BUSCADOR RECOLECTA

Relative quantification of metabolites in healthy and R. pseudosolanacearum CQPS-1-infected tobacco (cv. Yunyan87 and K326) xylem sap., The causal agent of bacterial wilt, Ralstonia pseudosolanacearum, can cause significant economic losses during tobacco production. Metabolic analyses are a useful tool for the comprehensive identification of plant defense response metabolites. In this study, a gas chromatography-mass spectrometry (GC-MS) approach was used to identify metabolites differences in tobacco xylem sap in response to R. pseudosolanacearum CQPS-1 in two tobacco cultivars: Yunyan87 (susceptible to R. pseudosolanacearum) and K326 (quantitatively resistant). Metabolite profiling 7 days post inoculation with R. pseudosolanacearum identified 88 known compounds, 42 of them enriched and 6 depleted in the susceptible cultivar Yunyan87, while almost no changes occurred in quantitatively resistant cultivar K326. Putrescine was the most enriched compound (12-fold) in infected susceptible tobacco xylem, followed by methyl-alpha-d-glucopyranoside (9-fold) and arabinitol (6-fold). Other sugars, amino acids, and organic acids were also enriched upon infection. Collectively, these metabolites can promote R. pseudosolanacearum growth, as shown by the increased growth of bacterial cultures supplemented with xylem sap from infected tobacco plants. Comparison with previous metabolic data showed that beta-alanine, phenylalanine, and leucine were enriched during bacterial wilt in both tobacco and tomato xylem., Peer reviewed

Table S2. Xylem sap metabolites altered by bacterial wilt disease in tobacco and tomato plants., The causal agent of bacterial wilt, Ralstonia pseudosolanacearum, can cause significant economic losses during tobacco production. Metabolic analyses are a useful tool for the comprehensive identification of plant defense response metabolites. In this study, a gas chromatography-mass spectrometry (GC-MS) approach was used to identify metabolites differences in tobacco xylem sap in response to R. pseudosolanacearum CQPS-1 in two tobacco cultivars: Yunyan87 (susceptible to R. pseudosolanacearum) and K326 (quantitatively resistant). Metabolite profiling 7 days post inoculation with R. pseudosolanacearum identified 88 known compounds, 42 of them enriched and 6 depleted in the susceptible cultivar Yunyan87, while almost no changes occurred in quantitatively resistant cultivar K326. Putrescine was the most enriched compound (12-fold) in infected susceptible tobacco xylem, followed by methyl-alpha-d-glucopyranoside (9-fold) and arabinitol (6-fold). Other sugars, amino acids, and organic acids were also enriched upon infection. Collectively, these metabolites can promote R. pseudosolanacearum growth, as shown by the increased growth of bacterial cultures supplemented with xylem sap from infected tobacco plants. Comparison with previous metabolic data showed that beta-alanine, phenylalanine, and leucine were enriched during bacterial wilt in both tobacco and tomato xylem., Peer reviewed

Document S1. Supplemental Figures 1–16 and Supplemental Tables 1–13. Supplemental Table 1. Primers. Supplemental Table 2. Statistics. Supplemental Table 3. DEGs. Supplemental Table 4. DEGs IN versus OUT. Supplemental Table 5. GO IN versus OUT. Supplemental Table 6. Gene list clusters IN. Supplemental Table 7. GO clusters IN PtoAvrRpm1. Supplemental Table 8. GO clusters OUT PtoAvrRpm1. Supplemental Table 9. GO DEGs. Supplemental Table 10 GO cluster IN mock. Supplemental Table 11. GO cluster OUT mock. Supplemental Table 12. Primers. Supplemental Table 13. Quantitative PCR raw data. Document S2. Article plus supplemental information., Peer reviewed

This dataset compiles the code for the research article "Robust transcriptional indicators of plant immune cell death revealed by spatio-temporal transcriptome analyses", currently pubished as a preprint in BioRxiv (DOI:10.1101/2021.10.06.463031). Both the raw and processed transcriptomic data experimentally generated and analysed here in order to identify transcriptional indicators of plant immune cell death are available at GEO (currently under embargo). In addition, supplementary data published with the article, some of which was generated using this code, is available (currently under embargo until manuscript publication) in a linked dataset (https://doi.org/10.34810/data136)., Peer reviewed

Figures S1-S11. -- Supplemental Data Set 1: Arabidopsis lines used in this study. -- Supplemental Data Set 2: List of plasmids used in this study. -- Supplemental Data Set 3: List of primers and synthetic sequences used in this study for genotyping and cloning. -- Supplemental Data Set 4. Yeast strains used in this study. -- Supplemental Data Set 5. Other materials used in this study. -- Supplemental Data Set 6. Statistical analysis., Supplementary figures_3rdSbmission.pdf, tpc.22.01238Supplemental Data Sets 1XXX6.xlsx, Peer reviewed

A) RNA sampling conditions from environmental (soil and mineral water) and previously obtained samples (rich B medium reference and three in planta conditions). B) Transcriptomic data analysis pipeline. First, raw RNA-seq data quality was evaluated with FastQC (v.0.11.5), trimmed with trimGalore (v.0.6.1) and potential rRNA contaminants were filtered out with the SortMeRNA software (v.4.2.0). Reads were mapped with Bowtie2 (v. 2.4.4) and alignments quantified with FADU v. 1.8. The R. solanacearum UY031 genome GCF_001299555.1_ASM129955v1 was used. DEG analyses were performed with Deseq2 (v. 1.34.0). Genes with |log2(fold-change)|>1.5 and adjusted p-value <0.01 were considered as differentially expressed (DEG) when compared to the reference medium. The UpsetR package (v. 1.4.0) (90) was used to detect unique DEG and intersections among the in the different conditions. Deseq2 transformed counts normalized for sample size were used for principal component analysis. C) DEGs in the different conditions. Bars show the total number of up- (yellow) and downregulated (blue) genes for each condition compared to the reference Rich B medium. The line graph and the right Y axis indicate the percentage of DEGs. Drawings created with BioRender., Peer reviewed

Dot plots of the KEGG (left) and GO (right) enrichment analyses of differentially expressed genes (DEGs) from soil (brown) and water (blue) conditions. Dot sizes represent the number of genes associated with each term and dot colour indicates the p. adjusted value. The gene ratio represented in the X axis is the proportion of associated genes to a term from the total gene set. The DEGs were extracted with DEseq2 using the thresholds: p-adj.value > 0.01 and log 2 FC ± 1.5 and ClusterProfiler was used to calculate the enrichment., Peer reviewed

R. solanacearum cultures grown overnight in rich B medium were washed and diluted to OD600 = 0.1 in water and luminescence and OD600 values were measured over a 24h period. Relative luminescence units (RLU) were normalised by bacterial concentration measured as OD600. RLU values were divided by 1000 to facilitate visualisation., Peer reviewed

Time-course expression of prhG, hrpB and hrpY reporter strains at native basic (A to F) or neutral pH (G) and after pH neutralisation with HCl or alkalinisation with KOH. For each time point, luminescence was measured (RLU) and normalised by OD600. All values were divided by 1000 to facilitate visualisation. Letters indicate the water sources detailed in the methods section., Peer reviewed

A) Representation of the main components of the nitrogen metabolism and their expression in different conditions (log2 fold change with respect to rich B medium). Genes depicted in A correspond to genes highlighted in bold in B. B) Heatmap representation of the log2 fold change in expression with respect to growth in rich B medium for all the genes classified in the nitrogen metabolism group. The colour palette ranges from blue (downregulated) to yellow (upregulated genes) as indicated in the key. Locus names are presented without the preceding letters RSUY_., Peer reviewed