Nod2 protects from diet-induced obesity in BALB/c mice

WT and Nod2 −/− female mice on BALB/c background, matched for weight (average 18 g) and age (6–7 weeks old) at the beginning of the experiment were maintained on HFD (fat 60 kcal%) or low fat diet (LFD, fat 10 kcal%) for 30 weeks. The total calories/g of food was the same for both diets. We observed a dramatic increase in weight gained by Nod2 −/− mice compared with WT mice on HFD (Fig. 1a). Nod2 −/− mice gained significantly more weight than WT mice starting from week 2 on HFD, and at week 30 Nod2 −/− mice gained almost twice as much weight as WT mice. As expected, WT and Nod2 −/− mice on HFD gained significantly more weight than WT and Nod2 −/− mice on LFD. There was no difference in weight gained between WT and Nod2 −/− mice on LFD. Our data with WT mice concur with previous data showing that WT BALB/c mice do not become obese on HFD4.

Figure 1 Nod2 −/− mice on HFD become obese and develop hyperlipidemia, hyperglycemia, and glucose intolerance. WT and Nod2 −/− mice were monitored for weight gain, increased adiposity, and assayed for metabolites. (a) Percent gain in body weight over week 0. (b–d) At week 30, (b) representative mice are shown for increase in overall size and visceral adipose tissue, (c) average increase in subcutaneous thickness and weight of visceral adipose tissue and liver per mouse, and (d) total visceral adipose tissue and liver from representative mice. (e–j) At week 30, mice were assayed for serum (e) cholesterol, (f) triglycerides, (g) glucose, (i) insulin, and (k) leptin, and for the development of (h) glucose tolerance and (j) insulin resistance. (l) Total caloric value in fecal samples. The results are (a) means ± SEM of 18–25 mice/group; (c,h,j) means ± SEM of 10–12 mice/group; or (e–g,i,k,l) for individual mice/group ± SEM. (h) Data for the glucose tolerance test is shown as ratio of HFD to LFD for each strain. *P ≤ 0.05, **P ≤ 0.001, Nod2 −/− HFD versus WT HFD; # P ≤ 0.05, ## P ≤ 0.001, Nod2 −/− HFD versus Nod2 −/− LFD; ^P ≤ 0.05, ^^P ≤ 0.001, WT HFD versus WT LFD; + P ≤ 0.05, ++ P ≤ 0.001, Nod2 −/− LFD versus WT LFD. The results for food consumed and voluntary wheel activity are shown in Fig. S1. Full size image

Nod2 −/− mice on HFD were visibly larger with substantially more fat deposits than WT HFD mice (Fig. 1b) and had significantly increased subcutaneous and visceral adipose tissue and an enlarged and fatty liver compared with WT HFD mice (Fig. 1c and d). There was no difference in the amount of food consumed or water intake between WT and Nod2 −/− HFD mice; average food consumed/mouse/day was 2.0 g for both genotypes and (Supplementary Fig. S1); the average water intake/mouse/day was 4.0 ml for both genotypes. There was also no significant difference in the average running distance/24 h between WT (9.48 km) and Nod2 −/− (9.59 km) mice on regular chow (Supplementary Fig. S1).

Thus, our data demonstrate that in WT mice Nod2 protects from the development of HFD-induced obesity and that Nod2 deletion reverses the resistance to obesity observed in WT BALB/c mice. The increased weight gain in Nod2 −/− HFD mice compared with WT HFD mice is not due to increased food consumption or due to an inherent lower activity.

Nod2 protects from diet-induced hyperlipidemia, hyperglycemia, and glucose intolerance in BALB/c mice

We next examined the effect of Nod2 and HFD on lipid and carbohydrate metabolism. Nod2 −/− HFD mice exhibited significantly higher levels of serum cholesterol and triglycerides compared with WT HFD mice and compared with Nod2 −/− and WT mice on LFD (Fig. 1e and f). Nod2 −/− HFD mice had significantly higher fasting glucose and impaired ability to restore blood glucose in response to a bolus of glucose compared with WT HFD mice (Fig. 1g and h), which indicates development of glucose intolerance. Nod2 −/− HFD mice had significantly higher levels of serum insulin than WT HFD, Nod2 −/− LFD, and WT LFD mice (Fig. 1i), and exhibited a mild but significantly reduced response to exogenous insulin compared with WT HFD mice 120 min after an insulin challenge (Fig. 1j), which indicates the development of insulin resistance and suggests that partial compensation may be achieved by increased insulin production. Nod2 −/− HFD mice had significantly higher serum levels of the anorexic hormone leptin than WT HFD mice, Nod2 −/− LFD mice, and WT LFD mice (Fig. 1k). WT HFD mice had significantly higher triglycerides than Nod2 −/− LFD and WT LFD mice, which indicates the development of mild metabolic dysfunction in WT HFD mice. Nod2 −/− LFD mice also had a smaller but significant increase in serum lipids, glucose, insulin, and leptin compared with WT LFD mice. Thus, our results demonstrate that Nod2 −/− HFD mice develop hyperlipidemia, hyperglycemia, and glucose intolerance, which are hallmark manifestations of metabolic syndrome in humans.

To determine any differences in the total energy extracted from food between Nod2 −/− HFD mice and WT HFD mice, we measured the total calories present in the stool samples of these mice. Our results show that total caloric value of Nod2 −/− HFD feces was significantly lower than WT HFD feces (Fig. 1l). These results indicate that Nod2 −/− mice on HFD extract more energy from the same amount of food than WT mice on HFD, which may be due to differences in the metabolism of host or gut microbiota.

Nod2 protects from diet-induced histopathology in BALB/c mice

We characterized the histopathology in the liver and adipose tissue of Nod2 −/− obese mice. Nod2 −/− HFD mice had significantly larger hepatocytes than WT mice on HFD and the majority of these cells had a foamy appearance, which indicates lipid accumulation (Fig. 2a). In BODIPY stained sections there was a dramatic and significant increase in the size of lipid droplets (LDs) in Nod2 −/− mice compared with WT mice (Fig. 2b). The area for LDs ranged from 2 μm2 to 300 μm2 with the highest percentage of LDs in the 36 to 75 μm2 range for Nod2 −/− mice and 5 to 9 μm2 range for WT mice (Fig. 2c). Nod2 −/− mice on HFD had significantly higher levels of liver cholesterol and triglycerides than WT HFD, Nod2 −/− LFD, and WT LFD mice (Fig. 2d and e). Thus, our histological and biochemical data further support our results showing development of obesity in Nod2 −/− HFD mice and also support our data for WT mice, which do not become obese and do not have a fatty liver (Fig. 1).

Figure 2 Nod2 −/− mice on HFD develop steatosis and have large stressed adipocytes with increased infiltration of macrophages. (a,b) Liver sections from Nod2 −/− and WT mice stained with (a) H&E or (b) BODIPY and DAPI. (c) Percent frequency distribution of the area (µm2) of ~5,000 LDs/group. ( d,e) Quantification of liver cholesterol and triglycerides. (f) Heatmap representation of the fold increase (red) or decrease (green) in the abundance of proteins present in LD-enriched fraction from liver. The fold ratio for individual Nod2 −/− HFD mice to the average of WT HFD mice were computed (lanes 1 to 5) with the average of the fold for all Nod2 −/− HFD mice. (g) Adipose tissue H&E sections and a dying cell (→) is indicated. (h) Percent frequency distribution the area of ~8,000 adipocytes/group. (i) Average numbers of dying adipocytes (crowns) per 3,000 cells in H&E stained sections. (j) Quantification of CD45+F4/80+ macrophage in adipose tissue. (k–m) Transcript levels for Adgre1, Cd68, and Tnfα in adipose tissue. Images are representative and results are (c,h,i) means ± SEM of 6 mice/group and (d,e,j–m) for individual mice with N = 5–10 mice/group. *P ≤ 0.05, **P ≤ 0.001, Nod2 −/− HFD versus WT HFD; # P ≤ 0.05, ## P ≤ 0.001, Nod2 −/− HFD versus Nod2 −/− LFD; ^P ≤ 0.05, WT HFD versus WT LFD; and + P ≤ 0.05, Nod2 −/− LFD versus WT LFD. Full size image

We next identified differences in the proteins associated with LDs between Nod2 −/− and WT mice on HFD. We isolated proteins from LD-enriched fractions and identified them by mass spectrometry. All proteins that were significantly different (P ≤ 0.05 and fold change ≥1.5 or ≤0.6) between Nod2 −/− and WT mice are directly or indirectly involved in lipid metabolism or in vesicle trafficking (Fig. 2f). Nod2 −/− HFD mice compared with WT HFD mice had significantly higher levels of Abhd5, Agpat2, Gpam, and Gpd2 but decreased levels of Gpat4, proteins associated with biosynthesis of glycerolipids. Tecr, a protein involved in the synthesis of very long chain fatty acids was increased in Nod2 −/− HFD mice. Many proteins that participate in the catabolism of lipids were also more abundant in Nod2 −/− HFD mice than in WT HFD mice, including Acaa1b, Acat1, Aldh7a1, Bdh1, Cyp2b9, Cyp4a14, Faah, Lipe, Lypla1, Mgll, and Pnpla3. Proteins associated with lipid storage were selectively up regulated or down regulated, Plin3 and Plin4 were present at higher and Faf2 and Plin1 at lower levels in Nod2 −/− HFD mice. Several proteins involved in vesicle trafficking were decreased in the LD-enriched fraction of Nod2 −/− HFD mice compared with WT HFD mice. However, Copb1, a protein associated with non-clathrin coated vesicles with a role in limiting lipid storage, was significantly higher in Nod2 −/− HFD mice than WT HFD mice. These data indicate that the larger LDs in Nod2 −/− HFD mice compared with WT HFD mice are accompanied by changes in lipid metabolizing enzymes and in vesicle trafficking proteins.

Nod2 −/− mice on HFD had enlarged adipocytes with significantly larger area than WT HFD mice (Fig. 2g and h). The area for adipocytes ranged from 31 μm2 to 16,000 μm2 with the highest percentage of cells in the 2000 to 4000 μm2 range for Nod2 −/− mice and 250 to 500 μm2 for WT mice (Fig. 2h). Nod2 −/− mice had significantly more “crowns”, which are dead adipocytes surrounded by immune cells (Fig. 2g and i, indicated by an arrow) and are a characteristic feature of stressed adipose tissue associated with obesity. Nod2 −/− mice on HFD had significantly more F4/80+ macrophages in adipose tissue than WT mice on HFD, Nod2 −/− LFD, and WT LFD mice (Fig. 2j) with a corresponding increase in the transcripts for Adgre1 (gene for F4/80) and Cd68, another marker for monocytes/macrophages (Fig. 2k and l). Expression of Tnfα, an inflammatory cytokine associated with obesity was enhanced (Fig. 2m). Thus, our data demonstrate that Nod2 protects from lipid accumulation in the adipose tissue and liver, and that development of diet-dependent obesity in Nod2 −/− HFD mice is associated with steatosis, formation of large LDs in hepatocytes, stressed adipocytes, and infiltration of macrophages in the adipose tissue.

Diet-dependent obesity in Nod2 −/− mice is associated with changes in the expression of adipose tissue genes involved in immune responses and intermediary metabolism

We identified genes that were differentially expressed in the visceral adipose tissue of WT and Nod2 −/− BALB/c mice maintained on HFD for 30 weeks using RNA transcriptomics. Nod2 −/− HFD mice had 357 genes with significantly increased expression (and fold change ≥2) and 169 genes with significantly decreased expression (and fold change ≤0.5) compared with WT mice on HFD (Supplementary Fig. S2). 79% of the differentially expressed genes are associated with a function or pathway (Ensembl or DAVID) and are shown in Fig. 3 and Supplementary Table S1. More than 100 genes that directly or indirectly participate in immune responses were differentially regulated and the majority of these genes (>80) were significantly up regulated in the adipose tissue of Nod2 −/− HFD mice compared with WT HFD mice. These genes code for transcription factors, signaling molecules, effector molecules, enzymes, and receptors, all involved in regulating immune cells and responses. For example, Nod2 −/− mice on HFD had increased expression of genes for (i) chemokines Ccl2, Ccl5, Ccl7, Ccl8, Ccl12, Ccl22, and Cxcl1, which recruit monocytes, eosinophils, and lymphocytes; (ii) enzymes involved in arachidonic acid and eicosanoid metabolism, Cyp2c39, Cyp2d10, Cyp4f14, Fam213b, Pla2g12b, and Ptges3l; (iii) receptors involved in T cell activation, including Cd3δ, Cd3ε, Cd3γ, Cd4, Cd5, Cd6, and Cd52; and (iv) adipokines Sfrp5, Stra6l, and Wisp2, and the protease Cpn1. Expression of genes for adipsin (Cfd) and regulators of adipokines, Hcar2 and Ptprn2, was decreased.

Figure 3 Differential expression of genes for immunity, metabolism, and other cellular functions in the adipose tissue of Nod2 −/− mice on HFD. Heatmap representation of the fold increase (red) or decrease (green) for gene expression in the adipose tissue of Nod2 −/− HFD mice compared with WT HFD mice. The genes are grouped based on function or pathway. The fold ratio for individual Nod2 −/− HFD mice to the average of WT HFD mice was computed and is shown (lanes 1 to 6) with the average of the fold for all Nod2 −/− HFD mice. Genes that had a fold change of ≥2 or ≤0.5 (≤−2) and P ≤ 0.05 with 5% FDR are included in the heatmap. N = 6 mice/group. The numerical data for fold increase in individual mice, the average, P value, and FDR are shown in Supplementary Table S1. Full size image

The second largest group of genes that was differentially regulated between WT and Nod2 −/− HFD mice directly or indirectly participates in intermediary metabolism, primarily lipid metabolism (Fig. 3, Supplementary Table S1). These genes include: (i) enzymes involved in breakdown of fatty acids and glycerolipids, for example, Acot3, Acot4, Ces4a, Agpat9, and Pnpla1 were increased; (ii) members of the acyl-CoA synthetase medium chain family were up regulated (Acsm1) or down regulated (Acsm3 and Acsm5); (iii) enzymes in the synthesis of fatty acids and triglycerides, Mogat2 and Scd1, were increased; (iv) transporters for fatty acids, cholesterol, glycerolipids, and glycerol, Abcc2, Aqp11, Atp8b5, Fabp5, and Mfge8, were up regulated, and Apold1, Glcci1, and Slc27a1, were down regulated.

Nod2 −/− mice on HFD had several differentially expressed genes that directly or indirectly participate in amino acid and carbohydrate metabolism compared with WT HFD mice (Fig. 3, Supplementary Table S1). These genes include: (i) enzymes in amino acid metabolism, Accsl, Agxt, and Aspg were decreased or Got1l1, Hgd, Sds, and Sdsl were increased and (ii) amino acid transport, Slc22a2, Slc7a14, and Uroc1 were increased. Genes for: (i) enzymes in carbohydrate metabolism, Gys2, Lctl, Mgam, and Ppp1r3e and (ii) glucose transport, Adamts5, Rtn2, Slc2a2, Smpd5, and Syp were up regulated, but (iii) insulin signaling, Dusp9, Fbxo40, Grb14, and Ptpre were down regulated.

Nod2 −/− mice on HFD had an overall decrease in the expression of genes involved in (i) neural signaling, including Brinp3, Cadps2, Dlg2, Itpka, Mylka, Prickle2, Shisa6, Sorcs1, Syt15; (2) nerve adhesion, Celsr2, Cntn1, Fat3, Lsamp, Ncam1, Ncam2, Nfasc, and Nlgn1; and (iii) transcriptional regulators for neural development, Ascl1, Hesx1, and Id4 (Fig. 3, Supplementary Table S1).

Genes involved in other cellular functions, including cell cycle, development, cell adhesion, and cytoskeleton were also differentially expressed (Fig. 3, Supplementary Table S1). Nod2 −/− HFD mice also had an overall decrease in the expression of genes involved in (i) cell adhesion and signaling, including Adgra1, Adgrg2, Cdh12, Cdh9, Cldn22, Col12a1, Col6a5, Col6a6, Pcdh20, Pcdhb12, Pcdhb16, Pcdhb18, Pcdhb9, Rassf6, Sned1, and Thsd4; and (ii) inhibition of apoptosis, including Angpt1, Dusp26, Egln3, Hspa1a, and Pde3a. There was an overall increase in expression of genes involved in: (i) DNA structure, repair and chromatin silencing, for example, Hist1h1d, Hist1h1e, Hist1h2al, Hist1h2be, Hist2h3c2, and Mutyh; (ii) transcription and post-transcriptional processing, Abra, Inpp4b, Lbx2, Pcbd1, Pnldc1, Rbm28, and Rpph1; and (iii) proteases and protease inhibitors, Adam23, Cpa2, Itih1, Itih3, Lonrf3, Psma8, Serpina11, Serpina1d, Serpina1e, Serpina3e-ps, Serpina3m, and Wfdc18. However, there was a noticeable decrease in genes involved in translation and post-translational processing, B3galt1, B3galt2, Fam129a, Galnt5, St8sia2, Tgm3, Tgm5, Ttll2, and Ttll7.

Thus, our results indicate that genes involved in a wide array of pathways and cellular functions are differentially regulated in the adipose tissue of Nod2 −/− HFD mice compared with WT HFD mice. These changes in gene expression may contribute to the increased adiposity, steatosis, obesity, and metabolic dysfunction observed in Nod2 −/− mice on HFD. Future studies should confirm these changes at the protein level and focus on their role in the development of obesity in Nod2 −/− HFD mice.

Diet-dependent obesity in Nod2 −/− mice is associated with changes in the expression of liver genes involved in intermediary metabolism

We next identified genes that were differentially expressed in the liver of WT and Nod2 −/− BALB/c mice maintained on HFD for 30 weeks using RNA transcriptomics. Nod2 −/− HFD mice had 188 genes with significantly increased expression (and fold change ≥2) and 130 genes with significantly decreased expression (and fold change ≤0.5) compared with WT mice on HFD (Supplementary Fig. S2). 87% of the differentially expressed genes are associated with a function or pathway (Ensembl or DAVID) and are shown in Fig. 4 and Supplementary Table S2. Of these genes, there were more than 60 genes that directly or indirectly participate in intermediary metabolism, primarily lipid metabolism and include genes for enzymes, transport, and regulation. For example, Nod2 −/− HFD mice had higher expression of enzymes and regulators involved in: (i) synthesis and storage of fatty acids, triglycerides, steroids, and glycolipids, Acacb, Acss2, Elovl3, Elovl6, Fitm1, G0s2, Hsd3b5, Mogat1, Scd1, and St6galnac4; (ii) catabolism of lipids, Pla2g4f, Pnpla3, Pnpla5, Pex11a, and Phyhip; and (iii) carbohydrate metabolism, Gck, Pdk4, and Ppp1r3e. Several genes involved in transport of metabolites and nutrients were down regulated, including Aqp4, Fabp5, Ndgr1, and Slco1A1, whereas other transporters were up regulated, including Cd36, Mfsd2a, Osbpl5, Pltp, Slc10a2, Slc16a13, and Slc2a4 (Glut4). Nod2 −/− HFD mice had decreased expression of the leptin receptor (Lepr).

Figure 4 Differential expression of genes for immunity, metabolism, and other cellular functions in the liver of Nod2 −/− mice on HFD. Heatmap representation of the fold increase (red) or decrease (green) for gene expression in the adipose tissue of Nod2 −/− HFD mice compared with WT HFD mice. The genes are grouped based on function or pathway. The fold ratio for individual Nod2 −/− HFD mice to the average of WT HFD mice was computed and is shown (lanes 1 to 6) with the average of the fold for all Nod2 −/− HFD mice. Genes that had a fold change of ≥2 or ≤0.5 (≤−2) and P ≤ 0.05 with 5% FDR are included in the heatmap. N = 6 mice/group. The numerical data for fold increase in individual mice, the average, P value, and FDR are shown in Supplementary Table S2. Full size image

Nod2 −/− mice on HFD had about 50 genes involved in immune responses that were differentially expressed in the liver compared with WT mice on HFD (Fig. 4, Supplementary Table S2). Transcription factors involved in the activation of immune cells, Arl2bp, Cbfa2t3, and Cebpε, were increased, whereas transcriptional repressors Bcl6 and Cam1kd were decreased. There was a noticeable increase in the expression of many interferon-induced genes, including the chemokines Cxcl9, Cxcl10, and Cxcl11. Genes for the T cell receptor Cd8α and retinoic acid metabolism, Cyp26b1, Raet1δ, and Raet1ε, that regulate T and NK cell immune responses were induced, but genes in arachidonic acid metabolism, Alox15, Cyp2c54, Cyp2g1, and Cyp2s1, were inhibited.

Nod2 −/− mice on HFD had increased expression of many liver genes involved in DNA structure, replication, and repair (Fig. 4, Supplementary Table S2). Genes for serine protease inhibitors (Itih5, Serpina4-ps1, Serpina7, and Serpina9), chaperones (Hsp1a and Hsp1b), and ubiquitination (Kelch33, Klhl33, Trim13, and Ube2ql1) were decreased. Genes for cell cycle and cell proliferation were overwhelmingly induced, however many genes involved in development were down regulated, including transcription factors (Irx1, Klf4, Meox1, Sox9, Sp5, and Tbx3), signaling molecules (Arhgef40, Dact2, Mpzl1, Mrgpre, and Pdgfc) and components of the Wnt pathway (Axin2, Bcl7c, Wif1, and Lgr5). Several genes involved in neural development were down regulated, including proteins involved in ion and vesicular transport (Adam11, Cacnα1d, Syngr1, and Syt9) and neural signaling (Aph1c, Cadm4, and Pde6c). However, genes for acetylcholine receptor (Chrna4) and signaling at the neuronal junction were up regulated (Clstn3, Cntnap1, and Pclo). The tyrosine kinase receptor, Ntrk2, which has a role in suppressing appetite, was also up regulated (Fig. 4, Supplementary Table S2).

Nod2 −/− mice on HFD had increased expression of many genes involved in extracellular matrix organization and cell adhesion, including Col27a1, Esm1, Hapln1, Hmcn2, Lamb3, Myo7b, and Pcdh17. Genes involved in vesicle trafficking (Rab11fip4, Rab2b, Rasl2–9, and Sptb) and proton, sodium and sulfur transport (Atp6v0d2, Slc4a9, Slc8a3, Sult3a1, Sult5a1, and Wnk4) were down regulated, whereas genes for zinc and iron uptake (Slc39a5 and Tfrc) were increased (Fig. 4, Supplementary Table S2).

These results indicate that in the liver, genes involved in a wide array of pathways and cellular functions are differentially regulated by HFD in Nod2 −/− mice compared with WT mice. These changes in gene expression may contribute to the increased adiposity, steatosis, obesity, and metabolic dysfunction observed in Nod2 −/− mice on HFD. Future studies should confirm these changes at the protein level and focus on their role in the development of obesity in Nod2 −/− HFD mice.

Nod2 −/− genotype and HFD and LFD affect diversity of stool microbiome

Because intestinal microbiome is important for energy extraction from food, we determined the diversity of intestinal bacteria in WT and Nod2 −/− mice on HFD and LFD, to identify in detail the differences in their intestinal microbiota. We isolated DNA from stool microbiota and performed genetic phylotyping (community profiling) using pyrosequencing of the variable regions of bacterial 16S ribosomal RNA (rRNA) genes. To determine the effect of genotype, we compared microbiomes in WT and Nod2 −/− mice on the same diets, and to determine the effect of diets, we compared microbiomes in mice of the same genotype fed HFD or LFD.

We first evaluated α-diversity of the microbiomes of WT and Nod2 −/− mice on HFD and LFD. We identified a total of 223 species and 4425 operational taxonomic units (OTUs) in the stools of all mice: 153, 172, 180, and 164 species and 2344, 2589, 2392, and 2381 OTUs in WT HFD, Nod2 −/− HFD, WT LFD, and Nod2 −/− LFD mice, respectively. The total number of OTUs identified in Nod2 −/− HFD mice was significantly higher than in WT HFD mice, whereas the total numbers of OTUs in Nod2 −/− LFD and WT LFD mice, as well as total numbers of species in all groups of mice were similar with no significant differences between the groups (Supplementary Fig. S3). The numbers of species and OTUs per mouse (microbiome richness) were similar in all groups of mice, except for WT LFD mice, which had significantly more species/mouse than WT HFD mice. Both Shannon diversity indices (H) and Shannon equitability indices (E H , reflecting microbiome evenness) were significantly higher for the species in Nod2 −/− HFD than in WT HFD mice, and for both the species and OTUs in WT LFD than in Nod2 −/− LFD mice, and also for both the species and OTUs in WT LFD than in WT HFD mice (Supplementary Fig. S3). These results show that both Nod2 −/− genotype on HFD and WT genotype on LFD may increase α-diversity, although these changes are very modest.

We then evaluated β-diversity of the microbiomes. Microbiota from stools of all four groups of mice (WT HFD, Nod2 −/− HFD, WT LFD and Nod2 −/− LFD) separated from each other in the Principal Coordinate Analysis (PCoA), with microbiota from each group of mice showing distinct and significant separation from the microbiota of all other groups of mice (Fig. 5a). These results suggested differences in β-diversity in the intestinal microbiomes between all four groups of mice with both the genotype (WT and Nod2 −/−) and the diet (HFD and LFD) affecting β-diversity of stool microbiomes. These results prompted us to further identify the differences between these microbiomes.

Figure 5 β-diversity in stool microbiota of WT HFD, Nod2 −/− HFD, WT LFD, and Nod2 −/− LFD mice. (a) Principal Coordinate Analysis (PCoA) by UniFrac (unweighted) of microbiomes. Each sphere with confidence elipsoid corresponds to a stool microbiome from one mouse. N = 6 mice/group. (b) Class abundance expressed as % of total stool microbiota; *classes with significantly (at P ≤ 0.05) increased abundance in WT versus Nod2 −/− mice (on HFD or LFD); #classes with significantly (at P ≤ 0.05) increased abundance in HFD versus LFD groups (for WT or Nod2 −/− mice); N = 6 mice/group. The results for individual mice are shown in Supplementary Fig. S4. The entire microbiome analysis data comparing bacterial diversity in the stools of WT and Nod2 −/− mice maintained on HFD and LFD have been deposited in NCBI SRA, accession No. SRP076031. Full size image

We detected many statistically significant effects of both Nod2 genotype and the diet on bacterial β-diversity, with many significant changes in the abundance of various bacterial groups in the stools at all taxonomic levels. For example, at the class level (Fig. 5b and Supplementary Fig. S4), WT HFD mice had significantly increased abundance of Epsilonproteobacteria compared with Nod2 −/− HFD mice, and Nod2 −/− HFD mice had significantly increased abundance of Deferribacteres compared with WT HFD mice. In mice on LFD, WT mice had significantly higher abundance of Candidatus saccharibacteria than Nod2 −/− mice, and Nod2 −/− mice had significantly higher abundance of Deferribacteres than WT mice. The diet also had a pronounced effect on stool microbiota. HFD significantly increased the abundance of Clostridia and Deltaproteobacteria in both WT and Nod2 −/− mice and also Deferribacteres in Nod2 −/− mice, whereas LFD significantly increased the abundance of Bacteroida, Bacilli, and Erysipelotrichia in both WT and Nod2 −/− mice, and also Candidatus saccharibacteria in WT mice.

At other taxonomic levels, significant differences in abundance in the following numbers of orders, families, genera, species, and OTUs (out of total of 27, 47, 109, 223, and 4425) were detected: between WT HFD and Nod2 −/− HFD mice, 2, 2, 9, 26, and 548; between WT LFD and Nod2 −/− LFD mice, 6, 10, 20, 46, and 601; between WT HFD and WT LFD, 8, 14, 24, 48, and 535; and between Nod2 −/− HFD and Nod2 −/− LFD mice, 6, 9, 16, 35, and 288, respectively (NCBI SRA, accession No. SRP076031). Thus, both Nod2 genotype of mice and their diet together significantly influence the diversity of their microbiomes.

We then further analyzed the differences in microbiomes between Nod2 −/− HFD mice and the remaining groups of mice, because these mice had significantly higher weight gain and significant manifestations of metabolic syndrome compared with the other groups of mice, and moreover, these differences were abolished by treatment with antibiotics (next section). Nod2 −/− HFD mice, compared with WT HFD mice, had significantly higher abundance of six Firmicutes, three Bacteroidetes, two Deferribacteres, one Proteobacteria, and one Actinobacteria species (Table 1). Importantly, three of these bacterial species, both Deferribacteres and one Firmicutes (Lachnoclostridium phytofermentans) had significantly higher abundance in Nod2 −/− HFD mice than in the other three groups of mice, thus showing the best correlation with obesity and metabolic syndrome, since Nod2 −/− HFD mice was the only group with significantly higher obesity and metabolic syndrome. There were no bacterial species with significantly decreased abundance in Nod2 −/− HFD mice compared with all other groups of mice.

Table 1 Bacterial species with significantly higher abundance in Nod2 −/− HFD mice than in WT HFD mice*. Full size table

Diet-induced obesity in Nod2 −/− BALB/c mice is abolished by long-term antibiotic treatment

We next determined the role of the gut microbiota in diet-dependent obesity in Nod2 −/− mice by depleting gut bacteria with antibiotics. WT and Nod2 −/− mice, starting at 4 weeks of age, were given an antibiotic mix (Abx) of ciprofloxacin and metronidazole in their drinking water, which is an established method for depleting gut bacteria20, 23,24,25. After three weeks the animals were placed on HFD and Abx were continued, and body weight was measured each week (Fig. 6a). Control mice were started on HFD at the same age, but never treated with Abx. Our results demonstrate that Abx treatment completely abolished the diet-dependent weight gain in Nod2 −/− mice, but did not affect the weight gain in WT mice (Fig. 6b). Nod2 −/− Abx HFD mice gained significantly less weight than Nod2 −/− HFD mice, and also less than WT HFD mice with and without Abx. There was no difference in weight gained between WT Abx HFD and WT HFD mice. There was no difference in food consumption or water intake between the WT Abx HFD and Nod2 −/− Abx HFD, as average food consumed/mouse/day was 1.86 g and 1.89 g, respectively, and the average water intake/mouse/day was 2.9 ml for both genotypes. There is some decrease in water intake between the antibiotic treated versus control mice, however this decrease does not account for the difference in the weight gain observed between WT and Nod2 −/− mice, because both genotypes on antibiotics had similar decrease in water intake but only Nod2 −/− mice had significantly reduced weight gain.

Figure 6 Antibiotic treatment prevents the development of obesity, steatosis, and metabolic dysfunction in Nod2 −/− mice on HFD. (a) Nod2 −/− and WT mice were treated with Abx to deplete their intestinal microbiota. Control mice were not treated with antibiotics. Three weeks after the start of Abx all mice were placed on HFD and monitored for weight gain, histopathology, and metabolites. (b) Percent gain in weight compared to week 0 of HFD. (c,d) After 14 weeks of HFD, mice were analyzed for liver histopathology in BODIPY and DAPI stained sections and (d) percent frequency distribution of LD area (µm2) for ~4,000 LDs/group. (e–h) After 14 weeks of HFD, (e) liver triglycerides, (f) liver cholesterol, (g) serum cholesterol, and (h) serum triglycerides were measured. (b,d) Results are means ± SEM, (C) representative images, and (e–h) individual data of 6–10 mice/group. *P ≤ 0.05 and **P ≤ 0.001, Nod2 −/− Abx + HFD versus Nod2 −/− HFD. Full size image

We next determined whether the antibiotic-induced loss in weight gain was accompanied by decreased lipid accumulation in the liver of Nod2 −/− mice using histological and biochemical assays. Our results demonstrate that Nod2 −/− mice treated with long-term Abx and maintained on HFD had smaller LDs in hepatocytes compared with Nod2 −/− mice not treated with Abx but maintained on HFD (Fig. 6c). The area for LDs ranged from 2 μm2 to 300 μm2 with the highest percentage of LDs in the 36 to 75 μm2 range for the HFD mice and 2 to 19 μm2 range for Abx + HFD mice (Fig. 6d). Nod2 −/− mice on Abx + HFD had significantly lower levels of liver cholesterol and triglycerides than control Nod2 −/− mice on HFD alone (Fig. 6e and f). Furthermore, Nod2 −/− mice on Abx + HFD had significantly lower levels of serum cholesterol and triglycerides (Fig. 6g and h), but no significant difference in glucose, compared with control Nod2 −/− mice on HFD alone.

Thus, our results demonstrate that the gut microbiota in Nod2 −/− HFD mice is required for the development of diet-dependent obesity, steatosis, and hyperlipidemia in Nod2 −/− mice, and that long-term treatment with broad-spectrum antibiotics abolishes weight gain and several aspects of metabolic dysfunction.

Intestinal microbiota from Nod2 −/− mice on high fat diet increases sensitivity to obesity

We next considered whether the altered gut microbiota in Nod2 −/− mice on HFD is sufficient for the development of diet dependent obesity. We colonized germ-free pregnant female WT Swiss-Webster mice by co-housing with either Nod2 −/− HFD mice or WT HFD mice, and also by weekly gavaging with microbiota from either Nod2 −/− HFD mice or WT HFD mice. We placed these mice on HFD after the first gavage (Fig. 7a). We removed the co-housed mice one day after delivery, but continued weekly gavaging and HFD, and monitored the weight gain of pups for 8 weeks. Germ-free pups colonized with microbiota from Nod2 −/− HFD mice were more susceptible to HFD-dependent weight gain than pups colonized with microbiota from WT HFD mice, as manifested by significantly higher weight gain (Fig. 7b). Furthermore, pups colonized with Nod2 −/− HFD microbiota were also more susceptible to HFD-induced metabolic dysfunction, as they had significantly higher liver cholesterol and triglycerides, and higher serum glucose than pups colonized with microbiota from WT HFD mice (Fig. 7c–e), but there was no difference in serum cholesterol or triglycerides between the 2 groups of mice. In conclusion, microbiota from Nod2 −/− HFD mice can transfer to WT outbred germ-free mice enhanced susceptibility to HFD-dependent weight gain and metabolic dysfunction.