Adrenergic stimulation of brown adipocytes alters mitochondrial dynamics, including the mitochondrial fusion protein optic atrophy 1 (OPA1). However, direct mechanisms linking OPA1 to brown adipose tissue (BAT) physiology are incompletely understood. We utilized a mouse model of selective OPA1 deletion in BAT (OPA1 BAT KO) to investigate the role of OPA1 in thermogenesis. OPA1 is required for cold-induced activation of thermogenic genes in BAT. Unexpectedly, OPA1 deficiency induced fibroblast growth factor 21 (FGF21) as a BATokine in an activating transcription factor 4 (ATF4)-dependent manner. BAT-derived FGF21 mediates an adaptive response, by inducing browning of white adipose tissue, increasing resting metabolic rates, and improving thermoregulation. However, mechanisms independent of FGF21, but dependent on ATF4 induction, promote resistance to diet-induced obesity in OPA1 BAT KO mice. These findings uncover a homeostatic mechanism of BAT-mediated metabolic protection governed in part by an ATF4-FGF21 axis, that is activated independently of BAT thermogenic function.
All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided for all figures.
- E Dale Abel
- E Dale Abel
- E Dale Abel
- Renata O Pereira
- Renata O Pereira
- Sarah Hartwick Bjorkman
- Luis Miguel García-Peña
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#8051408 and 0032294) of the University of Iowa.
- Joel K Elmquist, University of Texas Southwestern Medical Center, United States
© 2021, Pereira et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. However, the high sequence and structural conservation of the catalytic kinase domain complicates the development of selective kinase inhibitors. Inhibition of off-target kinases makes it difficult to study the mechanism of inhibitors in biological systems. Current efforts focus on the development of inhibitors with improved selectivity. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target effects. We develop a multicompound-multitarget scoring (MMS) method that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables optimization of inhibitor combinations for multiple on-targets. Using MMS with published kinase inhibitor datasets we determine potent inhibitor combinations for target kinases with better selectivity than the most selective single inhibitor and validate the predicted effect and selectivity of inhibitor combinations using in vitro and in cellulo techniques. MMS greatly enhances selectivity in rational multitargeting applications. The MMS framework is generalizable to other non-kinase biological targets where compound selectivity is a challenge and diverse compound libraries are available.
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