Computational protocol: Shotgun Proteomics of Tomato Fruits: Evaluation, Optimization and Validation of Sample Preparation Methods and Mass Spectrometric Parameters

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Protocol publication

[…] Data analysis was done using Proteome Discoverer (version 1.4, Thermo Scientific). S. lycopersicum iTAG2.3 proteome sequence (, downloaded on February 5, 2013, 26,705 sequences and 9,322,189 residues) was used as the database against which the searches were done. Peptide mass tolerance and fragment mass tolerance were set to 5 ppm and 0.8 Da respectively. Sequest was used as the search engine with the following search parameters- trypsin as the protease, a maximum of two missed cleavages were allowed, carbamidomethylation of cysteine and oxidation of methionine were selected as fixed and variable modifications respectively. Peptides were filtered for high confidence and these were used for assigning protein IDs. Percolator tool was used to assess peptide confidence; peptides with q ≤ 0.05 were selected (false discovery rate (FDR) of 1%), which was estimated based on the number of decoy hits. Proteins that passed the criteria of high confidence with XCorr threshold greater than 2.0 and a minimum number of two matched peptides were considered. Information regarding the number of MS and MS/MS scans, fill times were obtained from RawMeat version 2.1. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (Vizcaíno et al., ) via the PRIDE partner repository with the dataset identifier PXD003920. [...] Proteins identified in this study were annotated based on their molecular function, biological process and cellular component with Gene Ontology (GO) annotation using ProteinCenter (version 1) in Proteome Discoverer 1.4. […]

Pipeline specifications

Software tools Proteome Discoverer, Comet, Percolator, ProteinCenter
Databases ProteomeXchange
Applications Miscellaneous, MS-based untargeted proteomics
Organisms Solanum lycopersicum
Diseases Multiple Sclerosis
Chemicals Carbohydrates, Phenol