bioRxivCell Biology
FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity
N. Wieder, J. M. Coraor Fried, C. Kim, E.-H. Sidhom, M. R. Brown, J. L. Marshall, C. Arevalo, M. Dvela-Levitt, M. Kost-Alimova, J. Sieber, K. R. Gabriel, J. Pacheco, C. B. Clish, H. S. Abbasi, S. Singh, J. Rutter, M. Therrien, H. Yoon, Z. W. Lai, A. Baublis, R. Subramanian, R. Devkota, J. Small, V. Sreekanth, M. Han, , A. Greka
Abstract
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. HighlightsO_LIFALCON (Fatty Acid Library for Comprehensive ONtologies) enables multimodal profiling of 61 free fatty acids (FFAs) to reveal 5 FFA clusters with distinct biological effects C_LIO_LIFALCON is applicable to many and diverse cell types C_LIO_LIA subset of monounsaturated FAs (MUFAs) equally or more toxic than canonical lipotoxic saturated FAs (SFAs) leads to decreased membrane fluidity C_LIO_LINew approach prioritizes genes that represent the combined effects of environmental (FFA) exposure and genetic risk for disease C_LIO_LIC-Maf inducing protein (CMIP) is identified as a suppressor of FFA-induced lipotoxicity via Akt-mediated signaling C_LI
- organism: human
- assay: metabolomics
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: deep learning
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