Abstract

Description The joint disease rheumatoid arthritis (RA) is characterized by persistent synovitis, leading to cartilage damage, bone erosion, and ultimately impaired joint function. The disease affects 0.5 to 1.0% of adults in developed countries, and is three times more frequent in women than in men. A number of autoantibodies can be detected in RA patient’s serum targeting the patient’s own proteins. Several of these proteins, including rheumatoid factor, can also be detected in patients suffering from other autoimmune diseases, including the inflammatory bowel diseases (IBD). IBD and RA share several genetic risk logi, an altered gut microbiota, and environmental risk factors. Articular involvement is the most common extra-intestinal manifestation in patients diagnosed with IBD, with a prevalence between 17 to 39%. Additionally, methotrexate (MTX) is the most frequently prescribed immunosuppressive drug for RA and the second most for the IBD, indicating close similarities between the two diseases. We, therefore, characterized the protein content (the proteome) of the colon mucosa of gastrointestinal healthy RA patients, to investigate if we could detect IBD-related changes. The LC-MS/MS analysis was conducted as part of a previous study (ProteomeXChange submission PXD001608), enabling a comparison between the two datasets, containing the colon mucosal proteome of 11 RA patients, 10 IBD (ulcerative colitis) patients, and 10 controls. This data submission covers the triplicate proteome analysis of the colon mucosa of 11 gastrointestinal healthy RA patients. Sample Processing Protocol Study cohort At the out-patients clinic Diagnostic center Regional Hospital Silkeborg 11 RA patients and 10 controls were recruited in the period from 2012 to 2013. Information on diagnosis, medication, most recent C-reactive protein (CRP), number of swollen and tender joints, anti-cyclic citrullinated peptide (anti-CCP), and smoking habits was recorded from the patient records. Written informed consent was obtained from all participants prior to participation in the study, and the project was approved by The Regional Scientific Ethical Committee (S-20120204) and the Danish Data Protection Agency (2008-58-035). Sampling Colon mucosal biopsies were samples 40 cm from the anus by sigmoidoscopy. The biopsies were immediately transferred to cryotubes and snap-frozen in liquid nitrogen followed by storage at -80°C until proteomics sample preparation. Proteomic sample preparation The biopsies were prepared and analyzed by nanoscale liquid chromatography tandem mass spectrometry (LC-MS/MS) as described in (Bennike TB, et al 2015. Neutrophil Extracellular Traps in Ulcerative Colitis: A Proteome Analysis of Intestinal Biopsies. Inflamm Bowel Dis. PMID 25993694). We utilized a modified filter-aided sample preparation protein digestion protocol for the enzymatic digestion of proteins to peptides. Briefly explained, the biopsies were homogenized in 0.5 mL cold sample buffer (5% sodium deoxycholate, 50 mM triethylammonium bicarbonate, pH 8.5). The protein concentration of the lysates was estimated by a bicinchoninic acid assay with bovine serum albumin as standard, measured using an Infinite microplate reader (Tecan, Männedorf, Switzerland). A biopsy lysate volume corresponding to 100 µg total solubilized protein was transferred to 30 kDa molecular weight cutoff spin-filter (Millipore, Billerica, MA, USA) to facilitate buffer exchanges by centrifugation between all steps. Protein disulfide bonds were reduced with 10 mM tris(2-carboxyethyl)phosphine (Thermo Scientific, Waltham, MA, USA) and alkylated using 50 mM 2-iodoacetamide (Sigma-Aldrich, St. Louis, MO, USA) in sample buffer. Two µg sequencing grade modified trypsin (Promega, Madison, WI, USA) diluted in lysis buffer with 0.5% sodium deoxycholate was added to the spin-filter, and the proteins were digested to peptides overnight at 37°C. The peptide material was eluted from the spin-filter and purified by phase inversions with ethyl acetate and formic acid, and dried down in a vacuum centrifuge overnight. Proteomic analysis The peptides were analyzed by LC-MS/MS using an UltiMate 3000 UPLC system (Thermo Scientific, Waltham, MA, USA) coupled online to a Q Exactive plus mass spectrometer (Thermo Scientific, Waltham, MA, USA). Briefly explained, the peptides were separated and sequentially eluted based on polarity using a reverse phase C18 material trapping column setup with a 50 cm Acclaim PepMap100 columns (Thermo Scientific, Waltham, MA, USA). The liquid phase consisted of 96% solvent A (0.1% formic acid) and 4% solvent B (0.1% formic acid in acetonitrile), and the flow rate was kept constant at 300 nL/min. The peptides were eluted from the column by changing the liquid phase to 8% solvent B on a 5 minutes ramp gradient and subsequently to 30% solvent B on a 225 minutes ramp gradient. The eluting peptides were introduced directly into the mass spectrometer by a picotip emitter for electrospray ionization (New objective, Woburn, MA, USA). The mass spectrometer was operated in positive mode using a data-dependent acquisition method, alternating between survey spectra and isolation/fragmentation spectra. Based on the survey spectra, every second the 12 eluting peptides with highest intensity were selected for isolation, fragmentation, and identification. Selected eluting peptides were excluded from re-analysis for 30 seconds. All biopsies were analyzed in triplicates in a random order. Data Processing Protocol The measured peptide signal intensities were integrated using MaxQuant 1.5.2.8 software, and used to calculate the relative protein quantities (label-free quantitation). Fragmentation spectra were searched against a forward/reverse Uniprot Homo sapiens reference proteome database with isoforms (UP000005640, last modified 2015-01-16, entry count 90,434), and identified proteins and peptides were filtered to < 1% false discovery rate (FDR).[26] Additional filtering of the protein data was employed in Perseus v1.5.0.31 for quantifiable proteins, to ensure high quality quantitative data: 1) The quantitation of any protein was required to be based on at least two sequence-unique quantifiable peptides. 2) The sequence-unique peptides were required to be quantifiable in at least half of the RA biopsies or the control biopsies. 3) All biopsies had been analyzed in triplicates, which ideally should yield identical protein abundances represented by a Pearson’s correlation coefficient of one. Pearson correlation coefficients (R) were calculated for all technical repeats on the log2-transformed protein abundances, and replicate RA_8_3 and replicate RA_9_2 with R < 0.95 were removed from further analysis, which is recommended for future studies of the present dataset. Contact Tue Bjerg Bennike, Aalborg University Submission Date 20/10/2015 Publication Date 26/09/2016 Project PXD00308

    Similar works

    Full text

    thumbnail-image

    Available Versions