Wieder Nicolas, Fried Juliana Coraor, Kim Choah, Sidhom Eriene-Heidi, Brown Matthew R, Marshall Jamie L, Arevalo Carlos, Dvela-Levitt Moran, Kost-Alimova Maria, Sieber Jonas, Gabriel Katlyn R, Pacheco Julian, Clish Clary, Abbasi Hamdah Shafqat, Singh Shantanu, Rutter Justine, Therrien Martine, Yoon Haejin, Lai Zon Weng, Baublis Aaron, Subramanian Renuka, Devkota Ranjan, Small Jonnell, Sreekanth Vedagopuram, Han Myeonghoon, Lim Donghyun, Carpenter Anne E, Flannick Jason, Finucane Hilary, Haigis Marcia C, Claussnitzer Melina, Sheu Eric, Stevens Beth, Wagner Bridget K, Choudhary Amit, Shaw Jillian L, Pablo Juan Lorenzo, Greka Anna
Broad Institute of MIT and Harvard, Cambridge, USA.
Department of Medicine, Brigham and Women's Hospital, Boston USA.
bioRxiv. 2023 Feb 20:2023.02.19.529127. doi: 10.1101/2023.02.19.529127.
Cellular exposure to free fatty acids (FFA) is implicated in the pathogenesis of obesity-associated diseases. However, studies to date have assumed that a few select FFAs are representative of broad structural categories, and there are no scalable approaches to comprehensively assess the biological processes induced by exposure to diverse FFAs circulating in human plasma. Furthermore, assessing how these FFA- mediated processes interact with genetic risk for disease remains elusive. Here we report the design and implementation of FALCON (Fatty Acid Library for Comprehensive ONtologies) as an unbiased, scalable and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids (MUFAs) with a distinct lipidomic profile associated with decreased membrane fluidity. Furthermore, we developed a new approach to prioritize genes that reflect the combined effects of exposure to harmful FFAs and genetic risk for type 2 diabetes (T2D). Importantly, we found that c-MAF inducing protein (CMIP) protects cells from exposure to FFAs by modulating Akt signaling and we validated the role of CMIP in human pancreatic beta cells. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism.
FALCON (Fatty Acid Library for Comprehensive ONtologies) enables multimodal profiling of 61 free fatty acids (FFAs) to reveal 5 FFA clusters with distinct biological effectsFALCON is applicable to many and diverse cell typesA subset of monounsaturated FAs (MUFAs) equally or more toxic than canonical lipotoxic saturated FAs (SFAs) leads to decreased membrane fluidityNew approach prioritizes genes that represent the combined effects of environmental (FFA) exposure and genetic risk for diseaseC-Maf inducing protein (CMIP) is identified as a suppressor of FFA-induced lipotoxicity via Akt-mediated signaling.
细胞暴露于游离脂肪酸（FFA）与肥胖相关疾病的发病机制有关。然而，迄今为止的研究假定少数几种特定的FFA代表了广泛的结构类别，并且没有可扩展的方法来全面评估暴露于人类血浆中循环的多种FFA所诱导的生物学过程。此外，评估这些FFA介导的过程如何与疾病的遗传风险相互作用仍然难以捉摸。在这里，我们报告了FALCON（综合本体脂肪酸文库）的设计和实施，它是对61种结构多样的FFA进行无偏倚、可扩展和多模式的探究。我们鉴定出一组具有独特脂质组学特征且与膜流动性降低相关的脂毒性单不饱和脂肪酸（MUFA）。此外，我们开发了一种新方法来对反映暴露于有害FFA和2型糖尿病（T2D）遗传风险综合效应的基因进行优先级排序。重要的是，我们发现c-MAF诱导蛋白（CMIP）通过调节Akt信号传导保护细胞免受FFA暴露的影响，并且我们在人胰腺β细胞中验证了CMIP的作用。总之，FALCON助力基础FFA生物学的研究，并提供一种综合方法来识别与FFA代谢紊乱相关的多种疾病急需的靶点。
FALCON（综合本体脂肪酸文库）能够对61种游离脂肪酸（FFA）进行多模式分析，以揭示具有不同生物学效应的5个FFA簇FALCON适用于多种不同类型的细胞一组毒性与典型脂毒性饱和脂肪酸（SFA）相当或更高的单不饱和脂肪酸（MUFA）会导致膜流动性降低新方法对代表环境（FFA）暴露和疾病遗传风险综合效应的基因进行优先级排序c-Maf诱导蛋白（CMIP）被鉴定为通过Akt介导的信号传导抑制FFA诱导的脂毒性。
