Comparative proteome analysis of abdominal adipose tissues between fat and lean broilers
- Chun-Yan Wu†1,
- Yuan-Yuan Wu†1, 2,
- Chun-Dong Liu1,
- Yu-Xiang Wang1,
- Wei Na1,
- Ning Wang1Email author and
- Hui Li1Email author
© The Author(s). 2016
Received: 27 January 2016
Accepted: 16 August 2016
Published: 1 September 2016
The molecular mechanism underlying broiler fat deposition is still poorly understood.
Currently, we used two-dimensional gel electrophoresis (2DE) to identify differentially expressed proteins in abdominal adipose tissues of birds at 4 week of age derived from Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF).
Thirteen differentially expressed protein spots were screened out and identified by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The protein spots were matched to thirteen proteins by searching against the NCBInr database. These identified proteins were apolipoprotein A-I (Apo A-I), cytokeratin otokeratin, ATP synthase subunit alpha, peptidyl-prolyl cis-trans isomerase FKBP4 (PPIase FKBP4), aspartate aminotransferase, carbonic anhydrase II (CA-II), prostaglandin-H2 D-isomerase precursor, fibrinogen alpha chain, lamin-A (LMNA), superoxide dismutase [Mn] (MnSOD), heat shock protein beta-1 (HSPβ1) and two predicted proteins. These differentially expressed proteins are involved mainly in lipid metabolism, amino acid metabolism, signal transduction, energy conversion, antioxidant, and cytoskeleton. Differential expression of Apo A-I, PPIase FKBP4, and cytokeratin otokeratin proteins were further confirmed by Western blot analysis. Quantitative real-time RT-PCR analyses showed that, of these 13 differentially expressed proteins, only PPIase FKBP4 and cytokeratin otokeratin were differentially expressed at mRNA level between the two lines.
Our results have provided further information for understanding the basic genetics control of growth and development of broiler adipose tissue.
Great progress has been made in poultry breeding in the past half century. Daily gain and feed conversion have been improved considerably; however, in commercial flocks, the improved productive performance is accompanied by high percentages of body fat content and some other negative effects that bring huge economic losses to the broiler industry . Controlling fat deposition has been one of the major goals in the broiler breeding industry.
Adipose tissue not only serves as a fat storage site, but also as an endocrine organ that plays roles in a wide range of cellular processes including lipid metabolism and glucose homeostasis . In chicken, abdominal adipose tissue is the main tissue of body fat accumulation, accounting for about 22 % of total body fat . To control broiler fat deposition, it is necessary to understand gene expression and its regulation during adipose tissue development. Gene expression profiling of chicken abdominal adipose tissue has been performed, and a number of differentially expressed genes have been identified between fat and lean chickens [4–8]. With the advent of proteomic technologies, comprehensive proteomic approaches have been widely used to identify and relatively quantify proteins.
In the present study, we compared protein expression profiles of abdominal adipose tissues of birds at 4 week of age derived from NEAUHLF, and found 13 differentially expressed proteins between fat and lean broilers. Our findings provide further information for understanding the molecular mechanism of broiler fat deposition.
Animal and abdominal adipose tissue samples collection
The NEAUHLF  was used in the current study. All animal work was conducted on the basis of the guidelines for the care and use of experimental animals established by the Ministry of Science and Technology of the People’s Republic of China (Approval number: 2006-398) and approved by the Laboratory Animal Management Committee of Northeast Agricultural University. All broilers were kept in similar environmental conditions and had free access to feed and water. Commercial corn-soybean-based diets, which met all the NRC requirements were provided to the broilers .
Body weight (BW), abdominal fat weigh (AFW) and abdominal fat percentage (AFP) of the fat and lean broilers at 4 weeks of age
Protein samples preparation for 2DE
Total protein was isolated from the abdominal adipose tissues by Trizol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocol with minor modifications . The samples were then dissolved in lysis buffer containing 8 M urea, 2 M thiourea, 4 % (wt/vol) 3-[(3-cholamidopropyl) dimethylammonio]-1-propanesulfonate, 2 % carrier ampholytes (pH 3 to 10, GE Healthcare, Uppsala, Sweden), 50 mM dithiothreitol (DTT), and 1× protease inhibitor cocktails (Roche Diagnostics GmbH, Mannheim, Germany). The original protein samples were centrifuged at 20,000 g for 1 h to remove insoluble materials. For 2DE, salt and other small molecular impurities were removed using the 2D Clean-Up Kit (GE Healthcare, Chalfont St Giles, UK). Total protein concentration was determined using a 2D Quant Kit (Amersham Biosciences Corp., Piscataway, NJ, USA) and the protein samples were then stored at -80 °C.
2DE and image analyses
Protein samples were rehydrated at 650 μg/gel in 350 μL of rehydration solution containing 7 M urea, 2 M thiourea, 4 % (wt/vol) 3-[(3-cholamidopropyl) dimethylammonio]-1-propanesulfonate, 50 mM DTT and 0.8 % carrier ampholytes (pH 3 to 10, GE Healthcare). First-dimension electrophoresis was conducted with the IPGphor3 isoelectric focusing system (GE Healthcare) using the dry IPG strips (18 cm pH 3 to 10 nonlinear, GE Healthcare). The program setting was as follows: 50 V for 12 h, 100 V for 1 h, 300 V for 1 h, linear gradient to 1000 V in 2.5 h, linear gradient to 8000 V in 2 h and 8000 V until approximately 60,000 Vh. After the first dimension, the IPG strips were equilibrated in SDS equilibration buffer containing 75 mM Tris-HCl, pH 8.8, 6 M urea, 30 % (v/v) glycerol, 2 % (w/v) SDS, bromophenol blue 1 % (w/v) for 15 min, followed by a second equilibration with 2.5 % iodoacetamide replacing the 2 % DTT for 15 min. After equilibration, the proteins were separated on 12.5 % Trisglycine gels using an Ettan Dalt Six Electrophoresis System (GE Healthcare) at 12 °C. Gels were run at constant power, first with two W/strip for 45 min and then 15 W/strip until the bromophenol blue reached the bottom of the gels. Then, the gels were stained by the blue silver method with coomassie blue brilliant G250 . Finally, six 2-DE gels were obtained.
Protein spot detection, volume calculation, matching, and the patterns were analyzed using Image Master 2D Platinum 6.0 software (GE Healthcare). The parameter used for the quantifications was the % of volume (%VOL: integration of the OD over the feature area (VOL) normalized by the total VOL over the whole image). Differentially expressed protein spots were considered significant if they showed >2-fold relative differences (P <0.05, Student’s t test) between the fat and lean lines.
Protein identification by MALDI-TOF-MS
After image analyses, the differentially expressed protein spots were selected and excised from the gels. The protein spots were subjected to tryptic proteolysis, and the resultant peptides were analyzed by matrix-assisted laser desorption- ionization time-of-flight mass spectrometry (MALDI-TOF-MS) as described previously . The resultant peptide mass fingerprint was searched against the NCBInr protein sequence databases using the Mascot search engine . The search parameters were as follows: enzyme search specificity was trypsin for tryptic digest; carbamidomethylation on cysteines was set as fixed modification while methionine oxidation was considered as variable modification; one miscleavage for each peptide was allowed; no restrictions on protein mass and peptide mass tolerance was ±100 ppm. A Mascot score with P <0.05 was considered statistically significant .
Western blot analysis
The abdominal adipose tissue was homogenized in radio immunoprecipitation assay (RIPA) buffer (1 g/L SDS, 5 g/L sodium deoxycholate, 10 g/L Nonidet P-40, 150 mmol/L NaCl, 50 mmol/L Tris-HCl, pH 8.0), supplemented with protease inhibitors (1 mmol/L phenylmethylsulfonyl fluoride, 0.002 g/L aprotinin and 0.002 g/L leupeptin). Cellular debris and lipids were eliminated by centrifuging the solubilized samples at 13,000 rpm for 60 min. The protein concentration of the samples was determined using a 2D Quant kit.
Protein samples were separated by SDS-PAGE and transferred to an Immun-Blot PVDF membrane (Millipore, Billerica, MA, USA). To block nonspecific binding, the membrane was incubated in blocking buffer (PBS with 5 % nonfat dry milk) for 1 h at room temperature. Membranes were immunoblotted with antibodies against Apo A-I (BIOSS, Beijing, China; 1:500 dilution), PPIase FKBP4 (ProteinTech Group, Chicago, IL, USA; 1: 500 dilution), and cytokeratin otokeratin (ProteinTech Group, Chicago, IL, USA; 1: 500 dilution) for 1 h at room temperature. After washing with PBS with 0.05 % Tween-20 (PBST), the membrane was immunoblotted with goat anti-rabbit IgG conjugated with horseradish peroxidase (1:5000) (ZSGB-BIO, Beijing, China) for 1 h at room temperature. Immunoreactive protein on the membrane was visualized using enhanced chemiluminescence and exposed to X-ray-film (Kodak, New York, NY, USA). β-actin (as the control) was detected first by mouse anti-chicken (β-actin) antibody (Beyotime Institute of Biotechnology, Jiangsu, China) and then by peroxidase-conjugated AffiniPure goat anti-mouse IgG (H + L; ZSGB-Bio). Immunoreactive protein levels were determined semi-quantitatively by densitometric analysis using the UVP system Labworks TM software 3.0 (UVP, Upland, CA, USA). Results were expressed as the relative quantity of Apo A-I/β-actin, PPIase FKBP4/β-actin and cytokeratin otokeratin/β-actin.
Real-time RT-PCR analyses
Primers used for the quantitative real-time RT-PCR analysis
All results were expressed as mean ± SD and analyzed by student’s t-test. Statistical analysis was performed using Prism 5.0 software (GraphPad Software Inc.). P < 0.05 was considered to be statistically significant.
Differentially expressed proteins between the fat and lean lines of broilers
Features of the 13 differentially expressed proteins identified by MALDI-TOF-M
Fibrinogen alpha chain
Carbonic anhydrase II
Predicted: growth Hormone-regulated TBC protein 1
Superoxide dismutase [Mn]
Predicted: transcription factor 24-like
ATP synthase subunit alpha
Peptidyl-prolyl cis-trans isomerase FKBP4
Amino acid metabolism
Prostaglandin-H2 D-isomerase precursor
Heat shock protein beta-1
Western blot analysis
Real-time RT-PCR analysis
The NEAUHLF provides an unique experimental model to study growth and development of chicken adipose tissue. In the present study, we identified thirteen differentially expressed proteins in abdominal adipose tissue between fat and lean lines of NEAUHLF at 4 weeks of age. The discovery of these differentially expressed proteins between the NEAUHLF fat and lean broiler lines may provide useful clues for understanding the molecular mechanism of broiler abdominal fat deposition.
Based on the biological process in which they are involved, these differentially expressed proteins could be classified into six categories: lipid metabolism (Apo A-I and prostaglandin-H2 D-isomerase precursor), amino acid metabolism (aspartate aminotransferase), signal transduction (fibrinogen alpha chain and CA-II), energy conversion (ATP synthase subunit alpha), antioxidant (HSPβ1, PPIase FKBP4 and MnSOD), and cytoskeleton (LMNA and cytokeratin otokeratin).
Apo A-I is an important lipid-binding protein, and is the major constituent of high-density lipoprotein (HDL) cholesterol . It plays important roles in preventing lipid accumulation in tissues and in maintaining cholesterol dynamic balance [17, 18]. Genetic deficiency in Apo A-I has been associated with excessive cholesterol accumulation in human and poultry [19–21]. Association studies showed that a single nucleotide polymorphism (SNP) upstream of the ATG initiation codon of the chicken Apo A-I gene was associated with abdominal fat weight and abdominal fat percentage . Our previous proteomic analysis results showed that Apo A-I protein was down-regulated in the abdominal adipose tissue of fat broilers compared with the lean broilers at 7 weeks of age . In the present study, we also observed that Apo A-I was down-regulated in abdominal adipose tissue of the fat broilers. Taken together, these data suggest that the differential protein expression of Apo A-I in the two divergently selected lines may be partially responsible for the difference in abdominal fat deposition between the two broiler lines.
Prostaglandin-H2 D-isomerase precursor is an essential enzyme in arachidonic acid metabolism. It catalyzes the conversion of prostaglandin-H2 to prostaglandin-D2 . One of the dehydration products of prostaglandin-D2 is 15-deoxy-Δ [12, 14]-prostaglandin J2 (15d-PGJ2) , which binds directly to peroxisome proliferator-activated receptor γ (PPARγ) and promotes efficient adipocyte differentiation . These findings, combined with the results reported here, suggest that the differential expression of prostaglandin-H2 D-isomerase precursor may contribute to the phenotype difference between the fat and lean broiler lines.
Aspartate aminotransferase 1 is involved in adipocyte glyceroneogenesis, which controls fatty acid homeostasis by promoting glycerol 3-phosphate formation for fatty acid re-esterification when the supply of glucose is reduced . The expression of aspartate aminotransferase 1 is specifically induced by glucose deprivation and rosiglitazone in adipocytes, but it is not directly regulated by PPARγ . In the present study, aspartate aminotransferase 1 was more highly expressed in the lean chickens than in the fat chickens. The differential expression of aspartate aminotransferase 1 may reflect the difference in adipocyte glyceroneogenesis in the two chicken lines.
Fibrinogen alpha chain and CA-II are involved in signal transduction. Fibrinogen alpha chain is an important component of fibrinogen . Kim et al. found that plasma fibrinogen was significantly higher in obese groups compared with in non-obese groups using 2DE and MS, and proposed plasma fibrinogen as a new biomarker of obesity . Fibrinogen is regulated by interleukin-6 (IL-6) in adipose tissue and adipose tissue IL-6 expression was shown to be positively correlated with obesity. IL-6 was found to be the major regulator of fibrinogen, and stimulated fibrinogen synthesis . In high fat diet-induced atherosclerosis in rabbits, high levels of IL-6 and fibrinogen were detected in the plasma . In the present study, we also observed that fibrinogen alpha chain was up-regulated in the abdominal adipose tissue of the fat birds. Taken together, our data suggest fibrinogen alpha chain is involved in broiler fat deposition. Carbonic anhydrases (CAs) are a family of zinc metalloenzymes , which is critical to the entire process of fatty acid biosynthesis. A study in human adipose tissue showed that ethoxzolamide, an inhibitor of carbonic anhydrase, significantly reduced the conversion of pyruvate into carbon dioxide, glyceride-glycerol, and fatty acids . In the present study, CA-II was more highly expressed in the lean broilers than in the fat broilers, which is not in agreement with the human study results. This difference may be due to differences in fatty acid synthesis between mammals and birds. In mammals, adipose tissue is one of the major sites for fatty acid synthesis, whereas in birds, adipose tissue is not the major site for fatty acid synthesis, as most of the fatty acid synthesis in birds occurs in the liver.
ATP synthase is responsible for the synthesis of ATP from ADP and inorganic phosphate. Its alpha subunit is essential for its activity and mitochondrial membrane structure . In the present study, ATP synthase subunit alpha was down-regulated in the abdominal adipose tissue of fat birds compared to lean birds. This differential expression may reflect the difference in energy consumption between the fat and lean chicken lines.
Antioxidant enzymes play important roles in oxidative stress resistance. Animals have a complex network of antioxidant proteins that work together to prevent oxidative damage to cellular components such as proteins and lipids . Antioxidants either prevent reactive species from being formed, or remove them before they damage cell components . Adipogenesis is involved in adipocyte hypertrophy and hyperplasia. In human and mouse, adipocyte hypertrophy is correlated with increased oxidant stress and low-grade inflammation, and both are linked to disturbed cellular redox . In the present study, the antioxidant proteins (HSPβ1, PPIase FKBP4 and MnSOD) were differentially expressed between the fat and lean broilers, suggesting that adipose oxidative stress is different in the two chicken lines.
Two cytoskeleton proteins, LMNA and cytokeratin otokeratin, were found to be differentially expressed in adipose tissue between the fat and lean broiler lines in this study. LMNA plays a role in maintaining nuclear stability and chromatin structure . Mutations in the LMNA gene were associated with familial partial lipodystrophy . Further studies have shown that LMNA interacts with the adipocyte differentiation factor, sterol regulatory element-binding protein 1 (SREBP-1), and that the reduced binding of LMNA to SREBP1 may be the cause of the familial partial lipodystrophy . Another cytoskeleton, cytokeratin otokeratin, was first detected in the tegmentum vasculosum in chicken . In the present study, we observed that cytokeratin otokeratin was up-regulated in abdominal adipose tissue of the lean birds compared to the fat birds at 4 weeks of age, consistent with our previous proteomic study of adipose tissue in the same two lines at 7 weeks of age . Taken together, the differential protein expression of LMNA and cytokeratin otokeratin suggests that these two proteins are involved in chicken fat deposition.
In addition to the 11 proteins discussed above, transcription factor 24-like and growth hormone-regulated TBC protein 1 were identified by automated computational analysis. The functions of these two predicted proteins remain to be investigated.
It is noteworthy that in the present study, of these thirteen differentially expressed proteins, only two (PPIase FKBP4 and cytokeratin otokeratin) showed consistent expression results at both the mRNA and protein levels. Poor correlation between protein and mRNA levels has been reported in several genomic, transcriptomic and proteomic studies [42, 43]. There are several possible explanations for this poor correlation. One possible explanation is the complicated and varied post-transcriptional gene regulatory mechanisms, for example, microRNAs can inhibit protein synthesis either by repressing translation or by inducing mRNA degradation [44, 45]. Another possible explanation is that in vivo protein half-lives may differ substantially, and the protein half-lives can vary under different conditions . A third possible explanation is our study’s limitation. In the present study, due to the experimental cost, we used a small number (n = 3) of biological replicates of the lean and fat broiler lines. Despite the limitation, our study provides the potentially differentially expressed proteins in abdominal adipose tissue between lean and fat broilers.
In the study, we identified 13 proteins that were differentially expressed in abdominal adipose tissue between the fat and lean broiler lines. Of these proteins, one protein (fibrinogen alpha chain) was more highly expressed in fat broilers, while the other 12 proteins were more highly expressed in lean broilers. All or some of these differentially expressed proteins may be responsible for the phenotype difference between the fat and lean broiler lines.
The study was supported by the National 863 project of China (No. 2013AA102501), the National Basic Research Program of China (973 Program) (No.2009CB941604), the China Agriculture Research System (No.CARS-42) and the Program for Innovation Research Team at the University of Heilongjiang Province (No. 2010td02).
The study was supported by the National 863 project of China (No. 2013AA102501), the National Basic Research Program of China (973 Program) (No.2009CB941604), the China Agriculture Research System (No.CARS-42) and the Program for Innovation Research Team at the University of Heilongjiang Province (No. 2010td02). The funders had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.
Availability of data and materials
All data generated during this study are included in this article.
CYW performed Western blot experiment, participated in data analyses and wrote the manuscript. YYW and CDL carried out the 2DE experiment, participated in MALDI-TOF-MS data analyses, and modified the manuscript. YXW participated in the design of the studies. WN carried out Real-time RT-PCR experiment. HL and NW conceived the study, participated in its design, coordination and helped to draft the manuscript. All authors critically revised the manuscript for important intellectual contents and approved the final manuscript.
The authors declared that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
All animal work was conducted on the basis of the guidelines for the care and use of experimental animals established by the Ministry of Science and Technology of the People’s Republic of China (Approval number: 2006-398) and approved by the Laboratory Animal Management Committee of Northeast Agricultural University.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Baéza E, Le Bihan-Duval E. Chicken lines divergent for low or high abdominal fat deposition: a relevant model to study the regulation of energy metabolism. Animal. 2013;7:965–73.View ArticlePubMedGoogle Scholar
- Galic S, Oakhill JS, Steinberg GR. Adipose tissue as an endocrine organ. Mol Cell Endocrinol. 2010;316:129–39.View ArticlePubMedGoogle Scholar
- Picard FH, Rouvier R, Marche G, Melin JM. Étude de la composition anatomique du poulet. III. – Variabilité de la répartition des parties corporelles dans une souche de type cornish. Genet. Sel. Evol. 1969;1:1–15.Google Scholar
- Wang H, Li H, Wang Q, Zhang X, Wang S, Wang Y, et al. Profiling of chicken adipose tissue gene expression by genome array. BMC Genomics. 2007;8:193.View ArticlePubMedPubMed CentralGoogle Scholar
- Wang H, Li H, Wang Q, Wang Y, Han H, Shi H. Microarray analysis of adipose tissue gene expression profiles between two chicken breeds. J Biosci. 2006;31:565–73.View ArticlePubMedGoogle Scholar
- Larkina TA, Sazanova AL, Fomichev KA, Olu B, Sazanov AA, Malewski T, et al. Expression profiling of candidate genes for abdominal fat mass in domestic chicken Gallus gallus. Genetika. 2011;47:1140–4.PubMedGoogle Scholar
- Ji B, Middleton JL, Ernest B, Saxton AM, Lamont SJ, Campagna SR, et al. Molecular and metabolic profiles suggest that increased lipid catabolism in adipose tissue contributes to leanness in domestic chickens. Physiol Genomics. 2014;46:315–27.View ArticlePubMedGoogle Scholar
- Wang D, Wang N, Li N, Li H. Identification of differentially expressed proteins in adipose tissue of divergently selected broilers. Poult Sci. 2009;88:2285–92.View ArticlePubMedGoogle Scholar
- Guo L, Sun B, Shang Z, Leng L, Wang Y, Wang N, et al. Comparison of adipose tissue cellularity in chicken lines divergently selected for fatness. Poult Sci. 2011;90:2024–34.View ArticlePubMedGoogle Scholar
- Berg L, Bearse G. Nutrient requirements of poultry. Poult Sci. 1962;41:1328–35.View ArticleGoogle Scholar
- Young C, Truman P. Proteins isolated with TRIzol are compatible with two-dimensional electrophoresis and mass spectrometry analyses. Anal Biochem. 2012;421:330–2.View ArticlePubMedGoogle Scholar
- Candiano G, Bruschi M, Musante L, Santucci L, Ghiggeri GM, Carnemolla B, et al. Blue silver: a very sensitive colloidal Coomassie G‐250 staining for proteome analysis. Electrophoresis. 2004;25:1327–33.View ArticlePubMedGoogle Scholar
- Hindré T, Didelot S, Le Pennec J-P, Haras D, Dufour A, Vallée-Réhel K. Bacteriocin detection from whole bacteria by matrix-assisted laser desorption ionization-time of flight mass spectrometry. Appl Environ Microbiol. 2003;69:1051–8.View ArticlePubMedPubMed CentralGoogle Scholar
- Cottrell JS, London U. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis. 1999;20:3551–67.View ArticlePubMedGoogle Scholar
- Koenig T, Menze BH, Kirchner M, Monigatti F, Parker KC, Patterson T, et al. Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics. J Proteome Res. 2008;7:3708–17.View ArticlePubMedGoogle Scholar
- Barbaras R, Puchois P, Fruchart J, Ailhaud G. Cholesterol efflux from cultured adipose cells is mediated by LpA I particles but not by LpA I: A II particles. Biochem Biophys Res Commun. 1987;142:63–9.View ArticlePubMedGoogle Scholar
- Zannis VI, Chroni A, Krieger M. Role of apoA-I, ABCA1, LCAT, and SR-BI in the biogenesis of HDL. J Mol Med (Berl). 2006;84:276–94.View ArticleGoogle Scholar
- Zannis VI, Fotakis P, Koukos G, Kardassis D, Ehnholm C, Jauhiainen M, et al. HDL biogenesis, remodeling, and catabolism. Handb Exp Pharmacol. 2015;224:53–111.View ArticlePubMedGoogle Scholar
- Rosales C, Patel N, Gillard BK, Yelamanchili D, Yang Y, Courtney HS, et al. Apolipoprotein AI deficiency inhibits serum opacity factor activity against plasma high density lipoprotein via a stabilization mechanism. Biochemistry. 2015;54:2295–302.View ArticlePubMedPubMed CentralGoogle Scholar
- DiDonato JA, Aulak K, Huang Y, Wagner M, Gerstenecker G, Topbas C, et al. Site-specific nitration of apolipoprotein AI at tyrosine 166 is both abundant within human atherosclerotic plaque and dysfunctional. J Biol Chem. 2014;289:10276–92.View ArticlePubMedPubMed CentralGoogle Scholar
- Kiss RS, Ryan RO, Francis GA. Functional similarities of human and chicken apolipoprotein AI: dependence on secondary and tertiary rather than primary structure. Biochim Biophys Acta. 2001;1531:251–9.View ArticlePubMedGoogle Scholar
- Wang Q, Li H, Li N, Leng L, Wang G, Ao J, et al. Polymorphisms of Apo-AI gene associated with growth and body composition traits in chicken. Acta Vet Zootech Sin. 2005;36:751–4.Google Scholar
- Joo M, Sadikot RT. PGD Synthase and PGD2 in Immune Resposne. Mediators Inflamm. 2012;2012:503128.View ArticlePubMedPubMed CentralGoogle Scholar
- Zhu F, Wang P, Kontrogianni-Konstantopoulos A, Konstantopoulos K, Prostaglandin PG. D2 and 15-deoxy-Δ12, 14-PGJ2, but not PGE2, mediate shear-induced chondrocyte apoptosis via protein kinase a-dependent regulation of polo-like kinases. Cell Death Differ. 2010;17:1325–34.View ArticlePubMedPubMed CentralGoogle Scholar
- Kliewer SA, Lenhard JM, Willson TM, Patel I, Morris DC, Lehmann JM. A prostaglandin J 2 metabolite binds peroxisome proliferator-activated receptor γ and promotes adipocyte differentiation. Cell. 1995;83:813–9.View ArticlePubMedGoogle Scholar
- Plee-Gautier E, Aggerbeck M, Beurton F, Antoine Bnd, Grimal H, Barouki R, et al. Identification of an adipocyte-specific negative glucose response region in the cytosolic aspartate aminotransferase gene. Endocrinology. 1998;139:4936–44.PubMedGoogle Scholar
- Tordjman J, Leroyer S, Chauvet G, Quette J, Chauvet C, Tomkiewicz C, et al. Cytosolic aspartate aminotransferase, a new partner in adipocyte glyceroneogenesis and an atypical target of thiazolidinedione. J Biol Chem. 2007;282:23591–602.View ArticlePubMedGoogle Scholar
- Grieninger G. Contribution of the αEC Domain to the Structure and Function of Fibrinogen‐420. Ann N Y Acad Sci. 2001;936:44–64.View ArticlePubMedGoogle Scholar
- Kim OY, Shin M-J, Moon J, Chung JH. Plasma ceruloplasmin as a biomarker for obesity: a proteomic approach. Clin Biochem. 2011;44:351–6.View ArticlePubMedGoogle Scholar
- Lei H, Xu J, Cheng LJ, Guo Q, Deng AM, Li YS. An increase in the cerebral infarction area during fatigue is mediated by il-6 through an induction of fibrinogen synthesis. Clinics (Sao Paulo). 2014;69:426–32.View ArticleGoogle Scholar
- Zhou B, Pan Y, Hu Z, Wang X, Han J, Zhou Q, et al. All-trans-retinoic acid ameliorated high fat diet-induced atherosclerosis in rabbits by inhibiting platelet activation and inflammation. J Biomed Biotechnol. 2012;2012:259693.PubMedPubMed CentralGoogle Scholar
- Supuran CT. Carbonic anhydrases-an overview. Curr Pharm Des. 2008;14:603–14.View ArticlePubMedGoogle Scholar
- Mekary RA, Giovannucci E, Willett WC, van Dam RM, Hu FB. Eating patterns and type 2 diabetes risk in men: breakfast omission, eating frequency, and snacking. Am J Clin Nutr. 2012;95:1182–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Baker LA, Watt IN, Runswick MJ, Walker JE, Rubinstein JL. Arrangement of subunits in intact mammalian mitochondrial ATP synthase determined by cryo-EM. Proc Natl Acad Sci. 2012;109:11675–80.View ArticlePubMedPubMed CentralGoogle Scholar
- Vertuani S, Angusti A, Manfredini S. The antioxidants and pro-antioxidants network: an overview. Curr Pharm Des. 2004;10:1677–94.View ArticlePubMedGoogle Scholar
- Rochette L, Lorin J, Zeller M, Guilland JC, Lorgis L, Cottin Y, et al. Nitric oxide synthase inhibition and oxidative stress in cardiovascular diseases: possible therapeutic targets? Pharmacol Ther. 2013;140:239–57.View ArticlePubMedGoogle Scholar
- Guo W, Li Y, Liang W, Wong S, Apovian C, Kirkland JL, et al. Beta-mecaptoethanol suppresses inflammation and induces adipogenic differentiation in 3T3-F442A murine preadipocytes. PLoS One. 2012;7, e40958.View ArticlePubMedPubMed CentralGoogle Scholar
- Gonzalez-Suarez I, Gonzalo S. Nurturing the genome: A-type lamins preserve genomic stability. Nucleus. 2010;1:129–35.PubMedGoogle Scholar
- Shackleton S, Lloyd DJ, Jackson SN, Evans R, Niermeijer MF, Singh BM, et al. LMNA, encoding lamin A/C, is mutated in partial lipodystrophy. Nat Genet. 2000;24:153–6.View ArticlePubMedGoogle Scholar
- DubandGoulet I, Woerner S, Gasparini S, Attanda W, Kondé E, TellierLebègue C, et al. Subcellular localization of SREBP1 depends on its interaction with the C-terminal region of wild-type and disease related A-type lamins. Exp Cell Res. 2011;317:2800–13.View ArticleGoogle Scholar
- Heller S, Sheane CA, Javed Z, Hudspeth A. Molecular markers for cell types of the inner ear and candidate genes for hearing disorders. Proc Natl Acad Sci. 1998;95:11400–5.View ArticlePubMedPubMed CentralGoogle Scholar
- Tian Q, Stepaniants SB, Mao M, Weng L, Feetham MC, Doyle MJ, et al. Integrated genomic and proteomic analyses of gene expression in mammalian cells. Mol Cell Proteomics. 2004;3:960–9.View ArticlePubMedGoogle Scholar
- Schwanhäusser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, et al. Global quantification of mammalian gene expression control. Nature. 2011;473:337–42.View ArticlePubMedGoogle Scholar
- Eulalio A, Huntzinger E, Izaurralde E. Getting to the root of miRNA-mediated gene silencing. Cell. 2008;132:9–14.View ArticlePubMedGoogle Scholar
- Filipowicz W, Bhattacharyya SN, Sonenberg N. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet. 2008;9:102–14.View ArticlePubMedGoogle Scholar
- Glickman MH, Ciechanover A. The ubiquitin-proteasome proteolytic pathway: destruction for the sake of construction. Physiol Rev. 2002;82:373–428.View ArticlePubMedGoogle Scholar