RESUMO
The lack of registered drugs for nonalcoholic fatty liver disease (NAFLD) is partly due to the paucity of human-relevant models for target discovery and compound screening. Here we use human fetal hepatocyte organoids to model the first stage of NAFLD, steatosis, representing three different triggers: free fatty acid loading, interindividual genetic variability (PNPLA3 I148M) and monogenic lipid disorders (APOB and MTTP mutations). Screening of drug candidates revealed compounds effective at resolving steatosis. Mechanistic evaluation of effective drugs uncovered repression of de novo lipogenesis as the convergent molecular pathway. We present FatTracer, a CRISPR screening platform to identify steatosis modulators and putative targets using APOB-/- and MTTP-/- organoids. From a screen targeting 35 genes implicated in lipid metabolism and/or NAFLD risk, FADS2 (fatty acid desaturase 2) emerged as an important determinant of hepatic steatosis. Enhancement of FADS2 expression increases polyunsaturated fatty acid abundancy which, in turn, reduces de novo lipogenesis. These organoid models facilitate study of steatosis etiology and drug targets.
Assuntos
Hepatopatia Gordurosa não Alcoólica , Humanos , Hepatopatia Gordurosa não Alcoólica/tratamento farmacológico , Hepatopatia Gordurosa não Alcoólica/genética , Avaliação Pré-Clínica de Medicamentos , Hepatócitos/metabolismo , Metabolismo dos Lipídeos , Apolipoproteínas B/metabolismo , Fígado/metabolismoRESUMO
Addressing bioenergetics is key to evaluate the impact of metabolism on the regulation of biological processes and its alteration in disease. Organoids are in vitro grown self-organizing structures derived from healthy and diseased tissue that recapitulate with high fidelity the tissue of origin. Bioenergetics is commonly analyzed by Seahorse XF analysis. However, its application to organoid studies is technically challenging. Here, we share our in-house optimized protocols to examine organoid bioenergetics in response to drugs, gene knockdown, or to characterize the metabolism of specific cell types. For complete details on the use and execution of this protocol, please refer to Ludikhuize et al. (2020).