Project PXD000811

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Summary

Title

Mouse kidney glomerular extracellular matrix LC-MSMS

Description

Across the spectrum of human disease there are significant changes in the composition and organisation of extracellular matrix (ECM). Furthermore, disease severity can vary according to race and sex, yet mechanisms for these variations are unclear. Using the kidney glomerulus as a model system, we tested the hypothesis that genetic background and sex influence composition and organisation of ECM. We characterised ECM from healthy mice with different predisposition to glomerular disease using global microarray, discovery proteomics and electron microscopy. Transcriptomic and proteomic analyses revealed unique strain and sex dependent glomerular ECM signatures with novel ECM proteins, which relate to glomerular dysfunction with leakage of macromolecules into the glomerular filtrate. In addition, we found striking structural changes in basement membranes in disease-susceptible mice. These findings were not explained by mutations in known ECM or glomerular genes. Pathway analysis of merged transcriptomic and proteomic datasets identified potential ECM regulatory pathways involving inhibition of matrix metalloproteinases, LXR/RXR, NRF2, notch and CDK5. These pathways may therefore alter ECM and confer susceptibility to disease.

Sample Processing Protocol

The glomeruli of eighteen-week-old male and female B6 and FVB mice (n=3 in each group) were isolated through the Dynabead-based isolation method (Takemoto et al, 2002). All steps were carried out at 4oC to minimize proteolysis. Pure glomerular isolates from three mouse kidneys were incubated for 30 minutes in extraction buffer (10 mM Tris, 150 mM NaCl, 1% (v/v) Triton X-100, 25 mM EDTA, 25 μg/ml leupeptin, 25 μg/ml aprotinin and 0.5 mM AEBSF) to solubilize cellular proteins, and samples were then centrifuged at 14000 × g for 10 minutes to yield fraction 1. The remaining pellet was incubated for 30 minutes in alkaline detergent buffer (20 mM NH4OH and 0.5% (v/v) Triton X-100 in PBS) to further solubilize cellular proteins and to disrupt cell–ECM interactions. Samples were then centrifuged at 14000 × g for 10 minutes to yield fraction 2. The remaining pellet was incubated for 30 minutes in a deoxyribonuclease (DNase) buffer (10 μg/ml DNase I (Roche, Burgess Hill, UK) in PBS) to degrade DNA. The sample was centrifuged at 14000 × g for 10 minutes to yield fraction 3, and the final pellet was re-suspended in reducing sample buffer (50 mM Tris-HCl, pH 6.8, 10% (w/v) glycerol, 4% (w/v) sodium dodecylsulfate (SDS), 0.004% (w/v) bromophenol blue, 8% (v/v) β-mercaptoethanol) to yield the ECM fraction. Samples were heat denatured at 70oC for 20 minutes. Protein samples were resolved by SDS-PAGE and visualized by Coomassie staining. Gel lanes were sliced and subjected to in-gel trypsin digestion as described previously (Humphries et al, 2009). Liquid chromatography–tandem MS analysis was performed using a nanoACQUITY UltraPerformance liquid chromatography system (Waters, Elstree, UK) coupled offline to an Orbitrap Elite mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). Desalted peptides were separated on a bridged ethyl hybrid C18 analytical column (250mm length, 75 μm inner diameter, 1.7 μm particle size, 130 Å pore size; Waters) using a 45-min linear gradient from 1% to 25% (v/v) acetonitrile in 0.1% (v/v) formic acid at a flow rate of 200 nl/min. Peptides were selected for fragmentation automatically by data-dependent analysis.

Data Processing Protocol

Tandem mass spectra were extracted using extract_msn (Thermo Fisher Scientific) executed in Mascot Daemon (version 2.2.2; Matrix Science, London, UK). Peak list files were searched against a modified version of the Uniprot mouse database (version 3.70; release date, 3 May 2011), containing ten additional contaminant and reagent sequences of non-mouse origin, using Mascot (version 2.2.06; Matrix Science) (Perkins et al, 1999). Carbamidomethylation of cysteine was set as a fixed modification; oxidation of methionine and hydroxylation of proline and lysine were allowed as variable modifications. Only tryptic peptides were considered, with up to one missed cleavage permitted. Monoisotopic precursor mass values were used, and only doubly and triply charged precursor ions were considered. Mass tolerances for precursor and fragment ions were 0.4 Da and 0.5 Da, respectively. MS datasets were validated using rigorous statistical algorithms at both the peptide and protein level (Keller et al, 2002) (Nesvizhskii et al, 2003) implemented in Scaffold (version 3.6.5; Proteome Software, Portland, OR, USA). Protein identifications were accepted upon assignment of at least two unique validated peptides with ≥90% probability, resulting in ≥99% probability at the protein level. These acceptance criteria resulted in an estimated protein false discovery rate of 0.1% for all datasets.

Contact

M Randles, Faculty of Human and Medical Science
Rachel Lennon, Wellcome Trust Centre for Cell-Matrix Research, Faculty of Life Sciences and Institute of Human Development, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK ( lab head )

Submission Date

11/03/2014

Publication Date

09/07/2016

Publication

    Randles MJ, Woolf AS, Huang JL, Byron A, Humphries JD, Price KL, Kolatsi-Joannou M, Collinson S, Denny T, Knight D, Mironov A, Starborg T, Korstanje R, Humphries MJ, Long DA, Lennon R. Genetic Background is a Key Determinant of Glomerular Extracellular Matrix Composition and Organization. J Am Soc Nephrol. 2015 Dec;26(12):3021-34 PubMed: 25896609

Assay

Page 1 2 3 4
Page size 10 20
Showing 1 - 10 of 31 results
# Accession Title Proteins Peptides Unique Peptides Spectra Identified Spectra View in Reactome
1 35399 Fractionation of glomerular ECM A 635 2471 1589 9446 1679
2 35398 e.g. Control sample - Technical replicate #3 1081 3959 2739 10916 2945
3 35407 Fraction A3 1590 4953 3375 11755 3631
4 35391 Fraction A4 1808 5389 3601 12315 3892
5 35406 Fraction A5 1462 4047 2736 11137 2943
6 35392 Glomerular ECM fractionation 219 495 331 6246 339
7 35409 e.g. Control sample - Technical replicate #3 198 624 435 6561 459
8 35393 e.g. Control sample - Technical replicate #3 1295 3822 2485 11153 2621
9 35408 e.g. Control sample - Technical replicate #3 646 2284 1397 9851 1510
10 35394 e.g. Control sample - Technical replicate #3 473 1073 686 6583 708