Project description:We developed and validated ‘HIT-MAP’ (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets, and generate customisable spatial distribution maps. The uploaded files are an example dataset for the HiTMaP proteomics search engine, designed for MALDI-imaging proteomics annotation. The example data files contain one bovine lens tissue section and one mouse brain tissue section. The ID folder contains the protein/peptide identification result for each tissue segment, and the summary folder contains the protein cluster images.
Project description:We used phosphoproteomics to compare the responses of the ERK1/2 inhibitors, SCH772984 and GDC0994, and the MKK1/2 inhibitor, trametinib. These are compared with responses to the MKK1/2 inhibitor, selumetinib (AZD6244), previously measured by our lab in the same metastatic melanoma cell line. In three replicate experiments, we quantified a total of 12,805 class I phosphosites on 3,819 proteins in the trametinib-SCH772984-DMSO experiment, and 7,074 class I phosphosites on 2,453 in the GDC0994-SCH772984-DMSO experiment. This included 466 phosphosites that reproducibly decreased in response to at least one inhibitor in the trametinib-SCH772984-DMSO experiment and 414 phosphosites in the GDC0994-SCH772984-DMSO experiment. The results demonstrate linearity in signaling through the MAP kinase pathway. By comparing multiple inhibitors targeted to multiple tiers of protein kinases in the MAPK pathway, we gain insight into regulation and new targets of the oncogenic BRAF driver pathway in cancer cells, and a useful approach for evaluating the specificity of drugs and drug candidates. SILAC Experimental Design Experiment 1 Replicate 1: Heavy – DMSO, Medium – SCH772984, Light – Trametinib Replicate 2: Heavy – SCH772984, Medium – Trametinib, Light – DMSO Replicate 3: Heavy – Trametinib, Medium – DMSO, Light – SCH772984 SILAC Experimental Design Experiment 2 Replicate 1: Heavy – DMSO, Medium – SCH772984, Light – GDC0994 Replicate 2: Heavy – SCH772984, Medium – GDC0994, Light – DMSO Replicate 3: Heavy – GDC0994, Medium – DMSO, Light – SCH772984 File List 1. Zipped MaxQuant search results folder containing index and output folders for each raw file, ‘combined’ output folder, and mqpar.xml MaxQuant search parameters file 2. Individual raw files of phosphopeptide-enriched ERLIC fractions 3. Zipped MaxQuant version used for analysis 4. FASTA file containing Uniprot human identifications 5. Instructions for viewing annotated spectra
Project description:We used phosphoproteomics to compare the responses of the ERK1/2 inhibitors, SCH772984 and GDC0994, and the MKK1/2 inhibitor, trametinib. These are compared with responses to the MKK1/2 inhibitor, selumetinib (AZD6244), previously measured by our lab in the same metastatic melanoma cell line. In three replicate experiments, we quantified a total of 12,805 class I phosphosites on 3,819 proteins in the trametinib-SCH772984-DMSO experiment, and 7,074 class I phosphosites on 2,453 in the GDC0994-SCH772984-DMSO experiment. This included 466 phosphosites that reproducibly decreased in response to at least one inhibitor in the trametinib-SCH772984-DMSO experiment and 414 phosphosites in the GDC0994-SCH772984-DMSO experiment. The results demonstrate linearity in signaling through the MAP kinase pathway. By comparing multiple inhibitors targeted to multiple tiers of protein kinases in the MAPK pathway, we gain insight into regulation and new targets of the oncogenic BRAF driver pathway in cancer cells, and a useful approach for evaluating the specificity of drugs and drug candidates. SILAC Experimental Design Experiment 1 Replicate 1: Heavy – DMSO, Medium – SCH772984, Light – Trametinib Replicate 2: Heavy – SCH772984, Medium – Trametinib, Light – DMSO Replicate 3: Heavy – Trametinib, Medium – DMSO, Light – SCH772984 SILAC Experimental Design Experiment 2 Replicate 1: Heavy – DMSO, Medium – SCH772984, Light – GDC0994 Replicate 2: Heavy – SCH772984, Medium – GDC0994, Light – DMSO Replicate 3: Heavy – GDC0994, Medium – DMSO, Light – SCH772984 File List 1. Zipped MaxQuant search results folder containing index and output folders for each raw file, ‘combined’ output folder, and mqpar.xml MaxQuant search parameters file 2. Individual raw files of phosphopeptide-enriched ERLIC fractions and total protein fractions 3. Zipped MaxQuant version used for analysis 4. FASTA file containing Uniprot human identifications 5. Instructions for viewing annotated spectra
Project description:Supplementary proteome data of Vibrio alginolyticus strain: ZJ-T, the Wild-type raw files are in another project (ProteomeXchange ID: PXD035385).
Project description:The summary file contains summary information for all the raw files processed with a single MaxQuant run. The summary information consists of some MaxQuant parameters, information of the raw file contents, and statistics on the peak detection. Based on this file a quick overview can be gathered on the quality of the data in the raw file.
Project description:The summary file contains summary information for all the raw files processed with a single MaxQuant run. The summary information consists of some MaxQuant parameters, information of the raw file contents, and statistics on the peak detection. Based on this file a quick overview can be gathered on the quality of the data in the raw file.
Project description:The summary file contains summary information for all theraw files processed with a single MaxQuant run. Thesummaryinformation consists of some MaxQuantparameters, information of the raw file contents, andstatistics on the peak detection. Based on this file a quickoverview can be gathered on the quality of the data in theraw file.
Project description:This dataset was created to (i) compare the protein expression of E. coli DSM613 cells infected and uninfected with phage vB_EcoS-EE09 and (ii) detect structural proteins of phage vB_EcoS-EE09. Thus, this set provides proteomic data of three setups: 1. Uninfected E. coli DSM613 (file names [file ID]: 04_22A [F40]; 13_ecolicontrol_01 [F13]; 14_ecolicontrol_02 [F14]) 2. E. coli DSM613 infected with phage vB_EcoS-EE09 (file names [file ID]: 02_13A [F39]; 27_ecoliinfected_01 [F27]; 28_ecoliinfected_02 [F28]) 3. Cell-free phage lysate of phage vB_EcoS-EE09 (sample name: 01_EE09)
Project description:Purpose: microRNA profiles were generated from NIH-3T3 cells control and thapsigargin treated, in duplicate. The goal of this study was to compare microRNA profiles of untreated and thapsigargin treated NIH-3T3 fibroblast cells. Methods: NIH-3T3 cells were grown to confluency and either untreated or treated with 500 nM thapsigargin in media for 24 hours. Cells were harvested with TriZol and RNA isolated according to manufacturers protocol Analysis Outline: Short reads in fastq format were assembled using BclToFastq.pl script from Illumina CASAVA 1.8.1 software pipeline.Read quality was examined using FastQC program (http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc). Adapters were trimmed at the 3'end using Btrim prgram (PMID:21651976), only sequences equal to and longer than 18nt were retained, leading N base was trimmed at the 5' end. Unique reads were collapsed using Raw_data_parse program from miRExpress suite (PMID:19821977) (the result of this process is a file that contains unique sequences in one column and number of times this sequence was found in the library in another). They can be found in *.merge files in trimmed_reads directory. Collapsed reads were reformatted and uploaded into miRanalyzer web-based pipeline (http://bioinfo2.ugr.es/miRanalyzer/miRanalyzer.php; PMID:21515631) and matched to known mature miRNA (miRBase vesion 16), RFAM database (version 15) of known non-coding RNAs and known gene transcripts. The purpose of miRAnalyzer analysis was to only detect known miRNAs, prediction of novel miRNAs was not performed; search parameters were kept at default. MiRanalyzer output is saved in miRanalyzer folder with detailed information about mapping to known miRNA. Known miRNAs were divided into mature, maturestar (star sequences), maturestarunobs (star sequences not in miRBase) and hairpin. For each of the libraries there are files with unique and ambiguous mappings. Differentional expression analysis was based on unique alignments to known miRNAs (mature_unique.txt file in miRanalyzer folder). Mature_unique.txt has following columns: name: mature miRNA ID from miRBase; #unique reads: number of unique reads mapped; readCount: number of reads mapped; norm_expressed_all: normalized to all reads; norm_expressed_mapped: normalized to mapped reads. miRNA expression profiling was performed using edgeR bioconductor package (PMID:20478825). For differential expression analysis, used TMM normalization and analysis using common disperion (using tagwise dispersion yielded the same results). FDR was calculated according to Hochberg-Benjamini procedure (PMID:2218183). Results of differential expression analysis were saved in diff_exp folder as diff_exp.txt. diff_exp.txt contains miRNA concentrations in log scale, log2 ratio of WT to KO; p-values and FDR corrected p-values. miRNAs were sorted by p-value.