Hepatic lipid overload triggers biliary epithelial cell activation via E2Fs

During severe or chronic hepatic injury, biliary epithelial cells (BECs) undergo rapid activation into proliferating progenitors, a crucial step required to establish a regenerative process known as ductular reaction (DR). While DR is a hallmark of chronic liver diseases, including advanced stages of non-alcoholic fatty liver disease (NAFLD), the early events underlying BEC activation are largely unknown. Here, we demonstrate that BECs readily accumulate lipids during high-fat diet feeding in mice and upon fatty acid treatment in BEC-derived organoids. Lipid overload induces metabolic rewiring to support the conversion of adult cholangiocytes into reactive BECs. Mechanistically, we found that lipid overload activates the E2F transcription factors in BECs, which drive cell cycle progression while promoting glycolytic metabolism. These findings demonstrate that fat overload is sufficient to reprogram BECs into progenitor cells in the early stages of NAFLD and provide new insights into the mechanistic basis of this process, revealing unexpected connections between lipid metabolism, stemness, and regeneration.

The molecular basis by which BECs expand during the DR has been extensively studied in models of chemical biliary damage and portal fibrosis using the chemical 3,5-diethoxycarbonyl-1,4-dihydroc ollidine (DDC). Several signaling pathways involving YAP (Meyer et al., 2020;Pepe-Mooney et al., 2019;Planas-Paz et al., 2019), mTORC1 (Planas-Paz et al., 2019), TET1-mediated hydroxymethylation (Aloia et al., 2019) and NCAM1 (Tsuchiya et al., 2014) have been reported to drive this process. Importantly, DR has also been observed in late-stage NAFLD patients with fibrosis and portal inflammation (Gadd et al., 2014;Sato et al., 2019;Sorrentino et al., 2005). NAFLD, one of the most common chronic diseases, initiates with increased lipid accumulation, a stage called steatosis (Paschos and Paletas, 2009). This pathology progresses into inflammation and fibrosis that can cause cirrhosis and hepatocellular carcinoma, which are the most frequent liver transplantation indications (Byrne and Targher, 2015). YAP has been found to be activated in BECs in fibrotic livers but not in steatosis (Machado et al., 2015), suggesting that YAP activation is necessary to support DR in the late fibrotic NAFLD stages, and thus, leaving the early molecular mechanisms of BEC activation, which precede the onset of the DR, unexplored.
Here, we used BEC-organoids and BECs isolated from chow diet (CD)-or high-fat diet (HFD)-fed mice and reported that they are affected by acute and chronic lipid overload, one of the initial steps of NAFLD. Lipid accumulation turns BECs from quiescent to proliferative cells, the earliest step of a DR, and promotes their expansion through the E2F transcription factors and the concomitant induction of glycolysis. These observations hence attribute a pivotal role to E2Fs, regulators of cell cycle and metabolism, in priming BEC activation during the early stages of NAFLD.

BECs and BEC-organoids efficiently accumulate lipids in vivo and in vitro
To gain insight into how chronic lipid exposure, which induces liver steatosis, affects biliary progenitor function in vitro, we incubated single BECs with a mixture of oleic acid (OA) and palmitic acid (PA) (the fatty acid (FA) mix) -the two most abundant FAs found in livers of NAFLD patients (Araya et al., 2004), for 7 days and allowed BEC-organoid formation ( Figure 1A). Surprisingly, we observed that BEC-organoids efficiently accumulated lipid droplets in a dose-dependent manner ( Figure 1B), and this process did not affect organoid viability ( Figure 1C-D). To investigate how cells adapt their metabolism to lipid overload, we monitored the expression of several genes involved in lipid metabolism, including Scd1 (de novo lipogenesis) ( Figure 1E), Hmgcs2 (ketogenesis), Pdk4 (inhibition of pyruvate oxidation), and Aldh1a1 (prevention against lipid peroxidation products) ( Figure 1F) and found it to be affected by FA addition. These results suggest that BEC organoids actively reprogram their metabolism to cope with aberrant lipid overload.
To determine whether the observed phenotype was preserved in fully formed organoids, we treated already established BEC-organoids with the FA mix for 4 days (Figure 1-figure supplement  1A). In line with our previous observations, BODIPY staining ( Figure 1-figure supplement 1B), and triglyceride (TG) quantification ( Figure 1-figure supplement 1C) showed a pronounced increase in lipid accumulation after 4 days, without affecting cell viability (Figure 1-figure supplement 1D).
To assess whether chronic lipid exposure affects BECs in vivo, we fed C57BL/6 J mice for 15 weeks with CD or HFD ( Figure 1G) and analyzed their bile ducts. As expected, HFD-fed mice gained weight and developed liver steatosis, but no apparent fibrosis (Figure 1-figure supplement 1E). Of note, HFD-feeding led to an accumulation of lipid droplets in the periportal zone ( Figure 1-figure supplement 1F) and within bile ducts, as reflected by the localization of BODIPY signal in PANCK (BEC marker) positive cells ( Figure 1H), without inducing epithelial damage (Figure 1-figure supplement 1G-I). Moreover, flow cytometry analysis of BECs stained with EPCAM, a pan-BEC marker (Aloia et al., 2019;Pepe-Mooney et al., 2019;Planas-Paz et al., 2019) and BODIPY confirmed that these  The online version of this article includes the following figure supplement(s) for figure 1: cells are able to store lipids upon HFD feeding ( Figure 1I and Figure 1-figure supplement 1L). Together, these in vitro and in vivo results demonstrate that BECs accumulate lipids upon chronic FA exposure, raising the question of the functional consequences of this previously unrecognized event on BEC behavior.

HFD feeding promotes BEC activation and increases organoid formation capacity
To characterize in vivo the impact of chronic lipid overload on BECs at the molecular level, we isolated EPCAM + BECs from livers of CD/HFD-fed mice by fluorescence-activated cell sorting (FACS) (Figure 2A and To further explore the transcriptional changes, we performed gene set enrichment analysis (GSEA) on Gene Ontology (GO) terms ( Figure 2B) and KEGG (Figure 2-figure supplement 1F) pathways and identified cell proliferation, the most prevalent early feature of BEC activation (Sato et al., 2019) as the major process induced in these cells upon HFD feeding. Expansion of the reactive BECs requires detachment from their niche and invasion of the parenchyma toward the damaged hepatic area. This process is made possible by reorganizing the extracellular matrix (ECM) and reducing focal adhesion, effectively downregulated in EPCAM + BECs upon HFD ( Figure 2B and To validate the RNA-seq data, we monitored the activation of BECs in vivo by measuring the number of proliferating BECs in the portal region of the livers of mice fed either CD or HFD ( Figure 2C-D). Of note, we found that HFD feeding was sufficient to induce a marked increase in the number of active BECs (i.e. Ki67 + /OPN + cells- Figure 2C-D). Similar results were observed in two independent cohorts of mice challenged with HFD and injected with EdU either to track proliferating cells by immunofluorescence ( Figure 2E-F) or to quantify by flow cytometry the amount of EPCAM + /EdU + BECs in the liver ( Figure 2G), confirming that chronic lipid exposure stimulates the appearance of reactive BECs within the bile ducts.
The efficiency of BECs to generate organoids in vitro has been shown to mirror their activation status (Aloia et al., 2019). To functionally assess the impact of lipid overload on this process, we measured the organoid-forming capacity of isolated BECs, as a read-out of their regenerative potential. To this aim, we quantified the organoid formation efficiency of BECs isolated from CD-and HFDfed mouse livers ( Figure 2H). Strikingly, we observed that HFD-derived BECs were significantly more efficient in generating organoids than their CD counterparts ( Figure 2I). Altogether, these results demonstrate that HFD feeding is sufficient to induce, in vivo, the exit of BECs from a quiescent state and the acquisition of both proliferative and pro-regenerative features.

HFD feeding initiates BEC activation via E2Fs
To understand whether the mechanisms underlying BEC activation upon HFD in vivo involve canonical processes by which BECs expand during the DR in chronically damaged livers, we compared the transcriptional profile of BECs upon HFD with those of DDC-activated BECs (Pepe-Mooney et al., 2019;GSE125688). We identified the most pronounced changes shared between HFD and DDC samples by overlapping separate over-representation enrichment analyses (Supplementary file 2). Cell division, mitosis, and chromosome segregation were the shared enriched pathways for upregulated genes in HFD and DDC samples ( Figure 3A), while ECM organization was the shared enriched pathway for the downregulated genes in HFD and DDC conditions (Figure 3-figure supplement 1A). We concluded that the mechanisms of BEC activation induced by lipid overload partially overlap with those by which BECs expand during the DR with biliary epithelial damage. E2Fs are a large family of TFs with complex functions in cell cycle progression, DNA replication, repair, and G2/M checkpoints (Dimova and Dyson, 2005;Dyson, 1998;Dyson, 2016;Ren et al., 2002). Therefore, we hypothesized that the activation of E2Fs might represent an early event in the process of BEC activation, which is necessary for exiting the quiescent state and promoting BEC expansion. To test this hypothesis, we focused on E2F1, as it was the most enriched TF in our analysis, and assessed its role in BECs by feeding E2f1 +/+ and E2f1 -/mice with HFD ( Figure 3D). Remarkably, E2f1 -/mice were refractory to BEC activation induced by lipid overload upon HFD, as opposed to E2f1 +/+ mice ( Figure 3E-F). In addition, silencing of E2F1 in EPCAM + BECs from livers of C57BL/6 J HFD-fed mice (Figure 3-figure supplement 1D) reduced the capacity to form organoids in vitro ( Figure 3-figure supplement 1E). These results demonstrate a previously unrecognized role of E2F1 in controlling BEC activation during HFD-induced hepatic steatosis in vivo and support a pivotal role of this transcription factor in controlling BEC expansion.

E2Fs promote BEC expansion by upregulating glycolysis
The exit of terminally-differentiated cells from their quiescent state requires both energy and building block availability to support cell proliferation. Proliferative cells, therefore, reprogram their glucose metabolism to meet their increased need for biomass and energy (Vander Heiden et al., 2009). Supporting this notion, our interrogation of in vitro BEC-organoid formation dataset (Aloia et al., 2019) revealed the enrichment of purine and pyrimidine metabolism, as well as the pentose-phosphate pathway, which is tightly connected to glycolysis (Figure 4-figure supplement 1A). In line with these findings, a substrate oxidation test in BEC-organoids revealed a preference for glucose, as reflected by the decrease in maximal respiration, when UK5099, a mitochondrial pyruvate carrier inhibitor, was used ( Figure  To investigate the metabolic changes in BEC-organoids upon HFD, we treated CD/HFD BECorganoids with FA mix to mimic steatotic conditions in vitro ( Figure 4C). We hypothesized that the presence of glucose and FA in culture media would reveal a metabolic shift of BEC-organoids. Consistent with our hypothesis, HFD-FA BEC-organoids demonstrated increased compensatory glycolytic rates ( Figure  Besides their prominent role in cell cycle progression, E2Fs coordinate several aspects of cellular metabolism (Denechaud et al., 2017;Nicolay and Dyson, 2013), and promote glycolysis in different contexts (Blanchet et al., 2011;Denechaud et al., 2016;Huber et al., 2021). These findings prompted us to postulate that E2F might control glycolysis and, thus, the glucose preference observed in BEC-organoids. To investigate this hypothesis, we treated BEC organoids with an E2F inhibitor, HLM006474 ( Figure 4F). As expected, HLM006474 treatment reduced the transcriptional levels of several genes involved in cell cycle progression and glycolytic metabolism ( Figure 4G) and decreased HFD-fed mice. n=10 for Ki67 and n=5 for EdU. (G) Representative quantitative plots of the percentage (left) and quantification (right) of EdU + EPCAM + BECs, relative to panel A. n=5. (H) Schematic depicting BEC-organoid formation in vitro from CD/HFD-fed mouse livers. (I) Images of organoid colonies formed 6 days after seeding and quantification of organoids per well. n=5. Violin graphs depict the distribution of data points i.e the width of the shaded area represents the proportion of data located there. Other data are shown as mean ± SEM. **p<0.01; ****p<0.0001; unpaired, two-tailed Student's t-test was used. PV, portal vein. Arrowheads mark bile ducts. Scale bars, 20 μm (C, E), 200 μm (I).
The online version of this article includes the following figure supplement(s) for figure 2:   In conclusion, these results demonstrate that HFD-induced E2F activation controls the conversion of BECs from quiescent to active progenitors by promoting the expression of cell cycle genes while simultaneously driving a shift toward glycolysis.

Discussion
Through DR activation, BECs represent an essential reservoir of progenitors that are crucial for coordinating hepatic epithelial regeneration in the context of chronic liver diseases (Choi et al., 2014;Deng et al., 2018;Español-Suñer et al., 2012;Huch et al., 2013;Lu et al., 2015;Raven et al., 2017;Rodrigo-Torres et al., 2014;Russell et al., 2019). BEC functions are tightly controlled by YAP metabolic pathways (Meyer et al., 2020;Pepe-Mooney et al., 2019;Planas-Paz et al., 2019), and recent studies from different tissues have provided evidence that specific metabolic states play instructive roles in controlling cell fate and tissue regeneration (Beyaz et al., 2016;Capolupo et al., 2022;Miao et al., 2020;Zhang et al., 2016). Aberrant lipid accumulation is a hallmark of early NAFLD, and imbalances in lipid metabolism are known to affect hepatocyte homeostasis, including induction of lipo-toxicity and cell death (Wang et al., 2016b;Sano et al., 2021;De Gottardi et al., 2007;Wobser et al., 2009;Ipsen et al., 2018). However, the role of lipid dysregulation in BECs and whether it has an impact on BEC activation remains unexplored in the setting of NAFLD.
Here, using HFD-fed mouse models, we studied BEC metabolism in steatosis, the first stage of NAFLD, and demonstrated lipid accumulation in BECs during chronic HFD in vivo and their resistance to lipid-induced toxicity. By using BEC-organoids, we observed that FAs directly target BECs, without any involvement of hepatocytes and that BECs functionally respond to lipid overload. Importantly, BEC-organoids derived from CD-and HFD-fed mouse livers were shown to shift their cellular metabolism toward more glycolysis in the presence of lipids. Furthermore, we found that the HFD-induced metabolic shift was sufficient to reprogram BEC identity in vivo, allowing their exit from a quiescent state and the simultaneous acquisition of progenitor functions, such as proliferation and organoidinitiating capacity. These results highlight the metabolic plasticity of BECs and shed light on an unpredicted mechanism of BEC activation in HFD-induced hepatic steatosis. Importantly, we observed that lipid overload is sufficient to induce BEC activation in steatotic livers and that this process precedes parenchymal damage. While the functional contribution of lipid-activated BECs in liver regeneration during the late stages of NAFLD will require further studies, our data clearly point out the role of BECs as sensors and possibly effectors of early liver diseases such as steatosis.
To fully understand the underlying basis of the observed phenotype, we characterized the transcriptome of primary BECs derived from steatotic livers of HFD-fed mice and demonstrated that long-term feeding of a lipid-enriched diet strongly promotes BEC proliferation, suggesting a strong link between metabolic adaptation and progenitor function. By combining our transcriptomic analysis with data mining of publicly available DR datasets (Aloia et al., 2019;Pepe-Mooney et al., 2019), we identified the E2F transcription factors as master regulators of BEC activation in the context of NAFLD. Moreover, the expression of Pdk4, an E2F1 target (Hsieh et al., 2008;Wang et al., 2016a), was upregulated in FA-treated BEC-organoids and upon HFD. PDK4 limits the utilization of pyruvate for oxidative metabolism while enhancing glycolysis, which reinforces our data demonstrating that E2Fs rewire BEC metabolism toward glycolysis to fuel progenitor proliferation. These observations feature E2Fs as the molecular rheostat integrating the metabolic cell state with the cell cycle of organoid formation from single BECs (Organoids vs. T0) (GSE123133) (C). Asterisk (*) marks TFs of the 'TF_ZHAO' gene set. (D) Schematic depicting in vivo E2F1 analysis. (E-F) Representative images of PANCK/Ki67 co-staining in livers of E2f1 +/+ and E2f1 -/mice fed with chow diet (CD) or HFD (E) and quantification of proliferative BECs in the livers of the indicated mice (F). For CD, n=5 for E2f1 +/+ and E2f1 -/-. For HFD, n=7 for E2f1 +/+ , and n=8 for E2f1 -/-. Violin graphs depict the distribution of data points i.e., the width of the shaded area represents the proportion of data located there. ns, not significant; **p<0.01; two-way ANOVA with Tukey's test was used. PV, portal vein. Arrowheads mark bile ducts. Scale bars, 20 μm (E).
The online version of this article includes the following figure supplement(s) for figure 3:    machinery to coordinate BEC activation. However, how E2Fs are regulated upon HFD and whether they are interconnected with the already known YAP, mTORC1, and TET1 pathways remain unknown and will require further investigation.

R O T / A A 2 -D G
While our data are derived from obese mice, a recent report showed increased numbers of cholangiocytes in steatotic human livers (Hallett et al., 2022), and E2F1 has been found to be upregulated in the livers of obese patients (Denechaud et al., 2016). Moreover, human subjects with elevated visceral fat demonstrated increased glucose metabolism (Broadfield et al., 2021). These observations, while correlative, set the ground for future research in understanding the role and the therapeutic potential of lipid metabolism and E2Fs in controlling BEC activation and, thus, hepatic regeneration in humans.

Mouse studies and ethical approval
All the animal experiments were authorized by the Veterinary Office of the Canton of Vaud, Switzerland, under license authorizations VD3721 and VD2627.b. C57BL/6JRj (in the text referred to as C57BL/6 J) mice were obtained from Janvier Labs and E2f1 +/+ and E2f1 -/-(B6;129S4-E2f1tm1 Meg/J) mice were purchased from The Jackson Laboratory. 8-week-old C57BL/6 J male mice were fed with Chow Diet (CD -SAFE Diets, SAFE 150) or High Fat Diet (HFD -Research Diets Inc, D12492i) for 15 weeks. 7-week-old E2f1 +/+ and E2f1 -/male mice were fed with Chow Diet (CD -Kliba Nafag 3336) or High Fat Diet (HFD -Envigo, TD93075) for 29 weeks. The well-being of the animals was monitored daily, and body weight was monitored once per week until the end of the experiment. All mice had unrestricted access to water and food, and liver tissues were harvested at the end of the experiment.

Data reporting
Mice were randomized into different groups according to their genotype. A previous HFD experiment was used to calculate the sample size for C57BL/6 J mouse experiments. Mice showing any sign of severity, predefined by the Veterinary Office of the Canton of Vaud, Switzerland, were sacrificed and excluded from the data analyses. In vitro experiments were repeated with at least three biological replicates (BEC-organoids from different mice) or were repeated at least twice by pooling four mice per condition (for Seahorse analysis).

Proliferation assay
Cell proliferation was assessed by EdU assay (Click-iT EdU Alexa Fluor 647, ThermoFisher, C10340) following the manufacturer's instructions. For in vivo studies, EdU was resuspended in phosphatebuffered saline (PBS-ThermoFisher, 10010002), and 200 μl of the solution was injected intraperitoneally (50 μg per g of mouse weight) 16 hr before the sacrifice.

Silencing of E2F1 in EPCAM + BECs and organoid formation
To silence E2F1, 2 × 10 4 EPCAM + BECs isolated from the livers of HFD-fed mice were transfected with a pool of four ON-TARGETplus siRNAs for E2f1 (Horizon, L-044993-00-0005) or with scrambled siRNAs (Horizon, D-001810-10-05), using TransIT-X2 (Mirus, MIR6000) according to the manufacturer's instructions. Briefly, the cells and the TransIT-X2 mix were centrifuged at 600 g for 45 min at 32 °C and then incubated for 4 hr at 37 °C. The cell suspension was harvested and seeded in Matrigel in the isolation medium. Growth of BEC-organoids was followed with a luminescent MT Cell Viability Assay (Promega, G9711).

RNA preparation from EPCAM + BECs and bulk RNA-seq data analysis
RNA was isolated from sorted BECs using the RNeasy micro kit (QIAGEN, 74104), and the amount and quality of RNA were measured with the Agilent Tapestation 4200 (Agilent Technologies, 5067-1511). As a result, RNA-seq of five CD and seven HFD samples was performed by BGI with the BGISEQ-500 platform. FastQC was used to verify the quality of the reads (Andrews, 2010). No low-quality reads were present, and no trimming was needed. Alignment was performed against the mouse genome (GRCm38) following the STAR (version 2.6.0 a) manual guidelines (Dobin et al., 2013). The obtained STAR gene counts for each alignment were analyzed for differentially expressed genes using the R package DESeq2 (version 1.34.0) (Love et al., 2014). A threshold of 1 log2 fold change and adjusted p-value smaller than 0.05 were considered when identifying the differentially expressed genes. A principal component analysis (PCA) (Lê et al., 2008) was used to explore the variability between the different samples.

Gene set enrichment analysis (GSEA)
We used the clusterProfiler R package (Yu et al., 2012) to conduct GSEA analysis on various gene sets. Gene sets were retrieved from http://ge-lab.org/gskb/ for M. musculus. We ordered the differentially expressed gene list by log2 (Fold-changes) for the analysis with default parameters.

Over-representation enrichment analysis
All significantly changing genes (adjusted p-value <0.05 and an absolute fold change >1) were split into 2 groups based on the direction of the fold change (genes significantly up-& down-regulated). An over-representation analysis using the clusterProfiler R package was performed on each of the two groups to identify biologically overrepresented terms.

Figure generation with R
The R packages ggplot2 (Wickham, 2016) retrieved from https://ggplot2.tidyverse.org and ggpubr were used to generate figures.
For the FA treatment of BEC-organoids, palmitic acid (Sigma, P0500) and oleic acid (Sigma, O1008) were dissolved in 100% ethanol into 500 and 800 μM stock solutions, respectively, and kept at -20 °C. For each experiment, palmitic acid and oleic acid were conjugated to 1% fatty acid-free bovine serum albumin (BSA) (Sigma, A7030) in EM through 1:2000 dilution each (Malhi et al., 2006). The concentration of vehicle, ethanol, was 0.1% ethanol in final incubations, and 1% fatty acid-free BSA in EM was used as the control for FA treatment.
For IF of liver cryosections, the livers were frozen in O.C.T. compound (VWR chemicals) on dry ice filled with isopentane. 10 μm liver sections were cut from O.C.T embedded samples, hydrated, and washed twice in PBS. The sections were blocked in a blocking buffer for 1 hr at room temperature and incubated with BODIPY for 20 min. After fixation with 4% paraformaldehyde (PFA) solution (Sigma, 1004960700) for 15 min, sections were washed with PBS. Then, sections were permeabilized using 5% BSA in TBS-T and stained with primary antibody anti-PANCK diluted in blocking buffer for 16 hr at 4 °C. The next day, the sections were washed three times with PBS, and the appropriate Alexa Fluor secondary antibodies were diluted in blocking buffer (1:1000) and incubated with the sections for 1 hr at room temperature. The sections were washed in PBS and incubated with DAPI diluted 1:1000 in PBS for 1 hr at room temperature. Finally, the sections were mounted in ProLong Gold Antifade Mountant.
Stained sections were imaged by a virtual slide microscope (VS120, Olympus) and a confocal microscope (SP8, Leica). The image analysis was performed using QuPath (Bankhead et al., 2017) and Fiji software.
BEC-organoid whole-mount immunofluorescence BEC-organoids were incubated with BODIPY 558/568 for 20 min and then washed with PBS and extracted from Matrigel using Cell Recovery Solution (Corning,354253). After fixing with 4% PFA in PBS (30 min, on ice), they were pelleted by gravity to remove the PFA and were washed with PBS and ultra-pure water. BEC-organoids were then spread on glass slides and allowed to attach by drying. The attached BEC-organoids were rehydrated with PBS and permeabilized with 0.5% Triton X-100 in PBS (1 hr, room temperature) and blocked for 1 hr in a blocking buffer. After washing with PBS, samples were incubated for 1 hr at room temperature with Alexa Fluor Phalloidin 488 (Invitrogen, A12379). Following extensive washing, samples were counterstained with DAPI and were imaged by a confocal microscope (LSM 710,Zeiss). Signal intensity was adjusted on each channel using Fiji software (Schindelin et al., 2012).
Quantitative real-time qPCR for mRNA quantification BEC-organoids were extracted from Matrigel using Cell Recovery Solution (Corning, 354253). RNA was extracted from organoid pellets using the RNAqueous total RNA isolation kit (Invitrogen, AM1931) and the RNeasy Micro Kit (Qiagen, 74004) following the manufacturer's instructions. RNA was transcribed to complementary DNA using QuantiTect Reverse Transcription Kit (Qiagen, 205314) following the manufacturer's instructions. PCR reactions were run on the LightCycler 480 System (Roche) using SYBR Green (Roche, 4887352001) chemistry. Real-time quantitative polymerase chain reaction (RT-qPCR) results were presented relative to the mean of 36b4 (comparative ΔCt method). Primers for RT-qPCR are listed in Supplementary file 3.

E2F inhibition
For the E2F inhibition experiment, single BECs were grown for 7 days and allowed to form organoids. For the Seahorse experiment, BEC-organoids were treated with E2F inhibitor, HLM006474 (10 μM, Merck, 324461), overnight before the metabolic assay. For RT-qPCR analysis, BEC-organoids were treated with HLM006474 chronically for 4 days.

Bioenergetics with Seahorse extracellular flux analyzer
The oxygen consumption rate (OCR), extracellular acidification rate (ECAR), and proton-efflux rate (PER) of the BEC-organoids were analyzed by an XFe96 extracellular flux analyzer (Agilent) following the manufacturer's instructions according to assay type.
For Glycolytic Rate Assay, CD BEC-organoids were grown without FA mix, and CD/HFD-derived BEC-organoids were grown with FA mix for 7 days. The Seahorse assay preparations, including the E2F inhibitor were the same as mentioned above. GlycoPER was measured in a time course before and after the injection of 1 μM Rotenone/Antimycin A and 50 mM 2-DG (Sigma, D8375).
For the Substrate Oxidation Assay, CD BEC-organoids were grown without FA mix for 7 days. On day 8, they were dissociated and prepared for Seahorse assay without E2F inhibitor. Mitochondrial OCR was measured in a time course before and after the injection of Oligomycin (1.5 μM), FCCP (2.5 μM), and Rotenone/Antimycin A (1 μM) with or without UK5099 (Sigma, PZ0160), Etomoxir (Sigma, E1905) and BPTES (Sigma, SML0601), inhibitors of glucose oxidation, fatty acid oxidation and glutamine oxidation, respectively, in separate experiments.
All Seahorse experiments were normalized by cell number through injection of 10 μM of Hoechst (ThermoFisher, 62249) in the last Seahorse injection. Hoechst signal (361/486 nm) was quantified by SpectraMax iD3 microplate reader (Molecular Devices).

BEC-organoid growth assay
BEC-organoid formation efficiency was quantified by counting the total number of cystic/single layer (lumen-containing) CD/HFD-derived BEC-organoids 6 days after seeding and normalizing it to the total number of cells seeded initially (15,000 cells). Organoids were imaged by DM IL LED inverted microscope (Leica), selected as regions of interest (ROI) using widefield 4 x magnification, and counted manually.

BEC-organoid functional analysis
Grown BEC-organoids were treated with the FA mix for 4 days, and triglyceride levels were measured with a Triglyceride kit (Abcam, ab65336) following the manufacturer's instructions. Cell-titer Glo (Promega, G7570) was used to investigate cell viability. For functional assays involving single BECs, grown organoids were dissociated into single cells. 10,000 BECs were seeded, and organoid formation was allowed for 7 days. Cell viability, apoptosis, and cell death were investigated using Cell-titer Glo, Caspase 3/7 activity (Promega, G8091), and Nucgreen Dead 488 staining (Invitrogen, R37109), respectively, according to the protocol of manufacturers. For cell death staining, organoids were imaged using ECLIPSE Ts2 inverted microscope (Nikon).

Quantification and statistical analysis
Data were presented as mean ± standard error of the mean (mean ± SEM). n refers to biological replicates and is represented by the number of dots in the plot or stated in the figure legends. For the Seahorse experiments, n refers to technical replicates pooled from 4 biological replicates and is represented by the number of dots in the plot or stated in the figure legends. The statistical analysis of the data from bench experiments was performed using Prism (Prism 9, GraphPad). The differences with p<0.05 were considered statistically significant. No samples (except outliers) or animals were excluded from the analysis. Data are expected to have a normal distribution.
For two groups comparison, data significance was analyzed using a two-tailed, unpaired Student's t-test. In case of comparisons between more than two groups, one-or two-way ANOVA was used. Dunnet's, Tukey's, or Sidak's tests were used to correct for multiple comparisons. Statistical details of each experiment can be found in the respective figure legends.

• MDAR checklist
Data availability Computational analysis was performed using established packages mentioned in the Materials and methods, and no new code was generated. RNA-Seq data have been deposited in GEO under accession code GSE217739. Two publicly available RNA-Seq datasets of mouse BECs with accession numbers GSE123133 (Aloia et al., 2019) and GSE125688 (Pepe-Mooney et al., 2019) were downloaded from the GEO and used for GSEA and over-representation enrichment analysis as mentioned previously. Source code is available at https://github.com/auwerxlab/Yildiz_eLife_2023 (copy archived at Alam, 2023).
The following dataset was generated: