Proteomic analysis of liver proteome affected by intrauterine growth restriction in newborn piglets.
Intrauterine growth restriction (IUGR) impairs fetal growth and development, perturbs nutrient metabolism, and increases the risk of developing diseases in the postnatal life. However, the underlying mechanisms by which IUGR affects fetuses remain incompletely understood. Here, we applied high-throughput proteomics approach and biochemical analysis to investigate the impact of IUGR on fetal liver.
Sample Processing Protocol
Pigs and Tissue Samples After term birth (d 114 of gestation), one IUGR newborn piglet and one NW newborn piglet were obtained from each of 7 gilts (n=7). Animal maintenance and experimental treatments were conducted in accordance with the ethical guidelines for animal research established and approved by the institutional Animal Care and Use Committee at Huazhong Agricultural University. Liver tissue samples for iTRAQ and western blotting analysis were treated by liquid nitrogen, and then stored at -80 ℃. The liver tissue samples for hematoxylin and eosin (H&E) staining and periodic acid-Schiff (PAS) staining were ﬁxed in 4% paraformaldehyde for 24 h at room temperature, and then processed for parafﬁn embedding. Liver tissue samples for transmission electron microscopy assessment were fixed in 0.1 M sodium cacodylate-buffered (pH-7.4) 2.5% glutaraldeyde solution. It’s noteworthy that all of the tissue samples were collected from similar area on each organ. Additionally, the umbilical vein blood was collected and centrifuged at 3000 g for 10 min at 4 ℃, then plasma was immediately stored in 500 μL aliquots at 4 ℃ for glucose analysis. Protein Preparation, Digestion and iTRAQ Labeling The liver samples from three IUGR and three NB fetuses were used for protein extraction. Liver tissues were milled to powder in mortar with lipid nitrogen. Subsequently, 150 mg powder of each sample was mixed with 1 mL lysis buffer containing (50 mM Tris (pH-8.8), 150 mM NaCl, 1 mM EDTA, 1% Triton X-100) supplemented with protease inhibitors (1 µg/ml leupeptin, 2 µg/ml aprotinin, 1 µg/ml pepstatin A, and 100 µg/ml PMSF) in glass homogenizer. Homogenates were incubated on the ice for 20 min, and then centrifuged at 12 000g for 15 min at 4 ℃. Finally, the supernatants were kept at -80 ℃ for iTRAQ and western blotting analysis. The supernatant containing precisely 100 μg protein of each sample was digested with Trypsin Gold (Promega, Madison, WI, USA) at 37 ℃ for 16 h. Subsequently, peptides were dried by vacuum centrifugation and reconstituted in 0.5 M TEAB (Applied Biosystems, Milan, Italy). The tryptic peptides were labeled with isobaric iTRAQ tags (NW: 113, 114, 115; IUGR: 118, 119, 121). The labeled peptides were incubated for 2 h at room temperature, then mixed and dried by vacuum centrifugation. LC-MS/MS Analysis Strong cationic-exchange chromatography (SCX) was performed on a LC-20AB HPLC Pump system (Shimadzu, Kyoto, Japan) to separate samples. The labeled peptide mixtures were eluted with 4ml buffer A (25 mM NaH2PO4 in 25% ACN, pH-2.7) at a flow rate of 1 mL/min for 10min, and then a gradient elution with 5‒60% and 60‒100% buffer B (25 mM NaH2PO4, 1 M KCl in 25% ACN, pH-2.7) for 27 min and 1 min, respectively. The elution process was monitored by measuring the absorbance at 214 nm. 20 fractions were collected every 1 min, desalted with a Strata X C18 column (Phenomenex) and vacuum-dried. Subsequently, each fraction was centrifuged at 20 000g for 10 min after resuspend in buffer A (2% ACN, 0•1% FA). 5 μg labeled peptides was loaded onto a LC-20AD nano-HPLC (Shimadzu, Kyoto, Japan) by the autosampler onto a 2 cm C18 trap column with a flow rate of 8 μL/min for 4 min. Then, the peptides were eluted onto a 10 cm analytical C18 column (inner diameter 75 μm) with a 44-min linear gradient run at a flow rate of 300 nL/min was from 2% to 35% buffer B (95% ACN, 0.1% FA), followed by 2 min linear gradient to 80% buffer B, and maintenance at 80% buffer B for 4 min, finally return to 5% buffer B in 1 min. After liquid phase separation, the peptides were subjected to nanoelectrospray ionization follow by tandem mass spectrometry (MS/MS) in Q-EXACTIVE (Thermo Fisher Scientific, San Jose, CA) coupled online to the HPLC. Orbitrap detected intact peptides with a resolution of 70 000 and a mass range of 350‒2000 m/z. MS/MS analysis were recorded with a resolution of 17 500 and a mass range of 100‒1800 m/z. MS/MS analysis was required 15 most abundant precursor ions which above a threshold ion count of 20 000 in the MS survey scan, with a following dynamic exclusion duration of 15 s.
Data Processing Protocol
Data Analysis The MS raw data files were converted into MGF files using 5600 msconverter, and the MGF file were searched. Proteins identification was performed by using Mascot search engine (Matrix Science, London, UK; version 2.3.02) against the Uniport database containing pig protein sequences. The precursor mass tolerance was set as 0.05 Da, and 0.1 Da for fragmented mass tolerance to prevent precursor interference. Gln- > pyro-Glu (N-term Q), Oxidation (M), Deamidated (NQ) as the potential variable modifications, and Carbamidomethyl (C), iTRAQ8plex (N-term), iTRAQ8plex (K) as fixed modifications. The charge states of peptides were set to +2 and +3. Specifically, an automatic decoy database search was performed in Mascot by choosing the decoy checkbox in which a random sequence of database was generated and tested for raw spectra as well as the real database. To reduce the probability of false peptide identification, only peptide at the 95 % confidence interval by a Mascot probability analysis greater than “identity” were counted as identified, and each confident protein identification was supported by at least one unique peptide. For protein quantitation, it was required that a protein contains at least two unique spectra. A quantitative protein with a ratio >1.2 or <0.83 and the p value < 0.05 was regarded as differentially expressed protein. Differentially expressed proteins were further analyzed by core analysis of the Ingenuity Pathway Analysis (IPA, www.ingenuity.com), including functional classification, network analysis, and pathway analysis. The information of subcellular localization was based on the Gene Ontology (GO) annotation (http://www.geneontology.org).
Long B, Yin C, Fan Q, Yan G, Wang Z, Li X, Chen C, Yang X, Liu L, Zheng Z, Shi M, Yan X. Global Liver Proteome Analysis Using iTRAQ Reveals AMPK-mTOR-Autophagy Signaling Is Altered by Intrauterine Growth Restriction in Newborn Piglets. J Proteome Res. 2016 Mar 11 PubMed: 26967195