1. Cell Biology

The negative adipogenesis regulator Dlk1 is transcriptionally regulated by Ifrd1 (TIS7) and translationally by its orthologue Ifrd2 (SKMc15)

  1. Ilja Vietor  Is a corresponding author
  2. Domagoj Cikes
  3. Kati Piironen
  4. Theodora Vasakou
  5. David Heimdörfer
  6. Ronald Gstir
  7. Matthias David Erlacher
  8. Ivan Tancevski
  9. Philipp Eller
  10. Egon Demetz
  11. Michael W Hess
  12. Volker Kuhn
  13. Gerald Degenhart
  14. Jan Rozman
  15. Martin Klingenspor
  16. Martin Hrabe de Angelis
  17. Taras Valovka
  18. Lukas A Huber
  1. Institute of Cell Biology, Biocenter, Innsbruck Medical University, Austria
  2. IMBA, Institute of MolecularBiotechnology of the Austrian Academy of Sciences, Austria
  3. Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, Finland
  4. Division of Genomics and RNomics, Biocenter, Innsbruck Medical University, Austria
  5. ADSI – Austrian Drug Screening Institute GmbH, Austria
  6. Department of Internal Medicine II, Innsbruck Medical University, Austria
  7. Division of Histology and Embryology, Innsbruck Medical University, Austria
  8. Department Trauma Surgery, Innsbruck Medical University, Austria
  9. Department of Radiology, Medical University Innsbruck, Austria
  10. German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Germany
  11. German Center for Diabetes Research (DZD), Germany
  12. Chair of Molecular Nutritional Medicine, Technical University of Munich, School of Life Sciences, Germany
  13. EKFZ - Else Kröner Fresenius Center for Nutritional Medicine, Technical University of Munich, Germany
  14. ZIEL - Institute for Food & Health, Technical University of Munich, Germany
  15. Chair of Experimental Genetics, Technical University of Munich, School of Life Sciences, Germany
https://doi.org/10.7554/eLife.88350
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Cite this article
  1. Ilja Vietor
  2. Domagoj Cikes
  3. Kati Piironen
  4. Theodora Vasakou
  5. David Heimdörfer
  6. Ronald Gstir
  7. Matthias David Erlacher
  8. Ivan Tancevski
  9. Philipp Eller
  10. Egon Demetz
  11. Michael W Hess
  12. Volker Kuhn
  13. Gerald Degenhart
  14. Jan Rozman
  15. Martin Klingenspor
  16. Martin Hrabe de Angelis
  17. Taras Valovka
  18. Lukas A Huber
(2023)
The negative adipogenesis regulator Dlk1 is transcriptionally regulated by Ifrd1 (TIS7) and translationally by its orthologue Ifrd2 (SKMc15)
eLife 12:e88350.
https://doi.org/10.7554/eLife.88350
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Abstract

Delta-like homolog 1 (Dlk1), an inhibitor of adipogenesis, controls the cell fate of adipocyte progenitors. Experimental data presented here identify two independent regulatory mechanisms, transcriptional and translational, by which Ifrd1 (TIS7) and its orthologue Ifrd2 (SKMc15) regulate Dlk1 levels. Mice deficient in both Ifrd1 and Ifrd2 (dKO) had severely reduced adipose tissue and were resistant to high-fat diet-induced obesity. Wnt signaling, a negative regulator of adipocyte differentiation, was significantly upregulated in dKO mice. Elevated levels of the Wnt/β-catenin target protein Dlk1 inhibited the expression of adipogenesis regulators Pparg and Cebpa, and fatty acid transporter Cd36. Although both Ifrd1 and Ifrd2 contributed to this phenotype, they utilized two different mechanisms. Ifrd1 acted by controlling Wnt signaling and thereby transcriptional regulation of Dlk1. On the other hand, distinctive experimental evidence showed that Ifrd2 acts as a general translational inhibitor significantly affecting Dlk1 protein levels. Novel mechanisms of Dlk1 regulation in adipocyte differentiation involving Ifrd1 and Ifrd2 are based on experimental data presented here.

Editor's evaluation

This study provides important new insights into the molecular regulation of adipocyte differentiation. Two molecules, TIS7 and SKMc15, are shown to regulate the activity of the key transcriptional regulator DLK-1 via discrete mechanisms – one involving transcription and the other translation. These findings add valuable information to the well known roles of Wnt/catenin and PPARg on adipocyte differentiation and will provide an advance for those interested in the role of adipocytes in whole body metabolism.

https://doi.org/10.7554/eLife.88350.sa0

Introduction

Adipogenesis is a complex process in which multipotent stem cells are converted into preadipocytes before terminal differentiation into adipocytes (Sarantopoulos et al., 2018). These mechanisms involve protein factor regulators, epigenetic factors, and miRNAs. TPA-induced sequence 7 (TIS7) protein has been shown to be involved in the mainly transcriptional regulation of differentiation processes in various cell types, for example, neurons (Iacopetti et al., 1996), enterocytes (Wang et al., 2005), myocytes (Vadivelu et al., 2004), and also adipocytes (Nakamura et al., 2013).

Multiple lines of evidence link the regulation of Wnt/β-catenin signaling to the physiological function of Tis7, known in human as interferon-related developmental regulator 1 (Ifrd1) (Iezaki et al., 2016; Vietor et al., 2005). Experiments with Ifrd1 knockout mice generated in our laboratory show a negative effect of Ifrd1 on Wnt signaling and a positive effect on adipocyte differentiation (Vietor et al., 2005; Yu et al., 2010, #3955). Ifrd1 deficiency leads to a significant upregulation of Wnt/β-catenin transcriptional activity in both primary osteoblasts and in mouse embryonic fibroblasts (MEFs) derived from Ifrd1 knockout (KO) mice. It was shown that Ifrd1 is also involved in the control of adipocytes differentiation in mice and was upregulated in both visceral white adipose tissue (vWAT) and subcutaneous white adipose tissue (sWAT) of genetically obese ob/ob mice (Nakamura et al., 2013). Ifrd1 transgenic mice have increased total body adiposity and decreased lean mass compared with wild type (WT) littermates (Wang et al., 2005). On high-fat diet (HFD), Ifrd1 transgenic mice exhibit a more rapid and proportionately greater gain in body weight with persistently elevated total body adiposity. Enhanced triglyceride (TG) absorption in the gut of Ifrd1 transgenic mice (Wang et al., 2005) indicated that Ifrd1 expressed in the gut epithelium has direct effects on fat absorption in enterocytes. As a result of impaired intestinal lipid absorption, Ifrd1 KO mice displayed lower body adiposity (Yu et al., 2010). Compared with WT littermates, Ifrd1 KO mice do not gain weight when chronically fed an HFD and Ifrd1 deletion results in delayed lipid absorption and altered intestinal and hepatic lipid trafficking, with reduced intestinal TG, cholesterol, and free fatty acid mucosal levels in the jejunum (Garcia et al., 2014). Ifrd1 protein functions as a transcriptional co-regulator (Micheli et al., 2005) due to its interaction with protein complexes containing either histone deacetylases (HDAC) (Park et al., 2017; Vadivelu et al., 2004; Vietor et al., 2002; Wick et al., 2004) or protein methyl transferases, in particular PRMT5 (Lammirato et al., 2016). The analysis of adipocyte differentiation in preadipocytic 3T3-L1 cells suggested an involvement of Ifrd1 in the regulation of adipogenesis in the Wnt/β-catenin signaling context (Nakamura et al., 2013).

SKMc15, also known as interferon-related developmental regulator 2 (Ifrd2), a second member of the Ifrd gene family, is highly conserved in different species (Latif et al., 1997). Mouse Ifrd1 and Ifrd2 are homologous, with a remarkable identity at both the cDNA and amino acid levels (58 and 88%, respectively). However, there was so far no information about the physiological function and mechanisms of action of Ifrd2 protein and its possible involvement in differentiation of various tissues. Recently, cryo-electron microscopy (cryo-EM) analyses of inactive ribosomes identified Ifrd2 as a novel ribosome-binding protein inhibiting translation to regulate gene expression (Brown et al., 2018). The physiological function of Ifrd2 matching the mechanism based on the abovementioned cryo-EM data was so far not shown. Ifrd2 could be involved in adipogenesis since a significant reduction of whole protein synthesis was previously shown as a major regulatory event during early adipogenic differentiation (Marcon et al., 2017).

Adipogenesis occurs late in embryonic development and in postnatal periods. Adipogenic transcription factors CCAAT/enhancer binding protein α (Cebpa) and peroxisome proliferator-activated receptor γ (Pparg) play critical roles in adipogenesis and in the induction of adipocyte markers (Farmer, 2006). Pparg is the major downstream target of Delta-like protein 1 (Dlk1). It is inactivated by the induction of the MEK/ERK pathway, leading to its phosphorylation and proteolytic degradation (Wang and Sul, 2009). Dlk1, also known as Pref-1 (preadipocyte factor 1), activates the MEK/ERK pathway to inhibit adipocyte differentiation (Kim et al., 2007). Cebpa is highly expressed in mature adipocytes and can bind DNA together with Pparg to a variety of respective target genes (Lefterova et al., 2008). Besides, Pparg binding to Cebpa gene induces its transcription, thereby creating a positive feedback loop (Lowell, 1999). Both proteins have synergistic effects on the differentiation of adipocytes that requires a balanced expression of both Cebpa and Pparg.

Wnt/β-catenin signaling is one of the extracellular signaling pathways specifically affecting adipogenesis (Li et al., 2008; Ross et al., 2000; van Tienen et al., 2009) by maintaining preadipocytes in an undifferentiated state through inhibition of Cebpa and Pparg (Tontonoz and Spiegelman, 2008). Pparg and Wnt/β-catenin pathways are regarded as master mediators of adipogenesis (Xu et al., 2016). Wnt signaling is a progenitor fate determinator and negatively regulates preadipocyte proliferation through Dlk1 (Mortensen et al., 2012). Mice overexpressing Dlk1 are resistant to HFD-induced obesity, whereas Dlk1 KO mice have accelerated adiposity (Moon et al., 2002). Dlk1 transgenic mice show reduced expression of genes controlling lipid import (Cd36) and synthesis (Srebp1c, Pparg) (Barclay et al., 2011). Dlk1 expression coincides with altered recruitment of PRMT5 and β-catenin to the Dlk1 promoter (Paul et al., 2015). PRMT5 acts as a co-activator of adipogenic gene expression and differentiation (LeBlanc et al., 2012). SRY (sex determining region Y)-box 9 (Sox9), a transcription factor expressed in preadipocytes, is downregulated preceding adipocyte differentiation. Dlk1 prevents downregulation of Sox9 by activating ERK, resulting in inhibition of adipogenesis (Sul, 2009). The PRMT5- and histone-associated protein Coprs affects PRMT5 functions related to cell differentiation (Paul et al., 2012). Adipogenic conversion is delayed in MEFs derived from Coprs KO mice and WAT of Coprs KO mice is reduced when compared to control mice. Dlk1 expression is upregulated in Coprs KO cells (Paul et al., 2015).

Experimental data presented here show involvement of Ifrd1 and Ifrd2 in the process of adipocyte differentiation. dKO mice had strongly decreased amounts of the body fat when fed with even regular, chow diet and were resistant against the HFD-induced obesity. Two independent molecular mechanisms through which Ifrd1 and Ifrd2 fulfill this function were found. The fact that these two genes use independent mechanisms of action supported by the observation that whole-body deficiency of both genes led to a stronger phenotype when compared to single knockouts of Ifrd1 or Ifrd2. Ifrd1 regulates the Wnt signaling pathway activity and restricts Dlk1 protein levels, thereby allowing adipocyte differentiation. In contrast, Ifrd2 KO did not affect Wnt signaling, but as we show here, cells lacking Ifrd2 have significantly upregulated translational activity. In addition, strongly enriched Dlk1 mRNA concentrations were identified specifically in polyribosomes isolated from Ifrd2 knockout MEFs when compared to the WT MEFs. This was true also for dKO, but not for the single Ifrd1 knockout cells. The ablation of both Ifrd1 and Ifrd2 genes significantly affected the expression of genes essential for adipocyte differentiation and function. Since dKO mice render a substantially leaner phenotype on chow diet, even without any challenge by HFD induction, Ifrd1 and Ifrd2 represent novel players in the process of physiological adipocyte differentiation.

Results

Mice lacking Ifrd1 and Ifrd2 genes have lower body mass, less fat, and are resistant against HFD-induced obesity

In order to clarify whether both Ifrd1 and Ifrd2 are involved in the regulation of the adipocyte differentiation and whether they act through the same or different mechanisms, mice lacking both genes were generated by crossing Ifrd1 with Ifrd2 single KO mice. dKO pups were viable, and adult male and female mice were fertile. At birth, body weights of dKO and WT mice were similar. Nevertheless, already during weaning, both the male and female dKO mice failed to gain weight when compared to their WT littermates and this persisted in the following weeks when the mice were fed regular diet (RD; chow diet) containing 11% kcal of fat. At 10 wk of age, dKO mice displayed 30% and later up to 44.9% lower body weight compared with WT mice (Figure 1A). In all further presented experiments, we used only male mice.

Figure 1 with 2 supplements see all
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Double knockout (dKO) mice display postnatal growth retardation, less body fat, and are resistant against high-fat diet (HFD)-induced obesity.

(A) Growth curves of wild type (WT) and dKO mice on chow diet (n fluctuate depending on the time point of measurement). (B) Dual-energy X-ray absorptiometry (DEXA) measurements of WT and dKO mice. Left panel depicts the absolute values of fat and lean mass per animal, and the right panel represents values normalized to the total body weight of animals (n = 15). (C) Micro-computed tomography measurements identified a lack of abdominal fat in single and dKO mice. Three-dimensional reconstitution of images of the abdominal fat mass distribution in WT and KO mice. Yellow color represents subcutaneous and red visceral fat mass. Black compartments are shadows resulting as part of the lightning model for the 3D volume rendering. (D) Mass contribution (%) of the abdominal fat in correlation to the total body weight (g). A linear regression is overlaid for each group individually. The regression results for the WT group are y = 0.342x - 11.13 with an R2 of 0.74; for the Ifrd1 KO group y = 0.143x - 3.91 with an R2 of 0.82; for the Ifrd2 KO y = 0.005x + 0.48 with an R2 of 0.04 and; for the dKO y = 0.011x + 0.01 with an R2 of 0.1. ANCOVA for the fat mass as a percentage of the body weight as covariant was performed. (E) Effect of single Ifrd1 or Ifrd2 knockout and Ifrd1 Ifrd2 double knockout on total body weight in (g) and body fat amount normalized to the body weight in (%). (F) Ifrd1 and Ifrd2 knockout reduced the gain of body weight of mice fed with HFD. 7-week-old male WT and dKO mice were caged individually and maintained up to 21 d on HFD. Data shown are mean ± STD, n ≥ 9 per genotype. Data were analyzed applying one-way ANOVA with Holm–Šidák’s multiple-comparisons test. *p<0.05, **p<0.01, ****p<0.0001.

Figure 1—source data 1

DEXA and microCT measurements of IFRD1 and IFRD2 double knockout mice.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig1-data1-v3.xls

Based on dual-energy X-ray absorptiometry (DEXA) measurement, 6-month-old WT mice had substantially higher amounts of fat than their dKO littermates (Figure 1B, left panel). The effect of Ifrd1 and Ifrd2 dKO was even more pronounced when the total fat and lean mass values were normalized to the body weight since the dKO mice were smaller than their WT counterparts were. The percentage of fat was in the WT mice 37.7 ± 4% vs. 6 ± 3% of the total body mass in dKO animals. Furthermore, the percentage of lean tissue mass in WT animals was lower than those in dKO animals (60 ± 4.6% vs. 92 ± 3.14%; Figure 1B, right panel). The dKO mice were slightly, but statistically significantly, smaller since there was a difference in body length, including the tail between WT and dKO mice (Figure 1—figure supplement 1A). Next, we analyzed the contribution of Ifrd1 and Ifrd2 to the whole-body fat content of mice. Three-dimensional reconstruction of images based on micro-computed tomography (micro-CT) of sex-/age-matched adult mice disclosed that both Ifrd1 and Ifrd2 single KO mice already had less abdominal fat than WT controls and that the dKO of Ifrd1 and Ifrd2 genes caused the strongest decrease in abdominal fat content and size (Figure 1C). Quantitative analyses of micro-CT measurements showed that Ifrd1 deficiency caused a substantial lack of the abdominal fat tissues (p=0.002 when compared to WT mice, Figure 1D). Whereas Ifrd1 KO mice had less fat mass but were not significantly lighter than their WT littermates (Figure 1E), Ifrd2 KO were lighter (p=0.007) and leaner (p=0.0001) and dKO mice were both significantly lighter (p=0.0001) and had significantly less abdominal fat (p=0.006) than the WT mice (Figure 1D and E).

The indirect calorimetry trial with sex- and age-matched WT and dKO animals did not identify any significant difference in respiratory exchange ratios (RER = VCO2/VO2) of WT and dKO mice (Figure 1—figure supplement 1B). However, dKO mice showed significantly reduced body weight mainly because of lacking fat despite identical food intake, activity, and no major differences in several metabolic parameters. There were no statistically significant differences between WT and dKO mice even if the measured parameters were normalized to the smaller body mass (Table 1). To investigate potential links between Ifrd1, Ifrd2, and obesity, the response of dKO mice to HFD was studied. At 2 mo of age, male mice were housed individually and fed with HFD for 21 d. Food intake was measured every second day, and body weight was measured every fourth day. Feces were collected every second day to analyze the composition of excreted lipids, and blood samples were collected after the third week of HFD feeding to measure the concentrations of hepatic and lipoprotein lipases, respectively. Already within the first week of HFD feeding WT mice gained more weight than the dKO mice (Figure 1F), although there were no obvious differences in food consumption (Figure 1—figure supplement 2A) or in levels of lipolytic enzymes (Figure 1—figure supplement 2B and C). These differences in body weight gain continued to increase during the second and third weeks, at which time the body weight of WT mice increased additionally for 30% (30.0 ± 2.3%) when compared with the beginning of the HFD feeding period. In contrast, the weight of dKO animals increased only slightly (7.6 ± 1.6%) (Figure 1F). Both genes, Ifrd1 and Ifrd2, contributed to this phenotype, and we could see a stronger effect following their deletion (Figure 1F).

Table 1
Double knockout (dKO) mice do not differ from wild type mice in any metabolic parameter besides the body weight.

A 21-hr indirect calorimetry trial monitoring gas exchange (oxygen consumption and carbon dioxide production), activity (distance and rearing), and food intake. The genotype effects were statistically analyzed using one-way ANOVA. Food intake and energy expenditure were analyzed using a linear model including body mass as a co-variate.

ParameterANOVA (genotype)* LM (body mass as co-variate)
Wild typedKOGenotypeBody mass
n = 6n = 7
Mean ± STDEVMean ± STDEVp Valuep Value
Body mass (g)31.1 ± 2.620.4 ± 1.9<0.0001n/a
Body
temperature (°C)		36.56 ± 0.636.71 ± 0.50.6515n/a
* Food intake (g)4.0 ± 0.43.4 ± 0.50.58690.1277
* Mean VO2 (ml/hr)107.28 ± 8.4181.12 ± 5.690.64410.0241
* Min VO2 (ml/hr)78.83 ± 8.2657.71 ± 8.860.90470.1219
* Max VO2 (ml/hr)144.33 ± 6.98107.29 ± 7.590.19440.0082
Mean RER0.89 ± 0.010.90 ± 0.020.3754n/a
Mean dist D
(cm 20 min–1)		928 ± 173874 ± 2190.6399n/a
Mean Z
(rearing 20 min–1)		116 ± 3496 ± 250.2444n/a

  1. RER, respiratory exchange ratio.

Adipocyte differentiation in dKO mice is inhibited due to upregulated DLK1 levels

A possible explanation of the lean phenotype of dKO mice was that Ifrd1 and Ifrd2 regulate adipocyte differentiation. Primary MEFs derived from totipotent cells of early mouse mammalian embryos are capable of differentiating into adipocytes and are versatile models to study adipogenesis as well as mechanisms related to obesity such as genes, transcription factors, and signaling pathways implicated in the adipogenesis process (Ruiz-Ojeda et al., 2016). To test whether Ifrd1 and Ifrd2 are required for adipogenesis MEFs derived from WT, Ifrd2 and Ifrd1 single and dKO mice were treated according to an established adipocyte differentiation protocol (Wang et al., 2015). Expression levels of both Ifrd1 and Ifrd2 mRNA increased during the adipocyte differentiation of WT MEFs. Ifrd1 expression reached maximum levels representing 5.7-fold increase compared to proliferating WT MEFs on day 3 (Figure 1—figure supplement 2D) and Ifrd2 reached on day 5 the maximum of 2.5-fold expression levels of proliferating MEFs (Figure 1—figure supplement 2E). These data suggested that both proteins play a regulatory role in adipogenesis; however, they differ in their mechanisms and timing. Eight days after initiation of adipocyte differentiation, a remarkable reduction of adipocyte differentiation potential in Ifrd2, Ifrd1 KO MEFs, and dKO stromal vascular fraction (SVF) cells isolated from inguinal WAT was observed, as characterized by the formation of lipid droplets stained by oil red O (Figure 2A). Quantification of this staining revealed that fat vacuole formation in cells derived from Ifrd2, Ifrd1, and dKO mice represented 23, 48, and 12% of the WT cells, respectively (Figure 2B). Stable ectopic expression of Ifrd2 significantly increased adipocyte differentiation in both single and double Ifrd1 and Ifrd2 knockout MEF cell lines (Figure 1—figure supplement 1C and D and Figure 2—figure supplement 1). Ectopic expression of Ifrd1 significantly induced the adipocyte differentiation in Ifrd1 single knockout MEFs (Figure 1—figure supplement 1C). These data indicated that both Ifrd1 and Ifrd2 were critical for adipocyte differentiation and that the defect in adipogenesis could be responsible for the resistance of dKO mice to HFD-induced obesity.

Figure 2 with 1 supplement see all
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Adipocyte differentiation, Dlk1 levels, and Wnt signaling pathway are significantly affected in double knockout (dKO) mice.

(A) Representative oil red O staining of inguinal stromal vascular fraction (SVF) cells following 8 d of the adipocyte differentiation protocol. Scale bar is 20 µm. (B) Quantification of oil red O staining from three independent adipocyte differentiation experiments shown in panel (A). Ordinary one-way ANOVA ****p<0.0001. (C) Wnt signaling activity was measured in mouse embryonic fibroblasts (MEFs) transiently co-transfected with the Tcf reporter plasmid pTOPflash and β-galactosidase expression vectors. Transfection efficiency was normalized using the β-galactosidase values. The experiment was repeated three times. Data shown are mean ± STD. Ordinary one-way ANOVA Holm–Šídák’s multiple-comparisons test ****p<0.0001. (D) Left top panel: western blot analysis of β-catenin amounts in inguinal WAT samples. Representative western blot from three biological repetitions is shown. Right top panel: Dlk1 is significantly upregulated both in Ifrd1, Ifrd2 single KO and in dKO mice. Bottom panels: actin western blots were used for normalization of sample loading. (E) Dlk1 mRNA expression measured by qPCR in inguinal white adipose tissue (WAT) samples (top). Values were normalized on GAPDH, n = 3. Error bars indicate standard deviations. A representative western blot image detecting Dlk1 and GAPDH proteins (bottom). (F) Dlk1 mRNA expression detected in undifferentiated cells isolated from inguinal WAT SVF cells. Normalized on GAPDH. Error bars indicate standard deviations, ***p<0.001. (G) Dlk1 protein western blot analysis in undifferentiated cells isolated from inguinal WAT SVF cells. Mean of three biological repeats; inset is one representative western blot. ***p<0.001. (H) Dlk1 mRNA expression detected in 8 d adipocyte-differentiated cells isolated from inguinal WAT SVF cells. Normalized on GAPDH. Error bars indicate standard deviations, ***p<0.001.

Figure 2—source data 1

b-catenin and Dlk1 protein levels in inguinal WAT.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig2-data1-v3.zip
Figure 2—source data 2

Dlk1 mRNA levels in inguinal WAT.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig2-data2-v3.zip
Figure 2—source data 3

Dlk1 protein levels in inguinal WAT cells.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig2-data3-v3.zip

Wnt/β-catenin signaling is an important regulatory pathway for adipocyte differentiation (Prestwich and Macdougald, 2007). Ifrd1 deficiency causes upregulation of Wnt/β-catenin transcriptional activity. Therefore, Wnt signaling activity was assessed in MEFs by measuring transcriptional activity using TOPflash, TCF-binding luciferase reporter assays. As shown in Figure 2C, Wnt signaling activity, when compared to the WT MEFs, was not regulated in Ifrd2 KO, but highly significantly (p<0.0001) upregulated in Ifrd1 KO and also in dKO MEFs. Supporting these findings, western blot analyses also identified increased β-catenin protein levels in inguinal WAT of Ifrd1 KO and in dKO mice (p<0.0001), but not in Ifrd2 KO mice (Figure 2D, left top panel), suggesting the involvement of Ifrd1 but not Ifrd2 in the Wnt signaling pathway regulation.

Next, the expression levels of Dlk1, a negative regulator of adipogenesis and at the same time known target of Wnt signaling (Paul et al., 2015), were analyzed. Dlk1 protein was significantly upregulated in inguinal WAT isolated from Ifrd1 and Ifrd2 KO as well as from dKO mice (Figure 2D, right top panel). A significant (p<0.001) upregulation of Dlk1 mRNA and protein levels in dKO inguinal WAT samples revealed the qPCR and confirmed western blot analyses (Figure 2E). Upregulation of Dlk1 in dKO mice both on RNA and protein results was confirmed in undifferentiated SVF cells isolated from inguinal fat (Figure 2F and G). Dlk1 mRNA levels were even stronger upregulated following the 8-days differentiation protocol of SVF cells (Figure 2H). Moreover, whereas in WT MEFs the expression of Dlk1 was strongly upregulated only during the first day of adipocyte differentiation and then over the next days declined to basal levels, in dKO MEFs Dlk1 was upregulated (p<0.001) throughout the entire 8 d of differentiation (Figure 3A). This result complemented protein analyses of lysates from 8-day differentiated adipocytes (Figure 3—figure supplement 1, middle panel). A rescue experiment confirmed that Dlk1 expression was Ifrd1- and Ifrd2-dependent. Dlk1 mRNA levels were analyzed by RT-qPCR in dKO MEFs stably expressing Ifrd1 and/or Ifrd2. Ectopic expression of Ifrd1, Ifrd2 and mainly their combination significantly (p<0.001) downregulated Dlk1 mRNA and protein levels (Figure 3B). Accordingly, these experiments documented that Ifrd1 and/or Ifrd1 were involved in the regulation of Dlk1 expression, but the molecular mechanism remained unclear.

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Ifrd1 and Ifrd2 regulate Dlk1 and thereby affect adipocyte regulators expression.

(A) Dlk1 mRNA expression measured in mouse embryonic fibroblasts (MEFs) treated with the adipocyte differentiation cocktail for given times. Wild type (WT) MEF values were set as 1. *p<0.05, ***p<0.001. (B) Dlk1 mRNA levels (top) and protein levels (bottom) in double knockout (dKO) MEFs were downregulated following ectopic co-expression of Ifrd1 and Ifrd2. mRNA expression levels were analyzed by RT qPCR in stably transfected cells following 8-day adipocyte protocol differentiation. WT MEF values were set as 1, n = 3; error bars indicate standard deviations. ***p<0.001 (C) Pparg mRNA expression detected in undifferentiated cells isolated from inguinal white adipose tissue (WAT) stromal vascular fraction (SVF) cells. Normalized on GAPDH. Error bars indicate standard deviations, ***p<0.001. (D) Cebpa mRNA expression detected in undifferentiated cells isolated from inguinal WAT SVF cells. Normalized on GAPDH. Error bars indicate standard deviations, ***p<0.001. (E) Pparg mRNA expression detected in 8-day adipocyte-differentiated cells isolated from inguinal WAT SVF cells. Normalized on GAPDH. Error bars indicate standard deviations, ***p<0.001. (F) Cebpa mRNA expression detected in 8-day adipocyte-differentiated cells isolated from inguinal WAT SVF cells. Normalized on GAPDH. Error bars indicate standard deviations, ***p<0.001. (G) Recruitment of indicated proteins to regulatory regions of the Dlk1 promoter in WT and KO MEFs was analyzed by chromatin immunoprecipitation (ChIP) at day 8 of the adipocyte differentiation. Values are expressed as the percentage of immunoprecipitated chromatin relative to input and are the mean of triplicates. ChIP analysis identified increased specific β-catenin binding to its Dlk1 regulatory element in dKO samples. Pre-immune serum and IgG were used as background controls. n = 3, data shown are mean ± STD, Student’s t-test ***p<0.001. (H) Dlk1 mRNA expression detected in undifferentiated MEF cells. Normalized on GAPDH. Error bars indicate standard deviations, ***p<0.001. (I) Real-time qPCR detection of Dlk1 RNA in polyribosomes. Normalized on GAPDH. Error bars indicate standard deviations, ***p<0.001.

Figure 3—source data 1

Supplementary information for the Figure 3 - WB images.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig3-data1-v3.zip
Figure 3—source data 2

qPCR measurements for Figure 3G.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig3-data2-v3.zip
Figure 3—source data 3

Supplementary information for the Figure 3.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig3-data3-v3.zip

The adipocyte differentiation deficiency of dKO inguinal SVF cells suggested that Cebpa and Pparg might also be regulated through Ifrd1 and/or Ifrd2. It was previously shown that elevated levels of the cleaved ectodomain of Dlk1 have been correlated with reduced expression of Pparg (Lee et al., 2003). Therefore, the differences in Pparg expression between WT and dKO inguinal SVF cells were analyzed. While Pparg and Cebpa mRNA levels were strongly induced in undifferentiated WT, these were barely detectable in dKO SVF cells (Figure 3C and D). Similarly, significantly decreased Pparg and Cebpa mRNA levels in Ifrd1, Ifrd2, and dKO inguinal SVF cells following 8-day adipocyte differentiation protocol were identified (Figure 3E and F).

Earlier chromatin immunoprecipitation (ChIP) analysis revealed that Ifrd1 binds directly to DNA and via interaction with PRMT5 regulates gene expression (Lammirato et al., 2016). Therefore, ChIP experiments were performed to study binding of Ifrd1 and Ifrd2 proteins, transcription factor β-catenin, and symmetrically dimethylated histone H4 at arginine residue 3 (H4R3me2s) (Paul et al., 2015) to regulatory elements of the Dlk1 gene. dKO MEFs treated 8 d with the adipocyte differentiation cocktail were increased β-catenin binding to the β-catenin/TCF binding site 2 of the Dlk1 regulatory element found when compared to WT MEFs (Figure 3G). On the other hand, binding of H4R3me2s to the same Dlk1 regulatory element was significantly reduced (p<0.001). No direct binding of Irfd1 or Ifrd2 proteins to two different Dlk1 regulatory elements (Dlk1 region A and β-cat/TCFbs2), neither in WT nor in dKO MEFs, could be identified, suggesting rather an epigenetic regulation than via their direct binding to Dlk1 regulatory elements. These results suggested that proteins Ifrd1 and Ifrd2 are required to restrain the Dlk1 levels through the Wnt/β-catenin signaling pathway and yet another so far unknown mechanism.

After finding significantly increased Dlk1 protein levels in inguinal WAT of SKMc15 single knockout mice (Figure 2D), Dlk1 expression in MEFs generated from these mice was measured. These were significantly increased (>70-fold) when compared to WT MEFs (Figure 3H). In a search for a Ifrd2-specific regulatory mechanism of Dlk1 levels, primarily the translational regulation was studied. It was previously shown that general reduction of protein synthesis and downregulation of the expression and translational efficiency of ribosomal proteins are events crucial for the regulation of adipocyte differentiation (Marcon et al., 2017). Initially, specifically polyribosome-bound Dlk1 RNA in Ifrd2 knockout MEFs was measured. This analysis detected significantly (p<8.26104 E-07) higher Dlk1 mRNA levels in polyribosome RNA fraction of Ifrd2 KO when compared to WT MEFs (Figure 3I). Interestingly, Ifrd2 was recently identified as a novel specific factor capable of translationally inactivating ribosomes (Brown et al., 2018). Because Ifrd2 may play a crucial role in the adipogenesis regulation in the following experiment, the effect of Ifrd2 knockout on the general translational efficiency of WT, Ifrd1, Ifrd2 single and double KO MEFs was tested. Cells were incubated 30 min in the absence of methionine and cysteine, followed by 1 hr in the presence of 35S-methionine. As shown in Figure 4A, there was a significant increase in the general translational activity of MEFs lacking Ifrd2 alone or both Ifrd1 and Ifrd2, but not in TIS7 single knockout cells. These data suggested that Ifrd2 alone, but not Ifrd1, inhibits the general translational activity necessary for the induction of adipogenic differentiation, also via the translational regulation of Dlk1. This finding supported the result shown in Figure 2D where the Dlk1 protein levels were significantly induced in inguinal WAT samples isolated from Ifrd2 single knockout mice.

Figure 4 with 2 supplements see all
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Ifrd2 inhibits Dlk1 translation.

Double knockout (dKO)-secreted Dlk1 inhibits adipocyte differentiation through MEK/ERK signaling. (A) Translational analysis – in vivo metabolic staining of mouse embryonic fibroblasts (MEFs) with 35S-methionine. Equal numbers of cells were seeded and 24 hr later treated as explained in the ‘Methods’ section. Identical volumes of cell lysates were separated by SDS-PAGE, gel was dried and analyzed by a phosphorimager. Equal loading was documented by the Coomassie blue staining of the gel. (B) dKO MEFs secrete Dlk1 protein into the cell culture medium. Identical volumes of media from wild type (WT) and dKO MEF cells 8 d treated with the adipocyte differentiation cocktail were analyzed by western blot. Collagen I was present in both samples in similar amounts. Equal loading of samples was evaluated by amido black staining of the membrane. (C) dKO MEFs-conditioned medium inhibited adipocyte differentiation in WT MEFs. MEFs were treated 8 d with the adipocyte differentiation cocktail. WT MEFs treated with the dKO-conditioned medium (replaced three times every 2 d) showed reduced differentiation. Images representing three biological repeats were cropped, and space bars represent always 20 µm. (D) Quantification of oil red O staining from three independent adipocyte differentiation experiments. Data shown are mean ± STD, ordinary one-way ANOVA p=0.0016. Student’s t-test, **p<0.01, ***p<0.001. (E) Dlk1 mRNA levels in WT and dKO MEFs treated 8 d with the adipocyte differentiation cocktail or in WT MEFs treated with the dKO-conditioned medium, ***p<0.001. (F) Pparg mRNA expression levels in same cells as shown in panels (D) and (E), ***p<0.001. (G) Representative western blots of phospho-p44, phospho-p42, p44, and p42 in gonadal white adipose tissue (WAT) of WT and dKO mice. Normalization on p44 and p42; n = 3. Error bars indicate standard deviations. WT values were set as 1, ***p<0.001. (H) Pparg and Cebpa mRNA expression in gonadal WAT. Normalization on GAPDH; n = 3. Error bars indicate standard deviations. WT values were set as 1, **p<0.01. (I) Dlk1 protein is upregulated in brown adipose tissues (BAT) of Ifrd1, Ifrd2 single knockout and in dKO mice. Western blot analysis was performed on five samples of each genotype. Normalization on GAPDH. Error bars indicate standard deviations, ***p<0.001.

Figure 4—source data 1

Original images of the Figure 4A.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig4-data1-v3.zip
Figure 4—source data 2

Original images of the Figure 4B.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig4-data2-v3.zip
Figure 4—source data 3

Original images of the Figure 4G.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig4-data3-v3.zip
Figure 4—source data 4

Original images of the Figure 4I.

https://cdn.elifesciences.org/articles/88350/elife-88350-fig4-data4-v3.zip

TIS7 and SKMc15 regulate adipocyte differentiation through Dlk1, MEK/ERK pathway, Pparg, and Cebpa

Dlk1 protein carries a protease cleavage site in its extracellular domain (Lee et al., 1995) and is secreted. The extracellular domain of Dlk1 is cleaved by ADAM17, TNF-α converting enzyme to generate the biologically active soluble Dlk1 (Wang and Sul, 2009). DLK1 mRNA and protein levels are high in preadipocytes, but Dlk1 expression is absent in mature adipocytes. Hence, adding soluble Dlk1 to the medium inhibits adipogenesis (Garcés et al., 1999). To test whether the dKO MEFs secreted Dlk1, cell culture media from MEFs treated 8 d with the adipocyte differentiation cocktail were collected and analyzed by western blotting. As shown in Figure 4B, dKO cells secreted Dlk1 protein, but in an identical volume of the cell culture medium from WT MEFs no Dlk1 could be detected. In contrast, an unrelated secreted protein, namely collagen I, was found in media of both WT and dKO MEFs in similar, in the medium of WT MEFs even slightly higher, amounts. To prove that secreted Dlk1 could inhibit adipocyte differentiation of dKO MEFs, WT MEFs were cultured with conditioned medium from dKO MEFs. Adipocyte differentiation of WT MEFs was strongly inhibited by the dKO MEFs-conditioned medium when compared to the control WT cells (Figure 4C, quantified in Figure 4D). Another indication that dKO inhibited adipocyte differentiation via Dlk1 protein upregulation delivered the experiment where Dlk1 was specifically knocked down. Targeted were either all Dlk1 mRNA splice variants (oligo shDLK1 391) or only Dlk1 mRNA splice variants containing coding sequences for the protease site for extracellular cleavage (oligo shDLK1 393) as previously published in Mortensen et al., 2012. Both Dlk1 knockdown constructs stably expressed in dKO MEFs significantly increased (p<0.001) adipocyte differentiation as documented in Figure 4—figure supplement 1A. It is known from the literature that Hes1 levels, together with Dlk1, are continuously downregulated during the process of adipogenesis while Pparg are rising (Huang et al., 2010). The knockdown of Dlk1 levels was paralleled by a significant (p<0.001) decrease in Hes1 mRNA levels (Figure 4—figure supplement 1B). In contrast, treatment with a recombinant Dlk1 protein or stable Dlk1 ectopic expression documented by qRT-PCR (Figure 4—figure supplement 2C) significantly (p<0.001) inhibited adipocyte differentiation of WT MEFs as shown in Figure 4—figure supplement 2A and B. This was accompanied by a significant (p<0.001) decrease in Cebpa mRNA levels (Figure 4—figure supplement 2D). Furthermore, Dlk1 mRNA quantification (Figure 4E) documented that dKO MEF cell lysates contained significant amounts of Dlk1 mRNA when compared to WT control or WT cells treated with dKO MEFs-conditioned medium. In parallel, WT cells treated with dKO MEFs-conditioned medium expressed significantly lower amounts of Pparg mRNA when compared to WT cells incubated with control medium (Figure 4F). In addition, ectopic expression of Ifrd2 and co-expression with Ifrd1 in dKO MEFs rescued almost up to WT levels the adipocyte differentiation potential of these cells (Figure 2—figure supplement 1). Ectopic expression of both Ifrd1 and Ifrd2 significantly (p<0.001) downregulated Dlk1 mRNA expression in dKO MEFs (Figure 2—figure supplement 1). Moreover, conditioned medium from dKO MEFs expressing Dlk1 shRNA knockdown constructs significantly (p<0.001) lost the ability to inhibit adipocyte differentiation of WT MEFs as the medium from dKO MEFs did (Figure 4—figure supplement 2E). These results revealed that cells derived from dKO mice express increased Dlk1 levels and secreted; soluble Dlk1 may inhibit adipocyte differentiation in vivo.

Previous studies showed that soluble Dlk1 protein activates MEK/ERK signaling, which is required for inhibition of adipogenesis (Kim et al., 2007). As DLK1 was strongly upregulated in dKO SVF cells during adipocyte differentiation, the possible activation of the MEK/ERK pathway in gonadal WAT samples of WT and dKO mice was analyzed subsequently (Figure 4G). The phosphorylation of p44 and p42 was upregulated 1.8-fold (p<0.001) in the dKO when compared to the WT G WAT samples (Figure 4G). Next, the question of expression levels of Pparg and Cebpa in WAT depots was addressed. Both adipocyte differentiation regulators Pparg and Cebpa’s mRNA expression levels were in gonadal WAT samples isolated from dKO mice significantly (p<0.01) downregulated when compared to the values of WT control animals (Figure 4H). Furthermore, the possible effect of Ifrd1, Ifrd2 and their combined knockout on the Dlk1 levels in brown adipose tissue (BAT) was analyzed. Western blot analysis identified a significant (p<0.001) increase in Dlk1 protein levels in BAT samples in knockout mice of all three genotypes (Figure 4I). The MEK/ERK pathway was similarly as in gonadal WAT, upregulated also in MEFs generated from dKO mice (Figure 5A). The phosphorylation of p42 and of p44 was upregulated 3-fold and 4.3-fold, respectively (p<0.01), in the adipocyte-differentiated dKO when compared to the WT MEFs (Figure 5B). Previously, activation of MEK/ERK by Dlk1 was shown to upregulate the expression of the transcription factor Sox9, resulting in the inhibition of adipogenesis (Sul, 2009). Therefore, we measured Sox9 mRNA expression by RT qPCR in 8-day adipocyte-differentiated MEFs. Sox9 expression was significantly (p<0.001) upregulated in 8-day adipocyte-differentiated dKO when compared to WT MEFs (Figure 5C). Pparg and Cebpa mRNA levels were both continuously upregulated during the 8-day differentiation protocol of WT MEFs (Figure 5D and E). On the contrary, no significant increase in Pparg and Cebpa mRNA levels was found in dKO MEFs (Figure 5D and E). A rescue experiment showed that only the co-expression of Ifrd1 and Ifrd2 strongly increased the expression of the Pparg in undifferentiated dKO MEFs (p<0.001), almost up to the levels of WT MEFs (Figure 5F). The expression of Cebpa was also strongly upregulated by the co-expression of Ifrd1 and Ifrd2 (p<0.001) (Figure 5G). The conclusion of these results was that Ifrd1 and Ifrd2 regulate the expression of both Pparg and Cebpa, crucial regulators of adipocyte differentiation.

Figure 5
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MAPK signaling and Sox9 expression are induced while adipocyte differentiation regulatory genes are downregulated in double knockout (dKO) mouse embryonic fibroblasts (MEFs).

(A) Representative western blots of phospho-p44, phospho-p42, p44, and p42 from 8-day adipocyte differentiation cocktail-treated MEFs. (B) Quantitative analysis of western blot data. Normalization on p44 and p42; n = 3. Error bars indicate standard deviations. Wild type (WT) values were set as 1; **p<0.01. (C) Sox9 expression was measured by qPCR in 8-day adipocyte-differentiated WT and dKO MEFs. Sox9 values were normalized on GADPH expression. WT MEF values were set as 1, n = 3. Data shown are mean ± STD. Student’s t-test ***p<0.001. (D) Pparg and (E) Cebpa mRNA levels were downregulated in dKO adipocyte-differentiated MEFs. Gene expression was measured by qPCR during the treatment with the adipocyte differentiation cocktail. Values were normalized on GADPH expression. WT MEF values were set as 1, n = 3. Data shown are mean ± STD, *** p<0.001. (F) Ectopic co-expression of Ifrd1 and Ifrd2 in undifferentiated MEFs significantly increased levels of adipogenic genes Pparg and (G) Cebpa. Data shown are mean ± STD, Student’s t-test ***p<0.001.

Lipid absorption is reduced in Ifrd1 and Ifrd2 dKO mice

dKO mice were (Figure 1—figure supplement 1B, Figure 1—figure supplement 2B) leaner than their WT littermates despite identical food intake and RER. Therefore, the possibility that dKO mice store energy ectopically was tested. In the feces of dKO mice fed with HFD were identified significantly higher (p<0.05) amounts of free fatty acids than in that of their WT siblings (Figure 6A). Secondly, the energy content of dried feces from dKO mice determined by bomb calorimetry was significantly higher (p<0.001) than that of WT mice (Figure 6B). Pparg induces the expression of Cd36, a very long chain fatty acids (VLCFA) transporter in heart, skeletal muscle, and adipose tissues (Coburn et al., 2000). The regulation of Cd36 by Pparg contributes to the control of blood lipids. Interestingly, Cd36 null mice exhibit elevated circulating LCFA and TG levels consistent with the phenotype of dKO mice and Cd36 deficiency partially protected from HFD-induced insulin resistance (Wilson et al., 2016). Because of downregulated Pparg levels in adipose tissues of dKO mice, the regulation of Cd36 was studied more in detail as well. In inguinal WAT from dKO mice were found strongly reduced Cd36 mRNA expression levels (64% of the WT values) (Figure 6C). Next, we analyzed Cd36 in WT and dKO MEFs before onset and during adipocyte differentiation. As long as Cd36 mRNA expression substantially increased in WT MEFs, there were almost undetectable transcript levels of Cd36 in dKO cells treated with the adipocyte differentiation cocktail (Figure 6D). Diacylglycerol acyltransferase 1 (Dgat1), a protein associated with the enterocytic TG absorption and intracellular lipid processing (Nozaki et al., 1999), is besides Cd36 another target gene of adipogenesis master regulator Pparg (Koliwad et al., 2010). Dgat1 mRNA levels are strongly upregulated during adipocyte differentiation (Cases et al., 1998), its promoter region contains a Pparg binding site (Ludwig et al., 2002), and Dgat1 is also negatively regulated by the MEK/ERK pathway (Tsai et al., 2007). Dgat1 expression was shown to be increased in Ifrd1 transgenic mice (Wang et al., 2005), and its expression was decreased in the gut of HFD-fed Ifrd1 KO mice (Yu et al., 2010). Importantly, Dgat1 expression in adipocytes and inguinal WAT is upregulated by Pparg activation (Koliwad et al., 2010). Therefore, to analyze the role of Ifrd1 and Ifrd2 on the regulation of this protein involved in adipogenesis and TG processing, Dgat1 mRNA levels were measured during the differentiation of WT and dKO MEFs into adipocytes. As long as Dgat1 expression substantially increased during the differentiation of WT MEFs, there was no difference in Dgat1 mRNA levels in dKO cells treated with the adipocyte differentiation cocktail (Figure 6E). Gene expression analyses showed that Ifrd1 and Ifrd2 regulated expression of multiple proteins involved both in adipocyte differentiation and in fat uptake, thereby contributing to the lean phenotype of dKO mice through multiple means.

Figure 6
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Free fatty acid (FFA) uptake is inhibited in double knockout (dKO) mice.

(A) FFA concentrations in feces of wild type (WT) and dKO mice. Feces were collected every second day, and the composition of excreted lipids was determined by capillary gas chromatography. Data shown are mean ± STD, *p<0.05. (B) Energy content of dried egested feces samples was determined by bomb calorimetry. Data shown are mean ± STD, **p<0.01. (C) qPCR analysis of Cd36 mRNA levels in inguinal white adipose tissue (WAT). Data shown are mean ± STD, *p<0.05. (D) qPCR analysis of Cd36 in mouse embryonic fibroblasts (MEFs) differentiating into adipocytes. Relative expression levels were normalized on GAPDH expression. WT MEF values were set as 1. Data shown are mean ± STD, ***p<0.001. (E) Dgat1 mRNA levels were downregulated in dKO adipocyte-differentiated MEFs. Data shown are mean ± STD, ***p<0.001. (F) Proposed model of Ifrd1 and Ifrd2 molecular mechanisms of action during adipocyte differentiation. Two parallel mechanisms leading to a deficiency in adipocyte differentiation: Ifrd1-regulated Wnt signaling affected Dlk1 transcription and Ifrd2 acting as a translational inhibitor also contributed to the regulation of adipogenesis.

Discussion

Experimental data presented here show that simultaneous depletion of Ifrd1 and of its orthologue Ifrd2, a protein recently identified as a translational inhibitor, caused severe reduction of adipose tissues and resistance against high fat-induced obesity in mice. Two parallel mechanisms were identified, leading to a deficiency in adipocyte differentiation. Firstly, Ifrd1-regulated Wnt signaling affected Dlk1 transcription, and secondly, experimental evidence proved that Ifrd2 acted as a translational inhibitor that controls Dlk1 protein levels, thereby contributing to the regulation of adipogenesis (Figure 6F).

dKO mice were phenotypically similar to both Cd36-deficient and Dlk1 transgenic mice, namely in decreased amounts of WAT and resistance to HFD-induced obesity. Previous studies showed that overexpression of Ifrd1 caused increased intestinal lipid transport, resulting in elevated body weight gain during HFD feeding (Wang et al., 2015). Knockout of Ifrd1 and Ifrd2 impaired absorption of free fatty acids from the lumen into enterocytes and reduced rate of fat absorption from intestines into the circulation. Simultaneously, higher concentrations of free fatty acids in the feces of dKO mice (Figure 6A) suggested that mice lacking Ifrd1 and Ifrd2 suffer from an intestinal lipid uptake deficiency, yet another contributing reason for the lean phenotype of these mice. In dKO mice, Pparg and Cebpa levels were inhibited, induced MEK/ERK pathway, and decreased expression of Cd36 and Dgat1, all hallmarks of upregulated Dlk1, a known adipogenesis inhibitor. Ifrd1 and Ifrd2 acted after the commitment to the preadipocyte stage since the elevated Dlk1 and β-catenin levels found in WAT of dKO mice were characteristic of the preadipocyte stage (Gautam et al., 2017).

Disruption of Wnt signaling in embryonic fibroblasts results in spontaneous adipocyte differentiation (Bennett et al., 2003), and in contrast, stabilized β-catenin keeps cells in the preadipocyte stage (Ross et al., 2000). A subpopulation of the SVF of adipose tissue is adipogenic and at the same time has a weaker Wnt/β-catenin signal (Hu et al., 2015). Consistent with this knowledge, upregulated β-catenin protein levels and increased Wnt signaling activity in WAT of Ifrd1 single and dKO MEFs were found. It has to be mentioned that the data presented here differ from those published by Nakamura et al., who showed that following the Ifrd1 overexpression in adipocytes Wnt/β-catenin signaling was upregulated and inhibited oil red O staining (Nakamura et al., 2013). However, one has to take into consideration the difference in cell systems used in these two studies. In contrast to Nakamura’s study where results were obtained in 3T3-L1 cells fibroblasts overexpressing Ifrd1, the data presented here document the role of endogenous Ifrd1 in cells derived from WT or knockout mice. Moreover, Ifrd1 was found to be ubiquitously expressed in all WT mouse organs without any pretreatment such as hypoxia. On the other hand, Nakamura et al. identified upregulated Ifrd1 expression levels in WAT of obesity model mice. This result, however, fully supports the findings of lean phenotype in Ifrd1 and Ifrd2 dKO mice.

In dKO MEFs, induced for adipocyte differentiation, the increase in Wnt signaling led to upregulated binding of β-catenin to the Dlk1 gene regulatory elements, resulting in sustained Dlk1 expression. In adipogenesis, Dlk1 expression is downregulated through histone methylation by Coprs and PRMT5 proteins that prevent β-catenin binding to the Dlk1 gene (Paul et al., 2015). Interestingly, in dKO MEFs weaker binding of dimethylated H4R3 to the Dlk1 gene was found, consistent with the previous findings on the negative role of Ifrd1 in epigenetic regulation of gene expression including the PRMT5 activity (Lammirato et al., 2016).

The difference in the effects of ectopic expression of Ifrd1, Ifrd2 and their co-expression on Dlk1 levels (Figure 3B) confirmed the hypothesis that proteins Ifrd1 and Ifrd2 regulate Dlk1 levels via two independent pathways/mechanisms. Despite the fact that Ifrd2 knockout had no effect on Wnt signaling, it nevertheless affected Dlk1 levels, suggesting a contribution of Ifrd2. Since protein Ifrd2 was identified as a novel factor translationally inactivating ribosomes (Brown et al., 2018), downregulation of the protein synthesis machinery is an essential regulatory event during early adipogenic differentiation (Marcon et al., 2017). Therefore, there was a possibility that Ifrd2 regulates Dlk1 protein levels through translational regulation. The experimental data presented here confirmed specific regulation of Dlk1 through this mechanism. Elevated Dlk1 levels in dKO MEFs activated the MEK/ERK pathway, thereby decreasing Pparg and Cebpa levels important for adipogenic differentiation. Besides, the expression of Sox9 and Hes1 was upregulated, suggesting that the dKO MEFs keep their proliferative state and cannot enter differentiation into mature adipocytes (Kim et al., 2007).

Downregulation of Pparg and Cebpa implied changes in the expression of downstream adipogenesis-related genes. Among them, decreased Cd36 and Dgat1 levels were a plausible explanation of the dKO mice lean phenotype since it is known that both proteins play a functional role in the differentiation of murine adipocytes and their deficiency impairs fat pad formation independent of lipid uptake (Christiaens et al., 2012). The results presented here implicate that Ifrd1 and Ifrd2 play a up to now unknown role in the regulation of Cd36 and therefore possibly contribute to Cd36-related pathogenesis of human metabolic diseases, such as hypoglycemia (Nagasaka et al., 2011), hypertriglyceridemia (Kashiwagi et al., 2001), and disordered fatty acid metabolism (Glazier et al., 2002; Tanaka et al., 2001).

It is possible that due to the reduced Cd36 expression levels in intestines, Ifrd1 Ifrd2 dKO mice accumulated lower amounts of body fat and were resistant to diet-induced obesity also because of limited intestinal fat uptake. Furthermore, Ifrd1 Ifrd2 dKO mice displayed increased plasma TG levels due to impaired clearance of VLCFA transport by skeletal muscles. Co-expression of Ifrd1 and Ifrd2 in dKO myoblasts partially rescued the Cd36 expression on the transcriptional level as documented by the increase of the Cd36 promoter activity. Rescuing the free fatty acids transport by Cd36 overexpression in dKO myoblasts confirmed the hypothesis that the deficit in fatty acid transport was due to the diminished Cd36 expression. Thus, Ifrd1 Ifrd2 dKO mice accumulated lower amounts of adipose tissue also because of impaired lipid transport.

It was previously shown that Ifrd1 is involved in both chow and HFD conditions in intestinal TG absorption. The experimental data shown here document for the first time the role of Ifrd1 and its orthologue Ifrd2 in adipocyte differentiation. Moreover, they confirm the physiological function of Ifrd2 as a translational inhibitor. Surprisingly, although Ifrd1 and Ifrd2 share sequence homology and a functional role in the adipogenesis, they use two independent regulatory mechanisms.

Methods

Generation of animal models

All animal experiments were performed in accordance with Austrian legislation BGB1 Nr. 501/1988 i.d.F. 162/2005.

Mice lacking Ifrd1 were described previously (Vadivelu et al., 2004). Ifrd2 KO mice generation: targeting construct contained Ifrd2 gene locus exons. A loxP site and a neomycin resistance gene were inserted at position 105515 (AY162905). The neomycin cassette was flanked by two frt sites. A second loxP site was inserted at position 102082 (AY162905). Further downstream, 15 additional nucleotides, part of intron 1, exon 2 (splice site: donor and acceptor), and the CDS of hrGFP from the Vitality hrGFP mammalian expression vector pIRES-hrGFP-2a (Stratagene) were added. The targeted construct was electroporated into Sv129 mouse ES cells. After the selection with G418, single-cell clones were screened by PCR and confirmed by Southern blot analysis. After Cre recombinase treatment, cell clones were screened by PCR. Clones with floxed gene deleted were used for blastocyst injection into C57BL/6J mice. Two male chimeras with ≥40% or more agouti coat color were mated to C57BL/6J females. The knockout mouse strain was derived from one male mouse carrying the allele of interest. Heterozygous mice were back-crossed to C57BL6/J mice for nine generations. dKO mice were generated by crossing the Ifrd2 KO mice with the Ifrd1 single KO mice. The resulting mice were screened by PCR and double heterozygous mice used for further breeding until homozygosity. In order to achieve maximal homogeneity of experimental groups, in all experiments presented here we used only male mice.

Ifrd2 knockout Southern blot analysis

XbaI restriction sites (position 109042; position 102079; position 92253) were located in the Ifrd2 locus (AY162905). Fragment detected by the Southern probe: 9.6 kb wt (Figure 1—figure supplement 2F, inset, band V); 15 kb in deleted locus (band IV). The 566-bp-long probe for hybridization was from genomic DNA (96605–97171; AY162905). PCR primer sequences: RK 150 Fwd: 5′-GGTCCTGCCACTAATGCACTG-3′; RK 151 Rev: 5′-GCAGACAGATGCCAGGAAGAC-3′.

Ifrd2 knockout PCR genotyping analysis

hrGFP insert in the 3′ UTR was detected by primer GFP2 5′-AGCCATACCACATTTGTAGAG-3′ and RK101 3′ UTR (5′-TGATGATAGCTTCAAAGAGAA-3′; 100617–100591 of the Ifrd2 locus (AY162905). PCR product 1700 bp. Ifrd2 detection: RG1; 5′-TGTGGCCTTTATCCTGAGTC-3′; 102286–102266) and RG2; 5′-TGGCTTCATTTACACTACTCCTT-3′; 101860–101882 primers (Figure 1—figure supplement 2F). WT allele PCR product 426 bp and the targeted allele PCR product 1772 bp (Figure 1—figure supplement 2G). Ifrd1 genotype was tested as explained previously (Vadivelu et al., 2004; Figure 1—figure supplement 2H).

Growth monitoring and body composition measurement

Mice were weaned at 3 wk, regular chow diet, and weighed weekly. DEXA was measured with Norland scanner (Fisher Biomedical). Micro-CT experiments were performed using vivaCT 40 (Scanco Medical AG). The scans were performed using 250 projections with 1024 samples, resulting in a 38 µm isotropic resolution. Tube settings: 45 kV voltage, 177 µA current, integration time 300 ms per projection. Image matrix 1024 * 1024 voxels and a grayscale depth of 16 bit. The length of the image stack was individually dependent, starting from the cranial end of the fist lumbar vertebrae to the caudal end of the fifth lumbar vertebrae. The image reconstruction and postprocessing were performed using the Scanco Medical system software V6.6. For the adipose tissue evaluation, an IPL (image processing language) script by Judex et al., provided by Scanco Medical AG, was modified to the scanner individual parameters, leading to two values lower threshold than in the original script for the adipose tissue filters 76. The script calculated the total abdominal volume without potential air in the cavities. A separation of subcutaneous and visceral fat mass was used only for visualization. For the quantitative fat mass analysis, we used 56 male 5–12-month-old mice (mean age 9.35 ± 2.03 mo) reflecting an adult to mid-aged cohort defined by Flurkey et al., 2007; Neeland et al., 2013 #4207. The development of adipose tissue in healthy mice is stable between 4 and 12 mo (Lemonnier, 1972). Therefore, sex and age could have only very limited influence on the experimental results. For the quantitative comparison, the percent contribution of the abdominal fat to the body weight was calculated using a mean weight of 0.9196 g/ml for adipose tissue (Neeland et al., 2013). Statistics were performed using an ANCOVA with a Bonferroni corrected post hoc testing on the µCT fat data and the body mass data.

Metabolic measurements

The indirect calorimetry trial monitoring gas exchange, activity, and food intake was conducted over 21 hr (PhenoMaster TSE Systems). Body mass and rectal body temperature before and after the trial were measured. The genotype effects were statistically analyzed using one-way ANOVA. Food intake and energy expenditure were also analyzed using a linear model including body mass as a co-variate.

HFD feeding

Age-matched (7-week-old) male Ifrd1-/- Ifrd2-/- and WT mice were caged individually and maintained up to 3 wk on a synthetic, HFD diet (TD.88137; Ssniff). Animals were weighted every fourth day between 08:00 and 10:00. Intestines, liver, muscles, and adipose tissue were collected for total RNA and protein isolation. Unfixed intestines were flushed with PBS using a syringe, embedded in Tissue-Tek (Sakura, 4583) and frozen in liquid nitrogen for immunohistochemical analysis.

Quantitative food consumption and fecal fat determination

Adult mice were acclimatized to individual caging and to the HFD for a week, and monitored for weight gain and their food intake daily. The daily food intake data were pooled for the following 7 d, and the food intake was estimated (g/day). Feces were collected daily and weighted for 7 d after the second week of the HFD consumption. Lipids were extracted and methylated according to Lepage et al., 1989. After freeze-drying and mechanical homogenization, aliquots of feces were subjected to the same procedure as described by Lepage et al., 1989. The resulting fatty acid methyl esters were analyzed by gas chromatography to measure the total and individual amounts of major fatty acids (Minich et al., 2000). The energy content of dried egested feces samples (~1 g per sample) was determined by bomb calorimetry (IKA C 7000, IKA, Staufen, Germany) (Pfluger et al., 2015).

Plasma cholesterol and triglyceride analyses

Serum cholesterol and TG were measured using cholesterol/TG reagent (Cobas, Roche) according to the manufacturer’s instructions. Lipoprotein profiles were analyzed by fractionation of pooled serum using two Superose 6-columns (Cytiva) in series (FPLC), followed by cholesterol measurement (Demetz et al., 2020).

Antibodies, viral and cDNA constructs

Antibodies: anti-Cd36 AbD Serotec (MCA2748), Abcam (ab36977), p44/42 MAPK (Erk1/2), and Phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) Cell Signaling Technology (9102, 9101), β-catenin antibody Sigma (C2206), anti-Dlk1 Abcam (ab119930), anti-histone H4R3me2s antibody Active Motif (61187), and anti-Ifrd1 (Sigma-Aldrich Cat# T2576, RRID:AB_477566). For ChIP experiments, anti-Ifrd1 (Vietor et al., 2002) and anti- Ifrd2 (Vadivelu et al., 2004) rabbit polyclonal antibodies previously proven for ChIP suitability in Lammirato et al., 2016 were used. pTOPflash reporter construct was a gift from H. Clevers (University of Utrecht, Holland). Ifrd1 construct was described previously (Vietor et al., 2002). Partial CDS of mIfrd2 was amplified by PCR and cloned into pcDNA3.1(-)/MycHis6 (Invitrogen).

Cell culture and adipocyte differentiation

MEFs were generated from 16-day-old embryos. After dissection of head for genotyping and removal of limbs, liver and visceral organs, embryos were minced and incubated in 1 mg/ml collagenase (Sigma-Aldrich, C2674) 30 min at 37°C. Embryonic fibroblasts were maintained in growth medium containing DMEM high glucose (4.5 g/l), sodium pyruvate, L-glutamine, 10% FCS (Invitrogen, 41966029), and 10% penicillin/streptomycin (Sigma-Aldrich, P0781) at 37°C in 5% CO2. Adipocyte differentiation treatment was medium with 0.5 mM 3-isobutyl-1-methylxanthine (Sigma-Aldrich, I5879), 1 µM dexamethasone (Sigma-Aldrich, D4902), 5 µg/ml insulin (Sigma-Aldrich, I2643), and 1 µM tosiglitazone (Sigma-Aldrich, R2408). After 3-day growth medium containing 1 µg/ml insulin, cells were differentiated for 8 d. To visualize lipid accumulation, adipocytes were washed with PBS, fixed with 6% formaldehyde overnight, incubated with 60% isopropanol, air-dried, and then incubated with oil red O. Microscopic analysis was followed by isopropanol elution and absorbance measurement at 490 nm. MEF’s genotype was controlled by PCR reactions. Stromal vascular cells were prepared exactly according to the previously published protocol (Aune et al., 2013). A possible mycoplasma contamination was routinely controlled by PCR. All cells used for experiments were mycoplasma negative.

Construction of expression plasmids and generation of stable cell lines

The pRRL CMV GFP Sin-18 plasmid (Zufferey et al., 1998) was used to generate Ifrd1, Ifrd2, and Dlk1 expression of lentiviral constructs. For this, the corresponding cDNAs were cloned into the BamHI and SalI sites of the pRRL CMV GFP Sin-18 plasmid. A cap-independent translation enhancer (CITE) fused to the puromycin resistance pac gene and the woodchuck hepatitis virus post-transcriptional regulatory element (WPRE) were introduced downstream of the Ifrd1, Ifrd2, and Dlk1 coding sequences. All DNA constructs were verified by sequencing.

To generate the Dlk1 shRNA lentiviral vectors, oligonucleotides targeting either all Dlk1 mRNA splice variants (Dlk1 total: 5′-GATCCCCAGATCGTAGCCGCAACCAATTCAAGAGATTGGTTGCGGCTACGATCTTTTTTGGAAA-3′) or only Dlk1 mRNA splice variants containing the extracellular cleavage sequence (Dlk1PS: 5′-GATCCCCTCCTGAAGGTGTCCATGAATTCAAGAGATTCATGGACACCTTCAGGATTTTTGGAAA-3′) (Mortensen et al., 2012) were fused with the H1 promoter and cloned into the pRDI292 vector as reported (Reintjes et al., 2016). The GFP-targeting pRDI-shRNA-GFP plasmid was used as a control (Reintjes et al., 2016).

The viral supernatants were obtained as described previously (Leitner et al., 2022), concentrated with Retro-X Concentrator (Clontech, Takara Bio), and used to infect WT, Ifrd1, and Ifrd2 single and dKO MEFs. The selection was carried out for 2 wk in DMEM supplemented with 10% (v/v) FBS, 100 U/ml penicillin and 100 μg/ml streptomycin, and 2 µg/ml puromycin (Sigma-Aldrich, P7255).

Polysome profiling

Polysome profiling was performed as described in Savant-Bhonsale and Cleveland, 1992, with modifications. The day before harvesting the cells, continuous 15–45% (w/v) sucrose gradients were prepared in SW41 tubes (Beckman) in polysome gradient buffer (10 mM HEPES-KOH, pH 7.6; 100 mM KCl; 5 mM MgCl2) employing the Gradient Master ip (Biocomp) and stored overnight at 4°C. All steps of the protein extraction were performed on ice. Exponentially growing cells were washed twice with ice-cold DPBS (Gibco) supplemented with 100 µg/ml f. c. cycloheximide, scraped in 300 µl polysome lysis buffer (10 mM HEPES-KOH, pH 7.6; 100 mM KCl; 5 mM MgCl2; 0.5% IGEPAL CA-630; 100 µg/ml cycloheximide) supplemented with 0.1 U/µl murine RNase Inhibitor (NEB), and passed through a G25 needle 25 times. Nuclei were pelleted at 16,000 × g for 6 min at 4°C, and the supernatants were carefully layered onto the sucrose gradients. Samples were centrifuged at 35,000 rpm for 2 hr at 4°C (with brakes switched off) using an SW 41 Ti rotor (Beckmann). Twenty fractions of 0.6 ml were collected using a peristaltic pump P1 (Amersham Biosciences), and polysome profiles were generated by optical density measurement at 254 nm using optical unit UV-1 (Amersham Biosciences) and chart recorder Rec 111 (Amersham Biosciences).

Analysis of translation by metabolic labeling

Pulse labeling of proteins was performed as described before (Popow et al., 2015), with the following changes: 1 × 106 wild-type and dKO MEFs cells per plate were seeded and cultivated for 24 hr. Cells were washed twice with PBS followed by one wash with labeling medium (ESC medium without cysteine and methionine) and a 30 min incubation in labeling medium. To label newly translated products, 200 µCi of [35S]-methionine (10 mCi/ml; Hartman Analytic) were added and the cells were incubated for 1 hr. Cells were washed and incubated another 10 min in standard medium at 37°C. Cells were then harvested by trypsinizing, washed once with ice-cold PBS, extracted with ice-cold RIPA buffer containing protease-inhibitors, and briefly sonicated. Proteins were fractionated by gel electrophoresis in 16% Tricine gels (Thermo Fisher, EC66955BOX) and stained with Coomassie brilliant blue, and radioactive signals were visualized by phosphorimaging. Signal intensities were quantified using the Image Studio Lite (v5.2) software.

RT-PCR

Tissues from animals fed for 3 wk with HFD were snap-frozen and stored at –80°C. Total RNA was isolated using the TRIzol reagent (Invitrogen, 15596026). RNA was then chloroform-extracted and precipitated with isopropanol. The yield and purity of RNA were determined by spectroscopic analysis; RNA was stored at –80°C until use.

Quantitative RT-PCR and statistics

Total RNA were treated with DNAse1 and reverse transcribed to cDNA by Revert Aid First Strand cDNA Synthesis Kit (Thermo Scientific, K1622) with oligo dT primers. Quantitative RT-PCR was performed using TaqMan probes and primer sets (Applied Biosystems) specific for CD36 (assay ID Mm00432398_m1), Dgat1 (Mm00515643_m1), Pparg (Mm00440940_m1), Cebpa (Mm00514283_s1), Dlk1 (Mm00494477_m1), and Sox9 (Mm00448840_m1). Ribosomal protein 20 (assay ID Mm02342828_g1) was used as normalization control for quantification by the ddCt method. PCR reactions were performed using 10 µl cDNA in PikoReal 96 real-time PCR system (Thermo Scientific). Quantification data were analyzed by two-tailed, homoscedastic t-tests based on the assumption that variances between the two sample data ranges are equal to type 2 Student’s t-test.

Transient transfections and luciferase assay

pGL2-Basic (Promega, E1641) or pGLCD36 (Shore et al., 2002) were used as reporter constructs. Expression constructs or empty vector DNA as a control were co-transfected. pCMV-β-Gal plasmid was used to normalize for transfection efficiency. For luciferase reporter assays, 1.5 × 105 cells were seeded into 24-well plates and transfected after 24 hr with the indicated plasmid combinations using Lipofectamine Plus Reagent (Invitrogen, 15338030). The total amount of transfected DNA (2 μg DNA per well) was equalized by addition of empty vector DNA. Cells were harvested 48 hr post-transfection in 0.25 M Tris, pH 7.5, 1% Triton X-100 buffer and assayed for both luciferase and β-galactosidase activities. Luciferase activity and β-galactosidase activity were assayed in parallel using the Lucy 2 detection system (Anthos). Transfections were performed in triplicates, and all experiments were repeated several times.

Chromatin immunoprecipitation (ChIP)

Chromatin was isolated from Ifrd1 WT and dKO formaldehyde-treated, 8-day adipocyte-differentiated MEFs using the EpiSeeker Chromatin Extraction Kit (Abcam, ab117152). ChIP analyses were carried out as described previously (Reintjes et al., 2016). The sequence of the oligonucleotides for two regions of the Dlk1 promoter, encompassing TCF and β-catenin binding sites, were as defined in Paul et al., 2015. Sonicated chromatin was centrifuged at 15.000 × g for 10 min at 4°C, and the supernatant (65 µg of sheared DNA per each IP) was diluted tenfold with cold ChIP dilution buffer containing 16.7 mM Tris-HCl pH 8.1, 167 mM NaCl, 0.01% (w/v) SDS, 1.1% (w/v) Triton X-100, and 1.2 mM EDTA with protease inhibitors. Samples were pre-cleared for 1 hr with protein A Sepharose CL-4B (Sigma-Aldrich, 17-0780-01) beads blocked with 0.2 µg/µl sonicated herring sperm DNA (Thermo Fisher, 15634017) and 0.5 µg/µl BSA (NEB, B9000S). Immunoprecipitations were performed at 4°C overnight. Immune complexes were collected with protein A Sepharose for 1 hr at 4°C followed by centrifugation at 1000 rpm and 4°C for 5 min. Beads were washed with 1 ml low salt wash buffer (20 mM Tris-HCl pH 8.1, 150 mM NaCl, 0.1% [w/v] SDS, 1% [w/v] Triton X-100 [Merck], 2 mM EDTA), high salt wash buffer (20 mM Tris-HCl pH 8.1, 500 mM NaCl, 0.1% [w/v] SDS, 1% [w/v] Triton X-100, 2 mM EDTA), LiCl wash buffer (10 mM Tris-HCl pH 8.1, 250 mM LiCl, 1% [w/v] sodium deoxycholate, 1% [w/v] IGEPAL-CA630, 1 mM EDTA) for 5 min at 4°C on a rotating wheel, and twice with 1 ml TE buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA). Protein-DNA complexes were eluted from antibodies by adding a freshly prepared elution buffer containing 1% SDS and 0.1 M NaHCO3. The eluate was reverse cross-linked by adding NaCl to a final concentration of 0.2 M and incubating at 65°C for 4 hr. Afterward the eluate was treated with proteinase K at 45°C for 1 hr. The immunoprecipitated DNA was then isolated by phenol/chloroform precipitation and used as a template for real-time quantitative PCR. The primer pairs specific for regulatory regions of the Dlk1 gene were selected as described before (Paul et al., 2015). Reactions with rabbit IgG or with 1.23% of total chromatin (input) were used as controls. For real-time quantitative PCR, a PikoReal System was used. Signals were normalized to input chromatin and shown as % input. The raw cycle threshold (Ct) values of the input were adjusted to 100% by calculating raw Ct – log2(100/input). To calculate the % input of the immunoprecipitations, the equation 100 × 2[Ct (adjusted input to 100%) – Ct (IP)] was applied.

Statistical analyses

Statistical analyses were performed with one-way ANOVA, Student’s unpaired t-test using GraphPad Prism version 9.2 (GraphPad, La Jolla, CA) software, or as indicated in the legends. p-Value is indicated by asterisks in the figurees: *p≤0.05, **p<0.01, ***p<0.001, ****p<0.0001. Data from SVF cells were analyzed using ordinary one-way ANOVA with Holm–Šidák’s multiple-comparisons test.

Data availability

All data generated or analyzed during this study are included in the manuscript, figures and associated source data files.

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Decision letter

  1. David E James
    Senior and Reviewing Editor; University of Sydney, Australia

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

[Editors' note: this paper was reviewed by Review Commons.]

Thank you for submitting your article "The negative adipogenesis regulator DLK1 is transcriptionally regulated by TIS7 (IFRD1) and translationally by its orthologue SKMc15 (IFRD2)" for consideration by eLife. Your article has been reviewed by 3 peer reviewers at Review Commons, and the evaluation at eLife has been overseen by a Reviewing Editor and David James as the Senior Editor.

Based on the previous reviews and the revisions, the manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:

This study provides new insights into the molecular regulation of adipocyte differentiation. Two molecules, TIS7 and SKMc15, are shown to regulate the activity of the key transcriptional regulator DLK-1 via discrete mechanisms – one involving transcription and the other translation. These findings add additional information to the well known roles of Wnt/catenin and PPARg on adipocyte differentiation.

The authors have extensively addressed the comments of the referees and all referees are convinced that the manuscript is now improved and the mechanistic details of the link between SKMc15 and regulation of adipogenesis is now strengthened. However, as described below there are still some important issues that need to be addressed by the authors prior to publication. Many of these require editorial changes but there are some minor experimental details that need to be addressed. Also essential is that you discuss more thoroughly the lipid absorption issue as a contributor to the dKO mouse phenotype.

Specific Issues

1) All energy balance measurements need to be included in the manuscript, not just shown to reviewers. Readers will want to see them.

2) It is not quite clear how food intake is expressed. Since the mice are significantly smaller, it might be more appropriate to express the data as g of food/g of mouse, as a smaller mouse is likely to eat less.

3) In complementation experiments, it would be useful to know the levels of overexpression.

4) What is the levels of blood lipids in the dKO mice, since this is the first report of their existence, and presumably the defect in intestinal lipid absorption may affect these?

5) The methods need to be carefully edited. For instance, lines 564-65 state "Small intestines were harvested for oil red O staining to detect lipid accumulation"; these data are not shown anywhere in the paper. Similarly, the section on fecal fat determination describes a protocol to analyze neutral sterols and bile acids (nowhere in the paper), but it does not describe how the free fatty acid levels were determined. One more example, line 651 alludes to "pulse labeling of mitochondrial proteins" which is not what is presented in the paper.

6) The main text should indicate at the outset that only male mice were analyzed.

7) It is incorrect to state that the dKO mice are not smaller when the graph showing that data (panel A in Figure EV1) shows a significant difference.

https://doi.org/10.7554/eLife.88350.sa1

Author response

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

This study by Viedor et al. examines the role of TIS7 (IFRD1) and its ortholog SKMc15 (IFRD2) in the regulation of adipogenesis via their ability to modulate the levels of DLK1 (Pref-1), a well-known inhibitor of adipogenesis. They generate SKMc15 KO mice and cross them to previously published TIS7 KO mice. All 3 mutant strains show decreased fat mass, with the effect being most pronounced in double KO mice (dKO). Using mouse embryonic fibroblasts (MEFs) from mutant mice, they authors ascribe a defect in adipogenic differentiation of mutant cells to an upregulation of DLK-1. In the case of TIS7, they propose that this is due to its known inhibition of Wnt signaling, which regulates DLK-1 expression. In the case of SKMc15, they suggest a new mechanism linked to its ability to suppress translation. Overall, the work is of interest, with the finding, that SKMc15 regulates adipocyte differentiation being its novelty, and generally well done, though multiple aspects need to be improved to bolster the conclusions put forth.

Major concerns:

1) The main mechanism put forth by the authors to explain the inability of dKO cells to differentiate into adipocytes is the upregulation of DLK-1 levels. However, this notion is never directly tested. Authors should test if knockdown of DLK-1 in dKO cells is sufficient to correct the defect in differentiation, or if additional factors are involved.

In response to the reviewer’s concerns, we have generated two stable cell lines expressing short hairpin RNAs directed against DLK1 in the TIS7 SKMc15 dKO MEFs. With these two and the parental dKO MEF cell line, we have performed adipogenesis differentiation experiments as explained in the manuscript before. Figure EV2C (left and right panels) shows that knockdown of DLK1 with two different DLK1 shRNA constructs (targeting DLK1 with or without the extracellular cleavage site) significantly (P<0.001) increased the adipocyte differentiation ability of dKO MEFs. This result indicated that DLK1 knockdown alone was sufficient to correct the differentiation deficit of these cells.

2) There are multiple instances were the authors refer to "data not shown", such as when discussing the body length of dKO mice. Please show the data in all cases (Supplementary Info is fine) or remove any discussion of data that is not shown and cannot be evaluated.

Following three results were in the initial version of our manuscript mentioned as “data not shown”:

  1. line 137: “body length, including the tail did not significantly differ between WT and dKO mice”

  2. line 307: “higher concentrations of free fatty acids in the feces of dKO mice”

  3. line 331: “effects of ectopic expression of TIS7, SKMc15 and their co-expression on DLK-1 levels”

In the current version of the manuscript, we provide these results as:

3) Indirect calorimetry data shown in Figure S1 should include an entire 24 hr cycle and plots of VO2, activity and other measured parameters shown (only RER and food intake are shown), not just alluded to in the legend.

Based on the reviewer’s suggestion, we present here a table (Table 1) containing all parameters measured in the indirect calorimetry experiment.

Metabolic phenotyping presented in Figure EV1B containing 21 hours measurement was performed exactly according to the standardized protocol previously published by Rozman J. et al. [1]. All phenotyping tests were performed following the International Mouse Phenotyping Resource of Standardized Screens (IMPReSS) pipeline routines.

4) It is surprising that the dKO mice weight so much less than WT even though their food consumption and activity levels are similar, and their RER does not indicate a switch in fuel preference. An explanation could be altered lipid absorption. The authors indicate that feces were collected. An analysis of fat content in feces (NEFAs, TG) needs to be performed to examine this possibility. The discussion alludes to it, but no data is shown.

We thank the reviewer for bringing up this important point that prompted us to present data clarifying this aspect of the metabolic phenotype of dKO mice. As shown in Figures 6A,B, while fed with HFD, dKO mice had higher concentrations of free fatty acids in the feces (109 ± 10.4 µmol/g) when compared to the WT animals (78 ± 6.5 µmol/g) and a consequent increase in feces energy content (WT: 14.442 ± 0.433 kJ/g dry mass compared to dKO: 15.497 ± 0.482 kJ/g dry mass). Thus, lack of TIS7 and SKMc15 reduced efficient free fatty acid uptake in the intestines of mice.

5) It would be important to know if increased MEK/ERK signaling and SOX9 expression are seen in fat pads of mutant mice, not just on the MEF system. Similarly, what are the expression levels of PPARg and C/EBPa in WAT depots of mutant mice?

To address this point, we have now performed the MEK/ERK activity measurement for the revised version of the manuscript in gonadal WAT tissue (GWAT). As noted in samples from several mice, there was an increase in p42 and p44 MAPK phosphorylation in G WAT isolated from dKO mice compared with the G WAT from WT control mice (Figure 4G).

The mRNA expression levels of PPARg and C/EBPa were significantly downregulated in GWAT samples isolated from dKO mice compared with levels from WT control animals (Figure 4H). However, we did not find any significant difference in SOX9 expression in fat pads. Total amounts of Sox9 mRNA in terminally differentiated adipocytes were very low and not within the reliable detection range, and the variation between animals within the same group was too great. Therefore, we provide these data only for the reviewer’s information in Author response image 1 and do not present them in the manuscript.

Author response image 1
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6) Analysis of Wnt signaling in Figure 3c should also include a FOPflash control reporter vector, to demonstrate specificity. Also, data from transfection studies should be shown as mean plus/minus STD and not SEM. This also applies to all other cell-based studies (e.g., Figure 6b,c).

To address the reviewer’s concerns, we performed FOPflash control reporter measurements in MEFs of all four genotypes. As expected, in every tested cell line the luciferase activity of the FOPflash reporter was substantially lower than that of TOPflash, confirming the specificity of this reporter system.

Author response image 2
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We also thank the reviewer for this important reference to our statistical analyses. We have revised the original data and found that the abbreviation SEM was inadvertently used in the legends instead of STD. STD was always used in the original analyses and therefore we have corrected all legends accordingly in the new version of the manuscript.

7) It is unclear why the authors used the MEF model rather than adipocyte precursors derived from the stromal vascular fraction (SVF) of fat pads from mutant mice. If they did generate data from SVF progenitors, they should include it.

We agree with this comment, although performing the experiments was challenging enough for us. Therefore, we isolated inguinal fat pads and obtained SVF cells from mice of all four genotypes (WT, TIS7, SKMc15 single and double KOs) and have repeated crucial experiments, i.e. adipocyte differentiation, DLK1, PPARg and C/EBPa mRNA and protein analyses in these cells. Novel data gained in this cell system fully confirmed our previous observations in MEFs. Therefore, in the current version of the manuscript we have replaced figures describing the effects of lacking TIS7 and SKMc15 in MEFs by adipose tissues samples (Figures 2D,E, 4G,H,I and 6C) or SVF cells from inguinal WAT (Figures 2A,B,F,G,H, 3C,D,E and F). In addition to the results obtained from SVF cells of inguinal WAT, we also obtained comparable data from SVF cells isolated from fat pads of gonadal WAT. We provide the results from gonadal WAT in Author response image 3 and Author response image 4 for the reviewers' information only.

Author response image 3
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Author response image 4
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The only experiments where we have still used data obtained in MEFs are those where the ectopic expression or effects of shRNA were necessary (e.g. Figures 2C, 3B,H,I, 5F,G EV2B,C and EV3 A-F).

8) Given that the authors' proposed mechanism involves both, transcriptional and post-transcriptional regulation of DLK-1 by TIS7 and SKMc15, Figure 4d should be a Western blot capturing both of these events, and not just quantitation of mRNA levels.

As requested by the reviewer, we have added in Figure 3B the Western blot analysis of DLK1 expression. Secondly, this experiment was entirely redone and we now show the effects of ectopic expression of SKMc15, TIS7 alone and their combination side by side with the control GFP. We present here the effects of stable expression of ectopic TIS7 and SKMc15 in dKO MEFs following the viral delivery of expression constructs, antibiotic selection and 8 days of adipocyte differentiation.

9) There is no mention of the impact on brown adipose tissue (BAT) differentiation of KO of TIS7, SKMc15, or the combination. Given the role of BAT in systemic metabolism beyond energy expenditure, the authors need to comment on this issue.

We thank the reviewer for bringing up this important point that prompted us to better describe the phenotype of TIS7, SKMc15 and double knockout mice. We measured DLK1 protein levels in BAT isolated from WT, TIS7, and SKMc15 mice with single and double knockout and detected a significant increase in DLK1 protein levels in all three knockout genotypes. Five mice per genotype were analyzed, and the statistical analysis in Figure 4I represents the mean ± STD. The p-values are based on the results of the Student's t-test and one-way Anova analysis (p-value = 0.0241).

Minor comments:

10) The y axis in Figure 2c is labeled as gain of body weight (g). Is it really the case that WT mice gained 30 g of body weight after just 3 weeks of HFD? This rate of increase seems extraordinary, and somewhat unlikely. Please re-check the accuracy of this panel.

We thank the reviewer for drawing our attention to the apparent mislabeling of the y-axis. The correct labeling is: "Increase in body weight in %" and Figure 1F has been corrected accordingly.

11) The Methods indicates all statistical analysis was performed using t tests, but this is at odds with some figure legends that indicate additional tests (e.g., ANCOVA).

This inaccurate information in the manuscript was corrected.

12) Please specify in all cases the WAT depot used for the analysis shown (e.g., Figure 3d is just labeled as WAT, as are Figure 4a,e, etc.).

This information was added at all appropriate places of the manuscript.

13) Figure 5d is missing error bars, giving the impression that this experiment was performed only once (Figure 5c). The legend has no details. Please amend.

We thank the reviewer for this important point regarding the statistical analyses. In the new version of the manuscript, we have included a graph (now Figure 4D) depicting results of three independent experiments including the results of the statistical analysis performed. Statistical analysis was performed using One-Way ANOVA (P=0.0016).

Reviewer #1 (Significance (Required)):

The role of TIS7 in adipocyte differentiation is well established. The only truly novel finding in this work is the observation that SKMc15 also plays a role in adipogenesis. The molecular mechanisms proposed (modulation of DLK-1 levels) are not novel, but make sense. However, they need to be bolstered by additional data.

Referees cross-commenting

I think we are all in agreement that the findings in this work are of interest, but that significant additional work is required to discern the mechanisms involved. In my view, a direct and specific link between SKMc15 and translation of DLK-1 needs to be established and its significance for adipogenesis in cells derived from the SVF of fat pads determined. Reviewer 2 has suggested some concrete ways to provide evidence of a direct link.

We agree with the reviewer's comment and have also noted that this point will be crucial in assessing the novelty value of our manuscript, as was also expressed in the referees cross-commenting. Therefore, we have now additionally performed a polysomal RNA analysis, which has of course been included in the current version of the manuscript.

We analyzed the differences in DLK-1 translation between wild-type control cells and SKMc15 knockout cells in the gradient-purified ribosomal fractions by DLK-1 qPCR. Our analysis identified significantly (p<8,26104E-07) higher DLK-1 mRNA levels in polysomal RNA fraction of SKMc15 KO when compared to wild type MEFs (Figure 3I).

Similarly, as proposed by the reviewer, we have established stromal vascular fraction cell cultures from inguinal fat pads. In SVF cells of TIS7 and SKMc15 single and double knockout mice, we found increased DLK1 mRNA and protein levels (Figures 2F,G and H) as well as decreased PPARg and C/EBPa levels (Figures 3C,D,E and F). Specifically, we found that the ability of knockout SVF cells to differentiate into adipocytes was significantly downregulated (Figures 2A and B), fully confirming our original findings in TIS7 and SKMc15 knockout MEFs.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary:

In the current study, Vietor et al. aimed to explore the regulation of Δ-like homolog 1 (DLK-1), an inhibitor of adipogenesis, and demonstrated a role for TIS7 and its orthologue SKMc15 in the regulation of adipogenesis by controlling the level of DLK-1. Using mouse models with whole body deficiency of TIS7 (TIS7 KO) or SKMc15 (SKMc15KO) and double KO (TIS7 and SKMc15 dKO) mice, the authors used a combination of in-vivo experiments and cell culture experiments with mouse embryonic fibroblasts derived from the KO animals, to show that the concurrent depletion of TIS7 and SKMc15 dramatically reduced the amount of adipose tissues and protected against diet-induced obesity in mice, which was associated with defective adipogenesis in vitro.

Major Comments:

Overall, this study presents convincing evidence that TIOS7 and SKMc15 are necessary for optimal adipogenesis, and proposes a novel mechanism for the control of DLK1 abundance via coordinated regulation of DLK-1 transcription and translation. However, a number of questions remain largely unanswered. In particular, the direct ability of SKMc15 to regulate the translation of DLK-1 is lacking, and this claim remains speculative. SKMc15 being a general inhibitor of translation, SKMc15 may have an effect on adipogenesis independently of its regulation of DLK-1. Thus, addressing the following comments would further improve the quality of the manuscript:

We have been very attentive to these comments to improve the novelty and quality of our manuscript and have tried to address them experimentally. Therefore, this thorough revision of our manuscript took a longer time. First, we identified polysomal enrichment of DLK-1 RNA in SKMc15 KO MEFs, demonstrating that SKMc15 translationally affects DLK-1 levels (Figure 3I). Second, treatment with a recombinant DLK-1 protein as well as its ectopic expression quite clearly blocked adipocyte differentiation of WT MEFs (Figures EV3B,C). In addition, two different shRNA constructs targeting DLK-1 significantly induced adipocyte differentiation of TIS7 SKMc15 dKO MEFs (Figure EV2C, left and right panels). We believe that these results, taken together, sufficiently support our proposed mechanism, namely that TIS7 and SKMc15 control adipocyte differentiation through DLK-1 regulation.

The experimental evidence supporting that SKMc15 controls DLK-1 protein levels comes primarily from the observations that DLK-1 abundance is further increased in SKMc15 KO and dKO WAT than in TIS7KO WAT (Figure 3d), and that translation is generally increased in SKMc15 KO and dKO cells (Figure 5a). However, since the rescue experiment is performed in dKO cells, by restoring both TIS7 and SKMc15 together, it is impossible to disentangle the effects on DLK-1 transcription, DLK-1 translation and on adipogenesis. A more detailed description of the TIS7 and SKM15c single KO cells, with or without re-expression of TIS7 and SKMc15 individually, at the level of DLK-1 mRNA expression and DLK-1 protein abundance would be necessary. In addition, polyribosome fractioning followed by qPCR for DLK-1 in each fraction, and by comparison with DLK-1 global expression in control and SKMc15 KO cells, would reveal the efficiency of translation for DLK-1 specifically, and directly prove a translational control of DLK-1 by SKMc15. Alternatively, showing that DLK-1 is among the proteins newly translated in SKMc15 KO cells (Figure 5a) would be helpful.

As suggested by the reviewer we used single TIS7 and SKMc15 knockout cells and demonstrated that both, TIS7 and SKMc15, affect Dlk-1 mRNA levels. We identified a highly significant effect on total DLK-1 mRNA levels in SKMc15 knockout MEFs as presented in Figure 3H. We also show that DLK-1 mRNA is specifically enriched in polysomal fractions obtained from proliferating SKMc15 knockout MEFs when compared to WT MEFs. However, the strong accumulation of DLK-1 mRNA in polysomes cannot be explained by transcriptional upregulation of DLK-1 alone, suggesting that regulation also occurs at the translational level. We took up this suggestion and ectopically expressed TIS7 and SKMc15 separately or together. For this purpose, we used not only MEF cell lines with double knockout but also with single knockout. Our recent data showed that stable ectopic expression of SKMc15 significantly increased adipocyte differentiation in both, single and double TIS7 and SKMc15 knockout MEF cell lines (Figures EV1C,D and EV2A). Ectopic expression of TIS7 significantly induced the adipocyte differentiation in TIS7 single knockout MEFs (Figure EV1C). In addition, both genes down regulated DLK-1 mRNA expression in dKO MEFs (Figure EV2A, bar chart on the right). We fully agree with the opinion of both reviewers and as already explained above we identified by qPCR in the polysomes that SKMc15 directly regulates DLK-1 translation (Figure 3I).

While the scope of the study focuses on the molecular control of adipogenesis by TIS7 and SKMc15 via the regulation of DLK-1, basic elements of the metabolic characterization of the KO animals providing the basis for this study would be useful. Since the difference in body weight between WT and dKO animals is already apparent 1 week after birth (Figure 1a), it would be interesting to determine whether the fat mass is decreased at an earlier age than 6 months (Figure 1b). The dKO mice are leaner despite identical food intake, activity and RER (Sup Figure 1). It remains unclear whether defective fat mass expansion is a result or consequence of this phenotype. Is the excess energy stored ectopically? The authors mention defective lipid absorption, however, these data are not presented in the manuscript. It would be interesting to investigate the relative contribution of calorie intake and adipose lipid storage capacity in the resistance to diet-induced obesity. In addition, data reported in Figure 1c seem to indicate a preferential defect in visceral fat development, as compared to subcutaneous fat. It would be relevant if the authors could quantify it and comment on it. Are TIS7 and SKMc15 differentially expressed in various adipose depots? The authors used embryonic fibroblasts as a paradigm to study adipogenesis. It would be important to investigate, especially in light of the former comment, whether pre-adipocytes from subcutaneous and visceral stroma-vascular fractions present similar defects in adipogenesis.

We addressed the issue of lipid storage capacity raised by the reviewer using two experimental methods. First, we have analyzed feces of mice fed with high fat diet. The free fatty acids content in dKO mice feces was significantly (P<0.05) higher than in that of their WT siblings (Figure 6A). Second, the energy content of dried feces from dKO mice, as determined by bomb calorimetry, was significantly higher than that from WT mice (P<0.001) (Figure 6B).

Concerning the question of younger animals, we have repeated microCT fat measurements on a group of 1-2 months old WT and dKO male mice (n=4 per group). The total amount of abdominal fat was in WT mice significantly higher than in dKO mice (P=0.019; Student’s T-test). We provide these data only for the reviewer’s information in Author response image 5 and do not present them in the manuscript.

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We have also followed the reviewer’s advice and revisited our microCT measurements of abdominal fat and anylyzed the possible differences between subcutaneous and visceral fat. In all three types of abdominal fat mass measurement (total, subcutaneous and visceral) there was always significantly (ANOVA P=0.034 subcutaneous, P=0.002 total and P=0.002 visceral fat) less fat in the dKO group (n=8) of mice when compared to WT (n=12) mice. However, the difference was more prominent in visceral (P=0.001; Student’s T-test) than in subcutaneous fat (P=0.027; Student’s T-test). We provide these data only for the reviewer’s information in Author response image 6 and do not present them in the manuscript.

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In addition, we have analyzed the expression of TIS7 and SKMc15 mRNA expression in both, inguinal and gonadal WAT. Our qPCR result showed that both genes are expressed in different types of WAT. The qPCR analysis was performed on RNA isolated from undifferentiated SVF cells isolated from several animals. The expression of TIS7 and SKMc15 was normalized on GAPDH. Data represent mean and standard deviation of technical replicates from several mice as labeled in the graph. We provide these data only for the reviewer’s information in Author response image 7 and do not present them in the manuscript.

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Topics of (a) stromal vascular fraction as a source of pre-adipocytes and (b) comparison of TIS7 and SKMc15 roles in gonadal vs. inguinal fat pads we answered in response to the Reviewer #1, point 7. The results are presented in Figures 2, 3 and 4 and in this document.

Both data and methods are explained clearly. The experiments are, for the most part, adequately replicated. However, whenever multiple groups are compared, ANOVA should be employed instead of t-test for statistical analysis.

Thank you for pointing this out. Wherever it was applicable, we used ANOVA for the statistical analysis of data.

Minor comments:

Figure 4 d. The appropriate control would be WT with empty vector.

This experiment was entirely replaced by the new Figure 3B where stably transfected MEF cells expressing TIS7 or SKMc15 were used.

Figure 7c/d. The appropriate control would be WT with empty vector.

We have now generated new, confirmatory data in MEF cells stably expressing TIS7 or SKMc15 following lentiviral expression.

Figure 5C. An additional control would be WT with WT medium.

We agree with your suggestion and therefore we have incorporated this control in all experimental repeats presented in the new Figure 4C.

Figure 2: In the legends, the "x" is missing for the dKO regression formula.

Thank you, we have corrected this mistake. In the current version of the manuscript it is Figure 1D.

Since the role of SKMc15 in adipogenesis has never been described, the authors could consider describing the single SKMc15 KO in addition to the dKO, or explain the rationale for focusing the study on dKO.

The original reason for focusing on dKO mice and cells was the obvious and dominant phenotype in this animal model. However, we have sought to address the reviewer's concerns and have now also examined DLK-1 mRNA levels in proliferating SKMc15 knockout MEFs (Figure 3H). In addition to this experiment, we measured DLK-1 mRNA levels also during the process of adipocyte differentiation of single knockout cells. In WT MEFs we observed a transient increase of DLK-1 mRNA only on day 1. In contrast, significantly elevated DLK-1 mRNA levels were found in TIS7 single-knockout MEFs throughout the differentiation process, with the highest level reached at day 8. Interestingly, in SKMc15 single knockout MEFs we found an upregulation of DLK-1 mRNA level in proliferating cells but not a further increase during the differentiation. This supported our idea that SKMc15 acts mainly via translational regulation of DLK-1. We provide these data only for the reviewer’s information in Author response image 8 and do not present them in the manuscript.

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To emphasize this point, we revised the entire manuscript accordingly and added data on SKMc15 knockout mice. In particular, experiments presenting data characterizing SKMc15 single knockout mice are presented in: Figures 1C,D,E and F, Figures 2A,B,C and D, Figures 3E,F,H and I, Figures 4A and I and in Figure EV1D.

Reviewer #2 (Significance (Required)):

While the effects of DLK-1 on adipogenesis have been widely documented, the factors controlling DLK-1 expression and function remain poorly understood. Here the authors propose a novel mechanism for the regulation of DLK-1, and how it affects adipocyte differentiation. This study should therefore be of interest for researchers interested in the molecular control of adipogenesis and cell differentiation in general. Furthermore, the characterization of the function of SKMc15 in the control of translation may be of interest to a broader readership.

Referees cross-commenting

I agree with all the comments raised by the other reviewers. Addressing the often overlapping but also complementary questions would help to clarify the molecular mechanisms by which TIS7 and SKMc15 control adipogenesis, and support the conclusions raised by the authors.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

In the article, "The negative regulator DLK1 is transcriptionally regulated by TIS7 (IFRD1) and translationally by its orthologue SKMc15 (IFRD2)", the authors performed a double knockout (dKO) of TIS7 and its orthologue SKMc15 in mice and could show that those dKO mice had less adipose tissue compared to wild-type (WT) mice and were resistant to a high fat-diet induced obesity. The study takes advantage of number of different methods and approaches and combines both in vivo and in vitro work. However, some more detailed analysis and clarifications would be needed to fully justify some of the statements. Including the role of TIS7 as a transcriptional regulator of DLK1, SKMc15 as translational regulator of DLK1 and overall contribution of DLK1 in the observed differentiation defects. The observed results could still be explained by many indirect effects caused by the knock-outs and more direct functional connections between the studied molecules would be needed. Moreover, some assays appear to be missing biological replicates and statistical analysis. Please see below for more detailed comments:

Major comments:

– Are the key conclusions convincing? Yes.

– Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? No.

– Would additional experiments be essential to support the claims of the paper? Yes. Please see my comments.

– Are the suggested experiments realistic in terms of time and resources? Recombinant DLK1 10 μg – Tetu-bio – 112€ ; 8 days of adipocyte differentiation in 3 biological replicate ~ 1 month.

We followed the advice of the individual reviewers as expressed in “Referees cross-commenting” and tested this idea experimentally. Since the manufacturer couldn’t supply information on biological activities of recombinant DLK-1 proteins, we analyzed in vivo the effects of two different ones, namely RPL437Mu01 and RPL437Mu02. The 8-day adipocyte differentiation protocol showed that the RPL437Mu02 protein was cytotoxic to WT MEF cells and therefore could not be used for analysis. On the other hand, treatment with the Mu01 recombinant DLK-1 protein did not result in a substantial cell death. According to oil red O staining, incubation with 3.3 mg/ml (final concentration) RPL437Mu01 led to 75% inhibition of adipocyte differentiation when compared to not treated WT MEFs (Figure EV3B and C).

– Are the data and the methods presented in such a way that they can be reproduced? Yes.

– Are the experiments adequately replicated and statistical analysis adequate? Adequately reproduced yes. Please see my comments concerning the statistical analysis.

1) Figure 1A: In the method section it is written that an unpaired 2-tailed Student's t test was used for all statistical comparisons. However, here something like Multivariate analysis of variance (MANOVA) should rather be used to assess statistical significance between the mice. Moreover, the details of this should be clearly stated in the corresponding Figure legend.

Based on this suggestion, we have revised all of our statistical analyses. In several cases, (Figures 1F, 2B and C) we have replaced the statistical analysis using Student’s T test with Anova. However, based on the definition “the difference between ANOVA and MANOVA is merely the number of dependent variables fit. If there is one dependent variable then the procedure ANOVA is used”, in case of Figure 1A we used ANOVA.

2) Figure 2A: please use an appropriate title for Figure 2A instead of "Abdominal fat vs. body mass".

Title of the Figure 1D (formerly Figure 2a) we changed to “Effect of TIS7 and SKMc15 on the abdominal fat mass”.

3) Figure 2C: in the method section it is written that an unpaired 2-tailed Student's t test was used for all statistical comparisons. However, in Figure 2C 4 groups are compared (WT, TIS7 KO, SKMc15 KO and dKO) and thus something like Multivariate analysis of variance (MANOVA) should rather be used to assess statistical significance.

For Figure 1F (formerly Figure 2c), in the revised version of the manuscript, we applied the ordinary one-way ANOVA with Holm-Šidák's multiple comparison test. This analysis gave us statistically even more significant results concerning the difference between WT and dKO mice than previously found by Student's T test. The results in detail were as follows:

Author response table 1
Statistical analysis of results presented in Figure 1F.
Holm-Šidák's multiple comparisons testSummaryAdjusted P Value
WT vs. TIS7 KO**0,0096
WT vs. SKMc15 KO*0,0308
WT vs. dKO****<0,0001

4) Figure 2 conclusion: Additive or just showing stronger effect?

We have re-phrased the concluding summary for Figure 1F (formerly Figure 2c). We agree that the precise description of differences found between the weight of single and double knockout animals should be described as “stronger” and not additive effect of knockout of both genes.

5) Figure 3A: the microscope picture for SKMc15 KO shows that cells might have died. Please state the percentage of cell death.

We would like to comment on these concerns of the reviewer as follows: In the image in Figure 3 of the original manuscript, the density of SKMc15 KO MEF cells after the adipocyte differentiation protocol was lower than in the WT control. Regarding the possible cell death, the cells stained with Oil Red O were adherent and alive. The adipocyte differentiation protocol consists of 3 days proliferation and further 5 days of differentiation including three changes of media during which dead cells are washed away and their vitality cannot be checked. However, in the meantime, we have repeated this protocol and the density of SKMc15 knockout MEFs was now not substantially lower than those of controls. Despite the comparable cell density, we have seen a substantial negative effect of the SKMc15 knockout on the adipogenic differentiation ability of these cells. Several examples are shown in Author response image 9.

Author response image 9
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Importantly, in the current version of our manuscript we replaced MEFs (shown in the former Figure 3a) by SVF cells (Figure 2A in the current manuscript). In these cells we did not see any significant difference in their density after 8 days of the adipocyte differentiation protocol.

6) Figure 3B: It would be informative to additionally observe some of marker genes for adipogenesis and whether all of them are affected.

In our newly established SVF cell lines, derived from inguinal WAT we have confirmed data previously identified in MEFs. As shown in the new Figure 3, PPARg and C/EBPa mRNA levels were downregulated in all knockout SVF cell lines, both undifferentiated (Figures 3C and D) and adipocyte differentiated (Figures 3E and F). On the other hand, DLK-1 mRNA and protein levels, both in undifferentiated (Figures 2F and G) and adipocyte differentiated (Figure 2H) SVF cells were significantly upregulated in dKO cells when compared to WT cells.

7) Figure 3B: instead of using an unpaired 2-tailed Student's t test with proportion, an one-way ANOVA would be more appropriate.

On the recommendation of the reviewer, we applied a simple ANOVA to our new data from SVF cells using the Holm-Šidák test for multiple comparisons. The Anova summary using GraphPad Prism Ver. 9.2 identified statistically highly significant (P value <0,0001) differences between WT and all knockout SVF cells (now Figure 2B).

8) Figure 3C: Same comment as for Figure 3B.

Also, in this experiment (now Figure 2C) we used ordinary one-way ANOVA with Holm-Šidák's multiple comparisons test. The ANOVA summary identified statistically highly significant (P value <0,0001) differences between WT and TIS7 single and dKO MEF cells. On the other hand, there was no statistically significant difference between WT and SKMc15 knockout MEFs.

9) Fig3d: A representative Western blot for 3 independent experiments is shown. Please add the other two as supplementary materials.

In Author response image 10 we provide examples of the requested two additional, independent experiments. These refer now to the Figure 2D in the revised version of the manuscript:

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10) Fig3d: Is this distinguishing between the active and inactive catenin?

No, the b-catenin antibody, that we used is not discriminating between active and inactive b-catenin forms.

11) Figure 4A: Please perform qPCR for measuring DLK-1 mRNA levels in TIS7 KO and SKMc15 KO samples to check whether there is a correlation between mRNA and protein level as the statement of the authors is that "DLK1 is transcriptionally regulated by TIS7 (IFRD1) and translationally by its orthologue SKMc15".

Similar questions were raised by Reviewer 2 on p. 11 “Since the role of SKMc15 in adipogenesis has never been described, the authors could consider describing the single SKMc15 KO in addition to the dKO, or explain the rationale for focusing the study on dKO.” Please see our reply to his comment.

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12) Figure 4C: please add the other two western blots as supplementary materials.

In Author response image 12 we provide data from two additional, independent experiments.

Author response image 12
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13) Fig4d: The effects in MEFs appear quite modest. What about a rescue with TIS7 or SKMc15 alone?

As mentioned already in response to the question 2 of Reviewer #1, in our newly performed experiments we found significant inhibitory effects of ectopic TIS7 and SKMc15 expression on DLK1 levels, identified both by qPCR and WB analyses (Figure 3B).

14) Page 12, row 207: I would not call histones transcription factors.

We re-phrased this sentence accordingly.

15) Fig4e: Would be good to see a schematic overview of the locations of the ChIP primers in relation to the known binding sites and the gene (TSS, gene body). Moreover, the results include an enrichment for only one region while in the text two different regions are discussed. Importantly, to confirm the specificity of the observed enrichment, a primer pair targeting an unspecific control region not bound by the proteins should be included.

The selection of oligonucleotide sequences used for ChIP analyses of the binding of b-catenin, TIS7 and SKMc15 to the Dlk-1 promoter was, based on the following reference, as mentioned in Methods section of our original manuscript on p.21, line 494: Paul C, Sardet C, Fabbrizio E. “The Wnt-target gene Dlk-1 is regulated by the Prmt5-associated factor Copr5 during adipogenic conversion”. Biol Open. 2015 Feb 13;4(3):312-6. doi: 10.1242/bio.201411247.

We used two regions of the Dlk-1 promoter: a proximal one, encompassing the TCF binding site 2 (TCFbs2) and a more distal one, annotated as “A”:

Oligonucleotide sequences used for ChIP PCR:Dlk-1 TCFbs2 5'f CATTTGACGGTGAACATATTGG

5'r GCCCAGACCCCAAATCTGTC

Dlk-1 region A (-2263/-2143) 5'f TTGTCTAACCACCCTACCTCAAA

5’r CTCTGAGAAAAGATGTTGGGATTT

We observed specific binding at the proximal site.

16) Figure 5A: Has this experiment been replicated? That is no mention about the reproducibility or quantification of this result. This is the main experiment regarding the role of SKMc15 as a translational regulator of DLK1, also mentioned in the title of the manuscript.

This relates to the Figure 4A in the revised manuscript. Yes, we repeated this experiment several times. Here we provide images and quantifications of three independent experiments.

17) Figure 5B: Showing another unaffected secreted protein would be an appropriate control here.

As recommended by the reviewer, we have performed an additional WB with a recombinant anti-Collagen I antibody [Abcam, [EPR22209-75] ab255809]. Medium from 8 days adipocyte differentiated WT and dKO MEFs was concentrated using Centriprep 30K and resolved on 10% SDS-PAGE gel. Western blot presented in the new Figure 4 B shows even slightly higher amounts of Collagen-1 protein in medium from WT than in dKO MEFs. Mw of the detected band was approximately 35 kDa, which corresponded to the manufacturer’s information.

18) Figure 5C: I would recommend to perform additional experiments to prove that DLK-1 secreted in the medium can contribute and is responsible for the inhibition of the differentiation. Indeed, a time course of adipocyte differentiation followed by the addition of soluble DLK-1 would confirm that DLK-1 can inhibit adipocyte differentiation in this experimental setup. Moreover, silencing (for example RNAi) of DLK1 in the dKO cells before harvesting the conditioned media would allow to estimate the contribution of DLK1 to the observed inhibition of differentiation by the media. This is important because many other molecules could also be mediating this inhibition.

We agree with this reviewer’s concern, which are shared by other reviewers. Similarly, as in response to Reviewer #2 and as already mentioned above, in response to “major comments” of Reviewer #3, in our novel experiments we found that treatment with recombinant DLK-1 protein as well as ectopic expression of DLK-1 blocked adipocyte differentiation of WT MEFs (Figures EV3B,C,D and E) as well as medium from dKO shDLK-1 391 cells (Figure EV3F).

19) Figure 5C: The details and the timeline of the experiment with conditioned media are not provided in the figure or in the methods. At what time point was conditioned media changed? How long were the cells kept in conditioned media? How does this compare to the regular media change intervals? Could the lower differentiation capacity relate to turnover of the differentiation inducing compounds in the media due to longer period between media change? Moreover, is the result statistically significant after replication?

Based on the reviewer`s comment we have added technical information concerning the experimental protocol of the treatment with conditioned media. In general, the treatment for adipocyte differentiation was identical with the previous experiments. The only difference was that after three days in proliferation medium, we used either fresh differentiation medium or 2-day-old differentiation medium from dKO control or dKO-shDLK-1 391 cell cultures then for wild-type cells, as shown in the figure (Figure EV3F). Cells were incubated additional five days with the differentiation medium with two changes of media, every second day. The adipocyte differentiation of medium “donor” cells and the DLK-1 protein levels in these cells were monitored by oil red O staining and Western blot analysis, respectively.

Additionally, we show now in Figure 4C representative images from three independent biological repeats and in Figure 4D the statistical analysis confirming a significant decrease in adipocyte differentiation ability of WT MEFs following their incubation with a conditioned differentiation medium from dKO MEFs.

20) Fig5d: please add a statistical analysis of the oil-red-o quantification.

As requested, we included statistical analysis of at least three independent experiments. In Figure 4D we present the statistical analysis confirming a significant decrease in adipocyte differentiation of WT MEFs following their incubation with the differentiation medium from dKO cells. Additionally, Figure 4C shows representative images of oil red O staining from several independent experiments.

21) Fig7c-d: Does overexpression also rescue the PPARg and CEBPa induction during differentiation. The importance of their induction in undifferentiated MEFs is a little difficult to judge.

We have focused our attention primarily on the ability of TIS7 and SKMc15 to “rescue” the adipocyte differentiation phenotype of dKO MEFs. dKO MEFs stably expressing SKMc15, TIS7 or both genes were differentiated into adipocytes for 8 days and afterwards stained with oil red O. There was a statistically significant increase in oil red O staining following the individual ectopic expression of SKMc15 (p=5.7E-03), a negative effect of TIS7 ectopic expression and a significant (p=9.3E-03), positive effect of co-expression of both genes (Figure EV2A). We found a significant decrease in Dlk-1 mRNA expression following the ectopic expression of TIS7 and/or SKMc15 (Figure EV2A, very right panel). However, C/EBPa mRNA levels were only partially rescued in 8 days differentiated MEFs by TIS7 and/or SKMc15 ectopic expression, and PPARg mRNA levels were not significantly altered.

22) Fig8: it is not surprising that PPARg targets are not induced in the absence of PPARg. What is the upstream event explaining this defect? Is DLK1 alone enough to explain the results? Could there be additional mediators of the differences? How big are transcriptome-wide differences between WT MEFs and dKO MEFs?

We agree with the reviewer that the lean phenotype of dKO mice most likely cannot be explained by simple transcriptional regulation of PPARg. Although we showed that in undifferentiated MEFs, the levels of PPARg and C/EBPa are controlled (or upregulated) by both TIS7 and SKMc15, we also expected differences in the expression of genes regulating fat uptake. To determine changes in expression of lipid processing and transporting molecules, we performed transcriptome analyses of total RNA samples isolated from the small intestines of HFD-fed WT type and dKO animals. Cluster analyses of lipid transport-related gene transcripts revealed differences between WT type and dKO animals in the expression of adipogenesis regulators. Those included among other genes the following, mentioned as examples:

  • peroxisome proliferator-activated receptors γ (PPARγ) and d [2], fatty acid binding proteins 1 and 2 (FABP1, 2) [3],

  • cytoplasmic fatty acid chaperones expressed in adipocytes,

  • acyl-coenzyme A synthetases 1 and 4 (ACSL1,4) found to be associated with histone acetylation in adipocytes, lipid loading and insulin sensitivity [4],

  • SLC27a1, a2 fatty acid transport proteins, critical mediators of fatty acid metabolism [5],

  • angiotensin-converting enzyme (ACE) playing a regulatory role in adipogenesis and insulin resistance [6],

  • CROT, a carnitine acyltransferase important for the oxidation of fatty acids, a critical step in their metabolism [7],

  • phospholipase PLA2G5 robustly induced in adipocytes of obese mice [8]; [9].

Parts of the following text are embedded in the manuscript.

We decided to study in more detail the regulation of CD36 that encodes a very long chain fatty acids (VLCFA) transporter because CD36 is an important fatty acid transporter that facilitates fatty acids (FA) uptake by heart, skeletal muscle, and also adipose tissues [10]. PPARγ induces CD36 expression in adipose tissue, where it functions as a fatty acid transporter, and therefore, its regulation by PPARγ contributes to the control of blood lipids. Diacylglycerol acyltransferase 1 (DGAT1), a protein associated with the enterocytic triglyceride absorption and intracellular lipid processing is besides CD36 another target gene of adipogenesis master regulator PPARγ [11]. DGAT1 mRNA levels are strongly up regulated during adipocyte differentiation [12], its promoter region contains a PPARγ binding site and DGAT1 is also negatively regulated by the MEK/ERK pathway. DGAT1 expression was shown to be increased in TIS7 transgenic mice [13] and its expression was decreased in the gut of high fat diet-fed TIS7 KO mice [14]. Importantly, DGAT1 expression in adipocytes and WAT is up regulated by PPARγ activation [11].

Author response image 13
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Heatmap of hierarchical cluster analysis of intestinal gene expression involved in lipid transport altered in TIS7 SKMc15 dKO mice fed a high-fat diet for 3 weeks.

What is the upstream event explaining this defect?

Wnt pathway causes epigenetic repression of the master adipogenic gene PPARγ. There are three epigenetic signatures implicated in repression of PPARγ: increased recruitment of MeCP2 (methyl CpG binding protein 2) and HP-1α co-repressor to PPARγ promoter and enhanced H3K27 dimethylation at the exon 5 locus in a manner dependent on suppressed canonical Wnt. These epigenetic effects are reproduced by antagonism of canonical Wnt signaling with Dikkopf-1.

Zhu et al. showed that Dlk1 knockdown causes suppression of Wnt and thereby epigenetic de-repression of PPARγ [15]. Dlk1 levels positively correlate with Wnt signaling activity and negatively with epigenetic repression of PPARγ [16]. Activation of the Wnt pathway caused by DLK1 reprograms lipid metabolism via MeCP2-mediated epigenetic repression of PPARγ [17]. Blocking the Wnt signaling pathway abrogates epigenetic repressions and restores the PPARγ gene expression and differentiation [18].

Minor comments:

1) Please use the same font in the main text for the references.

We thank the reviewer for the remark. This issue was corrected.

Reviewer #3 (Significance (Required)):

The study provides interesting insights into the role of these factors in adipocyte differentiation that would be relevant especially to researchers working on adipogenesis and cellular differentiation in general. The authors find the studied factors to have additive contribution to the differentiation efficiency. However, the exact nature of the roles and whether they are strictly speaking additive or synergistic is not clear. More detailed analysis of their contribution and molecular interplay would add to the broader interest of the study on molecular networks controlling cellular differentiation.

Referees cross-commenting

I very much agree on the different points raised by the other reviewers, some of which are also matching my own already raised concerns. And therefore it makes sense to request these modifications from the authors.

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14. Yu, C., et al., Deletion of Tis7 protects mice from high-fat diet-induced weight gain and blunts the intestinal adaptive response postresection. J Nutr, 2010. 140(11): p. 1907-14.

15. Zhu, N.L., et al., Hepatic stellate cell-derived δ-like homolog 1 (DLK1) protein in liver regeneration. J Biol Chem, 2012. 287(13): p. 10355-10367.

16. Zhu, N.L., J. Wang, and H. Tsukamoto, The Necdin-Wnt pathway causes epigenetic peroxisome proliferator-activated receptor γ repression in hepatic stellate cells. J Biol Chem, 2010. 285(40): p. 30463-71.

17. Tsukamoto, H., Metabolic reprogramming and cell fate regulation in alcoholic liver disease. Pancreatology, 2015. 15(4 Suppl): p. S61-5.

18. Miao, C.G., et al., Wnt signaling in liver fibrosis: progress, challenges and potential directions. Biochimie, 2013. 95(12): p. 2326-35.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Based on the previous reviews and the revisions, the manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:

This study provides new insights into the molecular regulation of adipocyte differentiation. Two molecules, TIS7 and SKMc15, are shown to regulate the activity of the key transcriptional regulator DLK-1 via discrete mechanisms – one involving transcription and the other translation. These findings add additional information to the well known roles of Wnt/catenin and PPARg on adipocyte differentiation.

The authors have extensively addressed the comments of the referees and all referees are convinced that the manuscript is now improved and the mechanistic details of the link between SKMc15 and regulation of adipogenesis is now strengthened. However, as described below there are still some important issues that need to be addressed by the authors prior to publication. Many of these require editorial changes but there are some minor experimental details that need to be addressed. Also essential is that you discuss more thoroughly the lipid absorption issue as a contributor to the dKO mouse phenotype.

Specific Issues

1) All energy balance measurements need to be included in the manuscript, not just shown to reviewers. Readers will want to see them.

We added results of the indirect calorimetry trial to the manuscript as Table 1. Text changes are in lines 179-181 and the new legend is 973-978.

2) It is not quite clear how food intake is expressed. Since the mice are significantly smaller, it might be more appropriate to express the data as g of food/g of mouse, as a smaller mouse is likely to eat less.

This issue is addressed in Table 1. Four parameters, among them also food intake, were first statistically analyzed using one-way ANOVA and secondly using a linear model including body mass as a co-variate, meaning normalized on the body mass. This parameter was graphically presented in the Figure 1 —figure supplement 2A. In the legend to this figure (lanes 766-768) is explained that food intake, when adjusted to the body mass, was non-significantly decreased in dKO mice (4.0±0.4 g in WT vs. 3.4±0.5 g in dKO mice).

3) In complementation experiments, it would be useful to know the levels of overexpression.

Western blots of cell lysates from both wild type and SKMc15 or TIS7 over-expressing dKO MEFs were quantified using Vilber spectral imager hardware and software. Supplementary figure I depicts samples from dKO MEFs over-expressing TIS7 and figure J dKO MEFs over-expressing SKMc15. The over-expression levels were 14.7-fold for TIS7 and 10.91-fold for SKMc15, respectively in comparison to the endogenous levels of these proteins in wild type MEF cells. Images shown in Figure 1 —figure supplement 2I and J originate from the same membrane, just lanes with unrelated samples are here not shown.

4) What is the levels of blood lipids in the dKO mice, since this is the first report of their existence, and presumably the defect in intestinal lipid absorption may affect these?

In order to answer this question we have now measured cholesterol, triglycerides levels, and the lipoprotein profile in four wild type and four TIS7 SKMc15 dKO, 7 months old, male mice. None of these three analyses identified any statistically significant difference between wild type and dKO mice. Results of these measurements are presented in the Figure 1 —figure supplement 2K, L, and M and explained in the legend, lanes 798-806.

5) The methods need to be carefully edited. For instance, lines 564-65 state "Small intestines were harvested for oil red O staining to detect lipid accumulation"; these data are not shown anywhere in the paper. Similarly, the section on fecal fat determination describes a protocol to analyze neutral sterols and bile acids (nowhere in the paper), but it does not describe how the free fatty acid levels were determined. One more example, line 651 alludes to "pulse labeling of mitochondrial proteins" which is not what is presented in the paper.

We thank the editor for the careful reading of our manuscript. We corrected all mentioned inaccuracies in the Methods section and completely replaced a paragraph describing the analysis of fatty acids. The new version is now explained in lines 554-558. Plasma cholesterol and triglyceride analyses are described in lines 562-565.

6) The main text should indicate at the outset that only male mice were analyzed.

In the Results section, line 154-155 and in the Material and methods section, lines 496-497 we explicitly note that: “In order to achieve maximal homogeneity of experimental groups, in all experiments presented here we used only male mice”.

7) It is incorrect to state that the dKO mice are not smaller when the graph showing that data (panel A in Figure EV1) shows a significant difference.

This information was corrected, see lines 162-164.

https://doi.org/10.7554/eLife.88350.sa2

Article and author information

Author details

  1. Ilja Vietor

    Institute of Cell Biology, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing
    Contributed equally with
    Domagoj Cikes, Kati Piironen and Theodora Vasakou
    For correspondence
    ilja.vietor@i-med.ac.at
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1391-6793

  2. Domagoj Cikes

    1. Institute of Cell Biology, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    2. IMBA, Institute of MolecularBiotechnology of the Austrian Academy of Sciences, Vienna, Austria
    Contribution
    Conceptualization, Formal analysis, Investigation, Writing – original draft
    Contributed equally with
    Ilja Vietor, Kati Piironen and Theodora Vasakou
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0350-5672

  3. Kati Piironen

    1. Institute of Cell Biology, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    2. Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
    Contribution
    Formal analysis, Investigation
    Contributed equally with
    Ilja Vietor, Domagoj Cikes and Theodora Vasakou
    Competing interests
    No competing interests declared

  4. Theodora Vasakou

    Institute of Cell Biology, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Formal analysis, Investigation
    Contributed equally with
    Ilja Vietor, Domagoj Cikes and Kati Piironen
    Competing interests
    No competing interests declared

  5. David Heimdörfer

    Division of Genomics and RNomics, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  6. Ronald Gstir

    1. Institute of Cell Biology, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    2. ADSI – Austrian Drug Screening Institute GmbH, Innsbruck, Austria
    Present address
    Division of Hygiene and Medical Microbiology at the Medical University of Innsbruck, Innsbruck, Austria
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  7. Matthias David Erlacher

    Division of Genomics and RNomics, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Resources, Validation
    Competing interests
    No competing interests declared

  8. Ivan Tancevski

    Department of Internal Medicine II, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Conceptualization, Resources, Validation, Investigation
    Competing interests
    No competing interests declared

  9. Philipp Eller

    Department of Internal Medicine II, Innsbruck Medical University, Innsbruck, Austria
    Present address
    Medical University of Graz, Department of Internal Medicine, Graz, Austria
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  10. Egon Demetz

    Department of Internal Medicine II, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Investigation
    Competing interests
    No competing interests declared

  11. Michael W Hess

    Division of Histology and Embryology, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Conceptualization, Validation
    Competing interests
    No competing interests declared

  12. Volker Kuhn (deceased)

    Department Trauma Surgery, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Resources, Formal analysis, Validation
    Competing interests
    No competing interests declared

  13. Gerald Degenhart

    Department of Radiology, Medical University Innsbruck, Innsbruck, Austria
    Contribution
    Resources, Data curation, Formal analysis, Validation, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9961-1084

  14. Jan Rozman

    1. German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
    2. German Center for Diabetes Research (DZD), Neuherberg, Germany
    Contribution
    Conceptualization, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8035-8904

  15. Martin Klingenspor

    1. Chair of Molecular Nutritional Medicine, Technical University of Munich, School of Life Sciences, Weihenstephan, Germany
    2. EKFZ - Else Kröner Fresenius Center for Nutritional Medicine, Technical University of Munich, Freising, Germany
    3. ZIEL - Institute for Food & Health, Technical University of Munich, Freising, Germany
    Contribution
    Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4502-6664

  16. Martin Hrabe de Angelis

    1. German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
    2. German Center for Diabetes Research (DZD), Neuherberg, Germany
    3. Chair of Experimental Genetics, Technical University of Munich, School of Life Sciences, Freising, Germany
    Contribution
    Funding acquisition
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7898-2353

  17. Taras Valovka

    Institute of Cell Biology, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    Contribution
    Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Writing – review and editing
    Competing interests
    No competing interests declared

  18. Lukas A Huber

    1. Institute of Cell Biology, Biocenter, Innsbruck Medical University, Innsbruck, Austria
    2. ADSI – Austrian Drug Screening Institute GmbH, Innsbruck, Austria
    Contribution
    Conceptualization, Formal analysis, Funding acquisition, Validation, Visualization, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1116-2120

Funding

Austrian Science Fund (P18531-B12)

  • Ilja Vietor

Austrian Science Fund (P22350-B12)

  • Ilja Vietor

Helmholtz Zentrum München (01KX1012)

  • Martin Hrabe de Angelis

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Robert Kurzbauer for generation of dKO mice, Stephan Geley, Laura M de Smalen, Laura De Gaetano, and Karin Schluifer for the technical assistance, Christiane Heim for serum analyses and free fatty acid uptake measurements, Frans Stellaard for the analysis of fatty acids content in feces, Mayra Eduardoff for RNA processing for Affymetrix chip analysis, Alexander Magnutzki for advice with the statistical analyses of data, and David Teis and Zlatko Trajanoski for critical reading of the manuscript. Furthermore, we would like to thank Dr Paul Shore for providing us with the pGLCD36 construct. We are indebted to the staff at the Animal Facility of Innsbruck Medical University for their care of our mice. This work was supported by P18531-B12 and P22350-B12 grants from the Austrian FWF grant agency to Ilja Vietor and by the German Federal Ministry of Education and Research (Infrafrontier grant 01KX1012) to Martin Hrabe de Angelis.

Ethics

All animal experiments were performed in accordance with Austrian legislation BGB1 Nr. 501/1988 i.d.F. 162/2005.

Senior and Reviewing Editor

  1. David E James, University of Sydney, Australia

Version history

  1. Preprint posted: July 30, 2019 (view preprint)
  2. Received: April 20, 2023
  3. Accepted: August 20, 2023
  4. Accepted Manuscript published: August 21, 2023 (version 1)
  5. Version of Record published: August 30, 2023 (version 2)
  6. Version of Record updated: September 5, 2023 (version 3)

Copyright

© 2023, Vietor, Cikes, Piironen et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Ilja Vietor
  2. Domagoj Cikes
  3. Kati Piironen
  4. Theodora Vasakou
  5. David Heimdörfer
  6. Ronald Gstir
  7. Matthias David Erlacher
  8. Ivan Tancevski
  9. Philipp Eller
  10. Egon Demetz
  11. Michael W Hess
  12. Volker Kuhn
  13. Gerald Degenhart
  14. Jan Rozman
  15. Martin Klingenspor
  16. Martin Hrabe de Angelis
  17. Taras Valovka
  18. Lukas A Huber
(2023)
The negative adipogenesis regulator Dlk1 is transcriptionally regulated by Ifrd1 (TIS7) and translationally by its orthologue Ifrd2 (SKMc15)
eLife 12:e88350.
https://doi.org/10.7554/eLife.88350

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