Computational protocol: Combining  Omics to Unravel the Impact of Copper Nutrition on Alfalfa (Medicago sativa) Stem Metabolism

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[…] Proteomics extraction, labeling, migration and spot detection were performed as described previously ().Spot selection for multivariate analysis. Following spot detection using the DeCyder software (v7.0, GE-Healthcare), normalized spot volumes were extracted and standardized according to the spot volumes measured on the internal standard. All volumes were log(2) transformed. Only spots for which a value was obtained on at least three out of every four gels were conserved for statistical analysis. In cases where one missing value was reported, the fourth value was mathematically imputed by implementing the mean log(2)-transformed volume of the 10 spots having the nearest profile of expression on all other gels. Data were finally median normalized (Supplementary Table S3A).Further processing was performed using R (v3.1.2). Homoscedasticity was tested and, depending on this test, an ANOVA or a test of equal means in a one-way layout in the case of unequal variances were applied. This procedure was performed on (i) the global data set and separately on (ii) the apical samples and (iii) the basal samples (Supplementary Table S3B).In cases where a treatment effect was reported for a spot (P < 0.05) in at least one of the three statistical processings (treatment effect on the global data set, treatment effect on the apical samples, treatment effect on the basal samples), the spot was checked using the Decyder (v7.0, GE-Healthcare) spot view and selected for picking.Spot picking, digestion and MS/MS analysis. Selected spots were picked with an Ettan Spotted Picker (GE Healthcare). Digestion was carried out using a Freedom EVO II workstation (Tecan). Briefly, gel plugs were washed for 20 min in a 50 mM ammonium bicarbonate solution in 50% (v/v) MeOH/MQ water and dehydrated for 20 min with 75% acetonitrile (ACN). After dehydration, proteins were digested with trypsin Gold (Promega), 8 µl of a solution containing 5 ng µl–1 trypsin in 20 mM ammonium bicarbonate (overnight, 37°C). After digestion, peptides were extracted from the gel plugs with 50% (v/v) ACN containing 0.1% (v/v) trifluoroacetic acid (TFA) and dried.Peptides were then solubilized in 0.7 µl of 50% (v/v) ACN containing 0.1% (v/v) TFA and spotted manually on MALDI-TOF (matrix-assisted laser desorption ionization-time of flight) targets. A volume of 0.7 µl of 7 mg ml–1 α-cyano-4-hydroxycinnamic acid in 50% (v/v) ACN containing 0.1% (v/v) TFA was added. A MALDI peptide mass spectrum was acquired using the AB Sciex 5800 TOF/TOF (AB Sciex), and the 10 most abundant peaks, excluding known contaminants, were automatically selected and fragmented. MS analyses were carried out as described previously (). MS and MS/MS spectra were submitted for NCBInr database-dependent identification using the taxonomy Viridiplantae (2,471,722 sequences) ( downloaded on October 30, 2014 and containing 51,656,746 sequences on an in-house MASCOT server (Matrix Science, A second search was carried out against an EST (expressed sequence tag) Fabaceae database downloaded on December 17, 2013 and containing 19,932,450 sequences. The parameters used for these searches were mass tolerance MS 100 p.p.m., mass tolerance MS/MS 0.5 Da, fixed modifications cysteine carbamidomethylation, and variable modifications methionine oxidation, and double oxidation of tryptophan and of tryptophan to kynurenine. Proteins were considered as identified when at least two peptides passed the MASCOT-calculated 0.05 threshold scores (respectively a score of 53 for all NCBI Viridiplantae queries and 58 for the EST Fabaceae queries) (Supplementary Table S3C, D). Determination of the subcellular location of proteins was performed using TargetP 1.1 ( with the standard search parameters for plants. [...] Results from ionomics, RT-qPCR and proteomics were analyzed by multivariate analyses using the freeware R (v3.1.2) with the additional packages FactoMineR v1.0 and the functions ‘PCA’, ‘HCPC’ and ‘dimdesc’. PCA axes were characterized, and high contributors to the PCA axes were identified with the ‘dimdesc’ function (P < 0.05) as presented in the Results. For proteomics, the multivariate analysis was performed on the spots for which the calculated P-value for multiple comparison of means was inferior to 0.05 and in which one unique significant protein was identified. In particular, this procedure allowed extraction of 78 and 40 proteins that differentiated low, optimal and high Cu availability, and that were further clustered according to their standardized abundance in nine and six groups, respectively, using the ‘HCPC’ R function.Analyses were performed on four replicates per condition and per stem region for RT-qPCR and proteomics, and on four replicates per organ for mineral content analysis. […]

Pipeline specifications

Software tools Mascot Server, TargetP, FactoMineR
Diseases Drug-Related Side Effects and Adverse Reactions
Chemicals Copper, Iron, Methionine, Molybdenum, Zinc