Project description:A paediatric saliva protein spectral library was created using drool samples collected from children with small area burn injury as well as healthy controls. Iso-electric focussing, LDS-PAGE and a combination of both fractionation methods were utilised to increase the protein coverage of the library. This resulted in the identification of 1310 proteins at a 10% FDR cut-off. The library samples were analysed using DDA-MS. The generated protein spectral library was used to quantify the abundance of 742 proteins in each individual participant sample using SWATH-MS. All samples were run on a Sciex TripleTOF 6600 mass spectrometer, and the data was processed using the OneOmics Suite v3.0 (SCIEX). Index retention time proteins were used in this experiment. The effect of burn injury and various burn characteristics on salivary protein abundance profiles were evaluated.
Project description:Three AIEC strains were isolated from CD patients. We analyzed three types of cell: before adhesion and adhesion-invasion(control), after adhesion-invasion and after invasion. Proteins were assessed in an untargeted label-free bottom-up proteomic experiment using IDA approach (i.e. Information Dependent Acquisition) on Sciex TripleTOF 6600 Q-TOF mass-spectrometer couplet with LFQ (label-free quantification) by MaxQuant software. Dataset covers 54 samples (three biological replicates and two technical).
Project description:Plasma from lung cancer patients from EDTA tubes was fractionated using size exclusion chromatography. Fractions 1-5, 7-11, 12-15, 16-20 were pooled, cfDNA was extracted from the fractions and paired unfractionated samples and PE150bp sequencing was performed on an Illumina Novaseq S4 flowcell. Samples are provided as raw reads without any prior processing.
Project description:An experiment was designed to assess the reproducibility of SWATH-MS measurements collected from different mass spectrometers in a single facility over a period spanning approximately four months. Data were acquired with 90-minute gradient lengths at the Australian Cancer Research Foundation International Centre for the Proteome of Human Cancer (ProCan) on six SCIEX TripleTOF 6600 QTOF mass spectrometers. Multiple replicate aliquots were prepared for eight samples. These comprised a dilution series of ovarian cancer tissue (0%, 3.125%, 6.25%, 12.5%, 25% and 50%) offset by yeast and a fixed proportion (50%) of prostate cancer tissue (Samples 1-6), a 1:1 mix of ovarian cancer tissue and yeast cells (Sample 7), and a human cell line (HEK293T; Sample 8). On each mass spectrometer, sets of 20 replicate aliquots (three aliquots of Samples 2-5, and two aliquots of Samples 1, 6-8) were run during each of thirteen 48-hour periods. Experimental data were acquired in 48-hour time periods on each instrument continuously for eight days (with sets of 20 replicates commencing on days 1, 3, 5 and 7), once per week for the remainder of the month (commencing on days 14, 21 and 28), and then once per month for the remainder of the first three months (commencing on days 56 and 84). After each instrument underwent a major clean, the sets of 20 replicates were again run continuously for a further eight days (commencing on days 101, 103, 105 and 107). Data were therefore acquired during a total of thirteen 48-hour periods over approximately four months, during which time the mass spectrometry facility was fully operational. Mass spectrometer maintenance schedules varied according to each individual instrument's performance, and each instrument commenced data acquisition asynchronously within 28 days from the experiment start.
Project description:We have grown C6 glioma cells and rat astrocytes, as well as astrocyte cells co-cultured together with C6 glioma. We performed proteome-wide LC-MS analysis of this experimental groups. The data including LC-MS/MS raw files and exported MaxQuant report. For our co-cultivated in vitro model we used astrocytes and C6 glioma cells. Astrocytes cell lines isolated from rat brain tissue. We analyzed astrocytes in two conditions: beforeand after co-cultivation. Proteins were assessed in an untargeted label-free bottom-up proteomic experiment using IDA approach (i.e. InformationDependent Acquisition) on AB Sciex TripleTOF 6600 Q-TOF mass-spectrometer coupled with LFQ (label-free quantification) approach by MaxQuant software. Dataset covers 165 samples (11 biological rand 5 technical replicates)
Project description:This repository contains all the FASTQ files for the five data modalities (scRNA-seq, scATAC-seq, Multiome, CITE-seq+scVDJ-seq, and spatial transcriptomics) used in the article \\"An Atlas of Cells in The Human Tonsil,\\" published in Immunity in 2024. Inspired by the TCGA barcodes, we have named each fastq file with the following convention: [TECHNOLOGY].[DONOR_ID].[SUBPROJECT].[GEM_ID].[LIBRARY_ID].[LIBRARY_TYPE].[LANE].[READ].fastq.gz which allows to retrieve all metadata from the name itself. Here is a full description of each field: - TECHNOLOGY: scRNA-seq, scATAC-seq, Multiome, CITE-seq+scVDJ-seq, and spatial transcriptomics (Visium). We also include the fastq files associated with the multiome experiments performed on two mantle cell lymphoma patients (MCL). - DONOR_ID: identifier for each of the 17 patients included in the cohort. We provide the donor-level metadata in the file \\"tonsil_atlas_donor_metadata.csv\\", including the hospital, sex, age, age group, cause for tonsillectomy and cohort type for every donor. - SUBPROJECT: each subproject corresponds to one run of the 10x Genomics Chromium™ Chip. - GEM_ID: each run of the 10x Genomics Chromium™ Chip consists of up to 8 \\"GEM wells\\" (see https://www.10xgenomics.com/support/software/cell-ranger/getting-started/cr-glossary): a set of partitioned cells (Gel Beads-in-emulsion) from a single 10x Genomics Chromium™ Chip channel. We give a unique identifier to each of these channels. - LIBRARY_ID: one or more sequencing libraries can be derived from a GEM well. For instance, multiome yields two libraries (ATAC and RNA) and CITE-seq+scVDJ yields 4 libraries (RNA, ADT, BCR, TCR). - LIBRARY_TYPE: the type of library for each library_id. Note that we used cell hashing () for a subset of the scRNA-seq libraries, and thus the library_type can be \\"not_hashed\\", \\"hashed_cdna\\" (RNA expression) or \\"hashed_hto\\" (the hashtag oligonucleotides). - LANE: to increase sequencing depth, each library was sequenced in more than one lane. Important: all lanes corresponding to the same sequencing library need to be inputed together to cellranger, because they come from the same set of cells. - READ: for scATAC-seq we have three reads (R1, R2 or R3), see cellranger-atac's documentation. While we find these names to be the most useful, they need to be changed to follow cellranger's conventions. We provide a code snippet in the README file of the GitHub repository associated with the tonsil atlas to convert between both formats (https://github.com/Single-Cell-Genomics-Group-CNAG-CRG/TonsilAtlas/). Besides the fastq files, cellranger (and other mappers) require additional files, which we also provide in this repository: - cell_hashing_metadata.csv: as mentioned above, we ran cell hashing (10.1186/s13059-018-1603-1) to detect doublets and reduce cost per cell. This file provides the sequence of the hashtag oligonucleotides in cellranger convention to allow demultiplexing. - cite_seq_feature_reference.csv: similar to the previous file, this one links each protein surface marker to the hashtag oligonucleotide that identified it in the CITE-seq experiment. - V10M16-059.gpr and V19S23-039.gpr: these correspond to the two slides of the two Visium experiments performed in the tonsil atlas. They are needed to run spaceranger. - [GEM_ID]_[SLIDE]_[CAPTURE_AREA].jpg: 8 images associated with the Visium experiments. Here, GEM_ID refers to each of the 4 capture areas in each slide. - [TECHNOLOGY]_sequencing_metadata.csv: the GEM-level metadata for each technology. It includes the relationship between subproject, gem_id, library_id, library_type and donor_id. These are the other repositories associated with the tonsil atlas: - Expression and accessibility matrices: https://zenodo.org/records/10373041 - Seurat objects: https://zenodo.org/records/8373756 - HCATonsilData package: https://bioconductor.org/packages/release/data/experiment/html/HCATonsilData.html - Azimuth: https://azimuth.hubmapconsortium.org/ - Github: https://github.com/Single-Cell-Genomics-Group-CNAG-CRG/TonsilAtlas
Project description:Enriched Arabidopsis cytosol (cell culture) fractionated by SCX (15 fractions) and analysed by Q-TOF nanoLC-MS/MS (AB Sciex QStar Elite)
Project description:Forty seven healthy HK-Chinese subjects between ages 18-30 were recruited. Subjects need to pass the McMonnies Questionnaire prior to the data collection. Visual functions and anterior ocular health were first assessed. One hour later, the subjects’ tear osmolalities were tested by the TearLab Osmometer. Tear samples were then collected by disposable microcapillary tubes. TripleTOF 6600 Mass Spectrometer was used to analyze the tear protein components.
Project description:Gradient fractions of RNAi of XAC1 (Tb927.7.2780) in Trypanosoma brucei bloodstream forms. RNAi was induced using tetracycline and cell extracts were fractionated into polysomal and monosome-non-ribosome-associated fractions.
Project description:Radiotherapy remains a standard treatment for colorectal cancer. The clinical significance of the conventional treatment is based on accumulated dose and usually consists of single daily irradiations of 1.8 - 2 Gy fractions. However the repopulation of cancer cells during and/or after the treatment suggests that the surviving fraction of cells acquire the radioresistance to cancer therapy. It has been determined a number of radioresistance markers, but only limited data exist on the acquisition of the resistance to fractionated radiation therapy. This research provides the genomic data of gene expression changes in colorectal cancer cell HCT116 line following single and multiple fractions of irradiation, aiming to identify particular genes associated with the effect of fractionated radiotherapy.