Computational protocol: Comparative proteomic analysis of horseweed (Conyza canadensis) biotypes identifies candidate proteins for glyphosate resistance

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Protocol publication

[…] To identify molecular components underpinning glyphosate resistance in horseweed, we conducted comparative proteomics of GR and GS biotypes. We reasoned that the abundance of proteins with a putative function in resistance will either have different abundance between untreated tissues of the biotypes or exhibit differential response to glyphosate treatment. Protein samples were extracted from control and glyphosate-treated leaf discs 72 h after exposure to the herbicide. Each sample was an average of tissue from 5 independent plants to ensure representative results. We generated 4 independent biological replicates in order to account for biological variation and used a 2 dye labelling system, in which all samples are labelled with one dye (Cy3) and the pooled internal standard with the other dye (Cy5). This avoids technical variation arising from any potential discrepancies in labelling efficiency between the 2 dyes.We made three main comparisons in quantitative analyses of protein spot abundance across the different sample groups. The first was control GS versus control GR, which reveals proteins with different abundance between the biotypes prior to glyphosate treatment. Second, was the control versus glyphosate-treated GS biotype. Lastly was the control versus glyphosate-treated GR biotype. From the latter two groups, we were particularly interested in identifying proteins whose response to glyphosate in the susceptible biotype was blocked in the resistant biotype and vice-versa. The image analysis software Progenesis SameSpots generated ratios from the normalised spot volumes and gave probability values associated with the analysis of variance and Student’s t-tests. Protein spots that were significantly (p ≤ 0.05) different between any pair-wise comparisons, for which we obtained positive identification, are presented with the related descriptive statistics in . There is no complete genome sequence data for any species of Conyza in publicly available databases. By using sequence database searching with peptide precursor and fragment ion masses, proteins in families that are in common with related organisms can be easily identified, though gene identifications will await genome sequence data availability. Several studies have successfully used this approach on organisms with incomplete or completely non-existent full genome database. Therefore, we searched all green plant sequences available in the TrEMBL database for related protein families. Proteins with the highest molecular weight search (MOWSE) score generated by the MASCOT search engine were selected. All protein identification data are provided in . […]

Pipeline specifications

Software tools SameSpots, Mascot Server
Application MS-based untargeted proteomics
Chemicals Shikimic Acid