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Home / Equine Research Bank / Animals (Basel) / A Transcriptomic Regulatory Network among miRNAs, lncRNAs, c...
Animals : an open access journal from MDPI2023; 13(2); doi: 10.3390/ani13020208

A Transcriptomic Regulatory Network among miRNAs, lncRNAs, circRNAs, and mRNAs Associated with L-leucine-induced Proliferation of Equine Satellite Cells.

Abstract: In response to muscle injury, muscle stem cells are stimulated by environmental signals to integrate into damaged tissue to mediate regeneration. L-leucine (L-leu), a branched-chain amino acid (BCAA) that belongs to the essential amino acids (AAs) of the animal, has gained global interest on account of its muscle-building and regenerating effects. The present study was designed to investigate the impact of L-leu exposure to promote the proliferation of equine skeletal muscle satellite cells (SCs) on the regulation of RNA networks, including mRNA, long non-coding RNA (lncRNA), covalently closed circular RNA (circRNA), and microRNA (miRNA) in skeletal muscles. Equine SCs were used as a cell model and cultured in different concentrations of L-leu medium. The cell proliferation assay found that the optimal concentration of L-leu was 2 mM, so we selected cells cultured with L-leu concentrations of 0 mM and 2 mM for whole-transcriptiome sequencing, respectively. By high-throughput sequencing analysis, 2470 differentially expressed mRNAs (dif-mRNAs), 363 differentially expressed lncRNAs (dif-lncRNAs), 634 differentially expressed circRNAs (dif-circRNAs), and 49 differentially expressed miRNAs (dif-miRNAs) were significantly altered in equine SCs treated with L-leu. To identify the function of autoimmunity and anti-inflammatory responses after L-leu exposure, enrichment analysis was conducted on those differentially expressed genes (DEGs) related to lncRNA, circRNA, and miRNA. The hub genes were selected from PPI Network, including ACACB, HMGCR, IDI1, HAO1, SHMT2, PSPH, PSAT1, ASS1, PHGDH, MTHFD2, and DPYD, and were further identified as candidate biomarkers to regulate the L-leu-induced proliferation of equine SCs. The up-regulated novel 699_star, down-regulated novel 170_star, and novel 360_mature were significantly involved in the competing endogenous RNA (ceRNA) complex network. The hub genes involved in cell metabolism and dif-miRNAs may play fundamental roles in the L-leu-induced proliferation of equine SCs. Our findings suggested that the potential network regulation of miRNAs, circ-RNAs, lncRNAs, and mRNAs plays an important role in the proliferation of equine SCs, so as to build up new perspectives on improving equine performance and treatment strategies for the muscle injuries of horses.
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Publication Date: 2023-01-06 PubMed ID: 36670748PubMed Central: PMC9854542DOI: 10.3390/ani13020208Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research paper discusses an investigation into the impact of L-leucine, an essential amino acid notable for its muscle-building properties, on the RNA networks that regulate the proliferation of equine skeletal muscle satellite cells. The RNA networks studied include mRNA, long non-coding RNA, circular RNA, and microRNA. The study’s results suggest that these RNA networks play a significant role in promoting satellite cell growth, which can influence muscle regeneration properties and potentially improve horse performance and injury recovery.

Methodology of the Study

  • The researchers used equine satellite cells as a cell model and cultured them in different concentrations of an L-leucine medium.
  • They discovered the optimal concentration of L-leucine to promote cell proliferation was 2 mM.
  • Cells cultured with L-leucine concentrations of 0 mM and 2 mM were selected for whole-transcriptiome sequencing.
  • Through high-throughput sequencing analysis, the researchers identified changes in the expression of several types of RNA in equine satellite cells treated with L-leucine.

Differential Gene Expression

  • Significant alterations were found in 2470 differentially expressed mRNAs, 363 differentially expressed lncRNAs, 634 differentially expressed circRNAs, and 49 differentially expressed miRNAs in response to L-leucine treatment.
  • Following this, the researchers conducted an enrichment analysis on these differentially expressed genes to identify their function in anti-inflammatory responses and autoimmunity following L-leucine exposure.
  • Several hub genes were identified, including ACACB, HMGCR, IDI1, HAO1, SHMT2, PSPH, PSAT1, ASS1, PHGDH, MTHFD2, and DPYD. These were proposed as candidate biomarkers to regulate the L-leucine-induced proliferation of equine satellite cells.

Proposed Network Regulation

  • The RNA networks studied—miRNAs, circ-RNAs, lncRNAs, and mRNAs—are believed to play a significant role in regulating L-leucine’s ability to stimulate the growth of equine satellite cells.
  • Three genes—up-regulated novel 699_star, down-regulated novel 170_star, and novel 360_mature—were found to be significantly involved in the competing endogenous RNA network, which may drive the observed cell proliferation.
  • This study hints at the importance of RNA network regulation in optimizing muscle regeneration and performance enhancement strategies in horses.

Cite This Article

APA
Xing J, Qi X, Liu G, Li X, Gao X, Bou G, Bai D, Zhao Y, Du M, Dugarjaviin M, Zhang X. (2023). A Transcriptomic Regulatory Network among miRNAs, lncRNAs, circRNAs, and mRNAs Associated with L-leucine-induced Proliferation of Equine Satellite Cells. Animals (Basel), 13(2). https://doi.org/10.3390/ani13020208

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 13
Issue: 2

Researcher Affiliations

Xing, Jingya
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Qi, Xingzhen
  • Liaocheng Research Institute of Donkey High-Breeding and Ecological Feeding, College of Agronomy, Liaocheng University, Liaocheng 252000, China.
Liu, Guiqin
  • Liaocheng Research Institute of Donkey High-Breeding and Ecological Feeding, College of Agronomy, Liaocheng University, Liaocheng 252000, China.
Li, Xinyu
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Gao, Xing
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Bou, Gerelchimeg
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Bai, Dongyi
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Zhao, Yiping
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Du, Ming
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Dugarjaviin, Manglai
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Zhang, Xinzhuang
  • Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, Scientific Observing and Experimental Station of Equine Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Equine Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.

Grant Funding

  • 31902188 / National Natural Science Foundation of China
  • 3191101008 / National Natural Science Foundation of China
  • 31960657 / National Natural Science Foundation of China
  • 2021MS03016 / Natural Science Foundation of Inner Mongolia
  • NDGCC2016-01 / the startup project for High-level Talents of Inner Mongolia Agricultural University
  • QN202114 / Youth Foundation of College of Animal Science, Inner Mongolia Agricultural University
  • DC2100002428 / Postgraduate Research Innovation Funding Project
  • RZ2200001172 / Basic scientific research projects in colleges and universities
  • SDAIT-27 / Donkey innovation team of Shandong modern agricultural industry technology system
  • 2021TZXD012 / Rural Revitalization science and technology innovation promotion action plan project of Shandong
  • 318052120 / Doctoral Research Project of Liaocheng University
  • 319312101-03 / Open Project of Animal Science of Liaocheng University

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 89 references
  1. Cynober L. Introduction to the 5th amino acid assessment workshop.. J. Nutr. 2006;136:1633S–1635S.
    doi: 10.1093/jn/136.6.1633Spubmed: 16702332google scholar: lookup
  2. Fujita S, Volpi E. Amino acids and muscle loss with aging.. J. Nutr. 2006;136:277S–280S.
    doi: 10.1093/jn/136.1.277Spmc: PMC3183816pubmed: 16365098google scholar: lookup
  3. Ham D.J, Murphy K.T, Chee A, Lynch G.S, Koopman R. Glycine administration attenuates skeletal muscle wasting in a mouse model of cancer cachexia.. Clin. Nutr. 2014;33:448–458.
    doi: 10.1016/j.clnu.2013.06.013pubmed: 23835111google scholar: lookup
  4. Koopman R, Ly C.H, Ryall J.G. A metabolic link to skeletal muscle wasting and regeneration.. Front. Physiol. 2014;5:32.
    doi: 10.3389/fphys.2014.00032pmc: PMC3909830pubmed: 24567722google scholar: lookup
  5. Mok E, Violante C.E.-D., Daubrosse C, Gotrand F, Rigal O, Fontan J.-E., Cuisset J.-M., Guilhot J, Hankard R. Oral glutamine and amino acid supplementation inhibit whole-body protein degradation in children with Duchenne muscular dystrophy.. Am. J. Clin. Nutr. 2006;83:823–828.
    doi: 10.1093/ajcn/83.4.823pubmed: 16600934google scholar: lookup
  6. Hulmi J.J, Lockwood C.M, Stout J.R. Effect of protein/essential amino acids and resistance training on skeletal muscle hypertrophy: A case for whey protein.. Nutr. Metab. 2010;7:1–11.
    doi: 10.1186/1743-7075-7-51pmc: PMC2901380pubmed: 20565767google scholar: lookup
  7. Davoodi J, Markert C.D, Voelker K, Hutson S, Grange R.W. Nutrition strategies to improve physical capabilities in Duchenne muscular dystrophy.. Phys. Med. Rehabil. Clin. 2012;23:187–199.
    doi: 10.1016/j.pmr.2011.11.010pmc: PMC3437319pubmed: 22239883google scholar: lookup
  8. Lin C, Han G, Ning H, Song J, Ran N, Yi X, Seow Y, Yin H. Glycine enhances satellite cell proliferation, cell transplantation, and oligonucleotide efficacy in dystrophic muscle.. Mol. Ther. 2020;28:1339–1358.
    doi: 10.1016/j.ymthe.2020.03.003pmc: PMC7210708pubmed: 32209436google scholar: lookup
  9. Harper A, Miller R, Block K. Branched-chain amino acid metabolism.. Annu. Rev. Nutr. 1984;4:409–454.
    doi: 10.1146/annurev.nu.04.070184.002205pubmed: 6380539google scholar: lookup
  10. Fukagawa N.K. Protein and amino acid supplementation in older humans.. Amino Acids 2013;44:1493–1509.
    doi: 10.1007/s00726-013-1480-6pubmed: 23563921google scholar: lookup
  11. Buse M.G, Reid S.S. Leucine. A possible regulator of protein turnover in muscle.. J. Clin. Investig. 1975;56:1250–1261.
    doi: 10.1172/JCI108201pmc: PMC301988pubmed: 1237498google scholar: lookup
  12. Casperson S.L, Sheffield-Moore M, Hewlings S.J, Paddon-Jones D. Leucine supplementation chronically improves muscle protein synthesis in older adults consuming the RDA for protein.. Clin. Nutr. 2012;31:512–519.
    doi: 10.1016/j.clnu.2012.01.005pmc: PMC3640444pubmed: 22357161google scholar: lookup
  13. Ohtani M, Kawada S, Seki T, Okamoto Y. Amino acid and vitamin supplementation improved health conditions in elderly participants.. J. Clin. Biochem. Nutr. 2012;50:162–168.
    doi: 10.3164/jcbn.11-55pmc: PMC3303480pubmed: 22448099google scholar: lookup
  14. Ablondi M, Summer A, Vasini M, Simoni M, Sabbioni A. Genetic parameters estimation in an Italian horse native breed to support the conversion from agricultural uses to riding purposes.. J. Anim. Breed. Genet. 2020;137:200–210.
    doi: 10.1111/jbg.12425pubmed: 31310049google scholar: lookup
  15. McGivney B, Hernandez B, Katz L, MacHugh D, McGovern S, Parnell A, Wiencko H, Hill E. A genomic prediction model for racecourse starts in the Thoroughbred horse.. Anim. Genet. 2019;50:347–357.
    doi: 10.1111/age.12798pubmed: 31257665google scholar: lookup
  16. Sutcu H.H, Ricchetti M. Loss of heterogeneity, quiescence, and differentiation in muscle stem cells.. Stem Cell Investig. 2018;5:9.
    doi: 10.21037/sci.2018.03.02pmc: PMC5945914pubmed: 29780813google scholar: lookup
  17. Sakuma K, Yamaguchi A. Recent advances in pharmacological, hormonal, and nutritional intervention for sarcopenia.. Pflügers Arch. Eur. J. Physiol. 2018;470:449–460.
    doi: 10.1007/s00424-017-2077-9pubmed: 29043432google scholar: lookup
  18. Consalvi S, Brancaccio A, Dall’Agnese A, Puri P.L, Palacios D. Praja1 E3 ubiquitin ligase promotes skeletal myogenesis through degradation of EZH2 upon p38α activation.. Nat. Commun. 2017;8:1–11.
    doi: 10.1038/ncomms13956pmc: PMC5423270pubmed: 28067271google scholar: lookup
  19. Snow D.H. Ergogenic aids to performance in the race horse: Nutrients or drugs.. J. Nutr. 1994;124:2730S–2735S.
    doi: 10.1093/jn/124.suppl_12.2730Spubmed: 7996281google scholar: lookup
  20. Frost R.A, Lang C.H. mTor signaling in skeletal muscle during sepsis and inflammation: Where does it all go wrong?. Physiology 2011;26:83–96.
    doi: 10.1152/physiol.00044.2010pmc: PMC3606812pubmed: 21487027google scholar: lookup
  21. Tan H.W.S, Sim A.Y.L, Long Y.C. Glutamine metabolism regulates autophagy-dependent mTORC1 reactivation during amino acid starvation.. Nat. Commun. 2017;8:1–10.
    doi: 10.1038/s41467-017-00369-ypmc: PMC5569045pubmed: 28835610google scholar: lookup
  22. Saxton R.A, Sabatini D.M. mTOR signaling in growth, metabolism, and disease.. Cell 2017;168:960–976.
    doi: 10.1016/j.cell.2017.02.004pmc: PMC5394987pubmed: 28283069google scholar: lookup
  23. Ham D.J, Caldow M.K, Lynch G.S, Koopman R. Arginine protects muscle cells from wasting in vitro in an mTORC1-dependent and NO-independent manner.. Amino Acids 2014;46:2643–2652.
    doi: 10.1007/s00726-014-1815-ypubmed: 25096520google scholar: lookup
  24. Bandt J. Leucine and Mammalian Target of Rapamycin–Dependent Activation of Muscle Protein Synthesis in Aging.. J. Nutr. 2016;146:2616S.
    doi: 10.3945/jn.116.234518pubmed: 27934653google scholar: lookup
  25. Magne H, Savary-Auzeloux I, Rémond D, Dardevet D. Nutritional strategies to counteract muscle atrophy caused by disuse and to improve recovery.. Nutr. Res. Rev. 2013;26:149–165.
    doi: 10.1017/S0954422413000115pubmed: 23930668google scholar: lookup
  26. Yan G, Li X, Peng Y, Long B, Fan Q, Wang Z, Shi M, Xie C, Zhao L, Yan X. The fatty acid β-oxidation pathway is activated by leucine deprivation in HepG2 cells: A comparative proteomics study.. Sci. Rep. 2017;7:1–11.
    doi: 10.1038/s41598-017-02131-2pmc: PMC5432498pubmed: 28507299google scholar: lookup
  27. Zarfeshani A, Ngo S, Sheppard A.M. Leucine alters hepatic glucose/lipid homeostasis via the myostatin-AMP-activated protein kinase pathway-potential implications for nonalcoholic fatty liver disease.. Clin. Epigenet. 2014;6:1–12.
    doi: 10.1186/1868-7083-6-27pmc: PMC4391119pubmed: 25859286google scholar: lookup
  28. Morris K.V, Mattick J.S. The rise of regulatory RNA.. Nat. Rev. Genet. 2014;15:423–437.
    doi: 10.1038/nrg3722pmc: PMC4314111pubmed: 24776770google scholar: lookup
  29. Palazzo A.F, Lee E.S. Non-coding RNA: What is functional and what is junk?. Front. Genet. 2015;6:2.
    doi: 10.3389/fgene.2015.00002pmc: PMC4306305pubmed: 25674102google scholar: lookup
  30. Matsui M, Corey D.R. Non-coding RNAs as drug targets.. Nat. Rev. Drug Discov. 2017;16:167–179.
    doi: 10.1038/nrd.2016.117pmc: PMC5831170pubmed: 27444227google scholar: lookup
  31. Dai X, Zhang S, Zaleta-Rivera K. RNA: Interactions drive functionalities.. Mol. Biol. Rep. 2020;47:1413–1434.
    doi: 10.1007/s11033-019-05230-7pmc: PMC7089156pubmed: 31838657google scholar: lookup
  32. Cech T.R, Steitz J.A. The noncoding RNA revolution—Trashing old rules to forge new ones.. Cell 2014;157:77–94.
    doi: 10.1016/j.cell.2014.03.008pubmed: 24679528google scholar: lookup
  33. Kinoshita C, Aoyama K. The role of non-coding RNAs in the neuroprotective effects of glutathione.. Int. J. Mol. Sci. 2021;22:4245.
    doi: 10.3390/ijms22084245pmc: PMC8073493pubmed: 33921907google scholar: lookup
  34. Liu N, Williams A.H, Maxeiner J.M, Bezprozvannaya S, Olson E.N. microRNA-206 promotes skeletal muscle regeneration and delays progression of Duchenne muscular dystrophy in mice.. J. Clin. Investig. 2012;122:2054–2065.
    doi: 10.1172/JCI62656pmc: PMC3366415pubmed: 22546853google scholar: lookup
  35. Zhang W.R, Zhang H.N, Yi M.W, Yang D, Guo H. miR-143 regulates proliferation and differentiation of bovine skeletal muscle satellite cells by targeting IGFBP5.. Vitr. Cell. Dev. Biol. Anim. 2016;53:1–7.
    doi: 10.1007/s11626-016-0109-ypubmed: 27800570google scholar: lookup
  36. Liu B, Yu S, He H, Cai M, Lai S. miR-221 modulates skeletal muscle satellite cells proliferation and differentiation.. Vitr. Cell. Dev. Biol. Anim. 2018;54:147–155.
    doi: 10.1007/s11626-017-0210-xpubmed: 29197032google scholar: lookup
  37. Chen J.-F, Tao Y, Li J, Deng Z, Yan Z, Xiao X, Wang D.-Z. microRNA-1 and microRNA-206 regulate skeletal muscle satellite cell proliferation and differentiation by repressing Pax7.. J. Cell Biol. 2010;190:867–879.
    doi: 10.1083/jcb.200911036pmc: PMC2935565pubmed: 20819939google scholar: lookup
  38. Bolger A.M, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data.. Bioinformatics 2014;30:2114–2120.
    doi: 10.1093/bioinformatics/btu170pmc: PMC4103590pubmed: 24695404google scholar: lookup
  39. Kim D, Langmead B, Salzberg S.L. HISAT: A fast spliced aligner with low memory requirements.. Nat. Methods 2015;12:357–360.
    doi: 10.1038/nmeth.3317pmc: PMC4655817pubmed: 25751142google scholar: lookup
  40. Anders S, Pyl P.T, Huber W. HTSeq—A Python framework to work with high-throughput sequencing data.. Bioinformatics 2015;31:166–169.
    doi: 10.1093/bioinformatics/btu638pmc: PMC4287950pubmed: 25260700google scholar: lookup
  41. Nawrocki E.P, Eddy S.R. Infernal 1.1: 100-fold faster RNA homology searches.. Bioinformatics 2013;29:2933–2935.
    doi: 10.1093/bioinformatics/btt509pmc: PMC3810854pubmed: 24008419google scholar: lookup
  42. Gao Y, Wang J, Zhao F. CIRI: An efficient and unbiased algorithm for de novo circular RNA identification.. Genome Biol. 2015;16:1–16.
    doi: 10.1186/s13059-014-0571-3pmc: PMC4316645pubmed: 25583365google scholar: lookup
  43. Anders S, Huber W. Differential Expression of RNA-Seq Data at the Gene Level—The DESeq Package.. European Molecular Biology Laboratory (EMBL); Heidelberg, Germany 2012 p. 10.
  44. Altschul S.F, Gish W, Miller W, Myers E.W, Lipman D.J. Basic local alignment search tool.. J. Mol. Biol. 1990;215:403–410.
    doi: 10.1016/S0022-2836(05)80360-2pubmed: 2231712google scholar: lookup
  45. Griffiths-Jones S, Bateman A, Marshall M, Khanna A, Eddy S.R. Rfam: An RNA family database.. Nucleic Acids Res. 2003;31:439–441.
    doi: 10.1093/nar/gkg006pmc: PMC165453pubmed: 12520045google scholar: lookup
  46. Griffiths-Jones S, Saini H.K, Van Dongen S, Enright A.J. miRBase: Tools for microRNA genomics.. Nucleic Acids Res. 2007;36:D154–D158.
    doi: 10.1093/nar/gkm952pmc: PMC2238936pubmed: 17991681google scholar: lookup
  47. Friedländer M.R, Mackowiak S.D, Li N, Chen W, Rajewsky N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades.. Nucleic Acids Res. 2012;40:37–52.
    doi: 10.1093/nar/gkr688pmc: PMC3245920pubmed: 21911355google scholar: lookup
  48. Zhang Y.J, Ma Y.S, Xia Q, Yu F, Lv Z.W, Jia C.Y, Jiang X.X, Zhang L, Shao Y.C, Xie W.T. MicroRNA-mRNA integrated analysis based on a case of well-differentiated thyroid cancer with both metastasis and metastatic recurrence.. Oncol. Rep. 2018;40:3803–3811.
    doi: 10.3892/or.2018.6739pubmed: 30272320google scholar: lookup
  49. Tang Y, Li M, Wang J, Pan Y, Wu F.-X. CytoNCA: A cytoscape plugin for centrality analysis and evaluation of protein interaction networks.. Biosystems 2015;127:67–72.
    doi: 10.1016/j.biosystems.2014.11.005pubmed: 25451770google scholar: lookup
  50. Bandettini W.P, Kellman P, Mancini C, Booker O.J, Vasu S, Leung S.W, Wilson J.R, Shanbhag S.M, Chen M.Y, Arai A.E. MultiContrast Delayed Enhancement (MCODE) improves detection of subendocardial myocardial infarction by late gadolinium enhancement cardiovascular magnetic resonance: A clinical validation study.. J. Cardiovasc. Magn. Reson. 2012;14:1–10.
    doi: 10.1186/1532-429X-14-83pmc: PMC3552709pubmed: 23199362google scholar: lookup
  51. Enright A, John B, Gaul U, Tuschl T, Sander C. MicroRNA targets in Drosophila.. Genome Biol. 2003;5:R1.
    doi: 10.1186/gb-2003-5-1-r1pmc: PMC395733pubmed: 14709173google scholar: lookup
  52. Moss F.P, Leblond C.P. Satellite cells as the source of nuclei in muscles of growing rats.. Anat. Rec. Adv. Integr. Anat. Evol. Biol. 1971;170:421–435.
    doi: 10.1002/ar.1091700405pubmed: 5118594google scholar: lookup
  53. Snow M.H. An autoradiographic study of satellite cell differentiation into regenerating myotubes following transplantation of muscles in young rats.. Cell Tissue Res. 1978;186:535–540.
    doi: 10.1007/BF00224941pubmed: 627031google scholar: lookup
  54. Liu Y, Chen S, Li W, Du H, Zhu W. Isolation and characterization of primary skeletal muscle satellite cells from rats.. Toxicol. Mech. Methods. 2012;22:721–725.
    doi: 10.3109/15376516.2012.720302pubmed: 22901082google scholar: lookup
  55. Seale P, Sabourin L.A, Girgis-Gabardo A, Mansouri A, Rudnicki M.A. Pax7 is required for the specification of myogenic satellite cells.. Cell 2000;102:777–786.
    doi: 10.1016/S0092-8674(00)00066-0pubmed: 11030621google scholar: lookup
  56. Zhao Y, Cholewa J, Shang H, Yang Y, Xia Z. Advances in the Role of Leucine-Sensing in the Regulation of Protein Synthesis in Aging Skeletal Muscle.. Front. Cell Dev. Biol. 2021;9:646482.
    doi: 10.3389/fcell.2021.646482pmc: PMC8047301pubmed: 33869199google scholar: lookup
  57. Cui C, Wu C, Wang J, Zheng X, Ma Z, Zhu P, Guan W, Zhang S, Chen F. Leucine supplementation during late gestation globally alters placental metabolism and nutrient transport via modulation of the PI3K/AKT/mTOR signaling pathway in sows.. Food Funct. 2022;13:2083–2097.
    doi: 10.1039/D1FO04082Kpubmed: 35107470google scholar: lookup
  58. Liu T, Zuo B, Wang W, Wang S, Wang J. Dietary Supplementation of Leucine in Premating Diet Improves the Within-Litter Birth Weight Uniformity, Antioxidative Capability, and Immune Function of Primiparous SD Rats.. Biomed Res. Int. 2018;2018:1523147.
    doi: 10.1155/2018/1523147pmc: PMC5932505pubmed: 29850484google scholar: lookup
  59. Ko J.H, Olona A, Papathanassiu A.E, Buang N, Behmoaras J. BCAT1 affects mitochondrial metabolism independently of leucine transamination in activated human macrophages.. J. Cell Sci. 2020;133:jcs247957.
    doi: 10.1242/jcs.247957pmc: PMC7116427pubmed: 33148611google scholar: lookup
  60. Waskiw-Ford M. Leucine-Enriched Essential Amino Acids Enhance Post-Exercise Muscle Recovery Independent Of ‘Free-Living’ Myofibrillar Protein Synthesis: 413 Board #229 May 27 9:30 AM–11:00 AM.. Med. Sci. Sport. Exerc. 2020;52:105.
    doi: 10.1249/01.mss.0000671188.68270.42google scholar: lookup
  61. Petrocelli J.J, Mahmassani Z.S, Fix D.K, Montgomery J.A, Reidy P.T, McKenzie A.I, de Hart N.M, Ferrara P.J, Kelley J.J, Eshima H. Metformin and leucine increase satellite cells and collagen remodeling during disuse and recovery in aged muscle.. Fed. Am. Soc. Exp. Biol. J. 2021;35:e21862.
    doi: 10.1096/fj.202100883Rpmc: PMC8384128pubmed: 34416035google scholar: lookup
  62. Kakazu E, Ueno Y, Kondo Y, Fukushima K, Shiina M, Inoue J, Tamai K, Ninomiya M, Shimosegawa T. Branched chain amino acids enhance the maturation and function of myeloid dendritic cells ex vivo in patients with advanced cirrhosis.. Hepatology 2010;50:1936–1945.
    doi: 10.1002/hep.23248pubmed: 19885880google scholar: lookup
  63. Master P.B.Z, Macedo R.C.O. Effects of dietary supplementation in sport and exercise: A review of evidence on milk proteins and amino acids.. Nutrition 2020;61:1–15.
    doi: 10.1080/10408398.2020.1756216pubmed: 32363897google scholar: lookup
  64. Chen X, Xiang L, Jia G, Liu G, Huang Z.J. Leucine regulates slow-twitch muscle fibers expression and mitochondrial function by Sirt1/AMPK signaling in porcine skeletal muscle satellite cells.. Anim. Sci. J. 2019;90:255–263.
    doi: 10.1111/asj.13146pubmed: 30523660google scholar: lookup
  65. She Y, Deng H, Cai H, Liu G. Regulation of the expression of key signalling molecules in mTOR pathway of skeletal muscle satellite cells in neonatal chicks: Effects of leucine and glycine–leucine peptide.. J. Anim. Physiol. Anim. Nutr. 2019;103:786–790.
    doi: 10.1111/jpn.13090pubmed: 30900779google scholar: lookup
  66. Cirulli E.T, Singh A, Shianna K.V, Goldstein D.B. Screening the human exome: A comparison of whole genome and whole transcriptome sequencing.. Genome Biol. 2010;11:R57.
    doi: 10.1186/gb-2010-11-5-r57pmc: PMC2898068pubmed: 20598109google scholar: lookup
  67. Bigot A, Duddy W.J, Ouandaogo Z.G, Negroni E, Mariot V, Ghimbovschi S, Harmon B, Wielgosik A, Loiseau C, Devaney J. Age-associated methylation suppresses SPRY1, leading to a failure of re-quiescence and loss of the reserve stem cell pool in elderly muscle.. Cell Rep. 2015;13:1172–1182.
    doi: 10.1016/j.celrep.2015.09.067pubmed: 26526994google scholar: lookup
  68. Edelman G.M. CAMs and Igs: Cell adhesion and the evolutionary origins of immunity.. Immunol. Rev. 1987;100:11–45.
    doi: 10.1111/j.1600-065X.1987.tb00526.xpubmed: 3326819google scholar: lookup
  69. Rowlands D.S, Nelson A.R, Raymond F, Metairon S, Mansourian R, Clarke J, Stellingwerff T, Phillips S.M. Protein-leucine ingestion activates a regenerative inflammo-myogenic transcriptome in skeletal muscle following intense endurance exercise.. Physiol. Genom. 2016;48:21–32.
    doi: 10.1152/physiolgenomics.00068.2015pubmed: 26508702google scholar: lookup
  70. Kwon O.S, Tanner R.E, Barrows K.M. MyD88 regulates physical inactivity-induced skeletal muscle inflammation, ceramide biosynthesis signaling, and glucose intolerance.. Am. J. Physiol. Endocrinol. Metab. 2015;309:E11–E21.
    doi: 10.1152/ajpendo.00124.2015pmc: PMC4490331pubmed: 25968578google scholar: lookup
  71. Tuttle C.S.L, Thang L.A.N, Maier A.B. Markers of inflammation and their association with muscle strength and mass: A systematic review and meta-analysis.. Ageing Res. Rev. 2020;64:101185.
    doi: 10.1016/j.arr.2020.101185pubmed: 32992047google scholar: lookup
  72. Alameddine H.S, Morgan J.E. Matrix Metalloproteinases and Tissue Inhibitor of Metalloproteinases in Inflammation and Fibrosis of Skeletal Muscles.. J. Neuromuscul. Dis. 2016;3:455–473.
    doi: 10.3233/JND-160183pmc: PMC5240616pubmed: 27911334google scholar: lookup
  73. Perandini L.A, Chimin P, Lutkemeyer D, Cmara N.O.S. Chronic inflammation in skeletal muscle impairs satellite cells function during regeneration: Can physical exercise restore the satellite cell niche?. Fed. Eur. Biochem. Soc. J. 2018;285:1973–1984.
    doi: 10.1111/febs.14417pubmed: 29473995google scholar: lookup
  74. Beaudry A.G, Law M.L. Leucine Supplementation in Cancer Cachexia: Mechanisms and a Review of the Pre-Clinical Literature.. Nutrients 2022;14:2824.
    doi: 10.3390/nᐔ2824pmc: PMC9323748pubmed: 35889781google scholar: lookup
  75. Viana L.R, Canevarolo R, Luiz A.C.P, Soares R.F, Lubaczeuski C, Zeri A.C.d.M, Gomes-Marcondes M.C.C. Leucine-rich diet alters the 1H-NMR based metabolomic profile without changing the Walker-256 tumour mass in rats.. BMC Cancer 2016;16:1–14.
    doi: 10.1186/s12885-016-2811-2pmc: PMC5048609pubmed: 27716121google scholar: lookup
  76. Li Z, Zhang H. Reprogramming of glucose, fatty acid and amino acid metabolism for cancer progression.. Cell. Mol. Life Sci. 2016;73:377–392.
    doi: 10.1007/s00018-015-2070-4pmc: PMC11108301pubmed: 26499846google scholar: lookup
  77. Kelly B, Pearce E.L. Amino Assets: How Amino Acids Support Immunity.. Cell Metab. 2020;32:154–175.
    doi: 10.1016/j.cmet.2020.06.010pubmed: 32649859google scholar: lookup
  78. Nowosad A, Jeannot P, Callot C, Creff J, Perchey R.T, Joffre C, Codogno P, Manenti S, Besson A. Publisher Correction: p27 controls Ragulator and mTOR activity in amino acid-deprived cells to regulate the autophagy-lysosomal pathway and coordinate cell cycle and cell growth.. Springer Sci. Bus. Media 2021;23:1048.
    doi: 10.1038/s41556-021-00741-7pubmed: 34316048google scholar: lookup
  79. Moro T, Ebert S.M, Adams C.M, Rasmussen B.B. Amino Acid Sensing in Skeletal Muscle.. Trends Endocrinol. Metab. 2016;27:796–806.
    doi: 10.1016/j.tem.2016.06.010pmc: PMC5075248pubmed: 27444066google scholar: lookup
  80. Sah N, Wu G, Bazer F.W. Amino Acids in Nutrition and Health. Vol. 1332. Springer; New York, NY, USA: 2021. Regulation of Gene Expression by Amino Acids in Animal Cells; pp. 1–15.. .
    doi: 10.1007/978-3-030-74180-8_1pubmed: 34251635google scholar: lookup
  81. Kilberg M, Pan Y.-X, Chen H, Leung-Pineda V. Nutritional control of gene expression: How mammalian cells respond to amino acid limitation.. Annu. Rev. Nutr. 2005;25:59–85.
    doi: 10.1146/annurev.nutr.24.012003.132145pmc: PMC3600373pubmed: 16011459google scholar: lookup
  82. Hamanaka R.B, Nigdelioglu R, Meliton A.Y, Tian Y, Witt L.J, O’Leary E, Sun K.A, Woods P.S, Wu D, Ansbro B. Inhibition of phosphoglycerate dehydrogenase attenuates bleomycin-induced pulmonary fibrosis.. Am. J. Respir. Cell Mol. Biol. 2018;58:585–593.
    doi: 10.1165/rcmb.2017-0186OCpmc: PMC5946329pubmed: 29019702google scholar: lookup
  83. Shen L, Hu P, Zhang Y, Ji Z, Shan X, Ni L, Ning N, Wang J, Tian H, Shui G. Serine metabolism antagonizes antiviral innate immunity by preventing ATP6V0d2-mediated YAP lysosomal degradation.. Cell Metab. 2021;33:971–987.e6.
    doi: 10.1016/j.cmet.2021.03.006pubmed: 33798471google scholar: lookup
  84. Kim S, Lee M, Song Y, Lee S.-Y, Choi I, Park I, Kim J, Kim J.-s, Seo H.R. Argininosuccinate synthase 1 suppresses tumor progression through activation of PERK/eIF2α/ATF4/CHOP axis in hepatocellular carcinoma.. J. Exp. Clin. Cancer Res. 2021;40:1–18.
    doi: 10.1186/s13046-021-01912-ypmc: PMC8035787pubmed: 33838671google scholar: lookup
  85. Nilsson R, Jain M, Madhusudhan N, Sheppard N.G, Strittmatter L, Kampf C, Huang J, Asplund A, Mootha V.K. Metabolic enzyme expression highlights a key role for mthfd2 and the mitochondrial folate pathway in cancer.. Nat. Commun. 2014;5:3128.
    doi: 10.1038/ncomms4128pmc: PMC4106362pubmed: 24451681google scholar: lookup
  86. Kim D, Fiske B.P, Birsoy K, Freinkman E, Kami K, Possemato R.L, Chudnovsky Y, Pacold M.E, Chen W.W, Cantor J.R. SHMT2 drives glioma cell survival in ischaemia but imposes a dependence on glycine clearance.. Nature 2015;520:363–367.
    doi: 10.1038/nature14363pmc: PMC4533874pubmed: 25855294google scholar: lookup
  87. Martínez-Arnau F.M, Fonfría-Vivas R, Cauli O. Beneficial effects of leucine supplementation on criteria for sarcopenia: A systematic review.. Nutrients 2019;11:2504.
    doi: 10.3390/nᄐ2504pmc: PMC6835605pubmed: 31627427google scholar: lookup
  88. Lee S.Y, Lee H.J, Lim J.-Y. Effects of leucine-rich protein supplements in older adults with sarcopenia: A systematic review and meta-analysis of randomized controlled trials.. Arch. Gerontol. Geriatr. 2022;102:104758.
    doi: 10.1016/j.archger.2022.104758pubmed: 35777246google scholar: lookup
  89. Cruz B, Oliveira A, Gomes-Marcondes M.C.C. L-leucine dietary supplementation modulates muscle protein degradation and increases pro-inflammatory cytokines in tumour-bearing rats.. Cytokine 2017;96:253–260.
    doi: 10.1016/j.cyto.2017.04.019pubmed: 28494385google scholar: lookup
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