br LC MS MS data acquisition br LC

LC–MS/MS data acquisition
LC–MS/MS data analysis, statistical analysis and visualization Data were analyzed and filtered on MaxQuant version 1.2.2 [5] (20ppm error tolerance) with a FDR setting of 1% against the SPROT Yeast database and at a cutoff of at least 2 peptides seen to assign quantitation ratio. The exact MaxQuant settings used can be found in attached document. Each experiment was normalized to the ratio of the bait protein, i.e. SSA1 files using SSA1 ratio and HSP82 files normalized using HSP82 ratio. This produced a list of interactors and their respective quantitated changes upon DNA damage. Proteins were removed from the file if they were labeled as “Contaminants”, “Reverse” or “Only identified by site”. Three biological replicates were performed, with each biological replicate split into technical replicates (18O forward (FWD) labeling and 18O reverse (REV) labeling). A protein was considered identified if detected in at least three of the six replicates. Statistical analysis was performed using the R statistical package (http://www.r-project.org/). Proteins with three out of six observations within each group (SSA1 and HSP82) were retained. Missing values were imputed using row mean imputation. Z-score normalization was performed on the log of all protein ratios. An ANOVA test was then performed to identify proteins that indicate significant variability (P-value<0.05) between biological replicates within each group. These were removed from consideration. The full data obtained was uploaded to the PRIDE repository and can now be found under reference number PXD001284.
Data, experimental design, materials and methods A protein report summarizing the analysis of protein buy SCR 7 was generated in the body and headfoot of infected B. siamensis goniomphalos (Supplementary file 1 and 2 respectively). This file contains the experiment design, model description, statistical model and data summary as well as a detailed summary of each protein including peptide relative expression estimates in addition to protein level estimates. Furthermore, a detailed spreadsheet containing the raw data from the iQuantitator analysis including ID, mean, standard deviation, credible interval, log2 and description for every protein identified in the body and headfoot samples (Supplementary file 3 and 4 respectively) was generated for each timepoint studied.
Ethics statement The protocols used for animal experimentation were approved by the Animal Ethics Committee of Khon Kaen University, as described in [1].
Acknowledgments This work was supported by Project (613669) and program (1037304) grants from the National Health and Medical Research Council of Australia (NHMRC) and a Tropical Medicine Research Collaboration (TMRC) grant from the National Institute of Allergy and Infectious Disease, National Institutes of Health, USA (P50AI098639). AL is supported by a NHMRC principal research fellowship. Funding from Thailand Research Fund through the Royal Golden Jubilee Ph.D. Program (Grant no. PHD/0027/2551) to SP and ST is also gratefully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Value of the data
Data, experimental design, materials and methods
Specifications table
Value of the data
Data, experimental design, materials and methods
2-Dimensional gel electrophoresis (2-DE) 2-DE was performed as described previously [2]. Gel images were analyzed using the Melanie software (GeneBio, Geneva, Switzerland) as described previously [3]. Spot intensities were subjected to statistical analysis to identify differentially abundant proteins. Only those spots that showed statistical significant differences in roots or leaves of the two tested genotypes and exhibited more than 2-fold change in abundance were accepted as candidate drought-responsive proteins (DRPs). The details of number of reproducibly detected spots and the number of spots showed significant change in roots and leaves of the tolerant (SE) or sensitive (SW) genotypes upon drought stress are shown in Supplementary Table 2.