Research Article
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Gene Expression Profile as a Precursor of Inflammation in Mouse Models: BFMI860 and C57BL/6NCrl

Year 2024, Volume: 14 Issue: 2, 73 - 84, 26.08.2024
https://doi.org/10.26650/experimed.1384602

Abstract

Objective: We aimed to investigate the differences in the immune response to body fat content between the genetically mutant obese BFMI860 (BFMI) mouse strain and the lean C57BL/6Ncrl (B6) mouse strain as a control and the effects of obesity on gene expression on inflammation-related pathways in epididymal adipose tissue.
Materials and Methods: Six males from each strain were maintained on a standard maintenance diet (SMD) or a high-fat diet (HFD). At the age of 10 weeks, serum and epididymal adipose tissue samples were collected for cytokine and gene expression analyses. RNA samples from epididymal adipose tissue were hybridized using the microarray technique to study the quantitative transcript amounts of genes.
Results: Pathway analysis of gene expression data revealed no considerable development of inflammatory state in BFMI and B6 on SMD. Both strains responded to HFD distinctly; the inflammatory state was more prominent in the obese BFMI group than in the lean B6 group. Several genes, such as Adipoq, NFkbia, Plaur, F2r, C3ar1, and Nfatc4 in pathways involved in the immune system have been found to be differentially regulated in BFMI mice. Under the condition of obesity in BFMI mice, the induction of inflammation-related pathways indicates an increased risk of insulin resistance, atherosclerosis, and cardiovascular disease.
Conclusion: This study identified distinct expression patterns of genes involved in inflammatory pathways, particularly those associated with the adipocytokine signaling pathway and complement and coagulation cascades, in the epididymal adipose tissue of BFMI and B6 mice. The BFMI strain is a valuable and promising model for clarifying the mechanisms underlying obesity and the activation of inflammation in adipose tissue.

Ethical Statement

All experimental procedures were approved by the German Animal Welfare Authorities (approval no. G0152/04).

Supporting Institution

erman National Genome Research Network, German Research Foundation ,German Network for Systems Genetics

Thanks

This research was supported by grants of the German National Genome Research Network (NGFN: 01GS0486, 01GS0829) by grants of the German Research Foundation (GRK1209) and German Network for Systems Genetics (GeNeSys).

References

  • 1. Phillips CL, Grayson BE. The immune remodel: Weight loss-mediated inflammatory changes to obesity. Exp Biol Med (Maywood) 2020; 245(2): 109-121. google scholar
  • 2. Mikhailova SV, Ivanoshchuk DE. Innate-Immunity Genes in Obesity. J Pers Med 2021; 11(11): 1201. google scholar
  • 3. Wagener A, Goessling HF, Schmitt AO, Mauel S, Gruber AD, Reinhardt R, et al. Genetic and diet effects on Ppar-a and Ppar—Y signaling pathways in the Berlin Fat Mouse Inbred line with genetic predisposition for obesity. Lipids Health Dis 2010; 9: 99. google scholar
  • 4. Hantschel C, Wagener A, Neuschl C, Teupser D, Brockmann GA. Features of the metabolic syndrome in the Berlin Fat Mouse as a model for human obesity. Obes Facts 2011; 4(4): 270-7. google scholar
  • 5. Reimers M, Carey VJ. Bioconductor: an open source framework for bioinformatics and computational biology. Methods Enzymol 2006; 411: 119-34. google scholar
  • 6. Dunning MJ, Smith ML, Ritchie ME, Tavare S. beadarray: R classes and methods for Illumina bead-based data. Bioinformatics 2007; 23: 2183-4. google scholar
  • 7. Ihaka R, Gentleman R. A language for data analysis and graphics. J Comp Graph Statistics 1996; 5: 299-314. google scholar
  • 8. Cui X, Churchill GA. Statistical tests for differential expression in cDNA microarray experiments. Genome Biol 2003; 4: 210. google scholar
  • 9. Dahlquist KD, Salomonis N, Vranizan K, Lawlor SC, Conklin BR. GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nat Genet 2002; 31: 19-20. google scholar
  • 10. Von Frankenberg AD, Reis AF, Gerchman F. Relationships between adiponectin levels, the metabolic syndrome, and type 2 diabetes: A literatüre review. Arch Endocrinol Metab 2017; 61: 614-22. google scholar
  • 11. Choi HM, Doss HM, Kim KS. Multifaceted physiological roles of adiponectin in inflammation and diseases. Int J Mol Sci 2020; 21(4): 1219. google scholar
  • 12. Ghosh S, Karin M. Missing pieces in the NF-kappaB puzzle. Cell 2002; 109 Suppl: S81-96. google scholar
  • 13. Wunderlich CM, Hövelmeyer N, Wunderlich FT. Mechanisms of chronic JAK-STAT3-SOCS3 signaling in obesity. JAKSTAT 2013; 2(2): e23878. google scholar
  • 14. Mori H, Hanada R, Hanada T, Aki D, Mashima R, Nishinakamura H, et al. Socs3 deficiency in the brain elevates leptin sensitivity and confers resistance to diet-induced obesity. Nat Med 2004; 10: 739-43. google scholar
  • 15. Talior I, Yarkoni M, Bashan N, Eldar-Finkelman H. Increased glucose uptake promotes oxidative stress and PKC-delta activation in adipocytes of obese, insulin-resistant mice. Am J Physiol Endocrinol Metab 2003; 285: E295-302. google scholar
  • 16. Al Haj Ahmad RM, Al-Domi HA. Complement 3 serum levels as a pro-inflammatory biomarker for insulin resistance in obesity. Diabetes Metab Syndr 2017; 11 Suppl 1: S229-32. google scholar
  • 17. Atanes P, Ruz-Maldonado I, Pingitore A, Hawkes R, Liu B, Zhao M, et al. C3aR and C5aR1 act as key regulators of human and mouse P-cell function. Cell Mol Life Sci 2018; 75(4): 715-26. google scholar
  • 18. Moreno-Navarrete JM, Martı'nez-Bamcarte R, Catalan V, Sabater M, Gömez-Ambrosi J, Ortega FJ, et al. Complement factor H is expressed in adipose tissue in association with insulin resistance. Diabetes 2010; 59(1): 200-9. google scholar
  • 19. Shim K, Begum R, Yang C, Wang H. Complement activation in obesity, insulin resistance, and type 2 diabetes mellitus. World J Diabetes 2020;11(1):1-12. google scholar
  • 20. Bernardi F, Mariani G. Biochemical, molecular and clinical aspects of coagulation factor VII and its role in hemostasis and thrombosis. Haematologica 2021; 106(2): 351-62. google scholar
  • 21. Morrissey JH. Tissue factor interactions with factor VII: measurement and clinical significance of factor VIIa in plasma. Blood Coagul Fibrinolysis 1995; 6 Suppl 1: S14-19. google scholar
  • 22. Yi X, Wu P, Liu J, Gong Y, Xu X, Li W. Identification of the potential key genes for adipogenesis from human mesenchymal stem cells by RNA-Seq. J Cell Physiol 2019; 234(11): 20217-27. google scholar
  • 23. Macias-Velasco JF, St Pierre CL, Wayhart JP, Yin L, Spears L, Miranda MA, et al. Parent-of-origin effects propagate through networks to shape metabolic traits. Elife 2022; 11: e72989. google scholar
  • 24. Cancello R, Rouault C, Guilhem G, et al. Urokinase plasminogen activator receptor in adipose tissue macrophages of morbidly obese subjects. Obes Facts 2011; 4(1): 17-25. google scholar
  • 25. Song NJ, Kim S, Jang BH, Chang SH, Yun UJ, Park KM, et al. Small molecule-induced complement factor D (Adipsin) promotes lipid accumulation and adipocyte differentiation. PLoS One 2016; 11(9): e0162228. google scholar
  • 26. Van de Wouwer M, Plaisance S, De Vriese A, Waelkens E, Collen D, Persson J, et al. The lectin-like domain of thrombomodulin interferes with complement activation and protects against arthritis. J Thromb Haemost 2006; 4: 1813-24. google scholar
  • 27. Kopec, AK, Abrahams SR, Thornton S, Palumbo JS, Mullins ES, Divanovic S, et al. Thrombin promotes diet-induced obesity through fibrin-driven inflammation. J Clin Invest 2017; 127(8): 3152-66. google scholar
  • 28. Kim HB, Kong M, Kim TM, Suh YH, Kim WH, Lim JH, et al. NFATc4 and ATF3 negatively regulate adiponectin gene expression in 3T3-L1 adipocytes. Diabetes 2006; 55: 1342-52. google scholar
  • 29. Yang TTC, Suk HY, Yang XY, Olabisi O, Yu RYL, Durand J, et al. Role of transcription factor NFAT in glucose and insulin homeostasis. Mol Cell Biol 2006; 26: 7372-87. google scholar
  • 30. Zhang W, Sloan-Lancaster J, Kitchen J, Trible RP, Samelson LE. LAT: the ZAP-70 tyrosine kinase substrate that links T cell receptor to cellular activation. Cell 1998; 92: 83-92. google scholar
  • 31. Zhou L, Chen H, Xu P, Cong LN, Sciacchitano S, Li Y, et al. Action of insulin receptor substrate-3 (IRS-3) and IRS-4 to stimulate translocation of GLUT4 in rat adipose cells. Mol Endocrinol 1999; 13: 505-14. google scholar
  • 32. Son NH, Basu D, Samovski D, Pietka TA, Peche VS, Willecke F, et al. Endothelial cell CD36 optimizes tissue fatty acid uptake. J Clin Invest 2018; 128(10): 4329-42. google scholar
  • 33. Oguri Y, Shinoda K, Kim H, Alba DL, Bolus WR, Wang Q, et al. CD81 controls beige fat progenitor cell growth and energy balance via FAK signaling. Cell 2020; 182(3): 563-77.e20. google scholar
  • 34. Canaan A, Yu X, Booth CJ, Lian J, Lazar I, Gamfi SL, et al. FAT10/ diubiquitin-like protein-deficient mice exhibit minimal phenotypic differences. Mol Cell Biol 2006; 26: 5180-9. google scholar
  • 35. Rodgers KJ, Watkins DJ, Miller AL, Chan PY, Karanam S, Brissette WH, et al. Destabilizing role of cathepsin S in murine atherosclerotic plaques. Arterioscler Thromb Vasc Biol 2006; 26: 851-6. google scholar
  • 36. Hsing LC, Kirk EA, McMillen TS, Hsiao SH, Caldwell M, Houston B, et al. Roles for cathepsins S, L, and B in insulitis and diabetes in the NOD mouse. J Autoimmun 2010; 34: 96-104. google scholar
Year 2024, Volume: 14 Issue: 2, 73 - 84, 26.08.2024
https://doi.org/10.26650/experimed.1384602

Abstract

References

  • 1. Phillips CL, Grayson BE. The immune remodel: Weight loss-mediated inflammatory changes to obesity. Exp Biol Med (Maywood) 2020; 245(2): 109-121. google scholar
  • 2. Mikhailova SV, Ivanoshchuk DE. Innate-Immunity Genes in Obesity. J Pers Med 2021; 11(11): 1201. google scholar
  • 3. Wagener A, Goessling HF, Schmitt AO, Mauel S, Gruber AD, Reinhardt R, et al. Genetic and diet effects on Ppar-a and Ppar—Y signaling pathways in the Berlin Fat Mouse Inbred line with genetic predisposition for obesity. Lipids Health Dis 2010; 9: 99. google scholar
  • 4. Hantschel C, Wagener A, Neuschl C, Teupser D, Brockmann GA. Features of the metabolic syndrome in the Berlin Fat Mouse as a model for human obesity. Obes Facts 2011; 4(4): 270-7. google scholar
  • 5. Reimers M, Carey VJ. Bioconductor: an open source framework for bioinformatics and computational biology. Methods Enzymol 2006; 411: 119-34. google scholar
  • 6. Dunning MJ, Smith ML, Ritchie ME, Tavare S. beadarray: R classes and methods for Illumina bead-based data. Bioinformatics 2007; 23: 2183-4. google scholar
  • 7. Ihaka R, Gentleman R. A language for data analysis and graphics. J Comp Graph Statistics 1996; 5: 299-314. google scholar
  • 8. Cui X, Churchill GA. Statistical tests for differential expression in cDNA microarray experiments. Genome Biol 2003; 4: 210. google scholar
  • 9. Dahlquist KD, Salomonis N, Vranizan K, Lawlor SC, Conklin BR. GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nat Genet 2002; 31: 19-20. google scholar
  • 10. Von Frankenberg AD, Reis AF, Gerchman F. Relationships between adiponectin levels, the metabolic syndrome, and type 2 diabetes: A literatüre review. Arch Endocrinol Metab 2017; 61: 614-22. google scholar
  • 11. Choi HM, Doss HM, Kim KS. Multifaceted physiological roles of adiponectin in inflammation and diseases. Int J Mol Sci 2020; 21(4): 1219. google scholar
  • 12. Ghosh S, Karin M. Missing pieces in the NF-kappaB puzzle. Cell 2002; 109 Suppl: S81-96. google scholar
  • 13. Wunderlich CM, Hövelmeyer N, Wunderlich FT. Mechanisms of chronic JAK-STAT3-SOCS3 signaling in obesity. JAKSTAT 2013; 2(2): e23878. google scholar
  • 14. Mori H, Hanada R, Hanada T, Aki D, Mashima R, Nishinakamura H, et al. Socs3 deficiency in the brain elevates leptin sensitivity and confers resistance to diet-induced obesity. Nat Med 2004; 10: 739-43. google scholar
  • 15. Talior I, Yarkoni M, Bashan N, Eldar-Finkelman H. Increased glucose uptake promotes oxidative stress and PKC-delta activation in adipocytes of obese, insulin-resistant mice. Am J Physiol Endocrinol Metab 2003; 285: E295-302. google scholar
  • 16. Al Haj Ahmad RM, Al-Domi HA. Complement 3 serum levels as a pro-inflammatory biomarker for insulin resistance in obesity. Diabetes Metab Syndr 2017; 11 Suppl 1: S229-32. google scholar
  • 17. Atanes P, Ruz-Maldonado I, Pingitore A, Hawkes R, Liu B, Zhao M, et al. C3aR and C5aR1 act as key regulators of human and mouse P-cell function. Cell Mol Life Sci 2018; 75(4): 715-26. google scholar
  • 18. Moreno-Navarrete JM, Martı'nez-Bamcarte R, Catalan V, Sabater M, Gömez-Ambrosi J, Ortega FJ, et al. Complement factor H is expressed in adipose tissue in association with insulin resistance. Diabetes 2010; 59(1): 200-9. google scholar
  • 19. Shim K, Begum R, Yang C, Wang H. Complement activation in obesity, insulin resistance, and type 2 diabetes mellitus. World J Diabetes 2020;11(1):1-12. google scholar
  • 20. Bernardi F, Mariani G. Biochemical, molecular and clinical aspects of coagulation factor VII and its role in hemostasis and thrombosis. Haematologica 2021; 106(2): 351-62. google scholar
  • 21. Morrissey JH. Tissue factor interactions with factor VII: measurement and clinical significance of factor VIIa in plasma. Blood Coagul Fibrinolysis 1995; 6 Suppl 1: S14-19. google scholar
  • 22. Yi X, Wu P, Liu J, Gong Y, Xu X, Li W. Identification of the potential key genes for adipogenesis from human mesenchymal stem cells by RNA-Seq. J Cell Physiol 2019; 234(11): 20217-27. google scholar
  • 23. Macias-Velasco JF, St Pierre CL, Wayhart JP, Yin L, Spears L, Miranda MA, et al. Parent-of-origin effects propagate through networks to shape metabolic traits. Elife 2022; 11: e72989. google scholar
  • 24. Cancello R, Rouault C, Guilhem G, et al. Urokinase plasminogen activator receptor in adipose tissue macrophages of morbidly obese subjects. Obes Facts 2011; 4(1): 17-25. google scholar
  • 25. Song NJ, Kim S, Jang BH, Chang SH, Yun UJ, Park KM, et al. Small molecule-induced complement factor D (Adipsin) promotes lipid accumulation and adipocyte differentiation. PLoS One 2016; 11(9): e0162228. google scholar
  • 26. Van de Wouwer M, Plaisance S, De Vriese A, Waelkens E, Collen D, Persson J, et al. The lectin-like domain of thrombomodulin interferes with complement activation and protects against arthritis. J Thromb Haemost 2006; 4: 1813-24. google scholar
  • 27. Kopec, AK, Abrahams SR, Thornton S, Palumbo JS, Mullins ES, Divanovic S, et al. Thrombin promotes diet-induced obesity through fibrin-driven inflammation. J Clin Invest 2017; 127(8): 3152-66. google scholar
  • 28. Kim HB, Kong M, Kim TM, Suh YH, Kim WH, Lim JH, et al. NFATc4 and ATF3 negatively regulate adiponectin gene expression in 3T3-L1 adipocytes. Diabetes 2006; 55: 1342-52. google scholar
  • 29. Yang TTC, Suk HY, Yang XY, Olabisi O, Yu RYL, Durand J, et al. Role of transcription factor NFAT in glucose and insulin homeostasis. Mol Cell Biol 2006; 26: 7372-87. google scholar
  • 30. Zhang W, Sloan-Lancaster J, Kitchen J, Trible RP, Samelson LE. LAT: the ZAP-70 tyrosine kinase substrate that links T cell receptor to cellular activation. Cell 1998; 92: 83-92. google scholar
  • 31. Zhou L, Chen H, Xu P, Cong LN, Sciacchitano S, Li Y, et al. Action of insulin receptor substrate-3 (IRS-3) and IRS-4 to stimulate translocation of GLUT4 in rat adipose cells. Mol Endocrinol 1999; 13: 505-14. google scholar
  • 32. Son NH, Basu D, Samovski D, Pietka TA, Peche VS, Willecke F, et al. Endothelial cell CD36 optimizes tissue fatty acid uptake. J Clin Invest 2018; 128(10): 4329-42. google scholar
  • 33. Oguri Y, Shinoda K, Kim H, Alba DL, Bolus WR, Wang Q, et al. CD81 controls beige fat progenitor cell growth and energy balance via FAK signaling. Cell 2020; 182(3): 563-77.e20. google scholar
  • 34. Canaan A, Yu X, Booth CJ, Lian J, Lazar I, Gamfi SL, et al. FAT10/ diubiquitin-like protein-deficient mice exhibit minimal phenotypic differences. Mol Cell Biol 2006; 26: 5180-9. google scholar
  • 35. Rodgers KJ, Watkins DJ, Miller AL, Chan PY, Karanam S, Brissette WH, et al. Destabilizing role of cathepsin S in murine atherosclerotic plaques. Arterioscler Thromb Vasc Biol 2006; 26: 851-6. google scholar
  • 36. Hsing LC, Kirk EA, McMillen TS, Hsiao SH, Caldwell M, Houston B, et al. Roles for cathepsins S, L, and B in insulitis and diabetes in the NOD mouse. J Autoimmun 2010; 34: 96-104. google scholar
There are 36 citations in total.

Details

Primary Language English
Subjects Genetics (Other)
Journal Section Research Article
Authors

Ayça Doğan 0000-0002-6020-8327

Gudrun A. Brockmann 0000-0002-4387-2947

Publication Date August 26, 2024
Submission Date November 1, 2023
Acceptance Date August 5, 2024
Published in Issue Year 2024 Volume: 14 Issue: 2

Cite

Vancouver Doğan A, Brockmann GA. Gene Expression Profile as a Precursor of Inflammation in Mouse Models: BFMI860 and C57BL/6NCrl. Experimed. 2024;14(2):73-84.