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. 2024 Mar 27;12:RP91060. doi: 10.7554/eLife.91060

Intermittent fasting promotes type 3 innate lymphoid cells secreting IL-22 contributing to the beigeing of white adipose tissue

Hong Chen 1,2,, Lijun Sun 1,, Lu Feng 1, Xue Han 1, Yunhua Zhang 1, Wenbo Zhai 1, Zehe Zhang 1, Michael Mulholland 3, Weizhen Zhang 1,3,, Yue Yin 4,
Editors: Kiyoshi Takeda5, Tadatsugu Taniguchi6
PMCID: PMC10972562  PMID: 38536726

Abstract

Mechanism underlying the metabolic benefit of intermittent fasting remains largely unknown. Here, we reported that intermittent fasting promoted interleukin-22 (IL-22) production by type 3 innate lymphoid cells (ILC3s) and subsequent beigeing of subcutaneous white adipose tissue. Adoptive transfer of intestinal ILC3s increased beigeing of white adipose tissue in diet-induced-obese mice. Exogenous IL-22 significantly increased the beigeing of subcutaneous white adipose tissue. Deficiency of IL-22 receptor (IL-22R) attenuated the beigeing induced by intermittent fasting. Single-cell sequencing of sorted intestinal immune cells revealed that intermittent fasting increased aryl hydrocarbon receptor signaling in ILC3s. Analysis of cell-cell ligand receptor interactions indicated that intermittent fasting may stimulate the interaction of ILC3s with dendritic cells and macrophages. These results establish the role of intestinal ILC3s in beigeing of white adipose tissue, suggesting that ILC3/IL-22/IL-22R axis contributes to the metabolic benefit of intermittent fasting.

Research organism: Mouse

eLife digest

Obesity refers to a condition where a person has excessive fat accumulation, which can have negative impacts on their health. Managing obesity has typically relied on reducing energy intake and increasing energy use through diets and exercise.

For example, intermittent fasting is a diet strategy involving periods of time in a day or week where a person does not eat any food. Research has shown that intermittent fasting may improve the metabolism and increase energy use by enhancing a process known as “beigeing” of white fat tissue.

In this process, white fat cells or their precursor cells differentiate into beige fat cells, which can consume excess energy by burning fat. Consequently, understanding how beigeing of white fat cells is activated in intermittent fasting may reveal a promising strategy for tackling obesity and metabolic diseases.

Immune cells found in the gut known as innate lymphoid cells (ILCs) may play a role in the metabolic benefits from intermittent fasting. However, the roles of ILCs are complex: some types of ILCs can promote obesity, while others show metabolic benefits through their release of proteins like IL-17 and IL-22, which can help the body to metabolise glucose.

To find out if these immune cells play a role in intermittent fasting, Chen, Sun et al. used diet-induced obese mice that had to fast every other day. Intermittent fasting was found to cause a form of ILCs (ILC3s) to release IL-22, which resulted in beigeing of white fat cells in obese mice. Single-cell sequencing techniques of gut immune cells further revealed that intermittent fasting increased forms of signalling in ILC3s and caused ILC3s to interact with other immune cells, such as dendritic cells and macrophages.

The findings demonstrate how intermittent fasting causes beigeing of white adipose tissue through ILC3s, revealing mechanisms underpinning the metabolic benefits found from intermittent fasting. More research into this process may help identify new targets for treating obesity.

Introduction

Obesity is defined as an epidemic metabolic disease characterized by excessive fat accumulation as the consequence of long-term energy surplus. Thus, therapeutic management of obesity has been focused on the restoration of energy balance, either by decreasing energy intake or by increasing energy expenditure (Liu et al., 2021). Among these strategies, intermittent fasting is becoming a popular dietary approach. All intermittent fasting schemes including alternate day fasting, 5:2 intermittent fasting, and daily time-restricted feeding have shown the health benefits such as delaying aging (Colman et al., 2009; Mattison et al., 2012; Mattison et al., 2017; Ulgherait et al., 2021; Stekovic et al., 2019), improving metabolism (de Cabo and Mattson, 2019; Hepler et al., 2022), and enhancing cognition (Mattson et al., 2018; Liu et al., 2019; Mattson and Arumugam, 2018). The mechanism underlying metabolic benefit of intermittent fasting remains largely unknown. Its metabolic benefit was initially attributed to limitation of energy intake. Recent studies have indicated an alternative mechanism involving beigeing of white adipose tissue, which accounts for the major plasticity of energy expenditure. Studies by Kim et al., 2017, have shown that intermittent fasting induces white adipose beigeing via stimulation of angiogenesis and macrophage M2 polarization. On the other hand, studies by Li et al., 2017, have indicated that alternate day fasting induces white adipose tissue beigeing by shaping the gut microbiota and elevating the fermentation products acetate and lactate. Although gut microbiota is closely related to immune response, it remains unclear whether intestinal immune cells contribute to the metabolic benefit of intermittent fasting.

Innate lymphoid cells (ILCs) are a group of natural immune cells lacking antigen-specific receptors expressed on T cells and B cells (Gasteiger et al., 2015). Based on developmental trajectories, ILCs are divided into five groups: natural killer cells, type 1 ILCs, type 2 ILCs, type 3 ILCs (ILC3s), and lymphoid tissue-inducing cells (Vivier et al., 2018). Adipose-resident type 1 ILCs can promote adipose tissue fibrosis and obesity-associated insulin resistance (O’Sullivan et al., 2016; Wang et al., 2019) while type 2 ILCs promote beiging of white adipose tissue and limit obesity (Brestoff et al., 2015; Lee et al., 2015; Wang et al., 2021b). However, the contribution of ILC3s on adipocytes and obesity are less clear. ILC3s can produce interleukin-17 (IL-17) and interleukin-22 (IL-22) in response to extracellular bacteria and fungi (Sanos et al., 2009). ILC3s-derived IL-22 can enhance the intestinal mucosal barrier function, reduce endotoxemia and inflammation, ameliorate insulin sensitivity (Wang et al., 2014; Hasnain et al., 2014), and improve the metabolic disorder of polycystic ovary syndrome (Qi et al., 2019). However, ILC3s are also reported to be involved in the induction of obesity (Sasaki et al., 2019), contributing to the metabolic disease (Sasaki et al., 2019; Upadhyay et al., 2012; Wang et al., 2017; Kawano et al., 2022). Therefore, the role of ILC3s in metabolic disease seems complex and the role of ILC3s in intermittent fasting and beigeing of adipose tissue is not known.

Here, we showed that alternate day fasting promoted the secretion of IL-22 by ILC3s. Further, adoptive transfer of intestinal ILC3s increased thermogenesis in diet-induced obesity (DIO) mice. Exogenous IL-22 induced the beigeing of white adipose tissue. Deficiency of IL-22 receptor attenuated the beigeing of white adipose tissue induced by intermittent fasting. Our study demonstrates that intestinal ILC3-IL-22-IL-22R axis is actively involved in the regulation of adipose tissue beigeing. Our findings thus reveal a novel pathway in the dialog between the gut and adipose tissue.

Results

Intermittent fasting enhances IL-22 production by intestinal ILC3s

To explore the effect of intermittent fasting on intestinal immune cells, we applied alternate day fasting to mice fed normal chow diet (NCD-IF group) or high-fat diet (HFD-IF group) (Figure 1A). Intermittent fasting significantly reduced the body weight of mice fed HFD, while demonstrating no effect on food intake rate which was normalized to body weight (Figure 1—figure supplement 1A and B). Moreover, intermittent fasting decreased the respiratory quotient (RQ) on the fasting day while increased the energy consumption on the feeding day in mice fed HFD (Figure 1—figure supplement 1C and D), improved glucose and lipid metabolism in mice fed HFD (Figure 1—figure supplement 1E and F), and promoted white adipose tissue beigeing in mice fed NCD or HFD (Figure 1—figure supplement 2).

Figure 1. Intermittent fasting enhances interleukin-22 (IL-22) production by intestinal type 3 innate lymphoid cells (ILC3s).

(A) Schematic illustration of the alternate day fasting regimen. NCD, normal chow diet. HFD, high-fat diet. We applied alternate day fasting to mice fed normal chow diet (NCD-IF group) or high-fat diet (HFD-IF group). The control groups were at free access to NCD (NCD group) or HFD (HFD group). n=9 for each group. (B) mRNA expression levels of cytokine genes in the small intestine of NCD and NCD intermittent fasting (NCD-IF) mice. qPCR results were normalized to β-actin. n=6 for each group. (C) Protein levels of IL-22 in plasma of NCD and NCD-IF mice. n=9 for each group. (D) Fl IL-22+ cells in live CD127+ lineage- RORγt+ ILC3s from the small intestine lamina propria (siLP) of NCD and NCD-IF mice. Four independent experiments were performed with similar results. n=4. (E) Flow cytometric analysis of RORγt+ ILC3s in live CD127+ lineage- ILCs in the siLP of NCD and NCD-IF mice. n=4. (F) Flow cytometric analysis of IL-22+ cells in live lineage+ RORγt+ cells in the siLP of mice fed NCD with or without intermittent fasting. n=4. (G) Flow cytometric analysis of IL-22+ cells in CD90.2+ lineage- RORγt+ ILC3s from the stromal vascular fraction (SVF) cells of subcutaneous white adipose tissue (sWAT) in mice fed NCD with or without intermittent fasting. n=5. (H) mRNA expression levels of cytokine genes in the small intestine of mice fed HFD with or without intermittent fasting. qPCR results were normalized to β-actin. n=9. (I) Flow cytometric analysis of IL-22+ cells in live lineage+ RORγt+ cells in the siLP of mice fed HFD with or without intermittent fasting. n=4. (J) Levels of IL-22 in plasma of NCD mice, HFD mice, and HFD-IF mice. n=6. (K) Flow cytometric analysis of RORγt+ ILC3s in live CD127+ lineage- ILCs and flow cytometric analysis of IL-22+ cells in live CD127+ lineage- RORγt+ ILC3s from the siLP of NCD mice, HFD mice, and HFD-IF mice. n=5–8. * vs NCD, # vs HFD, p<0.05. All data represent the mean ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test (A–I) or one-way ANOVA (J and K). NCD, normal chow diet. HFD, high-fat diet. NCD-IF, normal chow diet with intermittent fasting. HFD-IF, high-fat diet with intermittent fasting.

Figure 1.

Figure 1—figure supplement 1. Intermittent fasting improves glucose metabolism and lipid metabolism.

Figure 1—figure supplement 1.

(A) Body weight and cumulative food intake normalized to body weight of mice fed normal chow diet (NCD) with or without intermittent fasting. n=9. (B) Body weight and cumulative food intake normalized to body weight of mice fed high-fat diet (HFD) with or without intermittent fasting. n=9. (C) Respiratory quotient (RQ) of mice fed NCD with or without intermittent fasting. n=5. (D) RQ, energy expenditure (EE) of mice fed HFD with or without intermittent fasting. n=5. (E) Oral glucose tolerance test (OGTT) and area under the curve (AUC). Insulin tolerance test (ITT) and AUC of NCD, NCD-IF, HFD, and HFD-IF mice. n=6 per group. (F) Levels of plasma triglycerides (TG), cholesterol, free glycerol, and free fatty acids (FFA). n=6mice/group. All data represent the mean ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test or one-way ANOVA.
Figure 1—figure supplement 2. Intermittent fasting promotes white adipose tissue beigeing.

Figure 1—figure supplement 2.

(A) Representative image of subcutaneous white adipose tissue (sWAT) from mice fed normal chow diet (NCD) with or without intermittent fasting. (B) Tissue weight of sWAT, epididymal white adipose tissue (eWAT), liver, BAT, from NCD and NCD intermittent fasting (NCD-IF) mice. n=6. (C) qPCR analysis of thermogenic genes in sWAT from NCD and NCD-IF mice. n=6mice/group. (D) qPCR analysis of inflammation and lipolysis genes in sWAT from NCD and NCD-IF mice. n=6mice/group. (E) UCP1 protein expression in the sWAT of NCD and NCD-IF mice detected by western blotting. β-Actin was used as the loading control. The relative protein signal intensity was quantified using ImageJ software. (F) Hematoxylin-eosin (H&E) staining in sWAT and eWAT. Cell sizes were measured using ImageJ. n=5 per group. Scale bar: 100μm. (G) Representative image for sWAT of HFD and HFD-IF mice. n=6. (H) Tissue weight of sWAT, BAT, liver, eWAT from HFD and HFD-IF mice. n=6. (I) qPCR analysis of thermogenic genes in sWAT from HFD and HFD-IF mice. n=6mice/group. (J) H&E staining in sWAT and eWAT from HFD and HFD-IF mice. Cell sizes were measured using ImageJ. n=5 per group. Scale bar: 100μm. All data represent the mean ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test (B–E, H, I).
Figure 1—figure supplement 2—source data 1. Original file for the western blot analysis in Figure 1—figure supplement 2E (anti-UCP1, anti-β-actin).
Figure 1—figure supplement 2—source data 2. PDF containing original scans of the relevant western blot analysis (anti-UCP1, anti-β-actin) with highlighted bands and sample labels.
Figure 1—figure supplement 3. Intermittent fasting demonstrates no effect on the number of type 3 innate lymphoid cells (ILC3s) in subcutaneous white adipose tissue (sWAT).

Figure 1—figure supplement 3.

(A) Gating strategy for flow cytometry analysis of live lineage-CD127+RORγt+ILC3s in the stromal vascular fraction (SVF) of sWAT. (B) Flow cytometric analysis of RORγt+ ILC3s in live CD127+ lineage- ILCs from the sWAT of normal chow diet (NCD) mice, NCD intermittent fasting (NCD-IF) mice. n=5. (C) Gating strategy for flow cytometry analysis of IL-22+ cells in live CD45+lineage-CD90.2+RORγt+ILC3s in the SVF of sWAT. All data represent the mean ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test.
Figure 1—figure supplement 4. Short-term intermittent fasting induces intestinal type 3 innate lymphoid cells (ILC3s) to secrete interleukin-22 (IL-22).

Figure 1—figure supplement 4.

Eight-week-old SPF mice were exposed to one cycle of intermittent fasting for 2days (IF-short), while the control group (normal chow diet [NCD]) has free access to NCD. n=6. (A) Body weight of NCD and IF-short mice. n=6. (B) qPCR analysis of thermogenic genes in subcutaneous white adipose tissue (sWAT) from NCD and IF-short mice. n=6mice/group. (C) Flow cytometric analysis of RORγt+ ILC3s in live CD127+ lineage- ILCs in the small intestine lamina propria of NCD or IF-short mice. Flow cytometric analysis of IL-22+ cells in live CD127+ lineage- RORγt+ ILC3s from the small intestine lamina propria of NCD or IF-short mice. Four independent experiments were performed with similar results. n=4. All data represent the mean ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test.

To explore whether gut immune system contributes to the effects of intermittent fasting on white adipose tissue beigeing, we examined levels of various cytokines in intestine. Notably, mRNA level of Il22 in the NCD-IF group was significantly higher relevant to the control group (Figure 1B). Consistently, plasma concentration of IL-22 detected by enzyme-linked immunosorbent assay (ELISA) was also increased (Figure 1C). These results suggest that intermittent fasting increases levels of IL-22 in the intestine and plasma. Since ILC3s are the main source of IL-22 in the small intestine (Seillet et al., 2020; Victor et al., 2017; Gronke et al., 2019), we detected the proportion of ILC3s in the lamina propria of small intestine using flow cytometry. In mice fed NCD, intermittent fasting significantly increased proportion of IL-22 positive ILC3s in the small intestine lamina propria (siLP) (Figure 1D), while demonstrating no effect on the percentile of total ILC3s (Figure 1E). Interestingly, intermittent fasting did not influence the secretion of IL-22 of T cells marked as lineage+ Rorγt+ cells (Figure 1F). Besides, intermittent fasting didn’t alter the levels of ILC3s and IL-22 in mouse adipose tissue (Figure 1G and Figure 1—figure supplement 3). Similar to NCD mice, intermittent fasting significantly increased mRNA levels of IL-22 in the intestine of HFD mice while didn’t influence the secretion of IL-22 by T cells (Figure 1H and I). Furthermore, mice fed HFD showed an obvious reduction in the plasma IL-22 (Figure 1J) and percentage of total and IL-22 positive ILC3s (Figure 1K). Further, the decrement of plasma IL-22 (Figure 1J) as well as IL-22 positive ILCs in intestine (Figure 1K) was attenuated by 30 days’ intermittent fasting.

In order to explain the chronological relationship between ILC3s secreting IL-22 and beigeing of white adipose tissue, the mice were exposed to one cycle of intermittent fasting for 2 days. At this time, the body weight of mice didn’t change and beige adipocytes haven’t been induced (Figure 1—figure supplement 4A and B). However, significant increase in proportion of IL-22 positive ILC3s was induced by intermittent fasting for 2 days whereas total percentile of ILC3s remained unaltered (Figure 1—figure supplement 4C). These results indicate that the beiging of white adipose tissue are subsequent to its effect on ILC3s secreting IL-22.

Intestinal ILC3s promote beigeing of white adipose tissue

Next, we examined whether adoptive transfer of intestinal ILC3s can increase beigeing of white adipose tissue in DIO mice. Intestinal ILC3s were isolated and purified from the siLP of NCD mice (Figure 2—figure supplement 1A). These cells were defined as lineage-CD127+KLRG1-c-Kit+ cells (Figure 2—figure supplement 1B). As shown in Figure 2A, DIO mice transferred with ILC3s demonstrated a significant increment in the proportion of small intestinal ILC3s. Previous researches report that intestinal ILC3s specifically express gut homing receptors CCR7, CCR9, and α4β7 (Kim et al., 2015; Mackley et al., 2015; Yu et al., 2021), which may explain transplantation of intestinal ILC3s can migrate mainly to the intestine instead of adipose tissue. Plasma concentration of IL-22 also increased significantly relevant to phosphate-buffered saline (PBS) control (Figure 2B). Relevant to PBS control, adoptive transfer of intestinal ILC3s decreased body weight and weight of sWAT (subcutaneous white adipose tissue) slightly, while had no impact on food intake and the liver weight (Figure 2—figure supplement 1C–E). In addition, ILC3s from CD45.1 mouse intestinal lamina propria lymphocytes were adoptively transferred into recipient mice, and CD45.1 positive immune cells were significantly increased in intestine but not in adipose tissue in mice transferred with ILC3s (Figure 2—figure supplement 1F), indicating the feasibility of ILC3s adoptive transfer. Notably, DIO mice transferred with intestinal ILC3s showed improved glucose tolerance (Figure 2C) and decreased levels of random blood glucose (Figure 2D). Cold exposure experiment showed that DIO mice transferred with intestinal ILC3s maintained significantly higher rectal temperatures during a 6 hr cold challenge (Figure 2E). Consistently, key thermogenic genes in sWAT including Ucp1 and Cidea were significantly increased (Figure 2F). Size of adipocytes in the sWAT and eWAT was markedly reduced (Figure 2G and H). Furthermore, differentiated stromal vascular fraction (SVF) cells co-cultured with intestinal ILC3s in vitro (Figure 2I) demonstrated a significant increment in the expression of Ucp1 and Pparg (Figure 2J), as well as a concurrent decrement in the size of lipid droplets (Figure 2K). On the other hand, co-culture with CD127- cells demonstrated no effect (Figure 2J and K). The in vitro experiment indicates the direct effect of ILC3s on adipocytes.

Figure 2. Type 3 innate lymphoid cells (ILC3s) promote beigeing of white adipose tissue.

Six-week-old male C57BL/6J SPF wild-type mice were fed with high-fat diet (HFD) for 16weeks and then injected with ILC3s (HFD + ILC3s group) or phosphate-buffered saline (PBS) (HFD+PBS group) intravenously six times in a month. n=8 for each group. (A) Flow cytometric analysis of RORγt+ ILC3s in live CD127+ lineage- ILCs from the small intestine lamina propria (siLP) of mice transferred with PBS or ILC3s. The proportion of ILC3s in ILCs was shown in the histogram. n=5 for each group. (B) Levels of interleukin-22 (IL-22) in plasma. n=8 for each group. (C) Oral glucose tolerance test (OGTT) and area under the curve (AUC). n=6mice/group. (D) Random blood glucose. n=6mice/group. (E) Rectal temperature of HFD mice transferred with PBS or ILC3s during a 6hr cold challenge (4°C). n=6mice/group. (F) qPCR analysis of thermogenic genes in subcutaneous white adipose tissue (sWAT). n=6mice/group. (G) Representative images of hematoxylin-and-eosin-stained sections of sWAT, epididymal white adipose tissue (eWAT), and BAT from HFD mice transferred with ILC3s or control (n=5). (H) Distribution and average adipocyte size of sWAT and eWAT were shown (n=5). (I) Schematic depicting the co-culture of ILC3s with stromal vascular fraction (SVF)-derived beige adipocytes. (J) qPCR analysis of thermogenic genes in SVF-derived cells. * indicates p<0.05vs control, # denotes p<0.05vs beige. n=3. (K) Oil red O staining of adipocytes after co-culture with ILC3s or CD127- cells. All data represent the means ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test (A–H) or one-way ANOVA (J).

Figure 2.

Figure 2—figure supplement 1. Adoptive transfer of type 3 innate lymphoid cells (ILC3s) has no effect on the body weight in mice fed high-fat diet (HFD).

Figure 2—figure supplement 1.

(A) Timeline for the recipient mice transferred with phosphate-buffered saline (PBS) or ILC3s. Mice were fed with HFD for 16weeks and then injected with ILC3s intravenously six times in a month. (B) Gating strategy for flow sorting of live CD127+ lineage- c-kit+ KLRG1-ILC3s in the small intestine lamina propria (siLP). (C) Body weight of HFD mice transferred with ILC3s or control. n=6 per group. (D) Food intake of HFD mice transferred with ILC3s or control. n=6 per group. (E) Tissue weight of subcutaneous white adipose tissue (sWAT), epididymal white adipose tissue.(eWAT), BAT, and liver from HFD mice transferred with ILC3s or control. n=6 per group. (F) Transfer of ILC3s from CD45.1 mice to wild-type (WT) mice. The percentage of CD45.1+ cells in ILCs in the small intestine and stromal vascular fraction (SVF). n=4–6. All data represent the mean ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test.

Exogenous IL-22 increases beigeing of white adipose tissue

The role of type 3 immunity in DIO and metabolic syndrome is complex. ILC3-derived IL-22 are beneficial in metabolic syndrome (Wang et al., 2014; Zou et al., 2018) but can also contribute to metabolic disease (Sasaki et al., 2019; Upadhyay et al., 2012; Wang et al., 2017). In order to examine the role of promoting beigeing of white adipose tissue of IL-22 in the context of NCD and HFD mice, we intraperitoneally administrated IL-22 at the dose of 4µg/kg body weight/every other day for 6weeks into mice fed NCD or HFD. Saline was used as control. Administration of IL-22 increased its plasma concentration in mice fed either NCD or HFD (Figure 3—figure supplement 1A). Exogenous IL-22 significantly increased oxygen consumption, carbon dioxide production, and energy expenditure in mice fed either NCD or HFD (Figure 3A–F). RQ was significantly reduced in mice fed NCD at dark and mice fed HFD at light (Figure 3G and H). No significant difference was observed for animal activity (Figure 3—figure supplement 1). In addition, exogenous IL-22 significantly improved glucose tolerance in mice fed HFD (Figure 4A). Interestingly, body weight and food intake were not altered (Figure 3—figure supplement 1), indicating that the metabolic benefit of IL-22 is not dependent on food intake. Consistent with previous research, IL-22 administration improves insulin sensitivity without change in body weight (Qi et al., 2019). In addition, IL-22 can increase Akt phosphorylation in muscle, liver, and adipose tissues, leading to improvement in insulin sensitivity (Wang et al., 2014).

Figure 3. Interleukin-22 (IL-22) promotes energy expenditure.

Six-week-old male C57BL/6J SPF wild-type mice were fed normal chow diet (NCD) or high-fat diet (HFD) for 12 weeks and then divided into four groups (NCD-saline, NCD-IL-22, HFD-saline, HFD-IL-22). Mice were intraperitoneally injected with 4 µg/kg IL-22 every other day for 6 weeks. The control groups were injected with saline. (A) VO2 of mice fed NCD or HFD. (B) Average VO2 at light and dark respectively. (C) VCO2 of mice fed NCD or HFD. (D) Average VCO2 at light and dark respectively. (E) Energy expenditure of mice fed NCD or HFD. (F) Average energy expenditure at light and dark respectively. (G) Respiratory quotient (RQ) of mice fed NCD or HFD. (H) Average RQ at light and dark respectively. * indicates p<0.05 vs NCD-saline or HFD-saline at light. # indicates p<0.05 vs NCD-saline or HFD-saline at dark. n = 5. Statistical significance was determined by one-way ANOVA (B, D, F, H).

Figure 3.

Figure 3—figure supplement 1. Exogenous interleukin-22 (IL-22) has no effect on the body weight of mice.

Figure 3—figure supplement 1.

(A) Levels of IL-22 in plasma of NCD-saline, NCD-IL-22, HFD-saline, HFD-IL-22 mice. n=6 mice/group. # vs HFD-saline. (B) Activity of mice fed NCD or HFD which were intraperitoneally injected with IL-22 or saline. n=5 for each group. (C) Body weight of NCD and HFD mice intraperitoneally injected with IL-22 or saline. n=6 for each group. (D) Daily food intake of NCD and HFD mice intraperitoneally injected with IL-22 or saline. n=6 for each group. All data represent the mean ± s.e.m. Statistical significance was determined by one-way ANOVA (A) or unpaired two-tailed Student’s t test (C, D). NCD, normal chow diet; HCD, high-fat diet.

Figure 4. Interleukin-22 (IL-22) promotes beigeing of white adipose tissue.

Six-week-old male C57BL/6J SPF wild-type mice were fed normal chow diet (NCD) or high-fat diet (HFD) for 12weeks and then divided into four groups (NCD-saline, NCD-IL-22, HFD-saline, HFD-IL-22). Mice were intraperitoneally injected with 4µg/kg IL-22 every other day for 6weeks. The saline group was injected with saline. n=6mice/group. (A) Oral glucose tolerance test (OGTT) and area under the curve (AUC). n=6mice/group. * indicates p<0.05vs NCD-saline; # denotes p<0.05vs HFD-saline. (B) Rectal temperature of mice during a 6hr cold challenge (4°C). n=6. * indicates p<0.05vs NCD-saline; # denotes p<0.05vs HFD-saline. (C) Representative image of sWAT of the four groups, NCD-saline, NCD-IL-22, HFD-saline, HFD-IL-22. (D) qPCR analysis of thermogenic genes of sWAT. n=6mice/group. * indicates p<0.05vs NCD-saline; # denotes p<0.05vs HFD-saline. (E) Representative images of hematoxylin-and-eosin-stained sections of sWAT and eWAT (n=5 for each group). (F) The distribution and average adipocyte size of sWAT and eWAT were determined by ImageJ. (G) Phase-contrast microscopic images of stromal vascular fraction (SVF) cells and adipocytes. (H) qPCR analysis of thermogenic genes in SVF cells and beige adipocytes. n=3. # denotes p<0.05vs beige. (I) pSTAT3, STAT3, pMAPK, MAPK, GAPDH, UCP1, β-actin protein expression in the beige adipocytes or beige adipocytes treated with IL-22 detected by western blotting. GAPDH and β-actin was used as the loading control. All data represent the mean ± s.e.m. Statistical significance was determined by one-way ANOVA (A–D, H) or two-tailed Student’s t test (F). sWAT, subcutaneous white adipose tissue; eWAT, epididymal white adipose tissue.

Figure 4—source data 1. Original file for the western blot analysis in Figure 4I (anti-pSTAT3, anti-STAT3, anti-pMAPK, anti-MAPK, anti-GAPDH, anti-UCP1, anti-β-actin).
Figure 4—source data 2. PDF containing original scans of the relevant western blot analysis (anti-pSTAT3, anti-STAT3, anti-pMAPK, anti-MAPK, anti-GAPDH, anti-UCP1, anti-β-actin) with highlighted bands and sample labels.

Figure 4.

Figure 4—figure supplement 1. Interleukin-22 (IL-22) can directly act on adipocytes.

Figure 4—figure supplement 1.

(A) qPCR analysis of Il22ra1 genes in adipocytes or stromal vascular fraction (SVF) cells isolated from subcutaneous white adipose tissue (sWAT). n=4. * denotes p<0.05vs sWAT adipocytes. (B) qPCR analysis of adipogenic marker genes of SVF cells and adipocytes. n=3. (C) Relative protein signal intensity quantified using ImageJ software. All data represent the mean ± s.e.m. Statistical significance was determined by one-way ANOVA (B) or unpaired two-tailed Student’s t test (A, C).

We next explored the effect of exogenous IL-22 on thermogenesis induced by 4°C cold exposure. Exogenous IL-22 rendered mice fed HFD resistant to core temperature drop induced by cold exposure (Figure 4B). Relevant to the pale yellow color in the control animals, subcutaneous fat of obese mice treated with exogenous IL-22 appeared dark yellowish (Figure 4C). The mRNA levels of thermogenic genes such as Ucp1 were significantly increased by IL-22 (Figure 4D). Adipocyte size of subcutaneous adipose tissue and epididymal adipose tissue was significantly reduced in the animals treated with IL-22 (Figure 4E and F). These observations suggest that intraperitoneal injection of IL-22 promotes the beigeing of white adipose tissue in mice.

To determine whether IL-22 can directly act on adipocytes to promote their beigeing, adipose tissue SVF was isolated and induced for beige differentiation. Il22ra1 mainly expressed on mature adipocytes (Figure 4—figure supplement 1A). IL-22 at the dose of 100 ng/mL was continuously administered during beige differentiation. IL-22 significantly increased SVF beige differentiation evidenced by cell morphology, increment in mRNA levels of genes relevant to thermogenesis, including Ucp1 and Cidea, and protein level of UCP1 (Figure 4G–I). IL-22 did not alter the levels of genes related to adipogenesis (Figure 4—figure supplement 1B). As expected, IL-22 increased the phosphorylation of STAT3 and MAPK (Figure 4I, Figure 4—figure supplement 1C), which can increase the expression of thermogenic genes (Li et al., 2021; Zhang et al., 2016). These results suggest that IL-22 can directly stimulate beigeing of white adipose tissue.

IL-22RKO blocks beigeing induced by intermittent fasting

To explore whether IL-22R mediates the effect of intermittent fasting on the beigeing of white adipose tissue, IL-22R knockout (IL-22RKO) mice and wild-type (WT) littermates were subjected to alternate day fasting diet for 30 days. Rectal temperature of WT-IF and IL-22RKO-IF mice was monitored during 2 consecutive days of intermittent fasting. On the fasting day, the rectal temperature of IL-22RKO-IF mice was significantly lower than that of WT-IF mice at 16:00 time point (Figure 5A). On the feeding day, the rectal temperature of IL-22RKO-IF mice was lower at three time points: 8:00, 12:00, and 20:00 (Figure 5B). These results indicate that IL-22RKO attenuates the thermogenesis induced by intermittent fasting. Knockout of IL-22R demonstrated no effect on the glucose tolerance and insulin sensitivity in mice fed NCD (Figure 5C and D). However, the weight of subcutaneous adipose tissue in IL-22RKO-IF mice increased significantly (Figure 5E). mRNA levels of the thermogenic gene Ucp1 decreased substantially, whereas Fabp4 increased (Figure 5F). Furthermore, knockout of IL-22R significantly attenuated the increment of multilocular lipid droplets and the decrement of adipocyte size in the subcutaneous fat induced by intermittent fasting (Figure 5G and H), indicating a reduction in beigeing.

Figure 5. Interleukin-22R knockout (IL-22RKO) blocks white adipose tissue beigeing induced by intermittent fasting.

Figure 5.

Eight-week-old IL-22RKO and wild-type (WT) mice were subjected to alternate day fasting for 30days. n=6mice per group. (A) Rectal temperature of mice at room temperature during the fasting day. n=6 per group. (B) Rectal temperature of mice at room temperature during the fed day. n=6 per group. (C) Oral glucose tolerance test (OGTT) of WT-IF mice and IL-22RKO-IF mice. n=6 per group. (D) Insulin tolerance test (ITT) of WT-IF mice and IL-22RKO-IF mice. n=6 per group. (E) Tissue weight of subcutaneous white adipose tissue (sWAT), epididymal white adipose tissue (eWAT), BAT, and liver from WT-IF and IL-22RKO-IF mice. n=6mice/group. (F) qPCR analysis of thermogenic genes in sWAT from WT-IF and IL-22RKO-IF mice. n=6mice/group. (G) Representative images of hematoxylin-and-eosin-stained sections of sWAT, eWAT, and BAT (n=5 for each group). (H) The distribution and average adipocyte size of sWAT and eWAT were determined by ImageJ. (I) Schematic depicting the co-culture of type 3 innate lymphoid cells (ILC3s) with stromal vascular fraction (SVF)-induced beige adipocytes from WT or IL-22RKO mice. n=3. Experiments were repeated three times. (J) Phase-contrast microscopy images of beige adipocytes differentiated from SVF cells co-cultured with or without ILC3s. Shown are representatives from one experiment. (K) qPCR analysis of thermogenic genes in SVF-derived cells co-cultured with or without ILC3s. n=3. All data represent the means  ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test (A–H) or one-way ANOVA (K).

To further explore whether IL-22R mediates the effect of ILC3s on beigeing of adipocytes, intestinal ILC3s isolated from intermittent fasting mice were co-cultured with beige adipocytes from subcutaneous SVF of WT or IL-22RKO mice (Figure 5I and J). Co-culture with ILC3s significantly increased the mRNA levels of thermogenic genes in beige adipocytes derived from WT mice, while demonstrating no effect on beige adipocytes derived from IL-22RKO mice (Figure 5K). These observations indicate that IL-22R mediates the effect of intestinal ILC3s on beigeing of white adipocytes.

Profiling of intestinal immune cells in mice fed NCD, HFD, or HFD-IF

To explore the mechanism by which intermittent fasting promotes the secretion of IL-22 by ILC3s, live CD45+ lineage (CD3, CD5, B220, CD19, Gr1)- cells isolated from the siLP of mice fed NCD, HFD, or HFD-IF were subjected for single-cell sequencing (Figure 6—figure supplement 1A). Following quality controls, we analyzed 7455, 4803, 5954 single cells for the NCD, HFD, and HFD-IF groups using Seurat-V3.1, respectively. Based on singleR, we identified 25 distinct clusters of immune cells (Figure 6A and Figure 6—figure supplement 1B), including ILC1s (cluster 7 and cluster 16), ILC2s (cluster 2, cluster 12, cluster 13, and cluster 14), ILC3s (cluster 3 and cluster 5), DCs (cluster 1, cluster 4, cluster 9, cluster 10, cluster 11, cluster 17, cluster 18, and cluster 21), eosinophils (cluster 0 and cluster 6), B cells (cluster 8 and cluster 24), macrophages (cluster 15, cluster 20, and cluster 23), NKT cells (cluster 22) and mast cells (cluster 19). As expected, ILC3s expressed high RNA levels of Il7r (CD127), Rorc, and IL-22 (Figure 6B, C and Figure 6—figure supplement 1C, D). ILC3s contain two distinct cell types with highly similar expression profiles: NCR+ and NCR-. These ILC3s were distinguished in our analysis as cluster 5 and cluster 3 respectively. NCR- ILC3s (cluster 3) were CCR6 positive and contained lymphoid tissue inducer cells (Figure 6B). Interestingly, NCR- ILC3s were characterized by high levels of vasoactive intestinal peptide receptor 2 (Vipr2) (Figure 6C), which is critical for the migration and function of ILC3s (Seillet et al., 2020; Yu et al., 2021; Talbot et al., 2020). The heatmap of cellular composition showed the differences in cell number and percentage among NCD, HFD, and HFD IF mice (Figure 6—figure supplement 2A). The change in ILC3 number was consistent with the flow cytometry results. The percentage of IL-22+ cells in NCR+ ILC3s was significantly increased by IF in mice fed HFD (Figure 6—figure supplement 2B). Moreover, GSEA revealed that HFD-induced decrement of cytokine-cytokine receptor interaction, in which IL-22 is included, was reversed by IF (Figure 6—figure supplement 2C). Besides, neuroactive ligand-receptor interaction, in which vipr2 is included, was upregulated in HFD-IF (Figure 6—figure supplement 2). The mRNA levels of Vipr2 had a tendency to increase in sorted ILC3s from the small intestine of HFD-IF mice compared with that of HFD mice (Figure 6—figure supplement 2E). Further, gene difference analysis revealed that HFD-induced increase of Zmat4 was significantly attenuated by IF (Figure 6D, Figure 6—figure supplement 2F, G).

Figure 6. Profiling of intestinal immune cells derived from mice fed normal chow diet (NCD), high-fat diet (HFD), and high-fat diet with intermittent fasting (HFD-IF).

Live CD45+ lineage-cells sorted from mice fed normal chow diet (NCD group), high-fat diet (HFD group), high-fat diet with alternate day fasting (HFD-IF group) were analyzed using single-cell sequencing. (A) Cell subsets in the small intestine lamina propria CD45+ lineage- immune cell atlas. Two-dimensional (2D) representation of cell profiles (dots) from the small intestine lamina propria, colored and numbered by cluster membership. (B and C) UMAP feature plots (B) and violin plots (C) showing RNA expression of cluster markers for the indicated cell populations. UMAP feature plots are based on the UMAP shown in (A). (D) The volcano plot of differentially expressed genes in cluster 5 (NCR+ type 3 innate lymphoid cells [ILC3s]). The red dots represent upregulated genes in HFD-IF group compared with HFD group, while the blue dots represent downregulated genes in HFD-IF group compared with HFD group. Hsp90ab1 is one of the notably upregulated genes. (E) Transcription factor prediction using the Jaspar database and TFBS tools. Red dots represent differentially expressed genes, purple dots represent transcription factors, and larger nodes represent more nodes connected to them. (F) Gene ontology (GO) of the top 20 differentially expressed genes in cluster 5. The cellular component up GO terms in HFD-IF group compared with HFD group. (G) The reactome up terms of cluster 5 top 20 differential genes in HFD-IF group compared with HFD group. (H) qPCR analysis of AHR target genes in ILC3s sorted from HFD and HFD-IF mice. n=4. *, p<0.05. All data represent the means ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test.

Figure 6.

Figure 6—figure supplement 1. Profiling of intestinal immune cells from mice fed normal chow diet (NCD), high-fat diet (HFD), or high-fat diet with intermittent fasting (HFD-IF).

Figure 6—figure supplement 1.

(A) Gating strategy for flow cytometry sorting of live CD45+ lineage- immune cells in the small intestine lamina propria. (B) scRNA-seq data quality control of sorted immune cells from mice fed NCD, HFD, or HFD-IF. (C) Unbiased heatmap of the gene levels of the top 20 unique cluster marker genes for each cell cluster. Cluster identities are shown above the heatmap. (D) Violin plots showing RNA expression of cluster markers for the indicated cell populations. UMAP feature plots are based on the UMAP shown in Figure 6A.
Figure 6—figure supplement 2. Effects of intermittent fasting on the gene expression of type 3 innate lymphoid cells (ILC3s).

Figure 6—figure supplement 2.

(A) Number and proportion of cells detected in each group in the study. Shown are fraction (color bar, out of all cells from that group) and number of cells from each of the 25cell clusters (rows) in each individual group (columns). (B) Percentage of IL-22+ cells defined by the mRNA levels using Loupe Browser 5.0 of NCR+ ILC3s in normal chow diet (NCD), high-fat diet (HFD), and high-fat diet with intermittent fasting (HFD-IF) mice. (C) GSEA demonstrating enrichment of cytokine-cytokine receptor interaction pathway genes upregulated by intermittent fasting (HFD-IF mice) vs. control (HFD mice) in NCR+ ILC3s. (D) GSEA demonstrating enrichment of neuroactive ligand-receptor interaction pathway genes upregulated by intermittent fasting (HFD-IF mice) vs. control (HFD mice) in NCR+ ILC3s. (E) qPCR analysis of Vipr2 in ILC3s sorted from small intestine lamina propria (siLP) of HFD or HFD-IF mice. (F) UMAP feature plots showing RNA expression of Zmat4 based on the UMAP shown in Figure 6B. (G) Violin plots showing RNA expression of Zmat4 in NCR-ILC3s (cluster 3) and NCR+ILC3s (cluster 5). (H) UMAP feature plots showing RNA expression of Hsp90ab1 based on the UMAP shown in Figure 6B.

Further, the expression level of Hsp90ab1 in both NCR- ILC3s and NCR+ was significantly increased by IF in mice fed HFD (Figure 6D, Figure 6—figure supplement 2H). Transcription factor analysis using the JASPAR database and TFBS Tools revealed that the expression of Hsp90ab1 may be regulated by aryl hydrocarbon receptor (AHR) (Figure 6D). AHR is located in the Hsp90:XAP2:p23:Src chaperone protein complex in the cytoplasm without stimulation. Upon binding with the ligand, AhR translocates to the nucleus and heterodimerizes with AhR nuclear translocator to control the transcription of target genes, including AhR repressor (Ahrr), Cyp1a1, Cyp1b1, and Il22 (Stockinger et al., 2014). Consistently, gene ontology analysis of the top 20 increased difference genes revealed that AHR signaling was one of the key pathways affected by intermittent fasting in HFD mice (Figure 6E and F). Furthermore, the AHR target genes, including Il22, Ahrr, Cyp1a1, Cyp1b1, increased significantly in ILC3s sorted from HFD-IF mice compared with HFD mice. These results indicate that intermittent fasting increases the production of IL-22 likely via activation of AhR.

IF ameliorates the impaired interaction between intestinal myeloid cells and ILC3s

Because DCs can influence the production of IL-22 by ILC3s, we next analyzed the change in DCs induced by intermittent fasting. IF significantly attenuated the increment of inflammatory factors, such as Ccl4, Ccl17, and Ccl22, of DCs in mice fed HFD (Figure 7A). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the top 20 differentially expressed genes in cluster 17 revealed that the increase of inflammation-related pathways induced by HFD was obviously attenuated by IF (Figure 7B and C). These observations indicate that intermittent fasting may ameliorate the inflammatory state of the intestine by decreasing the NOD-like receptor signaling pathway in DCs (Figure 7B and C).

Figure 7. Interaction between myeloid cells and type 3 innate lymphoid cells (ILC3s).

(A) Violin plots showing the RNA expression of chemokines in CD8- dendritic cells (DCs) (cluster 11 and cluster 17). (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment in upregulated genes of CD8-DCs of high-fat diet (HFD) group compared with normal chow diet (NCD) group (cluster 17). (C) KEGG enrichment of downregulated genes of CD8-DCs of high-fat diet with intermittent fasting (HFD-IF) group compared with HFD group (cluster 17). (D) Heatmap showing the number of significant interactions identified between cell types in sorted small intestine lamina propria (siLP) immune cells of HFD mice as determined by CellPhoneDB. The color represents the number of interactions between cell types, a higher number of interactions (red), and a lower number of interactions (blue). (E) Heatmap showing the number of significant interactions identified between cell types in sorted siLP immune cells of HFD-IF mice as determined by CellPhoneDB. The color represents the number of interactions between cell types: a higher number of interactions (red) and a lower number of interactions (blue). (F) Interaction pattern of the top 20 protein pairs and the top 20cell types in sorted siLP immune cells of HFD group mice. The x-axis is the cell-type interaction, and the y-axis is the protein interaction. The larger the point is, the smaller the p value. The color represents the average expression, and red to black indicates the level from high to low. (G) Interaction pattern of the top 20 protein pairs and the top 20cell types in sorted siLP immune cells of HFD-IF mice. The x-axis is the cell-type interaction, and the y-axis is the protein interaction. The larger the point is, the smaller the p value. The color represents the average expression, and red to black indicates the level from high to low.

Figure 7.

Figure 7—figure supplement 1. Cell-cell interactions in the intestine.

Figure 7—figure supplement 1.

(A) Connectome web analysis of intestine immune cell interacting cell types based on the expression of the ligand in mice fed normal chow diet (NCD). The vertex (colored cell node) represents the cell cluster. The thickness of the connecting lines is proportional to the number of interactions between the nodes. (B) Connectome web analysis of NCR+ type 3 innate lymphoid cells (ILC3s) with the 25cell clusters based on expression of the ligand. The vertex (colored cell node) represents the cell cluster, while the thickness of the connecting lines is proportional to the number of interactions between two nodes. (C) Heatmap showing the number of significant interactions identified between cell types in sorted small intestine lamina propria (siLP) immune cells of NCD mice as determined by CellPhoneDB. The color represents the number of interactions between cell types: a higher number of interactions (red) and a lower number of interactions (blue). (D) Interaction pattern of the top 20 protein pairs and the top 20cell types. The x-axis is the cell type interaction, and the y-axis is the protein interaction. The larger the point is, the smaller the p value. The color represents the average expression. Red to black indicates the level from high to low.
Figure 7—figure supplement 2. Increased expression of CD44 and CCl4 in macrophages.

Figure 7—figure supplement 2.

Flow cytometry-sorted macrophages and type 3 innate lymphoid cells (ILC3s) from high-fat diet (HFD) and high-fat diet with intermittent fasting (HFD-IF) mice were used to detect the mRNA levels of proteins involved in the interaction of macrophages and ILC3s. (A) Gating strategy for flow sorting of macrophages in the small intestine lamina propria (siLP). qPCR analysis of Il22, Gata3, and Rorc in ILC2s and ILC3s. n=3/group. (B) mRNA levels of proteins involved in the interaction and Il23 in macrophages. n=3/group. (C) mRNA levels of proteins involved in the interaction in ILC3s. n=3/group. All data represent the mean ± s.e.m. Statistical significance was determined by unpaired two-tailed Student’s t test.

We next analyzed the intestinal cellular communication networks using CellPhoneDB analysis based on homologous gene transformation on all immune cells acquired. CellPhoneDB ligand-receptor analysis revealed hundreds of immune-to-immune interactions (Figure 7—figure supplement 1A). Connectome web analysis of siLP immune cells revealed strong interactions among CD8+ DCs (cluster 4), CD127+ ILC1s (cluster 16), DC8- DC-1 (cluster 9), macrophages-1 (cluster 15), CD8- DC-2 (cluster 1), macrophages-2 (cluster 23), CD8- DC-3 (cluster 10), CD8- DC-4 (cluster 11), and CD8- DC-5 (cluster 17). Notably, NCR+ ILC3s strongly interacted with CD8+ DCs (cluster 4), CD127+ ILC1 s (cluster 16), DC8- DC (cluster 9), macrophages (cluster 15), CD8- DC (cluster 1), macrophages (cluster 23), CD8- DC (cluster 10), CD8- DC (cluster 11), and CD8- DC (cluster 17). ILC subsets, DCs, and macrophages were in the central communication hubs of the healthy small intestine (Figure 7—figure supplement 1B and C). Analysis of highly expressed interactions uncovered various uncharacterized and validated signaling pathways implicated in intestine homeostasis in mice (Figure 7—figure supplement 1D). Analysis of the NCD mouse interactome suggests that macrophages (cluster 15) may interact with NCR+ ILC3s through CD74_COPA, CD74_MIF, CD44_HBEGF, CD44_FGFR2, CCL4_SLC7A1, and IL1B_ADRB2. Similarly, DCs (cluster 9) may interact with NCR+ILC3s through CD74_COPA, CD74_MIF, IL1B_ADRB2, CD44_HBEGF, and CD44_FGFR2. All these observations indicate that macrophages and DCs play critical roles in the recruitment and maintenance of ILC3s.

HFD significantly reduced the interaction between ILC subsets, DCs, and macrophages in the small intestine (Figure 7D and Figure 7—figure supplement 1B). This reduction was reversed by IF (Figure 7E and Figure 7—figure supplement 1B). Analysis of the interactomes in mice fed HFD suggested that IF significantly altered the interacting proteins (Figure 7F and G). To further test this observation, we sorted macrophages and ILC3s from HFD and HFD-IF mice (Figure 7—figure supplement 2). As shown in Figure 7—figure supplement 2B and C, Ccl4 and Cd74 increased significantly in macrophages, while the receptors expressed on ILC3s remained largely unchanged (Figure 7—figure supplement 2). Together, these data suggest that IF may promote the production of IL-22 from ILC3s by altering the interactome in intestinal myeloid cells and ILC3s.

Discussion

Our present study demonstrates that intestinal ILC3s are critical for the beigeing of white adipose tissue induced by intermittent fasting. This conclusion is supported by following observations. First, intermittent fasting stimulates the secretion of IL-22 by intestinal ILC3s in either lean mice fed NCD, obese mice fed HFD, or mice with metabolic dysfunction induced by HFCD diet. Second, a comprehensive set of in vivo and in vitro experiments shows that intermittent fasting promotes adipose tissue beigeing through the intestinal ILC3-IL-22-IL-22R axis.

The role of ILC3s in metabolism remains largely unknown. Our studies provide evidence supporting the metabolic benefit of intestinal ILC3s in intermittent fasting. Adoptive transfer of intestinal ILC3s isolated from lean mice was sufficient to improve the metabolic dysfunctions in DIO mice, including increase of white adipose tissue beigeing and glucose tolerance. Interestingly, adoptive transfer of ILC3s significantly increased their number only in intestine. Further, alternate day fasting did not alter the ILC3s in adipose tissue. These observations indicate that ILC3s in intestine rather than in adipose tissue account for the metabolic benefit. In addition to directly promoting the beigeing of white adipose tissue through IL-22, intestinal ILC3s may enhance the intestinal mucosal barrier (Ibiza et al., 2016), reducing serum LPS and peptidoglycan, thus reducing the inhibitory effect of LPS and peptidoglycan on the beigeing of white adipose tissue (Chen et al., 2022). O’Sullivan et al., 2016, have reported that ILC3s are negligible in white adipose tissue of either lean or obese mice. Similarly, Sasaki et al., 2019, have demonstrated that transplanting bone marrow cells from Rag2-/- mice (lack of T cells, B cells) into Il2rg-/- Rag2-/- mice (lack of T cells, B cells, ILC cells) could not increase the number of ILC3s in the adipose tissue of recipient mice. However, it is worth noting that ILC3s have been detected in adipose tissue by other report. Using the marker lineage-KLRG1-Il-7rα+Thy-1+, ILC3s cells have been reported to account for approximately 20% of lineage-KLRG1-Il-7rα+ cells in adipose tissue. In our study, we also detected ILC3s defined as CD127+Lin-RORγt+ in adipose tissue. These ILC3s accounted for approximately 10% of CD127+Lin- cells. ILC3s have also been shown to be present in human adipose tissue (Hildreth et al., 2021). Importantly, the proportion and density of ILC3s in white adipose tissue of people with obesity increase relevant to healthy people, and positively correlate with BMI in obese patients. Thus, the existence and function of ILC3s in mouse and human adipose tissue deserve further investigation.

Communication between intestine and metabolic organs is currently under active investigation. Our studies identify ILC3s-IL-22-IL-22R as a novel pathway mediating the crosstalk between intestine and adipose tissue. Evidence supporting this conclusion are five folds. (1) Intermittent fasting reverses the reduction of intestinal ILC3s and IL-22 in DIO mice. (2) Adoptive transfer of intestinal ILC3s enhances beigeing of white adipose tissue. (3) Co-culture of intestinal ILC3s with SVF cells increases their differentiation into beige cells. (4) Exogenous IL-22 mimics the effect of intermittent fasting on beigeing of white adipose tissue. (5) Deficiency of IL-22R blocks the IF-induced beigeing of white adipose tissue. In lines with our observation, a series of recent studies have suggested that cytokines can act directly on adipocytes to regulate thermogenesis. For example, γδ T cells regulate heat production by secreting IL-17 (Hu et al., 2020). Deficiency of IL-10 increases energy consumption and renders mice resistant to DIO (Yu et al., 2021). IL-27-IL-27Rα signaling promotes thermogenesis, prevents DIO, and improves insulin resistance (Wang et al., 2021a). IL-33 induces the beigeing of white adipose tissue by activating ILC2s (Brestoff et al., 2015). Our studies extend the effect of cytokines on thermogenesis to IL-22. IL-22 promotes heat production, renders mice resistant to reduction of body temperature induced by cold exposure, and reduces obesity induced by HFD. Together with previous report showing that IL-22 increases the lipolysis of adipocytes, our studies suggest that IL-22 can directly act on adipocytes to alter the adipose tissue homeostasis. IL-22 activates IL-22 receptor, which then regulates the expression of downstream inflammatory factors, tissue repair molecules, chemokines, antimicrobial peptides, and other molecules via Jak-1- and Tyk-2-dependent phosphorylation of STAT3. Our studies suggest that IL-22 may promote the expression of downstream thermogenic genes in adipose tissue through IL-22R. Deficiency of IL-22R blocks the upregulation of thermogenic genes induced by intermittent fasting. SVF cells lacking IL-22R demonstrate no response to the upregulation of thermogenic genes induced by intestinal ILC3. Thus, our results provide novel evidence supporting the concept that intestinal ILC3s modulate beigeing of adipose tissue via IL-22-IL-22R pathway.

The physiological mechanism underlying the secretion of IL-22 by ILC3s remains largely unknown. Our studies reveal the distinct secretion pattern of IL-22 induced by intermittent fasting. Consistently, previous studies have shown that secretion of IL-22 by ILC3s changes between active and quiescent periods throughout the day which is regulated by the cycle patterns of food intake (Brooks et al., 2021). These suggest that secretion of IL-22 by ILC3s is altered by feeding rhythm. It is currently unclear how feeding influences the physiological function of ILC3s. Previous studies indicate a mechanism involving neuropeptide vasoactive intestinal peptide (VIP), which is able to stimulate the secretion of IL-22 by ILC3s (Seillet et al., 2020). Consistently, our single-cell RNA-seq data also showed that VIPR2 is highly expressed in intestinal ILC3s and intermittent fasting activates VIPR2 signaling pathway. Since release of VIP is stimulated by food intake, these observations indicate that VIP-VIPR signaling may coordinate with food intake to drive the production of IL-22. However, conflicting result exists. Studies by Talbot et al., 2020 have shown that VIP inhibits ILC3 secretion of IL-22. Reasons accounting for this difference remains unknown but may be context dependent. Alternatively, we found that intermittent fasting may promote ILC3s secreting IL-22 though activating AhR signaling. In addition, feeding may decrease the levels of antimicrobial peptides secreted by epithelial cells, while increasing the expression of lipid-binding proteins (Talbot et al., 2020). Moreover, segmented filamentous bacteria may account for the effect of feeding on the secretion of IL-22 by intestinal ILC3s by periodically attaching to the epithelial surface (Brooks et al., 2021). These alterations may substantially influence the immune networks in intestine, leading to subsequent change in the secretion of IL-22 by ILC3s. In support of this concept, our single-cell RNA-seq analysis shows a significant change in the intestinal immune cell network involving DCs, macrophages, and ILC3s. Further examination should focus on dissecting the novel molecular mechanism by which intestinal DCs and macrophages interact with ILC3s and its consequence on the IL-22 production.

In conclusion, our studies suggest that intermittent fasting can promote the secretion of IL-22 by intestinal ILC3s. IL-22 promotes beigeing of white adipose tissue through IL-22R. Intestinal ILC3s thus may serve as a potential target for the intervention of metabolic disorders.

Materials and methods

Key resources table.

Reagent type (species) or resource Designation Source or reference Identifiers Additional information
Antibody PerCP/Cy5.5 anti-mouse CD45(30-F11) (Mouse Monoclonal) BioLegend Cat# 103131 FACS (1:400)
Antibody FITC anti-mouse CD3ε(RA3-6B2) (Rabbit Monoclonal) BioLegend Cat# 103205 FACS (1:400)
Antibody FITC anti-mouse/human CD45R/B220(RA3-6B2) (Rabbit Monoclonal) BioLegend Cat# 103205 FACS (1:400)
Antibody FITC anti-mouse Ly-6G/Ly-6C(Gr-1)(RB6-8C5) (Rabbit Monoclonal) BioLegend Cat# 108405 FACS (1:400)
Antibody FITC anti-mouse CD19(6D5) (Rabbit Monoclonal) BioLegend Cat# 115506 FACS (1:400)
Antibody FITC anti-mouse CD5(53–7.3) (Rabbit Monoclonal) BioLegend Cat# 100605 FACS (1:400)
Antibody BV421 anti-mouse CD127(IL-7Rα) (A7R34) (Rabbit Monoclonal) BioLegend Cat# 135023 FACS (1:400)
Antibody PE/Cyanine7 anti-mouse CD90.2(30-H12) (Rabbit Monoclonal) BioLegend Cat# 105325 FACS (1:400)
Antibody PE/Cyanine7 anti-mouse CD45.1 (Mouse Monoclonal) BioLegend Cat# 110729 FACS (1:400)
Antibody PE anti-mouse RORγt(Q31-378) (Mouse Monoclonal) BD Pharmingen Cat# 562607 FACS (1:400)
Antibody Alexa Fluor 647 anti-mouse IL-22(Poly5164) (Mouse Polyclonal) BioLegend Cat# 516406 FACS (1:400)
Antibody BV605 anti-mouse/human KLRG1(MAFA)(2F1/KLRG1) (Syrian Hamster Monoclonal) BioLegend Cat# 138419 FACS (1:400)
Antibody PE anti-mouse CD117(c-kit) (2B8) (Rabbit Monoclonal) BioLegend Cat# 105807 FACS (1:400)
Antibody Rb polyclonal antibody to UCP1 (Rabbit Polyclonal) abcam Cat# ab10983 WB (1:1000)
Antibody Phospho-Stat3 (Tyr705) Rabbit mAb (Rabbit Monoclonal) Cell Signaling Technology Cat# 9145 WB (1:1000)
Antibody Stat3 (124H6) Mouse mAb (Mouse Monoclonal) Cell Signaling Technology Cat# 9139 WB (1:1000)
Antibody Phospho-p38 MAPK (Thr180/Tyr182) (D3F9) XP Rabbit mAb (Rabbit Monoclonal) Cell Signaling Technology Cat# 4511 WB (1:1000)
Antibody p38 MAPK (D13E1) XP Rabbit mAb (Rabbit Monoclonal) Cell Signaling Technology Cat# 8690 WB (1:1000)
Antibody Rb polyclonal antibody to UCP1 (Rabbit Polyclonal) abcam Cat# ab10983 WB (1:1000)
Commercial assay or kit eBioscience Fixation/Perm Diluent Invitrogen Cat# 00-8333-56
Commercial assay or kit eBioscience Fixable Viability Dye eFluorTM 606 Invitrogen Cat# 65-0866-14 FACS (1:400)

Animals

Four-week-old male C57BL/6 and CD45.1 mice were obtained from Charles River Laboratories (Peking, China). IL-22RKO mice (KO-00115) were purchased from BRL Medicine Inc Mice were housed in standard rodent cages and maintained in a regulated environment (21–24°C, humidity at 40–70%, 12:12 hr light:dark cycle with lights on at 8:00 AM) at the Department of Experimental Animal Science, Peking University Health Science Center. An NCD (D12450H; Research Diets) and water were available ad libitum. Obese mice (DIO) were induced with an HFD (60% fat, D12492; Research Diets) for 12 weeks. Eight-week-old C57BL/6 mice received intraperitoneal injection of saline control or IL-22 (R&D Systems, 582-ML) at a dose of 4 μg/kg/day every other day for 6 weeks. All of the animal experiments complied with the protocols for animal use, treatment and euthanasia approved by Peking University (Permit Number: LA2017099).

Cell preparation

For isolation of siLP cells, small intestines from euthanized mice were emptied of the contents, excised of Peyer’s patches, opened longitudinally and cut into 1 cm pieces. The intraepithelial lymphocytes were dissociated from the intestine fragments by first shaking the fragments for 20 min at 37°C in PBS containing 0.3% BSA, 5 mM EDTA, and 1 mM dithiothreitol. Vortex the fragments three times with PBS containing 2 mM EDTA. To isolate lamina propria cells, the remaining fragments were minced and digested at 37°C for 50 min in RPMI 1640 medium containing 0.04 mg/mL collagenase IV (Sigma), 0.1 mg/mL deoxyribonuclease (DNase) I (Roche), and 0.5 mg/mL dispase. The digestion suspension was then filtered through a 40 μm cell strainer and centrifuged at 540×g for 6 min. Cell pellets were resuspended in PBS containing 2% fetal bovine serum (FBS) for further analysis.

Flow cytometry

Single-cell suspensions were preincubated with anti-CD16/32 (clone 2.4G2) for 10 min to block the surface Fc receptors. Then, cell-surface molecules were stained with different antibody combinations for 30 min in cell staining buffer. Dead cells were excluded with Fixable Viability Dye eFluor 606 (Invitrogen). For intracellular transcription factor staining, the cells were fixed and permeabilized with a Foxp3 staining buffer set (eBioscience) according to the manufacturer’s protocol. Transcription factor staining usually lasted for more than 4 hr at 4°C. The gate strategy for ILC3s was live lineage (CD3, CD5, CD19, B220, and Gr-1)- CD127+RORγt+. For intracellular cytokine staining, the digested cells were first incubated in RPMI 1640 with 10% FBS and 10 ng/mL recombinant murine IL-7 (PeproTech), and stimulated with 50 ng/mL phorbol 12-myristate 13-acetate, 750 ng/mL ionomycin for 3 hr and added with 2 μM monensin for the last 2.5 hr.

Flow cytometry analyses were performed on an LSR Fortessa (BD Biosciences). The flow cytometry data were analyzed with FlowJo software (Tree Star). The antibodies used in this study are listed in Key resources table.

ILC3s sorting, transfer, and co-culture experiment

For ILC3s transfer experiment, co-culture experiment, and single-cell RNA-seq, ILCs were collected by FACS. siLP cells from male C57BL/6J mice were prepared and stained with surface molecules for 30 min at 4°C followed by sorting on a FACS Aria III cell sorter (BD Biosciences). A gating strategy of live lineage-CD127+KLRG1-c-Kit+ was used to sort the ILC3s.

Purification checks were performed after each sort. The cells were suspended in PBS and then intravenously injected into HFD mice (200 μL PBS/mouse). ILC3s were sorted from 20 WT NCD mice, and sorting for the adoptive transfer was performed six times within 4 weeks from the first injection. The total number of ILC3 injected into HFD mice was 2.4×105 cells/mouse/experiment. Mice were placed on an HFD for 16 weeks before ILC3s were transferred. In addition, to confirm that these cells indeed originate from NCD mice, we transferred ILC3s from CD45.1 mice to WT mice and detected the CD45.1 positive cells in recipient mice.

Single-cell RNA-seq

Single cells were captured via the GemCode Single Cell Platform using the GemCode Gel Bead, Chip, and Library Kits (10x Genomics) according to the manufacturer’s protocol. Briefly, flow-sorted cells were suspended in PBS containing 0.4% BSA and loaded at 6000 cells per channel. The cells were then partitioned into a GemCode instrument, where individual cells were lysed and mixed with beads carrying unique barcodes in individual oil droplets. The products were subjected to reverse transcription, emulsion breaking, cDNA amplification, shearing, 5′ adaptor, and sample index attachment. Libraries were sequenced on a HiSeq 2500 (Illumina).

Isolation of SVF cells and induction of beigeing

Isolation of SVF and induction of beigeing were performed as reported (Aune et al., 2013). Briefly, sWAT from male C57BL/6 mice was digested with 1 mg/mL type 2 collagenase (Sigma-Aldrich) at 37°C for 40 min with shaking. Digestion was terminated by complete DMEM/F12 medium containing 10% FBS, 100 units/mL penicillin, and 100 units/mL streptomycin (Invitrogen, CA, USA). The cell suspension was centrifuged at 700×g for 10 min to separate floating adipocytes from the SVF pellets. The pellets containing the SVF cells were resuspended in complete medium and filtered using a 70 μm diameter filter. The cell suspension was then centrifuged at 700×g for 10 min. Cell pellets were resuspended and mixed well and then plated on dishes in complete medium. Cells were grown to 95% confluence in complete medium and then differentiated into beige or white adipocytes as previously described (Seale et al., 2011). Briefly, for induction to beige adipocytes, cells were cultured for 2 days with induction medium supplemented with 5 μg/mL insulin, 1 nmol/L T3, 1 μmol/L rosiglitazone, 125 μmol/L indomethacin, 0.5 mmol/L isobutylmethylxanthine, and 5 μmol/L dexamethasone. Cells were then cultured in maintenance medium supplemented with 5 μg/mL insulin, 1 nmol/L T3, and 1 μmol/L rosiglitazone for 4 days. Fresh media were replaced every 2 days.

Co-culture experiments

To determine the direct effect of ILC3s on beige adipocytes differentiation, SVFs were co-cultured with ILC3s using a transwell system (0.4 μm pore size, BD Biosciences). In brief, SVFs isolated from adipose tissue were grown in the bottom chamber of the transwell insert in a 12-well plate and induced into beige adipocytes, while sorted ILC3s were seeded in the upper chamber. SVFs cultured alone and SVF cells co-cultured with CD127- cells were used as controls. After co-culture for 72 hr, beige adipocytes in the lower chamber were collected for further detection.

RNA isolation and qPCR analysis

RNA was extracted from cells or adipose tissue using RNATrip (Applied Gene, Beijing, China) and reverse-transcribed into cDNAs with Hifair III 1st Strand cDNA Synthesis SuperMix (Yeasen). SYBR Green-based quantitative real-time PCR was performed using the Agilent Aria Mx real-time PCR system. The primer sequences used in this study are listed in Supplementary file 1.

Western blot analysis

Differentiated SVF cells and sWAT were homogenized using RIPA lysis buffer. Proteins were separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and then transferred onto a nitrocellulose membrane. Membranes were incubated in 5% fat-free milk for 1 hr at room temperature and then incubated with primary antibodies overnight at 4°C. The reaction was detected with IRDye-conjugated secondary antibody and visualized using the Odyssey infrared imaging system (LI-COR Biosciences).

Histological studies

Paraffin-embedded sWAT sections were stained with hematoxylin-eosin (H&E). Images were scanned using a NanoZoomer-SQ (Hamamatsu).

Oil red O staining

Cells were washed with PBS for three times, and then fixed with 4% paraformaldehyde for 30 min. Next, the cells were stained with oil red O for 60 min, and washed with PBS for 5 min. Cells were then stained with hematoxylin for 5 s and washed with PBS. The dyed cells were photographed under the microscope (Leica, Germany).

Enzyme-linked immunosorbent assay

Levels of IL-22 were measured by double-antibody sandwich ELISAs (M2200; R&D Systems). Briefly, 100 µL of Assay Diluent were added to each well. 50 µL of blood samples and standards were added and incubated at room temperature for 2 hr. After washing, conjugates were added and incubated for 2 hr. After washing, the substrate solution was added and incubated for 30 min and washed. And stop solution were added finally. Optical density values were measured using a microplate reader (Bio-Rad, Hercules, CA, USA).

OGTT and ITT

Oral glucose tolerance tests (OGTT) and insulin tolerance tests (ITT) were performed after 16 or 6 hr of fasting, respectively. Mice were given with 3 g/kg glucose by gavage or injected intraperitoneally with 0.75 U/kg insulin. Blood samples were collected from the tail vain at 0, 15, 30, 60, 90, and 120 min after glucose or insulin treatment. Blood glucose levels were measured using a glucometer (Roche, Basel, CH).

Cold exposure

Mice were placed in a 4°C cold room for 6 hr. The rectal temperature was measured every hour during the cold challenge with a rectal probe (Braintree Scientific, Braintree, MA, USA).

Statistical analysis

Data were analyzed by GraphPad Prism software v.8.0 and presented as the mean ± s.e.m. The Shapiro-Wilk normality test was used to determine the normal distribution of samples. Unpaired Student’s t test (normal distribution) or Mann-Whitney U tests (non-normal distribution) were used to analyze data between two groups and one-way ANOVA followed by Bonferroni’s multiple-comparisons test (normal distribution) or Kruskal-Wallis test (non-normal distribution) was used for three or more groups. The sample sizes were determined by power analysis using StatMate v.2.0. No data were excluded during the data analysis.

Acknowledgements

This research was supported by grants from the National Natural Science Foundation of China (81930015, 81730020, 82070592, and 82270610), National Institutes of Health Grant R01DK112755 and 1R01DK129360.

Funding Statement

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

Contributor Information

Weizhen Zhang, Email: weizhenzhang@bjmu.edu.cn.

Yue Yin, Email: yueyin@bjmu.edu.cn.

Kiyoshi Takeda, Osaka University, Japan.

Tadatsugu Taniguchi, University of Tokyo, Japan.

Funding Information

This paper was supported by the following grants:

  • National Natural Science Foundation of China 81930015 to Weizhen Zhang.

  • National Natural Science Foundation of China 81730020 to Weizhen Zhang.

  • National Natural Science Foundation of China 82070592 to Yue Yin.

  • National Natural Science Foundation of China 82270610 to Yue Yin.

  • National Institutes of Health R01DK112755 to Weizhen Zhang.

  • National Institutes of Health 1R01DK129360 to Weizhen Zhang.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Methodology, Writing - original draft, Project administration, Writing – review and editing.

Resources, Data curation, Validation, Methodology, Project administration.

Data curation, Formal analysis, Investigation.

Formal analysis.

Resources, Data curation, Project administration.

Methodology, Project administration.

Project administration.

Resources, Visualization.

Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing – review and editing.

Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Writing – review and editing.

Ethics

All of the animal experiments complied with the protocols for animal use, treatment and euthanasia approved by Peking University (Permit Number: LA2017099).

Additional files

Supplementary file 1. Sequences of primers used in quantitative PCR.
elife-91060-supp1.docx (19.2KB, docx)
MDAR checklist

Data availability

All of the data supporting the findings of this study are included in the article and supplementary information. The Single-cell RNA sequencing data were uploaded to a public database (PRJNA1031585).

The following dataset was generated:

Hong C. 2023. ScRNAseq provides new information into intestine-resident immune cell profiling in response to repeated fasting and refeeding. NCBI BioProject. PRJNA1031585

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eLife assessment

Kiyoshi Takeda 1

This study provides valuable findings showing the production of IL-22 from intestinal ILC3 during intermittent fasting promotes beigeing of white adipose tissue. The authors provided solid data and mechanistic insight by which IL-22-derived from ILC3 directly induces beigeing.

Reviewer #1 (public Review):

Anonymous

In the present study, the authors carefully evaluated the metabolic effects of intermittent fasting on normal chow and HFD fed mice and reported that intermittent fasting induces beiging of subcutaneous white adipose tissue. By employing complementary mouse models, the authors provided compelling evidence to support a mechanism through ILC3/IL-22/IL22R pathway. They further performed comprehensive single-cell sequencing analyses of intestinal immune cells from lean, obese, obese undergone intermittent fasting mice and revealed altered interactome in intestinal myeloid cells and ILC3s by intermittent fasting via activating AhR. Overall, this is a very interesting and timely study uncovering a novel connection between intestine and adipose tissue in the context of executing metabolic benefits of intermittent fasting.

(1) The authors showed increased plasma IL-22 and its expression in intestine. Are intestinal ILC3s the main source of plasma IL-22?

(2) The authors transplanted intestinal ILC3s from NCD mice to DIO mice and showed significant metabolic improvements. However, in Fig. 1, intermittent fasting increased IL-22-positive ILC3s proportion rather than changing the total number. Please clarify whether this transplantation is due to increasing ILC3s number or introducing more IL-22 positive ILC3s (which are decreased in DIO). Are these transplanted ILC3s by default homing to intestine rather than to other tissues?

(3) The authors adopted cold challenge at 4 degree for 6 hours to assess beiging in subcutaneous WAT and showed difference in core temperature. However, thermogenesis in this acute cold challenge is mainly by brown adipose tissue. Beiging is a chronic and adaptive response. Based on the data in WAT, there is a beiging phenotype, but the core body temperature in acute cold challenge is not an accurate readout. It would be a missed opportunity by not evaluating thermogenic activity in BAT.

More browning genes should be included to strengthen the beiging phenotype of WAT. Moreover, inflammation in WAT can be examined to provide a whole picture of adipose tissue remodeling through this pathway.

(4) For the SVF beige adipocyte differentiation, 100 ng/mL IL-22 was used. This is highly above the physiological concentration at ~5 pg/mL. Please justify this high concentration used.

The authors showed increased Ucp1 and Cidea expression by IL-22 treatment in SVFs. Please be aware that these increases are likely due to boosted adipogenesis as told by the morphology. Please examine more adipogenic markers to confirm. Is this higher adipogenesis caused by the high concentration of IL-22?

In line 201, the authors drew the conclusion that IL-22 increased SVF beige differentiation. To fully support this conclusion, the authors should assure adipogenesis at the same baseline and then compare beiging, or examine the effect of IL-22 on normal adipogenesis to compare with beige differentiation.

Reviewer #2 (Public review):

Anonymous

Summary:

This study aims to investigate the mediatory role of intestinal ILC3-derived IL-22 in intermittent fasting-elicited metabolic benefits.

Strengths:

The observation of induction of IL-22 production by intestinal ILC3 is significant, and the scRNAseq provides new information into intestine-resident immune cell profiling in response to repeated fasting and refeeding.

Weaknesses:

The experimental design for some studies needs to be improved to enhance the rigor of overall study. There is a lack of direct evidence showing that the metabolically beneficial effects of IF are mediated by intestinal ILC3 and their derived IL-22. The mechanism by which IL-22 induces thermogenic program is unknown. The browning effect induced by IF may involve constitutive activation of lipolysis, which was not considered.

Majority of weaknesses have been addressed in the revision. Based on the analysis of thermogenic genes in addition to Ucp1 (Fig. 4D and S6F), the alteration on thermogenesis induced by IL-22 is dependent on UCP1 but not other markers such as PGC1a, PPARg, and Cidea. The data need to be discussed in the Section of Discussion.

Reviewer #3 (Public review):

Anonymous

Chen et al. investigated how intermittent fasting causes metabolic benefits in obese mice and find that intestinal ILC3 and IL-22-IL-22R signaling contribute to the beiging of white adipose tissue (WAT) and consequent metabolic benefits including improved glucose and lipid metabolism in diet-induced obese mice. They demonstrate that intermittent fasting causes increased IL22+ILC3 in small intestines of mice. Adoptive transfer of purified intestinal ILC3 or administration of exogenous IL-22 can lead to increases in UCP1 gene expression and energy expenditure as well as improved glucose metabolism. Importantly, the above metabolic benefits caused by intermittent fasting are abolished in IL-22R-/- mice. Using an in vitro experiment, the authors show that ILC3-derived IL-22 may directly act on adipocytes to promote SVF beige differentiation. Finally, by performing sc-RNA-seq analysis of intestinal immune cells from mice with different treatments, the authors indicate a possible way of intestinal ILC3 being activated by intermittent fasting. Overall, this study provides a new mechanistic explanation for the metabolic benefits of intermittent fasting and reveals the role of intestinal ILC3 in the enhancement of the whole-body energy expenditure and glucose metabolism likely via IL-22-induced beige adipogenesis.

Although this study presents some interesting findings, particularly IL-22 derived from intestinal ILC3 could induce beiging of WAT by directly acting on adipocytes, the experimental data are not sufficient to support the key claims in the manuscript.

eLife. 2024 Mar 27;12:RP91060. doi: 10.7554/eLife.91060.3.sa4

Author response

Hong Chen 1, Lijun Sun 2, Feng Lu 3, Xue Han 4, Yunhua Zhang Zhang 5, Wenbo Zhai 6, Zehe Zhang 7, Michael Mulholland 8, Weizhen Zhang 9, Yue Yin 10

The following is the authors’ response to the original reviews.

Comment 1: The authors showed increased plasma IL-22 and its expression in the intestine. Are intestinal ILC3s the main source of plasma IL-22?

Reply: ILC3s are the main source of IL-22 as reported previously (PMID: 30700914). In the small intestine, ILC3s account for about 62% of IL22+ cells. Other IL22+ cells include γδ T, Foxp3+T and CD4+T cells.

Comment 2: The authors transplanted intestinal ILC3s from NCD mice to DIO mice and showed significant metabolic improvements. However, in Fig. 1, intermittent fasting increased IL-22positive ILC3s proportion rather than changing the total number. Please clarify whether this transplantation is due to increasing ILC3s number or introducing more IL-22 positive ILC3s (which are decreased in DIO). Are these transplanted ILC3s by default homing to the intestine rather than to other tissues?

Reply: We believe that the transplantation increases ILC3s number, leading to the increment in IL22 levels. The transplanted ILC3s by default are homing to the intestine rather than to other tissues because ILC3s express several homing receptors such as CCR7, CCR9, and α4β7, which modulate their capacity to migrate to the gut (PMID: 26141583; PMID: 26708278; PMID: 25575242; PMID: 34625492). Our observation that ILC3s in adipose tissue remained unchanged by ILC3 cell transplantation (Supplementary Figure 5F) also supports this concept.

Comment 3: Thermogenesis in this acute cold challenge is mainly by brown adipose tissue. Beiging is a chronic and adaptive response. Based on the data in WAT, there is a beiging phenotype, but the core body temperature in acute cold challenge is not an accurate readout. It would be a missed opportunity by not evaluating thermogenic activity in BAT. More browning genes should be included to strengthen the beiging phenotype of WAT. Moreover, inflammation in WAT can be examined to provide a whole picture of adipose tissue remodeling through this pathway.

Reply: Per suggestion, we performed additional experiments to measure levels of inflammation genes such as Il4, Il1b, Il6, Il22, Il23, Il17a. As shown in supplemental figure 2D, these inflammation relevant genes were not altered.

Comment 4: For the SVF beige adipocyte differentiation, 100 ng/mL IL-22 was used. This is highly above the physiological concentration at ~5 pg/mL. Please justify this high concentration used.

Reply: We agree with the reviewer that the dose of IL-22 used is high. However, the efficient dose at 100 ng/ml used in our studies is consistent with the literatures. Previous reports have shown that IL-22 directly activates Stat3 in adipose tissue and primary adipocytes, and promotes the expression of genes involved in triglyceride lipolysis (Lipe and Pnpla2) and fatty-acid β-oxidation (Acox1) at the dose of 100 ng/ml (Wang X, Ota N, et al. Nature. 2014). Consistently, other studies have reported that IL-22 at 100 ng/ml significantly reversed the enhanced expression of CCL2, CCL20 and IL1B mRNAs in granulosa cells in vitro (Qi X, et al. Nat Med. 2019).

Comment 5: The authors showed increased Ucp1 and Cidea expression by IL-22 treatment in SVFs. Please be aware that these increases are likely due to boosted adipogenesis as told by the morphology. Please examine more adipogenic markers to confirm. Is this higher adipogenesis caused by the high concentration of IL-22?

Reply: Per suggestion, we examined the expression of adipogenic marker genes such as Pparγand Fabp4. We found that IL-22 did not increase the levels of these adipogenic marker genes relevant to the PBS control as shown in supplemental figure 6F.

Author response image 1.

Author response image 1.

Comment 6: In line 201, the authors drew the conclusion that IL-22 increased SVF beige differentiation. To fully support this conclusion, the authors should assure adipogenesis at the same baseline and then compare beiging, or examine the effect of IL-22 on normal adipogenesis to compare with beige differentiation.

Reply: We examined the expression of adipogenic marker genes such as Pparγ and Fabp4 and found that IL-22 did not increase the expression of these adipogenic marker genes relevant to the PBS control.

Reviewer #2:

This study aims to investigate the mediatory role of intestinal ILC3-derived IL-22 in intermittent fasting-elicited metabolic benefits.

Strengths:

The observation of induction of IL-22 production by intestinal ILC3 is significant, and the scRNAseq provides new information into intestine-resident immune cell profiling in response to repeated fasting and refeeding.

Weaknesses:

The experimental design for some studies needs to be improved to enhance the rigor of the overall study. There is a lack of direct evidence showing that the metabolically beneficial effects of IF are mediated by intestinal ILC3 and their derived IL-22. The mechanism by which IL-22 induces a thermogenic program is unknown. The browning effect induced by IF may involve constitutive activation of lipolysis, which was not considered.

Comment 1: Lack of direct evidence showing that IL-22-expressing ILC3s in intestine is the key contributor to intermittent fasting (IF)-mediated elevation of circulating IL-22 levels. The fraction of IL-22-expressing cells was increased threefold by IF but the increase in circulating IL-22 is moderate (Figs. 1J and 1K).

Reply: IL-22 in circulation is subjected to clearance, degradation, and binding with plasma proteins, et al. Thus, circulating levels of IL-22 may be much lower than the amount secreted by the intestinal IL-22 positive ILC3s.

Comment 2: The loss of fat mass by IF suggests that the active lipolysis may explain the white fat browning which was not considered. This may apply to the observations in IL-22 treated mice as well as IL-22R KO mice.

Reply: We analyzed the expression of genes relate to lipolysis in NCD and NCD-IF mice and found that IF did not alter the levels of these genes in white adipose tissues (Supplementary figure 2D). We have addressed this concerns in lines 119, page 6.

Author response image 2.

Author response image 2.

Comment 3: IL-22 administration and adoptive transfer of ILC3 had no significant effect on body weight. Not clear how IL-22 improves insulin sensitivity in this case.

Reply: Our results are consistent with previous report showing that IL-22 administration improves insulin sensitivity without change in body weight (Qi X, et al. Nat Med. 2019). In addition, previous studies have demonstrated that IL-22 can increase Akt phosphorylation in muscle, liver and adipose tissues, leading to improvement in insulin sensitivity (Wang X, et al. Nature. 2014). We have addressed this potential mechanism in lines192-195, page 9.

Comment 4: The energy expenditure data look unusual given that there was little increase in oxygen consumption during dark cycle compared to light cycle (Fig.3).

Reply: The not so obvious difference in oxygen consumption between dark cycle and light cycle may be due to the technical problem of the system.

Comment 5: The thermogenic capacity for the whole fat pad needs to consider the expression of UCP1 in certain amount of tissue and the total mass for each individual animal because the mRNA level itself does not reflect the whole tissue capacity.

Reply: We used the whole subcutaneous adipose tissue from one side for qPCR to reflect the whole tissue capacity.

Comment 6: The design of studies for the adoptive transfer of ILC3 was concerned. The PBS is not a good control for the group with ILC3 cells (Figs. 2A-2H). Similar issue applies for the co-culture study in which beige only is not an ideal control for Beige+ILC3 (Figs. 2I-2J).

Reply: We agree with the reviewer that the PBS is not a good control. Because we cannot find a similar immune cell without any effect on adipocytes, we designed this experiment based on other studies in which saline or PBS are used as ILC transfer experiment controls (Sasaki T, et al. Cell Rep. 2019; Wang H, et al. Nat Commun. 2019)

Comment 7: The induction of thermogenesis by IL-22 treatment may be related to enhanced differentiation rather than direct activation of thermogenic genes (Figs. 4G and 4H).

Reply: Our observation that IL-22 did not alter the levels of genes related to adipogenesis (Supplemental figure 6F) indicates that IL-22 may not alter the differentiation of adipocytes. We addressed this concern in Lines 211-212, page 10.

Reviewer #3:

Chen et al. investigated how intermittent fasting causes metabolic benefits in obese mice and found that intestinal ILC3 and IL-22-IL-22R signaling contribute to the beiging of white adipose tissue (WAT) and consequent metabolic benefits including improved glucose and lipid metabolism in diet-induced obese mice. They demonstrate that intermittent fasting causes increased IL22+ILC3 in small intestines of mice. Adoptive transfer of purified intestinal ILC3 or administration of exogenous IL-22 can lead to increases in UCP1 gene expression and energy expenditure as well as improved glucose metabolism. Importantly, the above metabolic benefits caused by intermittent fasting are abolished in IL-22R-/- mice. Using an in vitro experiment, the authors show that ILC3derived IL-22 may directly act on adipocytes to promote SVF beige differentiation. Finally, by performing sc-RNA-seq analysis of intestinal immune cells from mice with different treatments, the authors indicate a possible way of intestinal ILC3 being activated by intermittent fasting. Overall, this study provides a new mechanistic explanation for the metabolic benefits of intermittent fasting and reveals the role of intestinal ILC3 in the enhancement of the whole-body energy expenditure and glucose metabolism likely via IL-22-induced beige adipogenesis.

Although this study presents some interesting findings, particularly IL-22 derived from intestinal ILC3 could induce beiging of WAT by directly acting on adipocytes, the experimental data are not sufficient to support the key claims in the manuscript.

Comment 1: Only increased UCP1 expression on mRNA level is not enough to support the beiging of WAT. More methods such as western blotting and immunostaining of UCP1 in WAT are needed to confirm the enhanced beige adipogenesis.

Reply: Additional experiments have been performed to measure the UCP1 protein by Western blot. The data is included in Figure 4I and Supplementary Figure 2E.

Comment 2: IL-22 is known to modulate metabolic pathways via multiple downstream functions. The use of whole-body knockout of IL-22R could not exclude the indirect effect on the promotion of beiging of WAT. Specific deletion of IL-22R in adipose tissues is therefore needed to confirm the direct effect of IL-22 on adipocytes which is suggested by the in vitro study.

Reply: We agreed with the reviewer that specific deletion of IL-22R in adipose tissues is critical to confirm the direct effect of IL-22 on adipocytes. We will generate the AdioQ-IL-22R-/- mice to test this concept further in vivo.

Comment 3: The authors failed to show the cellular distribution of IL-22R in adipose tissues. This is important because the mechanism that explains the increased beige adipogenesis could be different based on the expression of IL-22R in adipose progenitor cells or mature adipocytes. So it is not appropriate to conclude that "IL-22 then directly activates IL-22R on adipocytes, leading to subsequent induction of beiging of white adipose tissue" in line 407. Additionally, Oil red O staining is needed for Fig 4G and Fig 5J, and protein levels of UCP1 and adipogenesis-related markers are needed to evaluate beige fat differentiation and the whole adipogenesis.

Reply: Per suggestion, we have added the expression of IL-22R in adipose progenitor cells or mature adipocytes (Supplementary Figure 6E). In addition, protein levels of UCP1 and adipogenesis-related markers to evaluate the whole adipogenesis (Figure 4I, Supplementary figure 6F) are now included. We have also addressed this issue in lines 207-215, page 10.

Comment 4: Although the authors provided some hypothesis about how intermittent fasting increases IL-22+ILC3 in small intestines by sc-RNA-seq analysis, some functional assays are needed to identify the factors, for example, how about the levels of macrophage-derived IL-23 or AHR ligands in small intestines and whether they contribute to increased percentages of intestinal IL-22+ILC3 following intermittent fasting.

Reply: We used flow cytometry sorting of macrophages combined with qPCR experiments to preliminarily demonstrate that intermittent fasting increases the expression of molecules such as Cd44 and CCl4 (Supplementary Figure 10B), which may contribute to the increase in the proportion of IL-22+ ILC3s in the intestine under intermittent fasting. Our observation that IL-23 mRNA levels were not changed indicates that this molecule may not the major contributor for the communication between macrophage and ILC3s. Other potential molecules such as AHR ligands remain to be explored.

Comment 5: What are the differences between adipose ILC3 and intestinal ILC3? Why do transferred ILC3 only migrate to the small intestine but not WAT of recipient mice? It would be better to examine or at least discuss whether other factors from intestinal ILC3 may also contribute to beiging of WAT following intermittent fasting.

Reply: Intestinal ILC3s specifically express gut homing receptors CCR7, CCR9, and α4β7 (PMID: 26141583; PMID: 26708278; PMID: 25575242; PMID: 34625492). This may explain transplantation of intestinal ILC3s can migrate mainly to the intestine instead of adipose tissue (PMID: 34625492). The proportion of ILC3s in adipose tissue of mice is very small. Their functions have not been clarified yet. We have addressed this issue in lines 156-158, page 8.

There are some other factors from intestinal ILC3 which may also contribute to beiging of WAT following intermittent fasting. By secreting IL-22, ILC3 enhanced the intestinal mucosal barrier, leading to reduction of the influx of LPS and PGN into the bloodstream under high-fat diet conditions, and subsequent increase in the beiging of white adipose tissue (Chen H, et al. Acta Pharm Sin B. 2022). We have addressed this potential mechanism in lines 344-347, page 16.

Comment 6: The sensitivity of the IL-22 ELISA kit used in the manuscript was 8.2 pg/mL, according to the information from the methods, however, in Fig. 1J and Fig. 2B, the IL-22 levels in mouse plasma were lower than 6 pg/mL, which was below the sensitivity of the ELISA kit and also the assay range. Please explain.

Reply: We have double-checked the original data and found that we have made a mistake in calculating the concentration of IL-22. We have corrected this error (Fig. 1J, Fig. 2B).

Comment 7: In Fig 7A, the significance of the Hypothesis testing should be marked. In Fig 7F and 7G, the contrast between the two groups is not apparent, other comparing ways could be used to enhance the readability.

Reply: Per suggestion, we have marked the significance of the hypothesis testing between HFD vs NCD and HFD-IF vs HFD in Fig7A. Shown in Fig 7F and 7G are the top 20 enriched interacting proteins between different cell types. The dot plot displays the average expression level and significance of protein interactions in cell types.

Comment 8: The total food intake of fasting mice fed with NCD or HFD was less than those without fasting, and the food intake rate the author showed in Fig S1 represents the value that was normalized to body weight. So the author should describe it precisely In line 114.

Reply: We have revised the statement accordingly in line 114-115.

Comment 9: Western blotting analysis has been described in methods, however, there is no corresponding experimental data in the result part.

Reply: The Western blotting results are now included.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Hong C. 2023. ScRNAseq provides new information into intestine-resident immune cell profiling in response to repeated fasting and refeeding. NCBI BioProject. PRJNA1031585

    Supplementary Materials

    Figure 1—figure supplement 2—source data 1. Original file for the western blot analysis in Figure 1—figure supplement 2E (anti-UCP1, anti-β-actin).
    Figure 1—figure supplement 2—source data 2. PDF containing original scans of the relevant western blot analysis (anti-UCP1, anti-β-actin) with highlighted bands and sample labels.
    Figure 4—source data 1. Original file for the western blot analysis in Figure 4I (anti-pSTAT3, anti-STAT3, anti-pMAPK, anti-MAPK, anti-GAPDH, anti-UCP1, anti-β-actin).
    Figure 4—source data 2. PDF containing original scans of the relevant western blot analysis (anti-pSTAT3, anti-STAT3, anti-pMAPK, anti-MAPK, anti-GAPDH, anti-UCP1, anti-β-actin) with highlighted bands and sample labels.
    Supplementary file 1. Sequences of primers used in quantitative PCR.
    elife-91060-supp1.docx (19.2KB, docx)
    MDAR checklist

    Data Availability Statement

    All of the data supporting the findings of this study are included in the article and supplementary information. The Single-cell RNA sequencing data were uploaded to a public database (PRJNA1031585).

    The following dataset was generated:

    Hong C. 2023. ScRNAseq provides new information into intestine-resident immune cell profiling in response to repeated fasting and refeeding. NCBI BioProject. PRJNA1031585


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