1
|
Cui J, Song L, Wang R, Hu S, Yang Z, Zhang Z, Sun B, Cui W. Maternal Metformin Treatment during Gestation and Lactation Improves Skeletal Muscle Development in Offspring of Rat Dams Fed High-Fat Diet. Nutrients 2021; 13:nu13103417. [PMID: 34684418 PMCID: PMC8538935 DOI: 10.3390/nu13103417] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 09/25/2021] [Accepted: 09/26/2021] [Indexed: 12/04/2022] Open
Abstract
Maternal high-fat (HF) diet is associated with offspring metabolic disorder. This study intended to determine whether maternal metformin (MT) administration during gestation and lactation prevents the effect of maternal HF diet on offspring’s skeletal muscle (SM) development and metabolism. Pregnant Sprague-Dawley rats were divided into four groups according to maternal diet {CHOW (11.8% fat) or HF (60% fat)} and MT administration {control (CT) or MT (300 mg/kg/day)} during gestation and lactation: CH-CT, CH-MT, HF-CT, HF-MT. All offspring were weaned on CHOW diet. SM was collected at weaning and 18 weeks in offspring. Maternal metformin reduced plasma insulin, leptin, triglyceride and cholesterol levels in male and female offspring. Maternal metformin increased MyoD expression but decreased Ppargc1a, Drp1 and Mfn2 expression in SM of adult male and female offspring. Decreased MRF4 expression in SM, muscle dysfunction and mitochondrial vacuolization were observed in weaned HF-CT males, while maternal metformin normalized them. Maternal metformin increased AMPK phosphorylation and decreased 4E-BP1 phosphorylation in SM of male and female offspring. Our data demonstrate that maternal metformin during gestation and lactation can potentially overcome the negative effects of perinatal exposure to HF diet in offspring, by altering their myogenesis, mitochondrial biogenesis and dynamics through AMPK/mTOR pathways in SM.
Collapse
Affiliation(s)
- Jiaqi Cui
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China;
| | - Lin Song
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (L.S.); (R.W.); (S.H.)
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an 710061, China
| | - Rui Wang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (L.S.); (R.W.); (S.H.)
| | - Shuyuan Hu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (L.S.); (R.W.); (S.H.)
| | - Zhao Yang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China;
| | - Zengtie Zhang
- Department of Pathology, Xi’an Jiao Tong University Health Science Center, Xi’an 710061, China;
| | - Bo Sun
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Xi’an Jiaotong University Health Science Center, Xi’an 710061, China; (L.S.); (R.W.); (S.H.)
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education of China, Xi’an Jiaotong University, Xi’an 710061, China
- Correspondence: (B.S.); (W.C.)
| | - Wei Cui
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China;
- Correspondence: (B.S.); (W.C.)
| |
Collapse
|
2
|
Bazile J, Jaffrezic F, Dehais P, Reichstadt M, Klopp C, Laloe D, Bonnet M. Molecular signatures of muscle growth and composition deciphered by the meta-analysis of age-related public transcriptomics data. Physiol Genomics 2020; 52:322-332. [PMID: 32657225 DOI: 10.1152/physiolgenomics.00020.2020] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
The lean-to-fat ratio is a major issue in the beef meat industry from both carcass and meat production perspectives. This industrial perspective has motivated meat physiologists to use transcriptomics technologies to decipher mechanisms behind fat deposition within muscle during the time course of muscle growth. However, synthetic biological information from this volume of data remains to be produced to identify mechanisms found in various breeds and rearing practices. We conducted a meta-analysis on 10 transcriptomic data sets stored in public databases, from the longissimus thoracis of five different bovine breeds divergent by age. We updated gene identifiers on the last version of the bovine genome (UCD1.2), and the 715 genes common to the 10 studies were subjected to the meta-analysis. Of the 238 genes differentially expressed (DEG), we identified a transcriptional signature of the dynamic regulation of glycolytic and oxidative metabolisms that agrees with a known shift between those two pathways from the animal puberty. We proposed some master genes of the myogenesis, namely MYOG and MAPK14, as probable regulators of the glycolytic and oxidative metabolisms. We also identified overexpressed genes related to lipid metabolism (APOE, LDLR, MXRA8, and HSP90AA1) that may contribute to the expected enhanced marbling as age increases. Lastly, we proposed a transcriptional signature related to the induction (YBX1) or repression (MAPK14, YWAH, ERBB2) of the commitment of myogenic progenitors into the adipogenic lineage. The relationships between the abundance of the identified mRNA and marbling values remain to be analyzed in a marbling biomarkers discovery perspectives.
Collapse
Affiliation(s)
- Jeanne Bazile
- INRAE, UMR Herbivores, Université Clermont Auvergne, VetAgro Sup, Saint-Genès-Champanelle, France
| | - Florence Jaffrezic
- INRAE, UMR1313 Génétique Animale et Biologie Intégrative, Jouy-en-Josas, France
| | - Patrice Dehais
- Plate-forme bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRAE, Castanet Tolosan, France.,SIGENAE, GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Matthieu Reichstadt
- INRAE, UMR Herbivores, Université Clermont Auvergne, VetAgro Sup, Saint-Genès-Champanelle, France
| | - Christophe Klopp
- Plate-forme bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRAE, Castanet Tolosan, France.,SIGENAE, GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Denis Laloe
- INRAE, UMR1313 Génétique Animale et Biologie Intégrative, Jouy-en-Josas, France
| | - Muriel Bonnet
- INRAE, UMR Herbivores, Université Clermont Auvergne, VetAgro Sup, Saint-Genès-Champanelle, France
| |
Collapse
|