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Protective cellular mechanism of estrogen against kidney stone formation: A proteomics approach and functional validation
Kidney stone disease is influenced by multiple factors, including but not limited to age, gender, genetic background, hydration status, diet and drug. Regarding the gender, epidemiologic data across the world has shown that females at the reproductive age (15-49 years) have lower incidence/prevalence of kidney stone disease approximately 1.5-2.5 folds as compared to males at the same age. However, this gap is narrower in the postmenopausal age, whereas the postmenopausal females with higher serum estrogen levels are less likely to have kidney stones. Furthermore, female stone formers (patients with kidney stones) are associated with lower estrogen levels. Therefore, estrogen has been proposed to serve as the protective hormone against kidney stone disease. However, the precise mechanisms underlying such protective effects of estrogen remain unclear and require further investigations. This study thus investigated the effects of estradiol (which is the most prevalent and potent form of estrogen in females at the reproductive age) on cellular proteome of renal tubular cells using a proteomics approach.
Sample Processing Protocol
Extraction of cellular proteins for proteomics analysis MDCK cells were incubated in the complete medium with or without 20 nM estradiol for 7 days (n=5 independent culture flasks per group). The cell monolayer was then collected and cellular proteins were extracted using a 2-D lysis buffer containing 7 M urea, 2 M thiourea, 4% 3-[(3-cholamidopropyl) dimethyl-ammonio]-1-propanesulfonate (CHAPS), 120 mM dithiothreitol (DTT), 40 mM Tris-HCl, and 2% ampholytes (pH 3–10) at 4°C for 30 min. Two-dimensional gel electrophoresis (2-DE) and staining Proteins derived from each culture flask were resolved in each 2-D gel (100 µg total protein/each gel; n=5 gels/group; a total of 10 gels were analyzed). Each protein sample was premixed with a rehydration buffer containing 7 M urea, 2 M thiourea, 2% CHAPS, 120 mM DTT, 40 mM Tris-base, 2% ampholytes (pH 3–10), and a trace of bromophenol blue to make a final volume of 150 μl. The mixture was rehydrated onto an Immobiline DryStrip (nonlinear pH gradient of 3-10, 7-cm-long) (GE Healthcare; Uppsala, Sweden) at 4°C for 10-15 h. The first dimensional separation or isoelectric focusing (IEF) was performed in Ettan IPGphor III IEF System (GE Healthcare) at 20°C, using a stepwise mode to reach 9,083 Vh with a current of 50 mA/strip. After IEF was complete, the IPG strips were incubated for 15 min in equilibration buffer I containing 6 M urea, 130 mM DTT, 112 mM Tris-base, 4% SDS, 30% glycerol, and 0.002% bromophenol blue, followed by another 15 min in equilibration buffer II containing similar compositions as of buffer I, but DTT was replaced with 135 mM iodoacetamide. The equilibrated IPG strips were subjected to the second dimensional separation in 12.5% SDS-polyacrylamide gel using SE260 Mini-Vertical Electrophoresis Unit (GE Healthcare) at 20 µA/gel for approximately 1.5 h. Thereafter, the proteins resolved in gels were stained with Deep Purple total protein fluorescence dye (GE Healthcare) and visualized by using Typhoon 9200 laser scanner (GE Healthcare). Spot matching and comparative analysis Protein spots visualized in 2-D gels were analyzed using ImageMaster 2D Platinum software (GE Healthcare). Parameters used for spot detection were (i) minimal area = 10 pixels; smooth factor = 2.0; and (iii) saliency = 200. A reference gel was created from an actual gel with the greatest number of protein spots and additional spots that were present in other gels were also combined to produce a single artificial reference gel with all protein spots present in all gels. The reference gel was then used for matching the corresponding protein spots across different gels. Background subtraction was performed and the intensity volume of each spot was normalized with total intensity volume (summation of the intensity volumes obtained from all spots within the same 2-D gel). Differentially expressed protein spots that reached statistically significant threshold (p < 0.05) were subjected to in-gel tryptic digestion and identification by mass spectrometry. In-gel tryptic digestion and protein identification by nanoLC-ESI-Q-TOF MS/MS The protein spots with significantly differential levels were excised from 2-D gels, washed with 1 ml dI water, and then destained with 100 µl of 100 mM NH4HCO3 at 25°C (RT) for 15 min. Thereafter, 100 µl acetonitrile (ACN) was added and incubated at RT for 15 min. After removing the solvent, the gel pieces were dried in a SpeedVac concentrator (Savant; Holbrook, NY) and rehydrated with 50 µl of 10 mM DTT in 100 mM NH4HCO3 at 56°C for 30 min using a heat box. After removing the reducing buffer, the gel pieces were incubated with 50 µl of 55 mM iodoacetamide in 100 mM NH4HCO3 at RT for 20 min in the dark. The buffer was then removed, whereas the gel pieces were incubated with 100 µl of 50 mM NH4HCO3 at RT for 15 min. Thereafter, 100 µl acetonitrile (ACN) was added and incubated at RT for 15 min. After removing the solvent, the gel pieces were dried in a SpeedVac concentrator, and then incubated with a minimal volume (just to cover gel pieces) of 12 ng/µl sequencing grade modified trypsin (Promega; Madison, WI) in 50 mM NH4HCO3 in a ThermoMixer® C (Eppendorf; Hauppauge, NY) at 37°C for 16-18 h. The digestion reaction was stopped by incubation with 100 µl of 5% formic acid/ACN (1:2 vol/vol) at 37°C for 15 min. The digested peptide mixtures were collected using a pipette with gel loader tip, transferred into a fresh tube, dried by a SpeedVac concentrator, and subjected to MS/MS analysis. Separation of the digested peptides was performed using 1260 Infinity II nanoHPLC (Agilent Technologies; Santa Clara, CA). Peptide sequences were then analyzed by an ultra-high resolution Q-TOF MS/MS system (6550 Q-TOF, Agilent Technologies) in positive mode with ESI nanosprayer ion source. The nanoLC and Q-TOF MS/MS systems were controlled by MassHunter Acquisition software (Agilent Technologies).
Data Processing Protocol
Data analyses The MS/MS raw spectra were converted into mzData.xml using MassHunter Qualitative Analysis software (Agilent Technologies). Mascot search engine (http://www.matrixscience.com) was used to query MS/MS spectra against UniProtKB/SwissProt mammalian database with the following standard Mascot parameters for CID: Enzyme = trypsin, maximal number of missed cleavages = 1, peptide tolerance = ±0.1 Da, MS/MS tolerance = ±0.5 Da, fixed modification = carbamidomethyl (C), variable modification = oxidation (M), charge states = 2+ and 3+, and instrument type = ESI-QUAD-TOF. Bioinformatics analysis STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) was used to classify protein precursors according to their cellular component, biological processes and molecular functions. Statistical analysis Data were presented as mean ± SEM. Mean difference between two groups was analyzed by Student’s T-test using SPSS version 11.5. Statistical significance was considered at P-value less than 0.05.
Visith Thongboonkerd, Mahidol University
Prof. Visith Thongboonkerd, Medical Proteomics Unit, Office for Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand ( lab head )
Peerapen P, Thongboonkerd V. Protective Cellular Mechanism of Estrogen Against Kidney Stone Formation: A Proteomics Approach and Functional Validation. Proteomics. 2019:e1900095 PubMed: 31475403
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