Peptidomics Mapping of Proteolysis Highlights Triple Activation of Sprouted Seeds by Germination, Homogenisation and Species Mixture.

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We investigated how seed proteolysis was enhanced by germination, by subsequent homogenisation (disrupting sprout compartments), and by co-incubation of homogenates from different species. We used mass spectrometry of released peptides to track proteolytic signatures from chickpea, lentil, mung and broccoli proteins, in soaked seeds, in sprouted seeds, and after sprout homogenisation followed by incubation alone or in mixture with other sprouts. MS data were analyzed using FragPipe v20 for peptide identification (length range 7-65 amino acids) with non-specific search. This repository contains scripts and input files used to analyse the peptidomics data obtained from Fragpipe. The intermediate output files and figures generated are also provided. Scripts for following are included: 1) Proteolytic Motif Extraction and Analysis Quantitative analyses were carried out using R (R Core Team, 2013), using the Biostrings package to import the plant FASTA files. Peptide-spectrum match (PSM) data obtained from FragPipe output files were read and merged with the corresponding protein sequences based on UNIPROT protein IDs. A binomial probability model (O’Shea et al., 2013) was implemented in R assuming a priori the same null background distribution of amino acids at each cleavage position; this estimated the statistical significance of amino acid enrichment or depletion at each cleavage site position, and the values were represented as a stacked sequence logo with the most significant amino acids having the largest letter height. 2) Regression quantification of inter-species proteolytic effects in sprout mixtures An interesting research problem is to determine the contribution of the proteases from each species in a given co-incubation experiment to its overall proteolytic profile. Thus, for each of the eight motif positions (P4-P4’), the frequency of amino acid Ri in position Pj was calculated as the number of peptides with Ri in Pj divided by the total number of peptides. The assumption is that these frequency measures are a realistic approximation of the underlying probability distributions. From these calculations a probability position matrix (PPM) was defined describing the likelihood of each amino acid appearing at a given position across all cleavage sites detected in a given experiment. Assuming linearity and additivity, the contributions of the proteases from two species incubated alone (sprout1 and sprout2) to the proteolytic profile when they are co-incubated (mixed) can be modelled as a linear regression where the independent variables are the PPMs derived from the isolated incubation experiments (PPMsprout1 and PPMsprout2) and the target is the PPM from the co-incubation experiment (PPMmixed). This linear model is described by the following equation: PPM(mixed) = a*PPMsprout1 + (1-a) * PPMsprout2 (Equation 1) where a represents the relative contribution of sprout1, and (1-a) represents the contribution of sprout2. This model was used to estimate the regression coefficient and its 95% confidence interval. If 0 is within the confidence interval, the contribution of PPMsprout1 is not statistically significant; if 1 lies within the confidence interval, then the contribution of PPMsprout2 is not significant. 3) Heatmap and statistical test on protein categories High-confidence protein identifications (Protein Probability > 0.99) were sorted on peptide abundance and the top 100 proteins were selected for further analysis for each of the species. Proteins were manually assigned to categories, and those with sufficient numbers in a species were tabulated. For each time point, the relative abundance of each protein group was calculated as a percentage of the total protein log-intensity . Rows were scaled using z-score standardization. Heatmaps of peptide counts per protein were generated. Statistical tests were performed to find whether the distribution of protein functional categories in peptides of a species changed significantly in germinated (e.g. 4 days) versus germinated+homogenised (e.g. 4.2 days), and between homogenised single species versus mixed species samples.

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