Table_1_Transcriptomic Regulation of Muscle Mitochondria and Calcium Signaling by Insulin/IGF-1 Receptors Depends on FoxO Transcription Factors.XLSX
Insulin and IGF-1, acting through the insulin receptor (IR) and IGF-1 receptor (IGF1R), maintain muscle mass and mitochondrial function, at least part of which occurs via their action to regulate gene expression. Here, we show that while muscle-specific deletion of IR or IGF1R individually results in only modest changes in the muscle transcriptome, combined deletion of IR/IGF1R (MIGIRKO) altered > 3000 genes, including genes involved in mitochondrial dysfunction, fibrosis, cardiac hypertrophy, and pathways related to estrogen receptor, protein kinase A (PKA), and calcium signaling. Functionally, this was associated with decreased mitochondrial respiration and increased ROS production in MIGIRKO muscle. To determine the role of FoxOs in these changes, we performed RNA-Seq on mice with muscle-specific deletion of FoxO1/3/4 (M-FoxO TKO) or combined deletion of IR, IGF1R, and FoxO1/3/4 in a muscle quintuple knockout (M-QKO). This revealed that among IR/IGF1R regulated genes, >97% were FoxO-dependent, and their expression was normalized in M-FoxO TKO and M-QKO muscle. FoxO-dependent genes were related to oxidative phosphorylation, inflammatory signaling, and TCA cycle. Metabolomic analysis showed accumulation of TCA cycle metabolites in MIGIRKO, which was reversed in M-QKO muscle. Likewise, calcium signaling genes involved in PKA signaling and sarcoplasmic reticulum calcium homeostasis were markedly altered in MIGIRKO muscle but normalized in M-QKO. Thus, combined loss of insulin and IGF-1 action in muscle transcriptionally alters mitochondrial function and multiple regulatory and signaling pathways, and these changes are mediated by FoxO transcription factors.
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References
- https://doi.org//10.1016/j.bbabio.2016.07.008
- https://doi.org//10.1007/s12079-018-0477-z
- https://doi.org//10.2337/dc08-1781
- https://doi.org//10.1016/j.celrep.2019.02.081
- https://doi.org//10.1172/JCI146415
- https://doi.org//10.1152/ajpheart.00549.2016
- https://doi.org//10.1093/bioinformatics/bts635
- https://doi.org//10.1038/nrm3507
- https://doi.org//10.2337/db15-0982
- https://doi.org//10.1007/s00109-012-0887-y
- https://doi.org//10.1016/j.ceca.2014.08.009
- https://doi.org//10.1074/jbc.274.24.17184
- https://doi.org//10.1038/nrm.2017.89
- https://doi.org//10.1016/j.freeradbiomed.2010.12.005
- https://doi.org//10.1016/j.cmet.2017.06.010
- https://doi.org//10.1074/jbc.M400674200
- https://doi.org//10.2337/diabetes.51.10.2944
- https://doi.org//10.2337/db05-1613
- https://doi.org//10.1083/jcb.200704179
- https://doi.org//10.1038/s41588-018-0223-8
- https://doi.org//10.1186/s13059-014-0550-8
- https://doi.org//10.1074/jbc.M112.442061
- https://doi.org//10.1093/bioinformatics/btp053
- https://doi.org//10.2337/db06-0981
- https://doi.org//10.3389/fphys.2021.671292
- https://doi.org//10.1074/jbc.274.23.15982
- https://doi.org//10.2337/db18-0416
- https://doi.org//10.1016/j.celrep.2015.04.037
- https://doi.org//10.1172/JCI86522
- https://doi.org//10.1007/s00592-017-0979-9
- https://doi.org//10.2337/db05-1183
- https://doi.org//10.1073/pnas.1032913100
- https://doi.org//10.1093/nar/gkv007
- https://doi.org//10.1186/gb-2010-11-3-r25
- https://doi.org//10.1074/jbc.M300293200
- https://doi.org//10.1172/JCI120843
- https://doi.org//10.1016/s0092-8674(04)00400-3
- https://doi.org//10.1016/s1097-2765(04)00211-4
- https://doi.org//10.1073/pnas.1332551100
- https://doi.org//10.1038/nrm1837
- https://doi.org//10.1007/s00125-017-4496-8
- https://doi.org//10.1017/erm.2014.17
- https://doi.org//10.1016/j.molmet.2021.101304
- https://doi.org//10.1073/pnas.0407574101
- https://doi.org//10.2337/db15-0823
- https://doi.org//10.1210/en.2011-1527
- https://doi.org//10.1074/jbc.M600272200
- https://doi.org//10.1016/j.cmet.2007.11.004