants at all three time points in comparison to the corresponding controls (Fig. 2 a). Increased level of lipid peroxidation was previously reported in phytoplasma-infected plants, compared to the uninfected plants (Kiprovski et al. 2018 ; Mitrovic et al. 2021 ). At the first and second time point, MDA content was the highest in M38-infected leaves. However, at the third time point, the MDA content was the highest in M54-infected leaves. Considering that FDp DNA abundance was higher in M54-infected leaves, higher level of lipid peroxidation was expected in these leaves as a result of the oxidative burst. However, it is known that FDp genomes possess superoxide dismutase ( sod ) gene (Carle et al. 2011 ), encoding an antioxidative enzyme responsible for quenching superoxide radicals. This potential phytoplasma-mediated suppression of plant-derived ROS could have led to the lower level of lipid peroxidation in grapevine leaves infected with higher phytoplasma titre at the first and second time points, as a mechanism for the protection from plant-derived oxidative burst. Only at the third time point, in which relative FDp DNA abundance in M54-infected leaves dropped more severely (which could have led to a more drastic drop in FDp SOD activity) than in M38-infected leaves, was the level of lipid peroxidation higher in M54- than in M38-infected leaves, corroborating this hypothesis. Also, phytoplasma effectors could potentially manipulate the induction of synthesis of antioxidative compounds (for example, phenolics) in plants to quench protective ROS, as proposed previously (Prezelj et al. 2016 ). Interestingly, absolute MDA content positively correlated with the L -ascorbic acid (AA) content ( r = 0.69), as did their relative content ( r = 0.74) (Fig. 3 , Supplementary material 1). Considering that the AA (vitamin C) is a strong antioxidant, its synthesis could be induced upon oxidative damage caused by the oxidative burst, thus establishing a link between the MDA and AA content. Indeed, AA levels were higher in infected leaves at all three time points (Fig. 2 c). Based on the metabolite and the expression of genes involved in AA biosynthesis, Xue et al. ( 2020 ) also recognised the involvement of AA in phytoplasma-infected plants. Indirect role of AA in plants battling biotic stress and its induction as a response to the oxidative burst have been reviewed (Khan et al. 2012 ), suggesting to it being a general response mechanism in plant-pathogen interactions, not specific to the phytoplasma infection. For M38-infected leaves, the highest AA concentration in comparison to the controls was at the second time point, and the lowest at the first time point. Likewise, in M54-infected leaves the lowest concentration was at the first time point, however, the highest was at the third time point (Fig. 2 d). Also, similarly to the MDA content, AA content was higher in M38-infected leaves at the first and second time points. However, at the third time point, AA content was also the highest in M54-infected leaves. This further supports the hypothesis that the mechanisms of induced ROS synthesis against FDp invasion are followed by responses to minimize oxidative damage by inducing the synthesis of antioxidants such as AA. Activation of responses to minimize oxidative damage could either be phytoplasma-induced, plant-induced (to minimize damage to its cells) or a combination of both and should be a subject of further studies. 3. 3. Osmolyte accumulation in FDp-infected grapevine Both proline and sugars, which often accumulate in plants as a response to abiotic and biotic stressors, are reliable biomarkers of stress conditions in plants (Jeandet et al. 2022 ; Liang et al. 2013 ; Sharma et al. 2019 ). Soluble sugars (SS) content at all three time points followed the same trend, being the highest in M38-infected leaves, and lowest in uninfected leaves (Fig. 2 e). Because phytoplasmas colonize phloem tissues in infected leaves, this causes the physical obstruction of transport of sugars due to callose deposition in phloem cell walls, leading to elevated sugar levels in leaves (Musetti et al. 2013 ). Furthermore, a substantial upregulation of genes involved in sugar biosynthesis was observed in FDp-infected leaves (Prezelj et al. 2016 ). However, it is still unknown whether this is induced by FDp effectors or is a more of an unspecific response of grapevine to the infection. Nevertheless, this sugar-rich environment creates a perfect setting for FDp replication, due to its metabolism, which is strictly oriented to glycolysis (Carle et al. 2011 ). Interestingly, a negative correlation was observed between relative SS content and FDp phytoplasma DNA abundance ( r = -0.90) (Fig. 3 b, Supplementary material 1). Particularly, lower SS content was recorded in M54-infected leaves, which had higher FDp DNA abundance. This could potentially be due to the M54 genotype having a less severe impact on sugar metabolism in infected grapevine than the M38 genotype. Also, the higher titre of M54 genotype could cause higher usage of leaf sugars by phytoplasmas, lowering the total SS in M54-infected leaves compared to M38-infected leaves. The same dynamics of relative SS content was observed for both genotypes, with the highest being at the first time point (Fig. 2 f). Similarly, Negro et al. ( 2020 ) reported lower relative SS in September than July in BNp-infected grapevine. This could be due to the lower photosynthetic capacity of infected grapevine at later time points, resulting in lower relative SS content (Rasool et al. 2020 ). Similarly to SS, upregulation of proline biosynthesis was also previously reported in phytoplasma-infected American cranberries (Pradit et al. 2019 ), as well as in phytoplasma-infected sweet orange (Rasool et al. 2020 ). At all three time points, proline content was the highest in M54-infected leaves (Fig. 2 g). Levels in M38-infected leaves were higher than the control only at the second time point. Proline acts as a protective molecule in plants during various stress conditions acting as an osmolyte, but also by being involved in the stabilization of proteins, direct scavenging of ROS and promoting downstream cellular signalling pathways related to plant defence mechanisms (Liang et al. 2013 ). Its relative content positively correlated ( r = 0.85) with relative FDp DNA abundance (Fig. 3 b, Supplementary material 1). This points that proline accumulation is a protective response mechanism against FDp infection. Although it appears to be a direct response mechanism and it is being affected by phytoplasma titre, the hypothesis is that this response is not a part of the PAMP-triggered immunity. Rather, our hypothesis is that proline accumulation is a response to FDp-induced symptoms in infected grapevine leaves, due to its general and fundamental role in stress response (Liang et al. 2013 ). But, contrary to SS, at all three time points, proline content was higher in M54-infected leaves than M38-infected leaves. It was previously discussed that proline could be associated with avirulent pathogen recognition (Zeier 2013 ). Potentially, higher proline content in M54-infected leaves could be linked to previously observed lower effect of the M54 genotype on SS and MDA levels. Therefore, proline levels reflect the FDp abundance in infected leaves better than the previously assessed parameters. Even though proline and soluble sugars both primarily act as osmolytes and have a synergistic effect in battling various abiotic stresses (Suprasanna et al. 2015 ), their dynamics in FDp-infected grapevine was dramatically different. This could possibly be due to the specific impact of FDp infection on sugar metabolism, which had a specific impact on grapevine SS content. Therefore, in this case, SS probably do not have a substantial protective role in battling FDp infection in grapevine. However, proline accumulation could possibly alleviate some symptoms of FDp-induced damage to grapevine. Nevertheless, both of those metabolites could be used as biomarkers of FDp infection. 3. 4. Differential effect of FDp genotypes on HO production in grapevine Role of hydrogen peroxide (H 2 O 2 ) in phytoplasma-infected plants and its potential involvement in recovery has been heavily discussed (Gambino et al. 2013 ; Musetti et al. 2007 ). Musetti et al. ( 2007 ) hypothesised that H 2 O 2 appears to be involved in counteracting phytoplasma virulence. Indeed, higher content of H 2 O 2 in infected leaves at the first time point in comparison to the uninfected leaves points to the protective role of H 2 O 2 , especially active at the earlier stages of the infection (Fig. 2 i). However, at the later time points, except in the M38-infected leaves at the third time point, H 2 O 2 content was lower in infected leaves than uninfected leaves. Lower H 2 O 2 content in FDp-infected leaves in comparison to the uninfected grapevine leaves was previously observed (Gambino et al. 2013 ). The same study recognised that overexpression of some H 2 O 2 scavenging genes ( APX2 , POX4 , POX5 ) reduced the quantity of H 2 O 2 . Similarly, a recent study also confirmed that symptomatic FDp-infected leaves of grapevine cultivar ‘Tocai friulano’ also accumulate less H 2 O 2 , accompanied by the upregulation of some H 2 O 2 scavenging-related genes (Casarin et al. 2023). Our hypothesis is that this overexpression could potentially be mediated by certain FDp effectors. This is supported by a negative correlation ( r = -0.86) between relative FDp DNA abundance and relative H 2 O 2 content. Therefore, higher FDp DNA abundance (i.e., phytoplasma abundance in infected leaves) caused the higher reduction in H 2 O 2 synthesis, potentially mediated by some FDp effector molecules inducing the overexpression of H 2 O 2 scavenging genes at later stages of the infection. This mechanism reduces the oxidative damage to FDp and enables higher level of FDp replication, supported by the fact that the more abundant M54 genotype caused the higher reduction of H 2 O 2 content. Interestingly, in M38-infected leaves at the third time point, H 2 O 2 content was higher than the control and M54-infected leaves, pointing to the higher ability of ‘Pinot gris’ leaves to overcome the proposed impact of M38 genotype, compared to its ability to battle the effect of potential M54 effectors. 3. 5. Impact of FDp infection on photosynthetic pigments Total chlorophyll content was the highest in uninfected leaves at all three time points during the development of infection, with M38-infected leaves having the lowest total chlorophyll content at all three time points (Table 1). Considering that the leaf chlorosis is a common symptom of FDp infection in many grapevine varieties (Teixeira et al. 2020 ), observed severe reduction in photosynthetic pigment content was expected. Even though initial studies argued that reduction of photosynthetic pigments could be linked to the increase in chlorophyllase activity in phytoplasma-infected grapevine (Bertamini and Nedunchezhian 2001 ), more recent studies concluded that no increase in pigment degradation is evident. Rather, general decrease in influx of chlorophyll precursors causes this severe reduction in photosynthetic pigments (Teixeira et al. 2020 ). Evidence point to leaf yellowing being a result of sugar accumulation in leaves infected by various phytoplasmas, leading to the metabolic feedback inhibition of photosynthesis, as previously reviewed (Dermastia et al. 2019 ). It is accompanied by a downregulation of genes involved in both light- and dark-dependent reactions and other genes related to photosynthetic processes in FDp-infected grapevine (Prezelj et al. 2016 ). In both M38 and M54-infected leaves, relative total chlorophyll content was the highest at the first time point (Supplementary material 2). In M38-infected leaves there was no statistically significant difference between relative chlorophyll content at the second and third time point. However, in M54-infected leaves, there was an increase in relative chlorophyll content at the third time point compared to the second time point. In fact, M54 had a lower impact on total chlorophyll content at all three time points. Potentially, M54 induced a higher accumulation of protective compounds by FDp effector proteins that protected photosynthetic pigments from UV-stress, which enabled an increase in their content. Similar dynamics was observed for chlorophyll a and b . For chlorophyll a , there was also an increase in its content at the third time point in M38, as well as in M54-infected leaves. On the other hand, in M38-infected leaves, relative chlorophyll b content dropped at the third time point, while in M54-leaves it increased. This opposite dynamics of chlorophyll a and b content at the third time point in M38-infected leaves probably lead to the total chlorophyll content being unchanged between second and third time points. Chlorophyll a / b ratio, however, had the same dynamics for M38- and M54-infected leaves, with it being reduced in infected leaves at all time points. This points to the higher impact of FDp infection on chlorophyll a , than chlorophyll b . Similarly, Teixeira et al. ( 2020 ) initially recorded a drop in chlorophyll a , but not chlorophyll b , pointing to its lower susceptibility to phytoplasma infection. Severe reduction in chlorophyll content of FDp-infected leaves causes inevitable reduction in photosynthetic performance. Importantly for agricultural production, this causes reduction in yield and drastic production losses in FDp-infected grapevine, as previously reported (Oliveira et al. 2020). Considering that chlorophylls are the major class of porphyrins, similar dynamics observed for chlorophylls was observed for the levels of total porphyrins. Interestingly, a negative correlation ( r = -0.67) was observed between absolute MDA levels and porphyrin content, highlighting the impact of oxidative stress in FDp-infected grapevine on the reduction in levels of porphyrins. Carotenoids (both total and individual) content also exhibited the same trend, with M38 genotype impacting carotenoids more severely and the lowest content recorded at the second time point for both M38- and M54-infected leaves, when the highest FDp titre was detected. Furthermore, ratio chlorophylls/carotenoids was reduced in FDp-infected leaves. However, no linear correlation between relative values of photosynthetic parameters and relative FDp DNA abundance was observed (Supplementary material 1), despite the obvious association between the dynamics patterns of those parameters. The reason behind this is that in M54-infected leaves, which had higher FDp DNA abundance, lower reduction of photosynthetic parameters was observed, and vice versa for M38-infected leaves, which prevented the establishment of a linear correlation. Therefore, separate correlation analyses were performed correlating the FDp DNA abundance with photosynthetic parameters for leaves infected with two separate genotypes independently (Supplementary material 3). Those results established a high positive correlation between the dynamics of all photosynthetic parameters and FDp DNA abundance. This indicates that dynamics of photosynthetic pigments in FDp-infected leaves is highly dependent of phytoplasma titre. However, there is an evident role of the FDp-genotype in the severity of the impact on photosynthetic parameters. Results point that M54 causes less severe changes in infected grapevine than M38 on the level of photosynthetic pigments. Considering that M54 caused a lower accumulation of SS than M38, and had a lower impact on photosynthetic pigments, because the reduction of pigments is caused by a metabolic inhibition loop, lower increase of SS potentially caused lower reduction of pigments in M54-infected grapevine. All photosynthetic pigment parameters mutually correlated, signifying that repression of their synthesis in FDp-infected leaves is probably trackable to the genes involved in the biosynthesis of mutual precursors of both chlorophylls and carotenoids, early in the isoprenoid biosynthetic pathway. Previous findings combining metabolomic and expression data (Teixeira et al. 2020 ) also point to a general repression of isoprenoid biosynthetic pathway, by the downregulation of key genes. However, further studies should focus on investigating the exact mechanism of FDp impact on photosynthetic pigments and take into consideration the impact of different FDp genotypes. 3. 6. Chemometric analyses Principal component analysis (PCA) and hierarchical clustering were used to establish the interrelationship between groups based on tested physiological parameters (Fig. 4 ). Unsurprisingly, PCA revealed a clear separation of uninfected leaves based on the evaluated physiological parameters according to the principal component 1 (PC1). Photosynthetic pigments highly attributed to the separation of uninfected leaves from the infected (Fig. 4 b), presumably because of the high impact of FDp on their content in infected leaves. Based on PC1, M54-infected leaves positioned more closely to the uninfected leaves, than M38-infected leaves at the June time point, pointing to the lower impact of M54 at the beginning of the vegetative season based on the level of tested parameters. AA levels attributed to the grouping of June-positive groups together with Sep-M54, presumably due to the highest AA levels observed at this time points. Results were also confirmed by the hierarchical clustering of the groups presented along with the heatmap based on the tested parameters (Fig. 4 c). At the August time point, both M54- and M38-infected leaves grouped together based on both PC1 and PC2. However, at the September time point, M54- and M38-infected leaves clearly separated from each other, with M54-infected leaves remaining close to its position at the August time point, while M38-infected leaves separated more severely from its August time point. Both PCA and hierarchical clustering results significantly point to the lower impact of M54 infection on assessed grapevine physiological parameters. Particularly interesting is the high M38 impact at the end of the vegetative season considering the clear separation of this group, while the M54-induced changes to the parameters appear to be less-severely modified at the latest analysed time point. This could possibly be linked to the higher drop in FDp titre in M54-infected leaves, than in M38-infected leaves. 4. Conclusions Altogether, M54 genotype caused lower accumulation of SS, lower reduction of photosynthetic pigments and lower oxidative damage, all while maintaining higher titre than M38. By doing this, M54 potentially causes less negative effects on assessed grapevine physiological parameters, what potentially enabled it to replicate in a higher capacity. This is unusual because morphologically, M54 caused more severe symptoms in terms of damage to grapevine, suggesting that assessed physiological parameters cannot be correlated with actual disease symptoms. M54-infected grapevine leaves physiology was modified less severely than by M38, potentially because M54 has a mechanism by which main grapevine physiological processes remain relatively preserved. Phytoplasma genotype-dependent changes in grapevine physiology, potentially caused by the differences between M54 and M38 on the level of the efficiency of their effectors should be further investigated in order to better understand pathogenicity mechanisms of FDp and manage the FD spread in the future. Furthermore, no previous study inferred the correlations between phytoplasma titre and observed changes to grapevine physiology. Mainly, FDp abundance correlated with H 2 O 2 , SS, proline and photosynthetic pigments, pointing that phytoplasma replication dynamics clearly affects main physiological processes in grapevine leaves. Roggia et al. ( 2014 ) were unable to correlate FDp titre with grapevine symptom severity. However, measuring grapevine biochemical parameters as a valuable indicators of stress conditions in FDp-infected grapevine could establish the link between FDp titre and symptom severity in future studies. Based on the observed interrelationship between tested physiological parameters, novel conclusions could be drawn and further investigated (Fig. 3 c). Particularly, of notice is potential phytoplasma-induced upregulation of AA and potentially biosynthesis of other antioxidants, in order to quench plant-derived ROS that have an effect on phytoplasma replication, as well as the established link between the impact on SS and photosynthetic pigments and FDp abundance. Results once again showcased a high versatility of phytoplasmas, offering for the first time a glimpse into the variable effect of different genotypes on host physiology, and open new questions and challenges to be tackled in future studies of these plant pathogens. Abbreviations Ca . Candidatus Car carotenoids Chl chlorophylls Ct cycle threshold value DW dry weight FDp flavescence dorée phytoplasma GY grapevine yellows diseases (incl. flavescence dorée and bois noir ) L-Asc AA L -ascorbic acid (vitamin C) MDA malondialdehyde PAMP pathogen-associated molecular patterns PCA principal component analysis Por porphyrins ROS reactive oxygen species RP-HPLC reversed-phase high-performance liquid chromatography RT room temperature SS soluble sugars Declarations Ethical Approval Not applicable. This article does not contain any studies with human or animal subjects performed by any of the authors. Competing interests The authors have no relevant financial or non-financial interests to disclose. Author contributions DD : Conceptualization, Methodology, Investigation, Formal Analysis, Data Curation, Validation, Writing – Original Draft, Writing – Review & Editing. IŠ : Resources, Methodology, Writing – Review & Editing. M ŠM : Conceptualization, Methodology, Investigation, Writing – Review & Editing, Validation, Resources, Funding Acquisition, Supervision. All authors have read and agreed to the published version of the manuscript. Funding This study was funded by the University of Zagreb and partially supported by Croatian Science Foundation grant no. IP-2019-04-2469. Availability of data and materials All data generated or analysed during this study are included in this published article and its supplementary information files. Acknowledgement The authors with to thank Barbara Novotni for the technical assistance and help with the extractions for the analyses of physiological parameters and Goran Ivančan for the help with grapevine sampling. References Abbà S, Galetto L, Carle P, Carrère S, Delledonne M, Foissac X et al (2014) RNA-Seq profile of flavescence dorée phytoplasma in grapevine. 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Pearson’s correlation coefficients ( r ) between the absolute and relative values of tested parameters. Statistically significant correlations (p ≤ 0.05) are marked in bold. Supplementarymaterial2.docx Supplementary Material 2. Relative content of (A) chlorophyll a , (B) chlorophyll b , (C) total chlorophyll, (D) ratio chlorophyll a/b , (E) content of porphyrins, (F) total carotenoids, (G) β -carotene, (H) lycopene and (I) ratio carotenoids/chlorophylls of M38- and M54-infected grapevine leaves at three time points, in relation to the corresponding controls. Values are ratios and represent mean ± standard deviation of three replicates with three technical replicates each. Different letters indicate a significant difference between different time points for the corresponding samples (ANOVA, Duncan test, p ≤ 0.05). Supplementarymaterial3.docx Supplementary Material 3. Pearson’s correlation coefficients ( r ) between relative values of photosynthetic parameters and relative FDp DNA abundance calculated separately for (A) M38-infected leaves and (B) M54-infected leaves. Statistically significant correlations (p ≤ 0.05) are marked in bold. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revisions 26 Oct, 2023 Reviewers agreed at journal 06 Sep, 2023 Reviewers invited by journal 04 Sep, 2023 Editor invited by journal 17 Aug, 2023 Editor assigned by journal 10 Aug, 2023 First submitted to journal 09 Aug, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3231755","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":230771113,"identity":"6f68a41c-dc3a-4ee9-9828-c03c11c89d96","order_by":0,"name":"Dino DAVOSIR","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dino","middleName":"","lastName":"DAVOSIR","suffix":""},{"id":230771114,"identity":"e69fc6fb-e5fd-41eb-9ccb-72232ee7a311","order_by":1,"name":"Ivana ŠOLA","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ivana","middleName":"","lastName":"ŠOLA","suffix":""},{"id":230771115,"identity":"c90c581d-306a-4d71-85d3-a58c3c6398eb","order_by":2,"name":"Martina Seruga Music","email":"data:image/png;base64,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","orcid":"","institution":"University of Zagreb, Faculty of Science","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Martina","middleName":"Seruga","lastName":"Music","suffix":""}],"badges":[],"createdAt":"2023-08-03 14:35:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3231755/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3231755/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":42826981,"identity":"b10acd87-7130-4fad-a4db-55533d32e673","added_by":"auto","created_at":"2023-09-08 13:30:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":61260,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Unrooted phylogenetic tree depicting the phylogenetic relationship between isolates (1-2) and reference sequences, inferred by neighbour-joining analysis (model number of differences) with bootstrap values obtained after 500 repeats. Affiliation to the map genotypes and clusters is shown to the right of the tree. mapFD1, mapFD2, mapFD3 = FD clusters; M38, M54, M122, M50, M51 = genotypes. Designations on reference strains indicate accession numbers from the NCBI database. (b) Relative phytoplasma DNA abundance (titre) determined from cycle threshold (Ct) values for FD-positive samples at three time points during the development of infection. Values represent mean of two replicates.\u003c/p\u003e","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/f1602daf0316a6ed3a9b6047.png"},{"id":42829429,"identity":"d5cfc2aa-b563-4b93-bc57-57222269ecdc","added_by":"auto","created_at":"2023-09-08 13:46:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":147987,"visible":true,"origin":"","legend":"\u003cp\u003eOxidative stress parameters in FDp-infected grapevines. Level of lipid peroxidation expressed as MDA (malondialdehyde) content (a), content of L-ascorbic acid (c), soluble sugars (e), proline (g) and hydrogen peroxide (H2O2) (i) in M38-infected, M54-infected, and uninfected grapevine leaves at three time points during the development of infection. Values represent mean ± standard deviation of three replicates with three technical replicates each. Different letters indicate a significant difference between the samples at a corresponding time point (ANOVA, Duncan test, p ≤ 0.05). DW = dry weight. On the right, relative content of (b) MDA, L-ascorbic acid (d), (f) soluble sugars, (h) proline and (j) H2O2 of M38- and M54-infected grapevine leaves at three time points, in relation to the corresponding controls. Values are ratios and represent mean ± standard deviation of three replicates with three technical replicates each. Different letters indicate a significant difference between different time points for the corresponding samples (ANOVA, Duncan test, p ≤ 0.05)\u003c/p\u003e","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/8183e9e1c7e00ed83b456bf3.png"},{"id":42828179,"identity":"e435949a-f7ab-43ba-a05e-904d1e572dbf","added_by":"auto","created_at":"2023-09-08 13:38:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":438754,"visible":true,"origin":"","legend":"\u003cp\u003ePearson’s correlations between (a) absolute and (b) relative values of physiological parameters. Statistically significant correlations (p ≤ 0.05) are marked. Exact coefficients obtained from correlation analyses are provided in the Supplementary material 1. (c) Schematic representation of hypothesised interrelationship between physiological parameters in FDp-infected grapevine based on the obtained data. Purple arrows describe FDp-induced changes to grapevine physiology; green arrows describe plant defence responses. The potential role of some FDp effectors on increase of antioxidants synthesis is marked with a question mark. ROS = reactive oxygen species, SOD = superoxide dismutase\u003c/p\u003e","description":"","filename":"OnlineFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/91558e397afcfaabfd0d0cf1.png"},{"id":42828181,"identity":"bcafb220-94a9-488f-be5e-6fd1fa5e7ce1","added_by":"auto","created_at":"2023-09-08 13:38:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":163921,"visible":true,"origin":"","legend":"\u003cp\u003eResults of chemometric analyses. Principal component analysis (PCA) based on the assessed physiological parameters: hydrogen peroxide (H2O2), soluble sugars (SS), proline (Pro), malondialdehyde (MDA), L-ascorbic acid (L-Asc) content and the content of photosynthetic pigments: total chlorophyll (Chl), chlorophyll a (Chl a), chlorophyll b (Chl b), ratio chlorophyll a/b (Chl a/b), porphyrins (Por), total carotenoids (Car), β-carotene (β-Car) and Lyc (lycopene). (a) Score plot separating the samples based on the measured parameters), and (b) loading plot of the measured parameters. June, Aug, Sep = June, August and September time points, respectively. M38 = M38-infected leaves, M54 = M54-infected leaves, neg = uninfected leaves. (c) Heatmap displaying the relationship between tested physiological parameters, with hierarchical clustering based on Euclidian distance applied to visualize the relationship between samples\u003c/p\u003e","description":"","filename":"OnlineFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/561abd48ab1eeba8dd0aa1b6.png"},{"id":42829430,"identity":"c8bfd2c8-968d-4d9d-b5c4-04fbea16ac36","added_by":"auto","created_at":"2023-09-08 13:46:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1100954,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/7c9f9a5c-e7c8-4c7e-bee3-425fc9f7a3d6.pdf"},{"id":42826982,"identity":"c77ac9b6-bdeb-4299-878c-c41c09930175","added_by":"auto","created_at":"2023-09-08 13:30:05","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10789,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Impact of FDp-infection on grapevine photosynthetic pigments. Content of total chlorophylls, chlorophyll a and b, ratio chlorophyll a/b, content of total porphyrins, total carotenoids, β-carotene, lycopene and ratio carotenoids/chlorophylls in M38-infected, M54-infected, and uninfected grapevine leaves at three time points during the development of infection.\u003c/p\u003e","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/e7d23dd6c812f83a3d2fa3fa.xlsx"},{"id":42828183,"identity":"674de672-0667-4ef3-a33f-18cfcc59c2fc","added_by":"auto","created_at":"2023-09-08 13:38:06","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":11860,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Material 1. \u003c/strong\u003ePearson’s correlation coefficients (\u003cem\u003er\u003c/em\u003e) between the absolute and relative values of tested parameters. Statistically significant correlations (p ≤ 0.05) are marked in bold.\u003c/p\u003e","description":"","filename":"Supplementarymaterial1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/2151a0558037769e6cd1bd98.xlsx"},{"id":42826985,"identity":"b357add3-aae1-46a6-a50e-8a518dcfdcca","added_by":"auto","created_at":"2023-09-08 13:30:05","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":121034,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Material 2. \u003c/strong\u003eRelative content of (A) chlorophyll \u003cem\u003ea\u003c/em\u003e, (B) chlorophyll \u003cem\u003eb\u003c/em\u003e, (C) total chlorophyll, (D) ratio chlorophyll \u003cem\u003ea/b\u003c/em\u003e, (E) content of porphyrins, (F) total carotenoids, (G) \u003cem\u003eβ\u003c/em\u003e-carotene, (H) lycopene and (I) ratio carotenoids/chlorophylls of M38- and M54-infected grapevine leaves at three time points, in relation to the corresponding controls. Values are ratios and represent mean ± standard deviation of three replicates with three technical replicates each. Different letters indicate a significant difference between different time points for the corresponding samples (ANOVA, Duncan test, p ≤ 0.05).\u003c/p\u003e","description":"","filename":"Supplementarymaterial2.docx","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/b3a546b163f70a5d499fe98b.docx"},{"id":42829428,"identity":"f71fede8-d14a-4a6c-bafd-979a1c748de2","added_by":"auto","created_at":"2023-09-08 13:46:05","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":16030,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Material 3. \u003c/strong\u003ePearson’s correlation coefficients (\u003cem\u003er\u003c/em\u003e) between relative values of photosynthetic parameters and relative FDp DNA abundance calculated separately for (A) M38-infected leaves and (B) M54-infected leaves. Statistically significant correlations (p ≤ 0.05) are marked in bold.\u003c/p\u003e","description":"","filename":"Supplementarymaterial3.docx","url":"https://assets-eu.researchsquare.com/files/rs-3231755/v1/ed4363b2a295cccb71c4c473.docx"}],"financialInterests":"","formattedTitle":"Physiological responses of grapevine (Vitis vinifera var. ‘Pinot gris’) affected by different flavescence dorée genotypes: Dynamics through the development of phytoplasma infection","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePhytoplasmas (genus \u0026lsquo;\u003cem\u003eCandidatus\u003c/em\u003e (\u003cem\u003eCa.\u003c/em\u003e) Phytoplasma\u0026rsquo;) are obligate intracellular parasitic bacteria constituting a large monophyletic group within the class Mollicutes, and pathogens of a wide variety of plants. Phytoplasmas are associated with causing diseases in a wide range of plants, including agriculturally important crops, as well as ornamental plants, timber and shade trees. The inability to routinely cultivate phytoplasmas in a pure culture \u003cem\u003ein vitro\u003c/em\u003e makes establishing the taxonomic status of phytoplasmas difficult, and also hampers establishing many research models (Namba \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Phytoplasmas are particularly interesting because despite severe genome reductions due to their parasitic lifestyle, a fair number of (putative) effectors have been recognised in genomes of various phytoplasmas by which they manipulate host physiology. Indeed, transcriptomic, proteomic and other studies of phytoplasma-infected plants confirm a high modification of their normal physiological processes upon phytoplasma infection. Most of the symptoms in phytoplasma-diseased plants are mirrored in specific alterations to gene expression and/or changed protein levels in comparison to uninfected plants. Several genes involved in photosynthesis are downregulated in phytoplasma-infected plants, paralleled by growing evidence that inhibition of photosynthesis is a result of carbohydrate accumulation in source leaves. Increase in concentration of carbohydrates is suggested to be a consequence of phytoplasma manipulation in host plants and severe changes to the expression of genes related to carbohydrate synthesis were observed in several phytoplasma-infected plants (Dermastia et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGrapevine \u003cem\u003eflavescence dor\u0026eacute;e\u003c/em\u003e phytoplasma (FDp; ribosomal group 16SrV) is associated with grapevine yellows diseases (GY). GY are independently caused by two taxonomically distant phytoplasmas, the other being \u0026lsquo;\u003cem\u003eCa\u003c/em\u003e. P. solani\u0026rsquo; (known as \u003cem\u003ebois noir\u003c/em\u003e phytoplasma, BNp; ribosomal group 16SrXII) (Angelini et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). They differ in symptom severity, as FDp is generally more aggressive (Prezelj et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, general symptoms of GY include yellowing or reddening of leaves (dependent of the variety), leaf rolling, shrivelled grapes and general plant decline. BNp is present in all viticultural areas worldwide and is mainly spread by the vector \u003cem\u003eHyalesthes obsoletus\u003c/em\u003e Signoret (Homoptera, Cixiidae). On the other hand, FDp is transmitted by the leafhopper vector \u003cem\u003eScaphoideus titanus\u003c/em\u003e Ball (Homoptera, Cicadellidae), and is spread in all main viticultural areas in Europe (Angelini et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), where it is a quarantine pathogen (EPPO Global Database \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Although FDp has been well characterized, a formal description of FDp as a new phytoplasma species remains to be published (Bertaccini and Lee \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The first complete genome of FDp (\u003cem\u003emap\u003c/em\u003e genotype M54) was recently published based on dual sequencing approach using both Illumina and Oxford Nanopore Technology. A total of 17 putative secreted proteins based on the presence of the signal peptide were detected. Based on that, these proteins could be potential pathogenicity factors (Debonneville et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Prior to the publishing of the complete genome sequence, many studies attempted to unravel the mechanisms of FDp pathogenicity by analysing the response of FDp-infected plants using proteomic (Margaria et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), transcriptomic (Abb\u0026agrave; et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Pacifico et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Teixeira et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and metabolomic (Ferrandino et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) approaches, or their combinations (Margaria et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Pagliarani et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Prezelj et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Particularly, role of hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) has been recognized in recovery against FDp (Gambino et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Musetti et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). A severe downregulation of genes involved in biosynthesis of photosynthetic pigments (Teixeira et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and an upregulation of phenolic metabolism (Prezelj et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) was observed in FDp-infected grapevine. Furthermore, varying response of different grapevine varieties to FDp infection was assessed (Pacifico et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Roggia et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, no previous study attempted to analyse the impact of different FDp genotypes on grapevine physiology and observe the changes in the seasonal dynamics of physiological responses through the vegetative season.\u003c/p\u003e \u003cp\u003eTherefore, in this study, we analysed the impact of FDp infection in grapevine leaves of variety \u0026lsquo;Pinot gris\u0026rsquo; at three time points during the vegetative season. Firstly, FDp was identified using a triplex real-time PCR assay, and the results were used for the relative quantification of FDp DNA. FDp from infected leaves was genotyped by amplification, sequencing and phylogenetic analysis of \u003cem\u003emap\u003c/em\u003e gene, conventionally used for the genotyping of FDp. Then, physiological status of infected leaves, as well as the uninfected controls, and potential oxidative stress conditions were assessed by spectrophotometric analyses of the level of lipid peroxidation, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content and proline content, as well as chromatographic analysis (RP-HPLC) of \u003cem\u003eL\u003c/em\u003e-ascorbic acid content. Because of the earlier reports on FDp impact on sugar metabolism, soluble sugars content in infected leaves was assessed. Furthermore, photosynthetic pigment content in grapevine leaves was analysed in samples considering the reported pronounced chlorosis symptoms in FDp-infected leaves to evaluate a potential FDp genotype-dependent effect. Finally, data was statistically analysed using PCA and hierarchical clustering. Correlation analysis was performed for the possible establishment of link between relative FDp DNA abundance and physiological parameters, as well as establishing the potential co-dependency of tested parameters in FDp-infected grapevine to aid the unravelling of FDp pathogenicity mechanisms.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\n\u003ch3\u003e2. 1. Sampling and plant material\u003c/h3\u003e\n\u003cp\u003eGrapevine (\u003cem\u003eVitis vinifera\u003c/em\u003e L. var. \u0026lsquo;Pinot gris\u0026rsquo;) leaves of symptomatic and asymptomatic plants were collected from a vineyard in central continental Croatia (Sveti Ivan Žabno, Koprivnica-Križevci County), which was previously under multi-year surveillance for presence of FD and BN phytoplasmas and a sampling location in previous studies (Plavec et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The vineyard was managed according to integrated pest and disease principles. The leaves of grapevine variety \u0026lsquo;Pinot gris\u0026rsquo; with symptoms of yellowing, leaves rolling and fruit drying were collected, as well as the leaves of asymptomatic plants. The leaves were taken randomly from same plants at three time points during the development of infection: at the end of June, at the end of August and at the end of September of 2021. Upon collecting, the samples were stored in a field refrigerator and in the laboratory, the leaves of similar size from the same plant were separated in three replicates for biochemical analyses, frozen under liquid nitrogen and stored at -80\u0026deg;C until freeze-drying. The plant material for biochemical analyses was freeze-dried using the Alpha 1\u0026ndash;2 lyophilizer (Martin Christ Gefriertrocknungsanlagen GmbH, Osterode am Harz, Germany) at -55\u0026deg;C and 0.05 mbar for approximately 32 h. Then, the material was grounded to fine powder in a mortar with pestle using liquid nitrogen and stored for later analyses. Each analysis was run in triplicate for each sample with three technical replicates.\u003c/p\u003e\n\u003ch3\u003e2. 2. Phytoplasma detection and identification\u003c/h3\u003e\n\u003cp\u003eA CTAB-based method for total nucleic acid extraction was used, according to the previously developed method (Seruga et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Nucleic acids were extracted from 250 mg of midribs isolated from grapevine leaves. To detect the causative agent of GY in grapevine samples, a triplex real-time PCR assay, which was developed by Pelletier et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) was performed for the 10x and 100x dilutions of nucleic acid extracts in duplicates. Amplification was performed using the TaqMan\u0026trade; Universal PCR Master Mix according to the manufacturer\u0026rsquo;s instructions using the reported primers and probes (Pelletier et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) as follows: 10 min at 95\u0026deg;C (1 cycle) followed by 45 cycles of 1 min at 94\u0026deg;C and 1.5 min at 59\u0026deg;C. Analyses were carried out using a 7300 Real Time PCR System (Applied Biosystems, Waltham, USA). To quantify the presence of phytoplasma DNA in the samples and compare the quantity of phytoplasma DNA at different analysed time points, cycle threshold (Ct) values from real-time PCR experiment were used as an indicator of relative amount of phytoplasma DNA in samples. All Ct values for FDp \u003cem\u003emap\u003c/em\u003e gene reporter were normalized to Ct values of corresponding \u003cem\u003eVitis\u003c/em\u003e sp. chloroplast \u003cem\u003etRNA\u003c/em\u003eL-F spacer reporter (endogenous control). Then, Ct/Ct\u003csub\u003econ\u003c/sub\u003e values were subtracted from 1 for simplification.\u003c/p\u003e \u003cp\u003eFor phytoplasma genotyping, nested PCR was used to amplify the phytoplasma \u003cem\u003emap\u003c/em\u003e gene fragment with primer pairs FD9f5/MAPr1 for direct and FD9f6/MAPr2 for nested PCR (Arnaud et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In PCR experiments, GoTaq Flexi DNA Polymerase (Promega) was used. Amplification of \u003cem\u003emap\u003c/em\u003e gene fragments was verified by agarose gel-electrophoresis. Amplified DNA fragments were Sanger sequenced in a commercial service (Genewiz, Leipzig, Germany). Sequencing of \u003cem\u003emap\u003c/em\u003e gene amplicons was performed using the primers used in the nested PCR (FD9f6/MAPr2). Obtained sequences were edited using the Geneious Prime software (Kearse et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). For phylogenetic analysis, sequence alignment was performed using ClustalX software (Thompson et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Phylogenetic analysis was performed in MEGA X (Kumar et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) using the neighbour-joining method with model No. of differences and bootstrap with 500 repeats. Reference \u003cem\u003emap\u003c/em\u003e gene sequences (LT221949, LT221933, LN850372, LT221945, LT221946) were obtained from NCBI database using the Nucleotide BLAST tool. In order to study the relatedness of detected genotypes, a phylogenetic tree based on concatenated sequences of \u003cem\u003emap\u003c/em\u003e was constructed.\u003c/p\u003e\n\u003ch3\u003e2. 3. Analysis of grapevine oxidative stress parameters\u003c/h3\u003e\n\u003cp\u003eSamples for the analyses of physiological parameters included three separate replicates of M38-infected leaves, M54-infected leaves and uninfected leaves at three time points during the development of infection, with each of three replicates for each of the three time points analysed in three technical replicates. For the estimation of the level of lipid peroxidation, determination of hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) content and proline content, 60 mg of each sample was homogenized in 1.5 mL of 0.1% (w/v) trichloroacetic acid (TCA) using a mortar and pestle. The homogenate was centrifuged at 15000 rpm and 4\u0026deg;C for 15 min, and the supernatant was used for the determination of lipid peroxidation according to the method in Linić et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) with some modifications. Briefly, 100 \u0026micro;L of each extract was mixed with 600 \u0026micro;L of 0.5% thiobarbituric acid (TBA) in 20% TCA and the mixture was homogenized and incubated for 30 min at 95\u0026deg;C. Every sample had a separate blank without TBA to minimize the absorbance of other compounds present in the extract. After the incubation, the reaction was stopped by placing the tubes on ice for 10 min. The mixture was centrifuged at 12000 rpm and 4\u0026deg;C for 5 min. After the incubation, colour intensity was quantified by measuring the absorbance at 532 and 600 nm. MDA content in the samples was calculated based on the molar extinction coefficient of 155 mM\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and expressed as ng of MDA per g of dry weight (DW).\u003c/p\u003e \u003cp\u003eH\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content in grapevine leaves was determined as described in (Junglee et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Supernatant (250 \u0026micro;L) was mixed with the same volume of potassium phosphate buffer (pH 7.0) and 500 \u0026micro;L of 1 M potassium iodide and the mixture was homogenized. Then, colour intensity was quantified by measuring the absorbance at 390 nm. Content of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e was calculated indirectly based on the calibration curve of standard H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e solutions of known concentrations. The results were expressed as \u0026micro;mol of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e per g of DW.\u003c/p\u003e \u003cp\u003eProline content in grapevine leaves was evaluated with a method optimized from Ljubej et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Supernatant (60 \u0026micro;L) was mixed with 600 \u0026micro;L of ninhydrin reagent (1% ninhydrin, 60% acetic acid, 20% ethanol) and the mixture was homogenized and incubated for 20 min at 95\u0026deg;C. Every sample had a separate blank to minimize the absorbance of other compounds present in the extract. After the incubation, colour intensity was quantified by measuring the absorbance at 520 nm. Proline content in the samples was calculated indirectly based on the calibration curve of standard \u003cem\u003eL\u003c/em\u003e-proline solutions of known concentrations. The results were expressed as mg of \u003cem\u003eL\u003c/em\u003e-proline per g of DW.\u003c/p\u003e \u003cp\u003eFor the analysis of soluble sugars, extracts were prepared in 70% ethanol as described (Davosir and Šola \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and their content was evaluated using the method adapted from Dubois et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1956\u003c/span\u003e). Volume of 200 \u0026micro;L of each extract diluted to 1 mg DW/mL and was mixed with 100 \u0026micro;L of 5% phenol (v/v) and 500 \u0026micro;L of concentrated H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e. Then, samples were homogenized and incubated for 10 min at RT after which the samples were incubated for 10 min in a water bath at 30\u0026deg;C. After the incubation, colour intensity was quantified by measuring the absorbance at 485 nm. Soluble sugar content in the samples was calculated indirectly as mg of sucrose equivalents (SE) per g of DW based on the calibration curve of standard sucrose solutions of known concentrations.\u003c/p\u003e\n\u003cdiv class=\"Heading\"\u003e\u003cem\u003e2. 4. RP-HPLC analysis of L\u003c/em\u003e-\u003cem\u003eascorbic acid content\u003c/em\u003e\u003c/div\u003e \u003cp\u003eFor quantitative analysis of \u003cem\u003eL\u003c/em\u003e-ascorbic acid from grapevine leaves extracts prepared in 70% ethanol as for the SS measurement, analysis was carried out using the reversed-phase high-performance liquid chromatography (RP-HPLC). Acidic hydrolysis was carried out prior to the analysis with 1.2 M HCl by incubating the extracts for 2 h at 80\u0026deg;C and 300 rpm. The RP-HPLC analyses were performed using a previously reported and validated method (Šola et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The analysis of \u003cem\u003eL\u003c/em\u003e-ascorbic acid was carried out at 254 nm and \u003cem\u003eL\u003c/em\u003e-ascorbic acid was identified based on the comparison with the retention time and UV-spectrum of a commercial standard. For the quantitative analyses, external standard was used, and calibration curve was obtained by injecting the known concentrations (0.25\u0026thinsp;\u0026minus;\u0026thinsp;0.01 mg/mL) of standard solutions. The results were expressed as mg/g DW.\u003c/p\u003e\n\u003ch3\u003e2. 5. Determination of grapevine photosynthetic pigments\u003c/h3\u003e\n\u003cp\u003eFor the spectrophotometric determination of the photosynthetic pigment content, method according to Sumanta et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) was used. For this purpose, extracts of photosynthetic pigments were prepared from lyophilized powdered plant tissue using the 80% acetone (v/v) as a solvent. Mass of 15 mg of each sample was mixed with 1 mL of 80% acetone and the solution was mixed for 20 sec. Then, the mixture was centrifuged at 13 000 rpm and 4\u0026deg;C for 5 min, after which the supernatant was transferred to a new tube on ice and the extraction was carried out once again following the same procedure, until the plant material became white. Absorbance of the extracts was monitored at 453, 470, 505, 575, 590, 682, 647 and 663 nm. The content of chlorophyll \u003cem\u003ea\u003c/em\u003e and chlorophyll \u003cem\u003eb\u003c/em\u003e, total carotenoids, \u003cem\u003eβ\u003c/em\u003e-carotene, lycopene, and porphyrins was determined from the previously reported equations (Sumanta et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003e2. 6. Statistical analysis\u003c/h3\u003e\n\u003cp\u003eStatistical analyses were conducted in Statistica 13.1 (Stat Soft Inc., USA). Analysis of statistically significant differences between the samples was carried out using one-way analysis of variance (ANOVA) and \u003cem\u003epost-hoc\u003c/em\u003e Duncan\u0026rsquo;s Multiple Range Test. Statistically significant differences between the samples at p\u0026thinsp;\u0026le;\u0026thinsp;0.05 were marked with different letters. To compare the dynamics of tested parameters during the development of infection, values were normalized to the values of corresponding uninfected controls to eliminate the effect of seasonal dynamics of tested parameters, and the values from different time points for the same sample were compared. Pearson\u0026rsquo;s correlation coefficients (\u003cem\u003er\u003c/em\u003e) were calculated between the absolute values of tested parameters, with statistical significance at p\u0026thinsp;\u0026le;\u0026thinsp;0.05. To calculate Pearson\u0026rsquo;s correlation coefficients between the relative FDp DNA abundance and tested parameters, relative values of tested parameters (compared to control) were used for analysis. Principal component analysis (PCA) and hierarchical clustering analysis based on Euclidian distance were performed to establish the relationship between samples based on tested physiological parameters.\u003c/p\u003e"},{"header":"3. Results and Discussion","content":"\u003cp\u003ePhytoplasmas cannot be cultivated in a pure culture \u003cem\u003ein vitro\u003c/em\u003e and sustaining the phytoplasma infection sometimes appears difficult, as previously shown in \u003cem\u003ein vitro\u003c/em\u003e grown grapevine (Eveillard et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, studies dealing with investigation of interactions between grapevine and FDp remain almost exclusively based on sampling and analysis of field-grown plants (Abb\u0026agrave; et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Gambino et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Margaria et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Prezelj et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Roggia et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Initially, it was believed that changes to host physiology are an indirect response to the infection; however, more recent studies revealed that phytoplasma genomes possess a wide variety of effector molecules which enable them to directly modulate host physiology (Tomkins et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although whole genomes of some phytoplasmas are extensively studied and many of their effectors recognized, for example for \u0026lsquo;\u003cem\u003eCa.\u003c/em\u003e P. solani\u0026rsquo; (Šeruga Musić et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), detailed whole genome analyses of FDp and functional analyses of putative effectors still await. Although there are some disadvantages of this approach, studying the physiological responses of field-infected grapevine could give an insight into potential targets of FDp effectors, and assist the identification of potential effectors of this phytoplasma. By combining the molecular identification with assessing the impact on grapevine physiology, this study will contribute to unravelling the mechanisms of FDp pathogenicity. Furthermore, to our knowledge, no previous study attempted to investigate the impact of different FDp strains, based on the phylogenetic relationship between relevant genes used in genotyping, on specific targets in grapevine physiology and correlate it with potential differences in pathogenicity.\u003c/p\u003e\n\u003ch3\u003e3. 1. Indications for the epidemiology of FDp\u003c/h3\u003e\n\u003cp\u003eFDp was detected in all symptomatic leaves at all three sampling time points. Phylogenetic analysis of \u003cem\u003emap\u003c/em\u003e gene amplicons revealed that all the FDp-positive samples were infected by the FD genotypes belonging to the mapFD2 genetic cluster (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). This is unsurprising, considering previous studies revealed that isolates belonging to the mapFD2 cluster were predominant in Croatian vineyards (Plavec et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, two different genotypes within the mapFD2 cluster were detected, M38 and M54. Identified FDp isolates within the mapFD2 genetic cluster comprise two genotypes with \u003cem\u003emap\u003c/em\u003e sequences 100% identical to sequences classified as genotypes M38 and M54. The same study (Plavec et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) discussed that M54 genotype within mapFD2 cluster could be the prevalent one in Croatian vineyards and its highly efficient transmission by the vector \u003cem\u003eS. titanus\u003c/em\u003e was hypothesised. This genotype was identified as responsible for heavy damage to the viticultural production in Istria region of Croatia (Plavec et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Prevalence of this genotype was also observed in Italian (Rossi et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and French vineyards, where this genotype represented 85% of all FD cases in 2000s (Malembic-Maher et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Present study revealed higher relative FDp DNA abundance in M54-infected grapevine, than in M38-infected grapevine, pointing to a higher phytoplasma titre (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). This could be linked to higher replicative potential of this genotype within grapevine plants and potentially, easier acquisition by the vector, leading to its higher geographic distribution. Indeed, Galetto et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) confirmed that acquisition capability of the FDp by the vector \u003cem\u003eS. titanus\u003c/em\u003e correlates with phytoplasma titre in the source plant. Therefore, ability to attain higher titre in infected grapevine could be a potential reason for the higher geographic distribution of M54 genotype. Relative FDp DNA abundance was quantified using a real-time PCR assay (Pelletier et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) through the development of infection at three time points for each identified FDp genotype. The trend of FDp DNA between different time points was similar for samples of both genotypes. As expected, for both M38- and M54-infected samples, the lowest DNA abundance was observed at the first time point in June, earlier in the vegetative season. The peak in FDp DNA abundance was in late summer (August time point) for both M38- and M54-infected samples. A lower DNA abundance at the third time point compared to the August time point was more pronounced in M54-infected grapevine, with a somewhat lower reduction of FDp DNA abundance in M38-infected grapevine. This dynamics is in agreement with the previous results for the FDp titre in field grown grapevine through the vegetative season (Roggia et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), reflecting the similar and conserved seasonal dynamics of FDp replication in grapevine. Interestingly, more effective phytoplasma acquisition by mature \u003cem\u003eS. titanus\u003c/em\u003e was observed, rather than \u003cem\u003eS. titanus\u003c/em\u003e larvae. Considering that \u003cem\u003eS. titanus\u003c/em\u003e matures in July/August (Chuche and Thi\u0026eacute;ry \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), the highest phytoplasma titre in grapevine at this time point could be the phytoplasma mechanism to maximize the rate of transmission to mature potential vectors who can acquire the phytoplasma more effectively than larvae.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003e3. 2. Oxidative stress conditions affected by FDp genotypes\u003c/h3\u003e\n\u003cp\u003eBoth M54- and M38-infected grapevine had characteristic GY symptoms at the first time-point: yellowing, leaf rolling and fruit drying. Morphologically, no difference in disease severity could be observed. However, at the second, and third time point particularly, stronger disease symptoms were observed in M54-infected grapevine. Malondialdehyde (MDA) content, an indicator of the level of membrane lipid peroxidation, is an often-used biomarker of stress conditions in plants, due to the susceptibility of membranes to ROS-induced damage (Hodges et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Enhanced ROS synthesis is a common defence mechanism against plant pathogens. This increase in ROS synthesis often leads to oxidative stress in infected plants (Suman et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The level of lipid peroxidation was higher in infected plants at all three time points in comparison to the corresponding controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Increased level of lipid peroxidation was previously reported in phytoplasma-infected plants, compared to the uninfected plants (Kiprovski et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mitrovic et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). At the first and second time point, MDA content was the highest in M38-infected leaves. However, at the third time point, the MDA content was the highest in M54-infected leaves. Considering that FDp DNA abundance was higher in M54-infected leaves, higher level of lipid peroxidation was expected in these leaves as a result of the oxidative burst. However, it is known that FDp genomes possess superoxide dismutase (\u003cem\u003esod\u003c/em\u003e) gene (Carle et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), encoding an antioxidative enzyme responsible for quenching superoxide radicals. This potential phytoplasma-mediated suppression of plant-derived ROS could have led to the lower level of lipid peroxidation in grapevine leaves infected with higher phytoplasma titre at the first and second time points, as a mechanism for the protection from plant-derived oxidative burst. Only at the third time point, in which relative FDp DNA abundance in M54-infected leaves dropped more severely (which could have led to a more drastic drop in FDp SOD activity) than in M38-infected leaves, was the level of lipid peroxidation higher in M54- than in M38-infected leaves, corroborating this hypothesis. Also, phytoplasma effectors could potentially manipulate the induction of synthesis of antioxidative compounds (for example, phenolics) in plants to quench protective ROS, as proposed previously (Prezelj et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Interestingly, absolute MDA content positively correlated with the \u003cem\u003eL\u003c/em\u003e-ascorbic acid (AA) content (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.69), as did their relative content (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.74) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary material 1). Considering that the AA (vitamin C) is a strong antioxidant, its synthesis could be induced upon oxidative damage caused by the oxidative burst, thus establishing a link between the MDA and AA content. Indeed, AA levels were higher in infected leaves at all three time points (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Based on the metabolite and the expression of genes involved in AA biosynthesis, Xue et al. (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) also recognised the involvement of AA in phytoplasma-infected plants. Indirect role of AA in plants battling biotic stress and its induction as a response to the oxidative burst have been reviewed (Khan et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), suggesting to it being a general response mechanism in plant-pathogen interactions, not specific to the phytoplasma infection. For M38-infected leaves, the highest AA concentration in comparison to the controls was at the second time point, and the lowest at the first time point. Likewise, in M54-infected leaves the lowest concentration was at the first time point, however, the highest was at the third time point (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Also, similarly to the MDA content, AA content was higher in M38-infected leaves at the first and second time points. However, at the third time point, AA content was also the highest in M54-infected leaves. This further supports the hypothesis that the mechanisms of induced ROS synthesis against FDp invasion are followed by responses to minimize oxidative damage by inducing the synthesis of antioxidants such as AA. Activation of responses to minimize oxidative damage could either be phytoplasma-induced, plant-induced (to minimize damage to its cells) or a combination of both and should be a subject of further studies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003e3. 3. Osmolyte accumulation in FDp-infected grapevine\u003c/h3\u003e\n\u003cp\u003eBoth proline and sugars, which often accumulate in plants as a response to abiotic and biotic stressors, are reliable biomarkers of stress conditions in plants (Jeandet et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liang et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Sharma et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Soluble sugars (SS) content at all three time points followed the same trend, being the highest in M38-infected leaves, and lowest in uninfected leaves (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Because phytoplasmas colonize phloem tissues in infected leaves, this causes the physical obstruction of transport of sugars due to callose deposition in phloem cell walls, leading to elevated sugar levels in leaves (Musetti et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Furthermore, a substantial upregulation of genes involved in sugar biosynthesis was observed in FDp-infected leaves (Prezelj et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, it is still unknown whether this is induced by FDp effectors or is a more of an unspecific response of grapevine to the infection. Nevertheless, this sugar-rich environment creates a perfect setting for FDp replication, due to its metabolism, which is strictly oriented to glycolysis (Carle et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Interestingly, a negative correlation was observed between relative SS content and FDp phytoplasma DNA abundance (\u003cem\u003er\u003c/em\u003e = -0.90) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, Supplementary material 1). Particularly, lower SS content was recorded in M54-infected leaves, which had higher FDp DNA abundance. This could potentially be due to the M54 genotype having a less severe impact on sugar metabolism in infected grapevine than the M38 genotype. Also, the higher titre of M54 genotype could cause higher usage of leaf sugars by phytoplasmas, lowering the total SS in M54-infected leaves compared to M38-infected leaves. The same dynamics of relative SS content was observed for both genotypes, with the highest being at the first time point (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). Similarly, Negro et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reported lower relative SS in September than July in BNp-infected grapevine. This could be due to the lower photosynthetic capacity of infected grapevine at later time points, resulting in lower relative SS content (Rasool et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilarly to SS, upregulation of proline biosynthesis was also previously reported in phytoplasma-infected American cranberries (Pradit et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), as well as in phytoplasma-infected sweet orange (Rasool et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). At all three time points, proline content was the highest in M54-infected leaves (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg). Levels in M38-infected leaves were higher than the control only at the second time point. Proline acts as a protective molecule in plants during various stress conditions acting as an osmolyte, but also by being involved in the stabilization of proteins, direct scavenging of ROS and promoting downstream cellular signalling pathways related to plant defence mechanisms (Liang et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Its relative content positively correlated (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.85) with relative FDp DNA abundance (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, Supplementary material 1). This points that proline accumulation is a protective response mechanism against FDp infection. Although it appears to be a direct response mechanism and it is being affected by phytoplasma titre, the hypothesis is that this response is not a part of the PAMP-triggered immunity. Rather, our hypothesis is that proline accumulation is a response to FDp-induced symptoms in infected grapevine leaves, due to its general and fundamental role in stress response (Liang et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). But, contrary to SS, at all three time points, proline content was higher in M54-infected leaves than M38-infected leaves. It was previously discussed that proline could be associated with avirulent pathogen recognition (Zeier \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Potentially, higher proline content in M54-infected leaves could be linked to previously observed lower effect of the M54 genotype on SS and MDA levels. Therefore, proline levels reflect the FDp abundance in infected leaves better than the previously assessed parameters. Even though proline and soluble sugars both primarily act as osmolytes and have a synergistic effect in battling various abiotic stresses (Suprasanna et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), their dynamics in FDp-infected grapevine was dramatically different. This could possibly be due to the specific impact of FDp infection on sugar metabolism, which had a specific impact on grapevine SS content. Therefore, in this case, SS probably do not have a substantial protective role in battling FDp infection in grapevine. However, proline accumulation could possibly alleviate some symptoms of FDp-induced damage to grapevine. Nevertheless, both of those metabolites could be used as biomarkers of FDp infection.\u003c/p\u003e\n\u003ch3\u003e3. 4. Differential effect of FDp genotypes on HO production in grapevine\u003c/h3\u003e\n\u003cp\u003eRole of hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) in phytoplasma-infected plants and its potential involvement in recovery has been heavily discussed (Gambino et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Musetti et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Musetti et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) hypothesised that H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e appears to be involved in counteracting phytoplasma virulence. Indeed, higher content of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in infected leaves at the first time point in comparison to the uninfected leaves points to the protective role of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, especially active at the earlier stages of the infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ei). However, at the later time points, except in the M38-infected leaves at the third time point, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content was lower in infected leaves than uninfected leaves. Lower H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content in FDp-infected leaves in comparison to the uninfected grapevine leaves was previously observed (Gambino et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The same study recognised that overexpression of some H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e scavenging genes (\u003cem\u003eAPX2\u003c/em\u003e, \u003cem\u003ePOX4\u003c/em\u003e, \u003cem\u003ePOX5\u003c/em\u003e) reduced the quantity of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. Similarly, a recent study also confirmed that symptomatic FDp-infected leaves of grapevine cultivar \u0026lsquo;Tocai friulano\u0026rsquo; also accumulate less H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, accompanied by the upregulation of some H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e scavenging-related genes (Casarin et al. 2023). Our hypothesis is that this overexpression could potentially be mediated by certain FDp effectors. This is supported by a negative correlation (\u003cem\u003er\u003c/em\u003e = -0.86) between relative FDp DNA abundance and relative H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content. Therefore, higher FDp DNA abundance (i.e., phytoplasma abundance in infected leaves) caused the higher reduction in H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e synthesis, potentially mediated by some FDp effector molecules inducing the overexpression of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e scavenging genes at later stages of the infection. This mechanism reduces the oxidative damage to FDp and enables higher level of FDp replication, supported by the fact that the more abundant M54 genotype caused the higher reduction of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content. Interestingly, in M38-infected leaves at the third time point, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e content was higher than the control and M54-infected leaves, pointing to the higher ability of \u0026lsquo;Pinot gris\u0026rsquo; leaves to overcome the proposed impact of M38 genotype, compared to its ability to battle the effect of potential M54 effectors.\u003c/p\u003e\n\u003ch3\u003e3. 5. Impact of FDp infection on photosynthetic pigments\u003c/h3\u003e\n\u003cp\u003eTotal chlorophyll content was the highest in uninfected leaves at all three time points during the development of infection, with M38-infected leaves having the lowest total chlorophyll content at all three time points (Table\u0026nbsp;1). Considering that the leaf chlorosis is a common symptom of FDp infection in many grapevine varieties (Teixeira et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), observed severe reduction in photosynthetic pigment content was expected. Even though initial studies argued that reduction of photosynthetic pigments could be linked to the increase in chlorophyllase activity in phytoplasma-infected grapevine (Bertamini and Nedunchezhian \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), more recent studies concluded that no increase in pigment degradation is evident. Rather, general decrease in influx of chlorophyll precursors causes this severe reduction in photosynthetic pigments (Teixeira et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Evidence point to leaf yellowing being a result of sugar accumulation in leaves infected by various phytoplasmas, leading to the metabolic feedback inhibition of photosynthesis, as previously reviewed (Dermastia et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It is accompanied by a downregulation of genes involved in both light- and dark-dependent reactions and other genes related to photosynthetic processes in FDp-infected grapevine (Prezelj et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In both M38 and M54-infected leaves, relative total chlorophyll content was the highest at the first time point (Supplementary material 2). In M38-infected leaves there was no statistically significant difference between relative chlorophyll content at the second and third time point. However, in M54-infected leaves, there was an increase in relative chlorophyll content at the third time point compared to the second time point. In fact, M54 had a lower impact on total chlorophyll content at all three time points. Potentially, M54 induced a higher accumulation of protective compounds by FDp effector proteins that protected photosynthetic pigments from UV-stress, which enabled an increase in their content. Similar dynamics was observed for chlorophyll \u003cem\u003ea\u003c/em\u003e and \u003cem\u003eb\u003c/em\u003e. For chlorophyll \u003cem\u003ea\u003c/em\u003e, there was also an increase in its content at the third time point in M38, as well as in M54-infected leaves. On the other hand, in M38-infected leaves, relative chlorophyll \u003cem\u003eb\u003c/em\u003e content dropped at the third time point, while in M54-leaves it increased. This opposite dynamics of chlorophyll \u003cem\u003ea\u003c/em\u003e and \u003cem\u003eb\u003c/em\u003e content at the third time point in M38-infected leaves probably lead to the total chlorophyll content being unchanged between second and third time points. Chlorophyll \u003cem\u003ea\u003c/em\u003e/\u003cem\u003eb\u003c/em\u003e ratio, however, had the same dynamics for M38- and M54-infected leaves, with it being reduced in infected leaves at all time points. This points to the higher impact of FDp infection on chlorophyll \u003cem\u003ea\u003c/em\u003e, than chlorophyll \u003cem\u003eb\u003c/em\u003e. Similarly, Teixeira et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) initially recorded a drop in chlorophyll \u003cem\u003ea\u003c/em\u003e, but not chlorophyll \u003cem\u003eb\u003c/em\u003e, pointing to its lower susceptibility to phytoplasma infection. Severe reduction in chlorophyll content of FDp-infected leaves causes inevitable reduction in photosynthetic performance. Importantly for agricultural production, this causes reduction in yield and drastic production losses in FDp-infected grapevine, as previously reported (Oliveira et al. 2020). Considering that chlorophylls are the major class of porphyrins, similar dynamics observed for chlorophylls was observed for the levels of total porphyrins. Interestingly, a negative correlation (\u003cem\u003er\u003c/em\u003e = -0.67) was observed between absolute MDA levels and porphyrin content, highlighting the impact of oxidative stress in FDp-infected grapevine on the reduction in levels of porphyrins. Carotenoids (both total and individual) content also exhibited the same trend, with M38 genotype impacting carotenoids more severely and the lowest content recorded at the second time point for both M38- and M54-infected leaves, when the highest FDp titre was detected. Furthermore, ratio chlorophylls/carotenoids was reduced in FDp-infected leaves.\u003c/p\u003e \u003cp\u003eHowever, no linear correlation between relative values of photosynthetic parameters and relative FDp DNA abundance was observed (Supplementary material 1), despite the obvious association between the dynamics patterns of those parameters. The reason behind this is that in M54-infected leaves, which had higher FDp DNA abundance, lower reduction of photosynthetic parameters was observed, and \u003cem\u003evice versa\u003c/em\u003e for M38-infected leaves, which prevented the establishment of a linear correlation. Therefore, separate correlation analyses were performed correlating the FDp DNA abundance with photosynthetic parameters for leaves infected with two separate genotypes independently (Supplementary material 3). Those results established a high positive correlation between the dynamics of all photosynthetic parameters and FDp DNA abundance. This indicates that dynamics of photosynthetic pigments in FDp-infected leaves is highly dependent of phytoplasma titre. However, there is an evident role of the FDp-genotype in the severity of the impact on photosynthetic parameters. Results point that M54 causes less severe changes in infected grapevine than M38 on the level of photosynthetic pigments. Considering that M54 caused a lower accumulation of SS than M38, and had a lower impact on photosynthetic pigments, because the reduction of pigments is caused by a metabolic inhibition loop, lower increase of SS potentially caused lower reduction of pigments in M54-infected grapevine. All photosynthetic pigment parameters mutually correlated, signifying that repression of their synthesis in FDp-infected leaves is probably trackable to the genes involved in the biosynthesis of mutual precursors of both chlorophylls and carotenoids, early in the isoprenoid biosynthetic pathway. Previous findings combining metabolomic and expression data (Teixeira et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) also point to a general repression of isoprenoid biosynthetic pathway, by the downregulation of key genes. However, further studies should focus on investigating the exact mechanism of FDp impact on photosynthetic pigments and take into consideration the impact of different FDp genotypes.\u003c/p\u003e\n\u003ch3\u003e3. 6. Chemometric analyses\u003c/h3\u003e\n\u003cp\u003ePrincipal component analysis (PCA) and hierarchical clustering were used to establish the interrelationship between groups based on tested physiological parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Unsurprisingly, PCA revealed a clear separation of uninfected leaves based on the evaluated physiological parameters according to the principal component 1 (PC1). Photosynthetic pigments highly attributed to the separation of uninfected leaves from the infected (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), presumably because of the high impact of FDp on their content in infected leaves. Based on PC1, M54-infected leaves positioned more closely to the uninfected leaves, than M38-infected leaves at the June time point, pointing to the lower impact of M54 at the beginning of the vegetative season based on the level of tested parameters. AA levels attributed to the grouping of June-positive groups together with Sep-M54, presumably due to the highest AA levels observed at this time points. Results were also confirmed by the hierarchical clustering of the groups presented along with the heatmap based on the tested parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). At the August time point, both M54- and M38-infected leaves grouped together based on both PC1 and PC2. However, at the September time point, M54- and M38-infected leaves clearly separated from each other, with M54-infected leaves remaining close to its position at the August time point, while M38-infected leaves separated more severely from its August time point. Both PCA and hierarchical clustering results significantly point to the lower impact of M54 infection on assessed grapevine physiological parameters. Particularly interesting is the high M38 impact at the end of the vegetative season considering the clear separation of this group, while the M54-induced changes to the parameters appear to be less-severely modified at the latest analysed time point. This could possibly be linked to the higher drop in FDp titre in M54-infected leaves, than in M38-infected leaves.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eAltogether, M54 genotype caused lower accumulation of SS, lower reduction of photosynthetic pigments and lower oxidative damage, all while maintaining higher titre than M38. By doing this, M54 potentially causes less negative effects on assessed grapevine physiological parameters, what potentially enabled it to replicate in a higher capacity. This is unusual because morphologically, M54 caused more severe symptoms in terms of damage to grapevine, suggesting that assessed physiological parameters cannot be correlated with actual disease symptoms. M54-infected grapevine leaves physiology was modified less severely than by M38, potentially because M54 has a mechanism by which main grapevine physiological processes remain relatively preserved. Phytoplasma genotype-dependent changes in grapevine physiology, potentially caused by the differences between M54 and M38 on the level of the efficiency of their effectors should be further investigated in order to better understand pathogenicity mechanisms of FDp and manage the FD spread in the future. Furthermore, no previous study inferred the correlations between phytoplasma titre and observed changes to grapevine physiology. Mainly, FDp abundance correlated with H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, SS, proline and photosynthetic pigments, pointing that phytoplasma replication dynamics clearly affects main physiological processes in grapevine leaves. Roggia et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) were unable to correlate FDp titre with grapevine symptom severity. However, measuring grapevine biochemical parameters as a valuable indicators of stress conditions in FDp-infected grapevine could establish the link between FDp titre and symptom severity in future studies. Based on the observed interrelationship between tested physiological parameters, novel conclusions could be drawn and further investigated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Particularly, of notice is potential phytoplasma-induced upregulation of AA and potentially biosynthesis of other antioxidants, in order to quench plant-derived ROS that have an effect on phytoplasma replication, as well as the established link between the impact on SS and photosynthetic pigments and FDp abundance. Results once again showcased a high versatility of phytoplasmas, offering for the first time a glimpse into the variable effect of different genotypes on host physiology, and open new questions and challenges to be tackled in future studies of these plant pathogens.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCa\u003c/b\u003e.\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eCandidatus\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCar\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecarotenoids\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eChl\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003echlorophylls\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCt\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecycle threshold value\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDW\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edry weight\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eFDp\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eflavescence dor\u0026eacute;e\u003c/em\u003e phytoplasma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGY\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egrapevine yellows diseases (incl. \u003cem\u003eflavescence dor\u0026eacute;e\u003c/em\u003e and \u003cem\u003ebois noir\u003c/em\u003e)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eL-Asc\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eL\u003c/em\u003e-ascorbic acid (vitamin C)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMDA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emalondialdehyde\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePAMP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epathogen-associated molecular patterns\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePCA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprincipal component analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePor\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eporphyrins\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eROS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereactive oxygen species\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRP-HPLC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereversed-phase high-performance liquid chromatography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRT\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eroom temperature\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esoluble sugars\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This article does not contain any studies with human or animal subjects performed by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDD\u003c/strong\u003e: Conceptualization, Methodology, Investigation, Formal Analysis, Data Curation, Validation, Writing \u0026ndash; Original Draft, Writing \u0026ndash; Review \u0026amp; Editing. \u003cstrong\u003eI\u0026Scaron;\u003c/strong\u003e: Resources, Methodology, Writing \u0026ndash; Review \u0026amp; Editing.\u0026nbsp;\u003cstrong\u003eM\u003c/strong\u003e\u003cstrong\u003e\u0026Scaron;M\u003c/strong\u003e: Conceptualization, Methodology, Investigation, Writing \u0026ndash; Review \u0026amp; Editing, Validation, Resources, Funding Acquisition, Supervision. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the University of Zagreb and partially supported by Croatian Science Foundation grant no. IP-2019-04-2469.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors with to thank Barbara Novotni for the technical assistance and help with the extractions for the analyses of physiological parameters and Goran Ivančan for the help with grapevine sampling.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbb\u0026agrave; S, Galetto L, Carle P, Carr\u0026egrave;re S, Delledonne M, Foissac X et al (2014) RNA-Seq profile of \u003cem\u003eflavescence dor\u0026eacute;e\u003c/em\u003e phytoplasma in grapevine. 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Plant Cell Environ 36:2085\u0026ndash;2103. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/pce.12122\u003c/span\u003e\u003cspan address=\"10.1111/pce.12122\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-plant-diseases-and-protection","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jpdp","sideBox":"Learn more about [Journal of Plant Diseases and Protection](https://www.springer.com/journal/41348)","snPcode":"41348","submissionUrl":"https://www.editorialmanager.com/jpdp","title":"Journal of Plant Diseases and Protection","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"ascorbic acid, biotic stress, grapevine yellows, hydrogen peroxide, oxidative stress, photosynthetic pigments","lastPublishedDoi":"10.21203/rs.3.rs-3231755/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3231755/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePhytoplasmas are phytopathogenic bacteria that cause serious damage to agriculture. A quarantine pathogen \u003cem\u003eflavescence dor\u0026eacute;e\u003c/em\u003e phytoplasma (FDp), often associated with grapevine yellows disease, affects viticultural production across Europe. However, the mechanisms of FDp pathogenicity still are not elucidated. In this study, symptomatic and asymptomatic grapevine (\u003cem\u003eVitis vinifera\u003c/em\u003e L. var. \u0026lsquo;Pinot gris\u0026rsquo;) were sampled. Two different FDp genotypes (M38 and M54) were identified, and genotype-dependent changes to grapevine physiological responses through the development of FDp infection were analysed. Correlation analyses established a potential linked between measured physiological parameters and relative FDp DNA abundance. Increased malondialdehyde levels pointed to the oxidative stress in infected leaves, and highly correlated with the activation of \u003cem\u003eL\u003c/em\u003e-ascorbic acid synthesis. Levels of hydrogen peroxide were reduced in infected leaves, possibly as FDp mechanism to avoid plant-derived oxidative damage. Genotype M54 was associated with a lower accumulation of soluble sugars and lower damage to photosynthetic pigments, while retaining a higher titre than M38. Therefore, pronounced phytoplasma genotype-dependent changes in grapevine physiology, potentially caused by the differences between M54 and M38 on the level of the efficiency of their effectors should be further investigated. Altogether, results provide data on certain targets of FDp in grapevine and could assist the identification of potential specific effectors of this phytoplasma to aid the efforts of FDp management in European vineyards.\u003c/p\u003e","manuscriptTitle":"Physiological responses of grapevine (Vitis vinifera var. ‘Pinot gris’) affected by different flavescence dorée genotypes: Dynamics through the development of phytoplasma infection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-09-08 13:30:00","doi":"10.21203/rs.3.rs-3231755/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2023-10-26T04:39:14+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2023-09-06T09:22:10+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-09-04T09:48:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Journal of Plant Diseases and Protection","date":"2023-08-17T08:43:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-08-10T05:02:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Plant Diseases and Protection","date":"2023-08-09T14:06:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-plant-diseases-and-protection","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jpdp","sideBox":"Learn more about [Journal of Plant Diseases and Protection](https://www.springer.com/journal/41348)","snPcode":"41348","submissionUrl":"https://www.editorialmanager.com/jpdp","title":"Journal of Plant Diseases and Protection","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6ca48bf8-d836-471b-bbfb-4769a4625ed8","owner":[],"postedDate":"September 8th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-05-03T05:56:39+00:00","versionOfRecord":[],"versionCreatedAt":"2023-09-08 13:30:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3231755","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3231755","identity":"rs-3231755","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}