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Marín-García PJ, Llobat L, Cambra-López M, Blas E, Larsen T, Pascual JJ, Hedemann MS. Biomarkers for ideal protein: rabbit diet metabolomics varying key amino acids. Commun Biol 2024; 7:712. [PMID: 38858508 PMCID: PMC11164918 DOI: 10.1038/s42003-024-06322-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 05/13/2024] [Indexed: 06/12/2024] Open
Abstract
With the main aim of identifying biomarkers that contribute to defining the concept of ideal protein in growing rabbits under the most diverse conditions possible this work describes two different experiments. Experiment 1: 24 growing rabbits are included at 56 days of age. The rabbits are fed ad libitum one of the two experimental diets only differing in lysine levels. Experiment 2: 53 growing rabbits are included at 46 days of age, under a fasting and eating one of the five experimental diets, with identical chemical composition except for the three typically limiting amino acids (being fed commercial diets ad libitum in both experiments). Blood samples are taken for targeted and untargeted metabolomics analysis. Here we show that the metabolic phenotype undergoes alterations when animals experience a rapid dietary shift in the amino acid levels. While some of the differential metabolites can be attributed directly to changes in specific amino acids, creatinine, urea, hydroxypropionic acid and hydroxyoctadecadienoic acid are suggested as a biomarker of amino acid imbalances in growing rabbits' diets, since its changes are not attributable to a single amino acid. The fluctuations in their levels suggest intricate amino acid interactions. Consequently, we propose these metabolites as promising biomarkers for further research into the concept of the ideal protein using rabbit as a model.
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Affiliation(s)
- Pablo Jesús Marín-García
- Department of Animal Production and Health, Veterinary Public Health and Food Science and Technology (PASAPTA), Institute of Biomedical Sciences, Cardenal Herrera-CEU University, CEU Universities, Valencia, Spain.
| | - Lola Llobat
- Department of Animal Production and Health, Veterinary Public Health and Food Science and Technology (PASAPTA), Institute of Biomedical Sciences, Cardenal Herrera-CEU University, CEU Universities, Valencia, Spain
| | - María Cambra-López
- Institute for Animal Science and Technology, Universitat Politècnica de València, Valencia, Spain
| | - Enrique Blas
- Institute for Animal Science and Technology, Universitat Politècnica de València, Valencia, Spain
| | - Torben Larsen
- Department of Animal and Veterinary Sciences, Aarhus University, Tjele, Denmark
| | - Juan José Pascual
- Institute for Animal Science and Technology, Universitat Politècnica de València, Valencia, Spain.
| | - Mette Skou Hedemann
- Department of Animal and Veterinary Sciences, Aarhus University, Tjele, Denmark
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Li Y, Zeng L. Comparison of seven anthropometric indexes to predict hypertension plus hyperuricemia among U.S. adults. Front Endocrinol (Lausanne) 2024; 15:1301543. [PMID: 38524637 PMCID: PMC10958198 DOI: 10.3389/fendo.2024.1301543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/05/2024] [Indexed: 03/26/2024] Open
Abstract
Purpose This study aims to compare the association of hypertension plus hyperuricemia (HTN-HUA) with seven anthropometric indexes. These include the atherogenic index of plasma (AIP), lipid accumulation product (LAP), visceral adiposity index (VAI), triglyceride-glucose index (TyG), body roundness index (BRI), a body shape index (ABSI), and the cardiometabolic index (CMI). Methods Data was procured from the National Health and Nutrition Examination Survey (NHANES), which recruited a representative population aged 18 years and above to calculate these seven indexes. Logistic regression analysis was employed to delineate their correlation and to compute the odds ratios (OR). Concurrently, receiver operating characteristic (ROC) curves were utilized to evaluate the predictive power of the seven indexes. Results A total of 23,478 subjects were included in the study. Among these, 6,537 (27.84%) were patients with HUA alone, 2,015 (8.58%) had HTN alone, and 2,836 (12.08%) had HTN-HUA. The multivariate logistic regression analysis showed that the AIP, LAP, VAI, TyG, BRI, ABSI, and CMI were all significantly associated with concurrent HTN-HUA. The OR for the highest quartile of the seven indexes for HTN-HUA were as follows: AIP was 4.45 (95% CI 3.82-5.18), LAP was 9.52 (95% CI 7.82-11.59), VAI was 4.53 (95% CI 38.9-5.28), TyG was 4.91 (95% CI 4.15-5.80), BRI was 9.08 (95% CI 7.45-11.07), ABSI was 1.71 (95% CI 1.45 -2.02), and CMI was 6.57 (95% CI 5.56-7.76). Notably, LAP and BRI demonstrated significant discriminatory abilities for HTN-HUA, with area under the curve (AUC) values of 0.72 (95% CI 0.71 - 0.73) and 0.73 (95% CI 0.72 - 0.74) respectively. Conclusion The AIP, LAP, VAI, TyG, BRI, ABSI, and CMI all show significant correlation with HTN-HUA. Notably, both LAP and BRI demonstrate the capability to differentiate cases of HTN-HUA. Among these, BRI is underscored for its effective, non-invasive nature in predicting HTN-HUA, making it a superior choice for early detection and management strategies.
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Affiliation(s)
- Ye Li
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
- West China School of Nursing, Sichuan University, Chengdu, China
| | - Ling Zeng
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
- West China School of Nursing, Sichuan University, Chengdu, China
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3
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Park AC, Chan CK, Hutchison DM, Patel U, Hong EM, Steward E, Dilley KK, Sterritt NL, Kim S, Hill MG, You JS, Wong BJF. In vivo electrochemical lipolysis of fat in a Yucatan pig model: A proof of concept study. Lasers Surg Med 2023; 55:135-145. [PMID: 36511512 DOI: 10.1002/lsm.23620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 11/01/2022] [Accepted: 11/26/2022] [Indexed: 12/15/2022]
Abstract
OBJECTIVES Traditional fat contouring is now regularly performed using numerous office- based less invasive techniques. However, some limitations of these minimally invasive techniques include high cost or limited selectivity with performing localized contouring and reduction of fat. These shortcomings may potentially be addressed by electrochemical lipolysis (ECLL), a novel approach that involves the insertion of electrodes into tissue followed by application of a direct current (DC) electrical potential. This results in the hydrolysis of tissue water creating active species that lead to fat necrosis and apoptosis. ECLL can be accomplished using a simple voltage-driven system (V-ECLL) or a potential-driven feedback cell (P-ECLL) both leading to water electrolysis and the creation of acid and base in situ. The aim of this study is to determine the long-lasting effects of targeted ECLL in a Yucatan pig model. METHODS A 5-year-old Yucatan pig was treated with both V-ECLL and P-ECLL in the subcutaneous fat layer using 80:20 platinum:iridium needle electrodes along an 8 cm length. Dosimetry parameters included 5 V V-ECLL for 5, 10, and 20 minutes, and -1.5 V P-ECLL, -2.5 V P-ECLL, -3.5 V P-ECLL for 5 minutes. The pig was assessed for changes in fat reduction over 3 months with digital photography and ultrasound. After euthanasia, tissue sections were harvested and gross pathology and histology were examined. RESULTS V-ECLL and P-ECLL treatments led to visible fat reduction (12.1%-27.7% and 9.4%-40.8%, respectively) and contour changes across several parameters. An increased reduction of the superficial fat layer occurred with increased dosimetry parameters with an average charge transfer of 12.5, 24.3, and 47.5 C transferred for 5 V V-ECLL for 5, 10, and 20 minutes, respectively, and 2.0, 11.5, and 24.0 C for -1.5 V P-ECLL, -2.5 V P-ECLL, -3.5 V P-ECLL for 5 minutes, respectively. These dose-dependent changes were also evidenced by digital photography, gross pathology, ultrasound imaging, and histology. CONCLUSIONS ECLL results in selective damage and long-lasting changes to the adipose layer in vivo. These changes are dose-dependent, thus allowing for more precise contouring of target areas. P-ECLL has greater efficiency and control of total charge transfer compared to V-ECLL, suggesting that a low-voltage potentiostat treatment can result in fat apoptosis equivalent to a high-voltage DC system.
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Affiliation(s)
- Asher C Park
- Beckman Laser Institute & Medical Clinic, University of California-Irvine, Irvine, California, USA
| | - Carmen K Chan
- Department of Otolaryngology-Head and Neck Surgery, School of Medicine, University of California-Irvine, Orange, California, USA
| | - Dana M Hutchison
- Beckman Laser Institute & Medical Clinic, University of California-Irvine, Irvine, California, USA
| | - Urja Patel
- Beckman Laser Institute & Medical Clinic, University of California-Irvine, Irvine, California, USA
| | - Ellen M Hong
- School of Medicine, Hackensack Meridian, Nutley, New Jersey, USA
| | - Earl Steward
- Department of Surgery, School of Medicine, University of California-Irvine, Orange, California, USA
| | - Katelyn K Dilley
- Beckman Laser Institute & Medical Clinic, University of California-Irvine, Irvine, California, USA
| | - Naya L Sterritt
- Department of Biomedical Engineering, University of California-Irvine, Irvine, California, USA
| | - Sehwan Kim
- Department of Biomedical Engineering, Beckman Laser Institute, Korea, Dankook University, Cheonan-si, Chungnam, Republic of Korea
| | - Michael G Hill
- Department of Chemistry, Occidental College, Los Angeles, California, USA
| | - Joon S You
- eLysis Inc., Laguna Niguel, California, USA
| | - Brian J F Wong
- Beckman Laser Institute & Medical Clinic, University of California-Irvine, Irvine, California, USA.,Department of Otolaryngology-Head and Neck Surgery, School of Medicine, University of California-Irvine, Orange, California, USA.,Department of Biomedical Engineering, University of California-Irvine, Irvine, California, USA
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4
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Despite similar clinical features metabolomics reveals distinct signatures in insulin resistant and progressively obese minipigs. J Physiol Biochem 2022. [DOI: 10.1007/s13105-022-00940-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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Chen Z, Sun Y, Chen L, Zhang Y, Wang J, Li H, Yan X, Xia L, Yao G. Differences in meat quality between Angus cattle and Xinjiang brown cattle in association with gut microbiota and its lipid metabolism. Front Microbiol 2022; 13:988984. [PMID: 36560955 PMCID: PMC9763702 DOI: 10.3389/fmicb.2022.988984] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 11/14/2022] [Indexed: 12/12/2022] Open
Abstract
Gut microbiota plays important roles in mediating fat metabolic events in humans and animals. However, the differences of meat quality traits related to the lipid metabolism (MQT-LM) in association with gut microbiota involving in lipid metabolism have not been well explored between Angus cattle (AG) and Xinjiang brown cattle (BC). Ten heads of 18-month-old uncastrated male AG and BC (5 in each group) raised under the identical conditions were selected to test MQT-LM, i.e., the backfat thickness (BFT), the intramuscular fat (IMF) content, the intramuscular adipocyte areas (IAA), the eye muscle area (EMA), the muscle fiber sectional area (MFSA) and the muscle shear force after sacrifice. The gut microbiota composition and structure with its metabolic function were analyzed by means of metagenomics and metabolomics with rectal feces. The correlation of MQT-LM with the gut microbiota and its metabolites was analyzed. In comparison with AG, BC had significant lower EMA, IMF content and IAA but higher BFT and MFSA. Chao1 and ACE indexes of α-diversity were lower. β-diversity between AG and BC were significantly different. The relative abundance of Bacteroidetes, Prevotella and Blautia and Prevotella copri, Blautia wexlerae, and Ruminococcus gnavus was lower. The lipid metabolism related metabolites, i.e., succinate, oxoglutaric acid, L-aspartic acid and L-glutamic acid were lower, while GABA, L-asparagine and fumaric acid were higher. IMF was positively correlated with Prevotella copri, Blautia wexlerae and Ruminococcus gnavus, and the metabolites succinate, oxoglutaric acid, L-aspartic acid and L-glutamic acid, while negatively with GABA, L-asparagine and fumaric acid. BFT was negatively correlated with Blautia wexlerae and the metabolites succinate, L-aspartic acid and L-glutamic acid, while positively with GABA, L-asparagine and fumaric acid. Prevotella Copri, Blautia wexlerae, and Ruminococcus gnavus was all positively correlated with succinate, oxoglutaric acid, while negatively with L-asparagine and fumaric acid. In conclusion, Prevotella copri, Prevotella intermedia, Blautia wexlerae, and Ruminococcus gnavus may serve as the potential differentiated bacterial species in association with MQT-LM via their metabolites of oxoglutaric acid, succinate, fumaric acid, L-aspartic acid, L-asparagine, L-glutamic acid and GABA between BC and AG.
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Affiliation(s)
- Zhuo Chen
- College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, China
| | - Yawei Sun
- College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, China
| | - Lijing Chen
- College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, China
| | - Yang Zhang
- Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Jinquan Wang
- College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, China
| | - Hongbo Li
- Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Xiangming Yan
- Institute of Animal Science, Xinjiang Academy of Animal Sciences, Urumqi, China
| | - Lining Xia
- College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, China,Xinjiang Key Laboratory of New Drug Study and Creation for Herbivorous Animals (XJKLNDSCHA), Xinjiang Agricultural University, Urumqi, China,*Correspondence: Lining Xia,
| | - Gang Yao
- College of Veterinary Medicine, Xinjiang Agricultural University, Urumqi, China,Xinjiang Key Laboratory of New Drug Study and Creation for Herbivorous Animals (XJKLNDSCHA), Xinjiang Agricultural University, Urumqi, China,Gang Yao,
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Cluzel GL, Ryan PM, Herisson FM, Caplice NM. High-fidelity porcine models of metabolic syndrome: a contemporary synthesis. Am J Physiol Endocrinol Metab 2022; 322:E366-E381. [PMID: 35224983 DOI: 10.1152/ajpendo.00413.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
This review aims to describe and compare porcine models of metabolic syndrome. This syndrome and its associated secondary comorbidities are set to become the greatest challenge to healthcare providers and policy makers in the coming century. However, an incomplete understanding of the pathogenesis has left significant knowledge gaps in terms of efficacious therapeutics. To further our comprehension and, in turn, management of metabolic syndrome, appropriate high-fidelity models of the disease complex are of great importance. In this context, our review aims to assess the most promising porcine models of metabolic syndrome currently available for their similarity to the human phenotype. In addition, we aim to highlight the strengths and shortcomings of each model in an attempt to identify the most appropriate application of each. Although no porcine model perfectly recapitulates the human metabolic syndrome, several pose satisfactory approximations. The Ossabaw miniature swine in particular represents a highly translatable model that develops each of the core parameters of the syndrome with many of the associated secondary comorbidities. Future high-fidelity porcine models of metabolic syndrome need to focus on secondary sequelae replication, which may require extended induction period to reveal.
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Affiliation(s)
- Gaston L Cluzel
- Centre for Research in Vascular Biology, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Paul M Ryan
- Centre for Research in Vascular Biology, University College Cork, Cork, Ireland
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Florence M Herisson
- Centre for Research in Vascular Biology, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Noel M Caplice
- Centre for Research in Vascular Biology, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
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Zhang L, Wang X, He Y, Cao J, Wang K, Lin H, Qu C, Miao J. Regulatory Effects of Functional Soluble Dietary Fiber from Saccharina japonica Byproduct on the Liver of Obese Mice with Type 2 Diabetes Mellitus. Mar Drugs 2022; 20:91. [PMID: 35200621 PMCID: PMC8877147 DOI: 10.3390/md20020091] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/14/2022] [Accepted: 01/18/2022] [Indexed: 02/01/2023] Open
Abstract
Though the relationship between dietary fiber and physical health has been investigated widely, the use of dietary fiber from marine plants has been investigated relatively rarely. The Saccharina japonica byproducts after the production of algin contain a large amount of insoluble polysaccharide, which will cause a waste of resources if ignored. Soluble dietary fiber (SDF)prepared from waste byproducts of Saccharina japonica by alkaline hydrolysis method for the first time had a wrinkled microscopic surface and low crystallinity, which not only significantly reduced liver index, serum levels of aspartate aminotransferase (AST) and alanine amiotransferase (ALT), and liver fat accumulation damage to the livers of obese diabetic mice, but also activated the PI3K/AKT signaling pathway to increase liver glycogen synthesis and glycolysis. By LC-MS/MS employing a Nexera UPLC tandem QE high-resolution mass spectrometer, the 6 potential biomarker metabolites were screened, namely glycerophosphocholine (GPC), phosphocholine (PCho), pantothenic acid, glutathione (GSH), oxidized glutathione (GSSG), and betaine; several pathways of these metabolites were associated with lipid metabolism, glycogen metabolism, and amino acid metabolism in the liver were observed. This study further provided a detailed insight into the mechanisms of SDF from Saccharina japonica byproducts in regulating the livers of obese mice with type 2 diabetes and laid a reliable foundation for the further development and utilization of Saccharina japonica.
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Affiliation(s)
- Liping Zhang
- Department of Special Medicine, School of Basic Medicine, Qingdao University, Qingdao 266071, China;
| | - Xixi Wang
- Key Laboratory of Marine Eco-Environmental Science and Technology, First Institute of Oceanography, Ministry of Natural Resource, Qingdao 266061, China; (X.W.); (Y.H.); (J.C.); (K.W.); (H.L.)
| | - Yingying He
- Key Laboratory of Marine Eco-Environmental Science and Technology, First Institute of Oceanography, Ministry of Natural Resource, Qingdao 266061, China; (X.W.); (Y.H.); (J.C.); (K.W.); (H.L.)
| | - Junhan Cao
- Key Laboratory of Marine Eco-Environmental Science and Technology, First Institute of Oceanography, Ministry of Natural Resource, Qingdao 266061, China; (X.W.); (Y.H.); (J.C.); (K.W.); (H.L.)
| | - Kai Wang
- Key Laboratory of Marine Eco-Environmental Science and Technology, First Institute of Oceanography, Ministry of Natural Resource, Qingdao 266061, China; (X.W.); (Y.H.); (J.C.); (K.W.); (H.L.)
| | - Huan Lin
- Key Laboratory of Marine Eco-Environmental Science and Technology, First Institute of Oceanography, Ministry of Natural Resource, Qingdao 266061, China; (X.W.); (Y.H.); (J.C.); (K.W.); (H.L.)
| | - Changfeng Qu
- Key Laboratory of Marine Eco-Environmental Science and Technology, First Institute of Oceanography, Ministry of Natural Resource, Qingdao 266061, China; (X.W.); (Y.H.); (J.C.); (K.W.); (H.L.)
- Laboratory for Marine Drugs and Bioproducts, Qingdao Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China
| | - Jinlai Miao
- Key Laboratory of Marine Eco-Environmental Science and Technology, First Institute of Oceanography, Ministry of Natural Resource, Qingdao 266061, China; (X.W.); (Y.H.); (J.C.); (K.W.); (H.L.)
- Laboratory for Marine Drugs and Bioproducts, Qingdao Pilot National Laboratory for Marine Science and Technology, Qingdao 266237, China
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Hallowell HA, Higgins KV, Roberts M, Johnson RM, Bayne J, Maxwell HS, Brandebourg T, Hiltbold Schwartz E. Longitudinal Analysis of the Intestinal Microbiota in the Obese Mangalica Pig Reveals Alterations in Bacteria and Bacteriophage Populations Associated With Changes in Body Composition and Diet. Front Cell Infect Microbiol 2021; 11:698657. [PMID: 34737972 PMCID: PMC8560744 DOI: 10.3389/fcimb.2021.698657] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 09/13/2021] [Indexed: 11/29/2022] Open
Abstract
Due to its immunomodulatory potential, the intestinal microbiota has been implicated as a contributing factor in the development of the meta-inflammatory state that drives obesity-associated insulin resistance and type 2 diabetes. A better understanding of this link would facilitate the development of targeted treatments and therapies to treat the metabolic complications of obesity. To this end, we validated and utilized a novel swine model of obesity, the Mangalica pig, to characterize changes in the gut microbiota during the development of an obese phenotype, and in response to dietary differences. In the first study, we characterized the metabolic phenotype and gut microbiota in lean and obese adult Mangalica pigs. Obese or lean groups were created by allowing either ad libitum (obese) or restricted (lean) access to a standard diet for 54 weeks. Mature obese pigs were significantly heavier and exhibited 170% greater subcutaneous adipose tissue mass, with no differences in muscle mass compared to their lean counterparts. Obese pigs displayed impaired glucose tolerance and hyperinsulinemia following oral glucose challenge, indicating that a metabolic phenotype also manifested with changes in body composition. Consistent with observations in human obesity, the gut microbiota of obese pigs displayed altered bacterial composition. In the second study, we characterized the longitudinal changes in the gut microbiota in response to diet and aging in growing Mangalica pigs that were either limit fed a standard diet, allowed ad libitum access to a standard diet, or allowed ad libitum access to a high fat-supplemented diet over an 18-week period. As expected, weight gain was highest in pigs fed the high fat diet compared to ad libitum and limit fed groups. Furthermore, the ad libitum and high fat groups displayed significantly greater adiposity consistent with the development of obesity relative to the limit fed pigs. The intestinal microbiota was generally resilient to differences in dietary intake (limit fed vs ad libitum), though changes in the microbiota of pigs fed the high fat diet mirrored changes observed in mature obese pigs during the first study. This is consistent with the link observed between the microbiota and adiposity. In contrast to intestinal bacterial populations, bacteriophage populations within the gut microbiota responded rapidly to differences in diet, with significant compositional changes in bacteriophage genera observed between the dietary treatment groups as pigs aged. These studies are the first to describe the development of the intestinal microbiota in the Mangalica pig, and are the first to provide evidence that changes in body composition and dietary conditions are associated with changes in the microbiome of this novel porcine model of obesity.
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Affiliation(s)
- Haley A Hallowell
- Department of Biological Sciences, Auburn University, College of Science and Mathematics, Auburn, AL, United States
| | - Keah V Higgins
- Department of Biological Sciences, Auburn University, College of Science and Mathematics, Auburn, AL, United States
| | - Morgan Roberts
- Department of Animal Sciences, College of Agriculture, Auburn University, Auburn, AL, United States
| | - Robert M Johnson
- Department of Biological Sciences, Auburn University, College of Science and Mathematics, Auburn, AL, United States
| | - Jenna Bayne
- Department of Clinical Sciences, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
| | - Herris Stevens Maxwell
- Department of Clinical Sciences, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
| | - Terry Brandebourg
- Department of Animal Sciences, College of Agriculture, Auburn University, Auburn, AL, United States
| | - Elizabeth Hiltbold Schwartz
- Department of Biological Sciences, Auburn University, College of Science and Mathematics, Auburn, AL, United States
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9
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Obesity Development and Signs of Metabolic Abnormalities in Young Göttingen Minipigs Consuming Energy Dense Diets Varying in Carbohydrate Quality. Nutrients 2021; 13:nu13051560. [PMID: 34066330 PMCID: PMC8148203 DOI: 10.3390/nu13051560] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 04/27/2021] [Accepted: 04/29/2021] [Indexed: 01/10/2023] Open
Abstract
Consumption of fructose has been associated with a higher risk of developing obesity and metabolic syndrome (MetS). The aim of this study was to examine the long-term effects of fructose compared to starch from high-amylose maize starch (HiMaize) at ad libitum feeding in a juvenile Göttingen Minipig model with 20% of the diet provided as fructose as a high-risk diet (HR, n = 15) and 20% as HiMaize as a lower-risk control diet (LR, n = 15). The intake of metabolizable energy was on average similar (p = 0.11) among diets despite increased levels of the satiety hormone PYY measured in plasma (p = 0.0005) of the LR pigs. However, after over 20 weeks of ad libitum feeding, no difference between diets was observed in daily weight gain (p = 0.103), and a difference in BW was observed only at the end of the experiment. The ad libitum feeding promoted an obese phenotype over time in both groups with increased plasma levels of glucose (p = 0.005), fructosamine (p < 0.001), insulin (p = 0.03), and HOMA-IR (p = 0.02), whereas the clinical markers of dyslipidemia were unaffected. When compared to the LR diet, fructose did not accelerate the progression of MetS associated parameters and largely failed to change markers that indicate a stimulated de novo lipogenesis.
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Abstract
Pigs represent a potentially attractive model for medical research. Similar body size and physiological patterns of kidney injury that more closely mimic those described in humans make larger animals attractive for experimentation. Using larger animals, including pigs, to investigate the pathogenesis of acute kidney injury (AKI) also serves as an experimental bridge, narrowing the gap between clinical disease and preclinical discoveries. This article compares the advantages and disadvantages of large versus small AKI animal models and provides a comprehensive overview of the development and application of porcine models of AKI induced by clinically relevant insults, including ischemia-reperfusion, sepsis, and nephrotoxin exposure. The primary focus of this review is to evaluate the use of pigs for AKI studies by current investigators, including areas where more information is needed.
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Affiliation(s)
- Jianni Huang
- Department of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
| | - George Bayliss
- Department of Medicine, Rhode Island Hospital and Alpert Medical School, Brown University, Providence, Rhode Island
| | - Shougang Zhuang
- Department of Nephrology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.,Department of Medicine, Rhode Island Hospital and Alpert Medical School, Brown University, Providence, Rhode Island
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van der Peet-Schwering CMC, Verschuren LMG, Hedemann MS, Binnendijk GP, Jansman AJM. Birth weight affects body protein retention but not nitrogen efficiency in the later life of pigs. J Anim Sci 2020; 98:5849889. [PMID: 32479590 DOI: 10.1093/jas/skaa180] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 05/25/2020] [Indexed: 01/10/2023] Open
Abstract
Exploring factors that might affect nitrogen (N) efficiency in pigs could support the development of precision feeding concepts. Therefore, an experiment was conducted to determine the effects of birth weight (BiW) on N retention, N efficiency, and concentrations of metabolites in plasma and urine related to N efficiency in male pigs of 14 wk of age. BiW of the low BiW (LBW) and high BiW (HBW) pigs was 1.11 ± 0.14 and 1.79 ± 0.12 kg, respectively. Twenty LBW and 20 HBW pigs were individually housed in metabolism cages and were subjected to an N balance study in two sequential periods of 5 d, after an 11-d adaptation period. Pigs were assigned to a protein adequate (A) or protein restricted (R, 70% of A) regime in a change-over design and fed restrictedly 2.8 times the energy requirements for maintenance. Nontargeted metabolomics analyses were performed in urine and blood plasma samples. The N retention in g/d was higher in the HBW than in the LBW pigs (P < 0.001). The N retention in g/(kg BW0.75·d) and N efficiency (= 100% × N retention / N intake), however, were not affected by BiW of the pigs. Moreover, fecal digestibility of N and urinary concentration of N and urea were not affected by BiW of the pigs. The concentration of insulin (P = 0.08) and insulin-like growth factor-1 (IGF-1;P = 0.05) in blood plasma was higher in HBW pigs, whereas the concentration of α-amino N tended to be lower in HBW pigs (P = 0.06). The LBW and HBW pigs could not be discriminated based on the plasma and urinary metabolites retrieved by nontargeted metabolomics. Restricting dietary protein supply decreased N retention (P < 0.001), N efficiency (P = 0.07), fecal N digestibility (P < 0.001), urinary concentration of N and urea (P < 0.001), and concentration of urea (P < 0.001), IGF-1 (P < 0.001), and α-amino N (P < 0.001) in blood plasma. The plasma and urinary metabolites differing between dietary protein regime were mostly amino acids (AA) or their derivatives, metabolites of the tricarboxylic acid cycle, and glucuronidated compounds, almost all being higher in the pigs fed the A regime. This study shows that BiW affects absolute N retention but does not affect N efficiency in growing pigs. Therefore, in precision feeding concepts, BiW of pigs should be considered as a factor determining protein deposition capacity but less as a trait determining N efficiency.
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Affiliation(s)
| | - Lisanne M G Verschuren
- Wageningen Livestock Research, Wageningen, The Netherlands.,Topigs Norsvin Research Center B.V., Beuningen, The Netherlands.,Agrocampus Ouest, UMR1348 Pegase, Saint-Gilles, France
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12
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Obesity-Related Metabolome and Gut Microbiota Profiles of Juvenile Göttingen Minipigs-Long-Term Intake of Fructose and Resistant Starch. Metabolites 2020; 10:metabo10110456. [PMID: 33198236 PMCID: PMC7697781 DOI: 10.3390/metabo10110456] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 11/02/2020] [Accepted: 11/10/2020] [Indexed: 01/04/2023] Open
Abstract
The metabolome and gut microbiota were investigated in a juvenile Göttingen minipig model. This study aimed to explore the metabolic effects of two carbohydrate sources with different degrees of risk in obesity development when associated with a high fat intake. A high-risk (HR) high-fat diet containing 20% fructose was compared to a control lower-risk (LR) high-fat diet where a similar amount of carbohydrate was provided as a mix of digestible and resistant starch from high amylose maize. Both diets were fed ad libitum. Non-targeted metabolomics was used to explore plasma, urine, and feces samples over five months. Plasma and fecal short-chain fatty acids were targeted and quantified. Fecal microbiota was analyzed using genomic sequencing. Data analysis was performed using sparse multi-block partial least squares regression. The LR diet increased concentrations of fecal and plasma total short-chain fatty acids, primarily acetate, and there was a higher relative abundance of microbiota associated with acetate production such as Bacteroidetes and Ruminococcus. A higher proportion of Firmicutes was measured with the HR diet, together with a lower alpha diversity compared to the LR diet. Irrespective of diet, the ad libitum exposure to the high-energy diets was accompanied by well-known biomarkers associated with obesity and diabetes, particularly branched-chain amino acids, keto acids, and other catabolism metabolites.
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13
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Wang Y, Zhang W, Wu X, Wu C, Qian L, Wang L, Zhang X, Yang M, Li D, Ding J, Wang C, Yin Z, Ding Y. Transcriptomic comparison of liver tissue between Anqing six-end-white pigs and Yorkshire pigs based on RNA sequencing. Genome 2020; 63:203-214. [DOI: 10.1139/gen-2019-0105] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Chinese indigenous pig and Western commercial pig breeds show different patterns of lipid metabolism, fat deposition, and fatty acid composition; for these reasons, they have become vitally important models of energy metabolism and obesity in humans. To compare the mechanisms underlying lipid metabolism between Yorkshire pigs (lean type) and Anqing six-end-white pigs (obese type), the liver transcriptomes of six castrated boars with a body weight of approximately 100 kg (three Yorkshire and three Anqing) were analyzed by RNA-seq. The total number of reads produced for each liver sample ranged from 47.05 to 62.6 million. Among 362 differentially expressed genes, 142 were up-regulated and 220 were down-regulated in Anqing six-end-white pigs. Based on these data, 79 GO terms were significantly enriched. The top 10 (the 10 with lowest corrected P-value) significantly enriched GO terms were identified, including lipid metabolic process and carboxylic acid metabolic process. Pathway analysis revealed three significantly enriched KEGG pathways including PPAR signaling pathway, steroid hormone biosynthesis, and retinol metabolism. Based on protein–protein interaction networks, multiple genes responsible for lipid metabolism were identified, such as PCK1, PPARA, and CYP7A1, and these were considered promising candidate genes that could affect porcine liver lipid metabolism and fat deposition. Our results provide abundant transcriptomic information that will be useful for animal breeding and biomedical research.
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Affiliation(s)
- Yuanlang Wang
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Wei Zhang
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Xudong Wu
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Chaodong Wu
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Li Qian
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Li Wang
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Xiaodong Zhang
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Min Yang
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Dengtao Li
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Jian Ding
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Chonglong Wang
- Key Laboratory of Pig Molecular Quantitative Genetics of Anhui Academy of Agricultural Sciences, Anhui Provincial Key Laboratory of Livestock and Poultry Product Safety Engineering, Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei, Anhui 230031, China
| | - Zongjun Yin
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Yueyun Ding
- Anhui Provincial Laboratory of Local Animal Genetic Resource Conservation and Bio-Breeding, College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui 230036, China
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14
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Zhang L, Huang Y, Wang M, Guo Y, Liang J, Yang X, Qi W, Wu Y, Si J, Zhu S, Li Z, Li R, Shi C, Wang S, Zhang Q, Tang Z, Wang L, Li K, Fei JF, Lan G. Development and Genome Sequencing of a Laboratory-Inbred Miniature Pig Facilitates Study of Human Diabetic Disease. iScience 2019; 19:162-176. [PMID: 31376679 PMCID: PMC6677790 DOI: 10.1016/j.isci.2019.07.025] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 06/11/2019] [Accepted: 07/13/2019] [Indexed: 01/10/2023] Open
Abstract
Pig has been proved to be a valuable large animal model used for research on diabetic disease. However, their translational value is limited given their distinct anatomy and physiology. For the last 30 years, we have been developing a laboratory Asian miniature pig inbred line (Bama miniature pig [BM]) from the primitive Bama xiang pig via long-term selective inbreeding. Here, we assembled a BM reference genome at full chromosome-scale resolution with a total length of 2.49 Gb. Comparative and evolutionary genomic analyses identified numerous variations between the BM and commercial pig (Duroc), particularly those in the genetic loci associated with the features advantageous to diabetes studies. Resequencing analyses revealed many differentiated gene loci associated with inbreeding and other selective forces. These together with transcriptome analyses of diabetic pig models provide a comprehensive genetic basis for resistance to diabetogenic environment, especially related to energy metabolism.
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Affiliation(s)
- Li Zhang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Yuemeng Huang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China; College of Veterinary Medicine, Northwest A&F University, Yangling 712100, China
| | - Meng Wang
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Yafen Guo
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Jing Liang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China.
| | - Xiurong Yang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Wenjing Qi
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Yanjun Wu
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Jinglei Si
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Siran Zhu
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Zhe Li
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Ruiqiang Li
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Chao Shi
- Shandong Provincial Key Laboratory of Biochemical Engineering, College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China.
| | - Shuo Wang
- Shandong Provincial Key Laboratory of Biochemical Engineering, College of Marine Science and Biological Engineering, Qingdao University of Science and Technology, Qingdao 266042, China
| | - Qunjie Zhang
- Institution of Genomics and Bioinformatics, South China Agricultural University, Guangzhou 510642, China
| | - Zhonglin Tang
- Research Centre for Animal Genome, Agricultural Genome Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genome Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Lixian Wang
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Kui Li
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ji-Feng Fei
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Ganqiu Lan
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China.
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