Obesity and its associated comorbidities (for example, diabetes mellitus and hepatic steatosis) contribute to approximately 2.5 million deaths annually1 and are among the most prevalent and challenging conditions confronting the medical profession2,3. Neurotensin (NT; also known as NTS), a 13-amino-acid peptide predominantly localized in specialized enteroendocrine cells of the small intestine4 and released by fat ingestion5, facilitates fatty acid translocation in rat intestine6, and stimulates the growth of various cancers7. The effects of NT are mediated through three known NT receptors (NTR1, 2 and 3; also known as NTSR1, 2, and NTSR3, respectively)8. Increased fasting plasma levels of pro-NT (a stable NT precursor fragment produced in equimolar amounts relative to NT) are associated with increased risk of diabetes, cardiovascular disease and mortality9; however, a role for NT as a causative factor in these diseases is unknown. Here we show that NT-deficient mice demonstrate significantly reduced intestinal fat absorption and are protected from obesity, hepatic steatosis and insulin resistance associated with high fat consumption. We further demonstrate that NT attenuates the activation of AMP-activated protein kinase (AMPK) and stimulates fatty acid absorption in mice and in cultured intestinal cells, and that this occurs through a mechanism involving NTR1 and NTR3 (also known as sortilin). Consistent with the findings in mice, expression of NT in Drosophila midgut enteroendocrine cells results in increased lipid accumulation in the midgut, fat body, and oenocytes (specialized hepatocyte-like cells) and decreased AMPK activation. Remarkably, in humans, we show that both obese and insulin-resistant subjects have elevated plasma concentrations of pro-NT, and in longitudinal studies among non-obese subjects, high levels of pro-NT denote a doubling of the risk of developing obesity later in life. Our findings directly link NT with increased fat absorption and obesity and suggest that NT may provide a prognostic marker of future obesity and a potential target for prevention and treatment.


To examine the potential role of NT in fat deposition and obesity, we initially compared NT-deficient mice10,11 to wild-type littermates fed a standard diet (18% kcal from fat) for 6 months. Average body length, small intestine weight and length, villus height and crypt number did not differ between genotypes (Extended Data Fig. 1a–f). However, the epididymal and retroperitoneal fat pads of Nt–/– mice were consistently smaller as compared to wild type (Extended Data Fig. 2a–c). Indeed, when challenged with a high-fat diet (HFD; 60% kcal from fat), epididymal, retroperitoneal and pericardiac fat deposits were markedly smaller in Nt–/– mice (Extended Data Fig. 2d–f). Moreover, body weight was significantly less in both male and female Nt–/– mice fed a HFD (Fig. 1a, b) and male Nt–/– mice fed a low-fat diet (LFD; 10% kcal from fat) (Extended Data Fig. 2g) compared with wild type. No differences in body weight were noted between female Nt+/+ and Nt–/– mice fed a LFD (Extended Data Fig. 2g). EchoMRI assessment of total fat (corrected for body weight) further confirmed reduced body fat composition in male Nt–/– mice (Extended Data Fig. 2h).

Figure 1: Protective effects of NT deficiency on obesity and comorbid conditions.
Figure 1

a, b, Representative male (a) and female (b) Nt+/+ and Nt–/– mice fed a HFD for 22 weeks (top). Body weight (BW) was measured weekly (bottom) (male Nt+/+ n = 18 and Nt–/– n = 17 mice; female Nt+/+ n = 15 and Nt–/– n = 12 mice). Body weight slopes were compared: *P < 0.05 Nt+/+ versus Nt–/– mice. c, Plasma glucose (top) and insulin (bottom) levels quantified in 24-h-fasted male mice maintained on a LFD or HFD for 24 weeks (LFD Nt+/+ n = 10, Nt–/– n = 10; HFD Nt+/+ n = 8, Nt–/– n = 10). *P < 0.05 versus LFD in Nt+/+ and Nt–/– mice, respectively; ‡P < 0.05 versus HFD in Nt+/+ mice. d, Blood glucose (BG) during insulin tolerance test (ITT) (left; n = 5) and glucose tolerance test (GTT) (right; n = 3) in 6-h-fasted male mice fed a HFD for 24 weeks. *P < 0.05 versus Nt–/– mice. e, Gross, haematoxylin and eosin (H&E) and oil red O (ORO) imaging of livers of male mice fed a HFD for 24 weeks (n = 5). Scale bar, 50 μm. f, Hepatic TG and cholesterol were analysed by liquid chromatography–mass spectrometry (LC–MS) in 24-h-fasted male mice fed a HFD for 24 weeks (n = 3). *P < 0.05 versus Nt+/+ mice. g, H&E staining of epididymal fat from male Nt+/+ and Nt–/– mice fed a LFD or HFD for 24 weeks (n = 5). h, Quantitative analysis of adipocyte area (n = 3). *P < 0.05 versus LFD in Nt+/+ and Nt–/– mice, respectively; ‡P < 0.05 versus LFD in Nt+/+ mice; ‡P < 0.05 versus HFD in Nt+/+ mice. All data are mean ± standard deviation (s.d.). Linear mixed model for a, b; analysis of variance (ANOVA) with Holm’s P-value adjustment for c, h; two-sided Student’s t-test for d, f (see Methods).

Obesity-associated insulin resistance was also attenuated in NT-deficient mice. On a HFD, NT-deficient mice demonstrated lower levels of fasting plasma glucose and insulin (Fig. 1c), greater insulin sensitivity and faster glucose clearance (Fig. 1d) compared with wild type. Consistently, insulin-stimulated phosphorylated (p)-Akt expression was decreased in the livers of Nt+/+ mice fed a HFD, whereas Nt–/– mice fed the same diet demonstrated a similar induction of p-Akt after injection of insulin, as noted for both wild-type and NT-deficient mice fed a LFD (Extended Data Fig. 2i). In contrast, there was no difference in insulin secretion when comparing Nt+/+ and Nt–/– mice maintained on a normal chow diet following either glucose administration by gavage or refeeding after a 16 h fast (Extended Data Fig. 2j, k). Hepatic steatosis (Fig. 1e), liver triglyceride (TG) and cholesterol accumulation (Fig. 1f) were significantly decreased in Nt–/– mice fed a HFD. Adipocytes in epididymal fat pads of Nt–/– mice showed a reduction in size (Fig. 1g, h) and decreased inflammatory infiltrates and numbers of macrophages (F4/80-positive cells) (Extended Data Fig. 2l, m). Together, these results indicate that NT deficiency protects against comorbidities (that is, increased insulin resistance and hepatic steatosis) associated with high dietary fat intake.

NT has been linked to hypothalamic leptin signalling12 and is considered to be an anorectic peptide based on acute suppression of food intake in rats after intracerebral or intraperitoneal (i.p.) administration of NT13,14. When considering total food intake over 22 weeks, there were no differences between genotypes in either male or female mice fed a LFD or males fed a HFD; however, a slight 10% decrease in female Nt–/– mice fed a HFD reached significance (Extended Data Fig. 3a). Weekly food consumption was not statistically different in male or female mice fed a LFD or males fed a HFD (Extended Data Fig. 3b, c); only the week 9 comparison in females fed a HFD reached significance (Extended Data Fig. 3c). Energy expenditure, locomotor activity, energy intake and respiratory exchange ratios were not different between Nt+/+ and Nt–/– mice fed either a HFD or LFD (Extended Data Fig. 3d–g). Although we cannot completely dismiss a potential effect of NT deficiency on feeding behaviour, this factor alone does not appear to play a major part in the lower weight gain observed in Nt–/– mice fed a HFD.

We next evaluated differences in intestinal lipid absorption as a possible mechanism for the decreased weight gain noted in NT-deficient mice. Compared to Nt+/+ mice, faecal TG content was increased by ~25% in Nt–/– mice fed a HFD (Fig. 2a), but was not associated with a change in stool colour, consistency or output (Extended Data Fig. 4a), indicating that NT deficiency decreases lipid absorption without overt signs of fat malabsorption (that is, steatorrhoea). Consistently, fewer and smaller lipid droplets were noted in the mucosa of the proximal intestine of Nt–/– mice at 30 and 60 min after olive oil gavage compared with Nt+/+ mice (Fig. 2b). To track and quantify intestinal absorption better, 13C18-oleic acid (13C18-OA) was administered by gavage and measured in the proximal intestine and plasma by Fourier-transform-based mass spectrometry (FT-MS). 13C18-OA was significantly decreased in the intestine and at 2 and 3 h in the plasma of Nt–/– mice (Fig. 2c). NT administration (3,600 nmol kg−1 body weight, i.p.)14 restored TG accumulation in Nt–/– mice to levels similar to those in Nt+/+ mice (Fig. 2d). Similarly, pre-treatment of C57BL/6 mice with SR 48692 (2.5 mg kg−1, i.p.), a selective non-peptide NTR1 antagonist that acts peripherally and centrally when administered either i.p. or by gavage15, decreased intestinal fatty acid absorption after olive oil gavage (Fig. 2e). To demonstrate further that the effect of SR 48692 was due to disruption of NT signalling, we repeated the experiment using Nt–/– mice and their wild-type littermates and found that, similar to our initial results, pre-treatment with SR 48692 inhibited intestinal fatty acid absorption in wild-type mice (as measured by TG accumulation); however, SR 48692 pre-treatment in Nt–/– mice did not further decrease lipid absorption after olive oil administration, which, as expected, was significantly decreased compared to wild-type mice (Extended Data Fig. 4b). These results indicate that SR 48692 attenuation of fat uptake reflects the disruption of normal NT signalling and is not due to an unanticipated off-target effect. NT treatment also increased fatty acid uptake in rat intestinal epithelial-1 (RIE-1) cells (Extended Data Fig. 4c, d) that express NTR1 and 3 (similar to human intestinal cells (FHs 74 Int)) and mouse intestinal mucosa (Extended Data Fig. 4e–g), and short interfering RNA (siRNA) knockdown of either NTR1 or NTR3—the protein products of which have been demonstrated to heterodimerize on the cell surface and to broaden the response range for NT signalling15—reduced NT-mediated fatty acid absorption (Extended Data Fig. 4h, i). Consistent with a role for NT in HFD-induced weight gain, treatment with SR 48692 (2.5 mg per kg body weight, oral gavage, twice a day) for 13 weeks significantly attenuated body weight gain in wild-type mice fed a HFD (Fig. 2f) without altering food intake (Extended Data Fig. 4j). Collectively, these results indicate that NT promotes intestinal lipid uptake through NTR1, and possibly NTR3, promoting weight gain in mice fed a HFD. Interestingly, it was recently demonstrated16 that NTR3-deficient mice, when placed on a HFD, exhibited a similar phenotype as NT-deficient mice, thus further emphasizing the potential importance of the NT/NTR axis in weight gain associated with an overabundance of fat.

Figure 2: NT deficiency reduces intestinal lipid absorption.
Figure 2

a, Faecal TG was analysed in male mice fed a HFD for 24 weeks (n = 3). *P = 0.05 versus Nt+/+ mice. b, ORO staining of proximal intestines from male mice fed normal chow with or without olive oil by oral gavage after overnight fasting (n = 3). Scale bar, 50 μm. c, Levels of 13C18-OA in male mice fed normal chow and given 13C18-OA mixed in olive oil by gavage after an overnight fast were analysed by nanospray FT-MS. Left (n = 5), *P < 0.05 versus Nt+/+ mice. Right (n = 4), *‡P < 0.05 versus 0 h in Nt+/+ and Nt–/– mice, respectively; ‡P < 0.05 versus 2 h and 3 h in Nt+/+ mice. d, ORO staining of proximal intestines from male mice following gavage with saline, olive oil, or olive oil plus NT (3,600 nmol kg−1 body weight, i.p.) after an overnight fast (left; n = 5). Scale bar, 50 μm. TG (in mg) was quantified in proximal intestines and normalized to the amount of protein (in mg) as described in Methods (right; n = 5). Graph presents the fold change versus saline in Nt+/+ mice. *P < 0.05 versus saline in Nt+/+ and Nt–/– mice, respectively; ‡P < 0.05 versus olive oil in Nt+/+ mice; ‡P < 0.05 versus olive oil in Nt–/– mice; P < 0.05 versus olive oil in Nt+/+. e, Proximal intestines from mice given saline, olive oil, or olive oil plus SR 48692 were collected and TG levels were quantified as described earlier (n = 8). Graph presents the fold change versus control mice. *P < 0.05 versus control mice; ‡P < 0.05 versus mice with olive oil only. f, Weekly body weight was measured in male wild-type C57BL/6 mice fed a HFD and treated with SR 48692 (2.5 mg per kg body weight, diluted in distilled H2O and administered by oral gavage twice a day) or vehicle (vehicle n = 12; SR 48692 n = 13). Body weight slopes were compared: *P < 0.05 vehicle versus SR treatment. g, FHs 74 Int cells were pre-treated with or without NT at different doses as indicated for 30 min followed by combined treatment with oleate (0.1 mM) or bovine serum albumin (BSA) for 1 h and western blotting of cell extracts (top); densitometric analysis of p-AMPK is from three separate experiments and normalized to total AMPK; graph demonstrates the fold change of p-AMPK versus control (BSA; bottom). *P < 0.05 versus BSA; ‡P < 0.05 versus oleate alone. h, FHs 74 Int cells were treated with or without NT (2 μM) for 30 min followed by AICAR (1 mM) for 2 h and oleate (0.1 mM) or BSA for 1 h and analysed by western blot (top); p-AMPK levels were determined as in g from three separate experiments (bottom). *P < 0.05 versus control (BSA); ‡P < 0.05 versus oleate alone; ‡P < 0.05 versus oleate plus AICAR. i, FHs 74 Int cells were treated with NT (2 μM) for 30 min followed by addition of AICAR (1 mM) for another 3 h; cells were then incubated with BSA or 4,4-difluoro-5,7-dimethyl-4-bora-3a,4a-diaza-s-indacene-3-hexadecanoic acid C16 (BODIPY FL C16) for 15 min and images were taken by confocal microscopy (original magnification, ×180). Representative images are from three experiments. All data are mean ± s.d. Two-sided Student’s t-test for a, c (left); ANOVA with Holm’s P-value adjustment for c (right), d (right), e, g (bottom), h (bottom); linear mixed model for f (see Methods). (See Supplementary Fig. 1 for gel source data.)

AMPK, a key fuel-sensing enzyme and a critical regulator of metabolism, mediates the effects of a variety of hormones17,18. Phosphorylated-AMPK (p-AMPK) was increased in the proximal intestinal mucosa of Nt–/– mice fed a standard diet compared with wild type (Extended Data Fig. 5a). p-AMPK expression was decreased in the proximal intestine of Nt+/+ mice after olive oil gavage but was restored to control levels with SR 48692 pre-treatment (Extended Data Fig. 5b). Treatment of FHs 74 Int and RIE-1 cells with oleate led to an increase in p-AMPK (Extended Data Fig. 5c), which was reduced by NT pre-treatment (Fig. 2g and Extended Data Fig. 5d). Pharmacological activation of AMPK with 5-aminoimidazole-4-carboxamide-1-β-d-ribofuranoside (AICAR) further increased oleate-stimulated p-AMPK (Fig. 2h) and concomitantly decreased fatty acid absorption (Fig. 2i); these effects were blocked by NT pre-treatment. NT-mediated suppression of p-AMPK was prevented by either NTR1 or NTR3 knockdown (Extended Data Fig. 5e, f). Knockdown of the upstream AMPK kinase Ca2+-calmodulin-dependent protein kinase kinase (CaMKK2)19,20, but not liver kinase B1 (LKB1)21, decreased oleate-stimulated p-AMPK (Extended Data Fig. 5g). Moreover, overexpression of CaMKK2 attenuated NT-mediated suppression of p-AMPK (Extended Data Fig. 5h). Together, these findings suggest that NT, acting through NTR1 and/or NTR3, increases fatty acid absorption through suppression of CaMKK2-mediated AMPK phosphorylation.

Drosophila provide a powerful model system to understand molecular mechanisms regulating human metabolic disorders better. To establish further the role of NT on intestinal lipid absorption and AMPK regulation, human full-length NT complementary DNA (cDNA) was expressed in Drosophila midgut enteroendocrine cells using the enteroendocrine-cell-specific driver Gr36C-Gal4 (ref. 22) (see colocalization with enteroendocrine-cell-specific transcription factor Prospero23,24; Extended Data Fig. 6a, b); mature NT1,2,3,4,5,6,7,8,9,10,11,12,13 peptide was detected in larval gut (3.1 fg per gut) and Drosophila S2 cells transfected with NT cDNA (Extended Data Fig. 7). Compared to control, NT expression markedly increased lipid droplets in the midgut of 7-day-old adult (Fig. 3a) and larvae (Extended Data Fig. 6c) fed a standard diet, and also increased the accumulation of lipid droplets in oenocytes (Fig. 3b) and fat bodies (Fig. 3c) of Gr36C-NT 3rd instar larvae. Next, we used a diet-induced obesity model in Drosophila25 to demonstrate increased lipid droplets in the midgut of control flies fed a HFD compared with flies fed standard food (SDF). NT expression dramatically increased lipid accumulation in the midgut (Fig. 3d) and total body TG levels (Fig. 3e) with either a SDF or HFD, suggesting that NT promotes efficient lipid absorption, and that this effect is further enhanced by increased fat concentration. Consistently, we also found that NT expression decreased gut p-AMPK levels in both adults and larvae (Fig. 3f and Extended Data Fig. 6d). These findings suggest that, similar to mice, the effects of NT on lipid absorption are mediated, in part, through AMPK regulation. Indeed, we found that AMPK overexpression decreased, whereas AMPK knockdown increased lipid droplets in the midgut of 7-day-old adults (Fig. 3g) and the midgut, fat body and oenocytes of larvae (Extended Data Fig. 6e–g).

Figure 3: NT suppresses AMPK activation and promotes lipid accumulation in Drosophila.
Figure 3

a, Midguts from 7-day-old adult flies expressing either Gr36C-w1118 (control, 100%, n = 7; the percentage used here and in subsequent analyses indicates the percentage of organs exhibiting the phenotype) or Gr36C-NT (93%, n = 15) were stained with BODIPY. Scale bar, 100 μm. b, Oenocytes on the basal surface of the lateral epidermis of 3rd instar larvae expressing Gr36C-w1118 (100%, n = 15) or Gr36C-NT (93%, n = 15) were stained with BODIPY to monitor lipid accumulation (green) and the anti-HNF4 antibody to mark the oenocytes (red). Scale bar, 50 μm. c, Fat bodies attached to the salivary gland from the 3rd instar larvae expressing Gr36C-w1118 (100%, n = 14) or Gr36C-NT (100%, n = 8) were stained with BODIPY. Scale bar, 50 μm. d, Flies expressing Gr36C-w1118 or Gr36C-NT (n = 5) were fed either SDF or HFD, and guts were stained with Nile Red to examine the accumulation of lipids (arrows). Scale bar, 100 μm. e, NT was expressed by voila-Gal4 and TG (in mg) was measured and normalized to body weight (in mg) in male adult flies fed either SDF or HFD (n = 3). voila-w1118 served as control. *P < 0.05 versus SDF in control- and NT-expressing flies, respectively; ‡P < 0.05 versus SDF in control flies; ‡P < 0.05 versus HFD in control flies. f, Western blotting was performed to monitor the levels of AMPK in adult midgut shown in a. g, Myo1A-Gal4 combined with tub-Gal80ts (Myots) does not express active Gal4 at 20 °C permissive temperature. Shown on the left is the midgut from a 7-day-old adult expressing Myots-AMPK raised at 20 °C, stained with BODIPY, and used as a control (100%, n = 11). Midguts expressing AMPK (middle; 94%, n = 16) or AMPKRNAi25931 (right; 100%, n = 12) from 7-day-old adults at 29 °C (active Gal4) were stained with BODIPY. Scale bar, 100 μm. The levels of AMPK were monitored by western blot. All data are mean ± s.d. ANOVA with Holm’s P-value adjustment for e (see Methods). (See Supplementary Fig. 1 for gel source data.)

To identify the endogenous Drosophila NTR, we carried out a targeted RNA interference (RNAi) screen in S2 cells; expression of NT or treatment with NT peptide consistently decreased p-AMPK (Extended Data Fig. 8a, b). Among the three potential Drosophila NTRs26,27, RNAi of CG9918 (Pyrokinin 1 receptor (PK1-R)), but not CG8784 or CG8795, blocked the decrease in p-AMPK levels in NT-expressing cells (Extended Data Fig. 8a). The effect of NT does not appear to be due to interference with PK-1 signalling, since PK-1 (encoded by Capability) knockdown did not alter p-AMPK levels (Extended Data Fig. 8d). Knockdown of CG9918 expression in enterocytes using Myo1A-Gal4 to drive UAS-CG9918 RNAi (TRiP 27539) expression in flies also expressing NT driven by the enteroendocrine-cell-specific tachykinin (TK) promoter28,29 markedly attenuated NT-induced lipid droplet accumulation (Extended Data Fig. 8c). These results indicate that NT increases lipid accumulation, at least in part, through CG9918, an NTR-like receptor that shares 32% identity and 50% similarity with mouse NTR1 (Extended Data Fig. 8e), suggesting an evolutionarily conserved function for NTR signalling in lipid uptake.

The mouse and Drosophila data prompted us to assess the possible role of NT in the development of obesity and its metabolic complications in humans. Fasting plasma concentrations of pro-NT were analysed from 4,632 middle-aged subjects of the population-based Malmö Diet and Cancer Study Cardiovascular Cohort (MDC-CC)9 (Extended Data Table 1). The age- and sex-adjusted likelihood of being obese, abdominally obese and insulin resistant significantly increased across quartiles of pro-NT plasma levels (P = 0.01, 0.001 and <0.0001, respectively; Table 1). Continuous values of pro-NT were also significantly related to continuous values of body mass index (BMI), waist circumference and homeostasis model assessment of insulin resistance (Extended Data Table 2). Among non-obese subjects, the risk of developing obesity during an average follow-up time of 16.5 ± 1.5 years increased gradually with pro-NT quartiles, independently of baseline BMI, age and gender (P < 0.0001; Table 1). Importantly, non-obese subjects in the top quartile of baseline pro-NT levels had greater than double the risk of developing obesity compared to those in the lowest quartile (odds ratio = 2.05, 95% confidence interval (CI): 1.38–3.06). Whereas the cross-sectional relationship between pro-NT and obesity became non-significant after additional adjustment for insulin resistance, the prospective relationship between pro-NT and risk of new-onset obesity remained highly significant (P = 0.001) after adjustment for insulin resistance (data not shown). Thus, pro-NT levels strongly predict new onset obesity in a graded manner, which is independent of baseline BMI and insulin resistance. These findings in adults warrant further prospective studies to evaluate whether pro-NT levels can be used to predict future obesity in children and adolescents.

Table 1: Pro-NT levels and association with clinical outcomes

Our findings demonstrate a critical role of NT in HFD-induced obesity that involves decreased AMPK activation and increased intestinal lipid absorption. Moreover, we identify increased pro-NT levels as a strong risk factor of human obesity. From an evolutionary perspective, metabolically ‘thrifty’ genes, such as NT, are highly beneficial to ensure the efficient absorption of all ingested fats, but with the abundance of fats in typical Western diets, NT can have a detrimental effect by contributing to increased fat storage, obesity and related metabolic disorders.



Phospho-AMPKα (Thr172) (2535), AMPKα (2532), LKB1 (3050), phospho-Akt (Ser-473) (4058) and pan-Akt (4691) antibodies were from Cell Signaling Technology (Danvers, MA). NTR1 antibody (sc-374492) was from Santa Cruz Biotechnology (Dallas, TX). CaMKK2 (ab168818), NTR3 (ab16640), and F4/80 (ab100790) antibodies were from Abcam (Cambridge, MA). Flag (F1804) and β-actin (A5316) antibodies were from Sigma-Aldrich (St Louis, MO). AICAR was from Cayman (Ann Arbor, MI). Oleate sodium, NT1–13, glucose and human insulin were from Sigma. Deuterated oleic acid (CLM-460-PK) was obtained from Cambridge Isotope Laboratories (Tewksbury, MA). SR 48692 was from Tocris (Minneapolis, MN). Lipofectamine RNAiMAX and LTX Reagent with PLUS transfection reagents and Trizol were from Life Technologies (Grand Island, NY). pSG5-Flag-CaMKK2 rat FL was a gift from A. Means30 (Addgene plasmid #32449, Cambridge, MA). Primers for RT–PCR were from Integrated DNA Technologies (Coralville, IA).

siRNA and sequences



All procedures were approved by the Institutional Animal Care and Use Committee of the University of Kentucky. Nt–/– mice and their wild-type littermates (Nt+/+) were bred from Nt+/– mice and randomly grouped for all experiments. Mice were maintained with a 14 h light/10 h dark cycle and provided with food and water ad libitum. For diet-induced obesity studies, male and female Nt+/+ and Nt–/– mice were placed on a 60% HFD or 10% LFD (catalogue no. D12492 and D12450B, respectively; Research Diets, New Brunswick, NJ) at weaning for 22–24 weeks. Body weight (and food intake were measured weekly. Food intake was measured for each cage (3–5 mice per cage) and divided by mouse number to obtain total grams consumed per mouse per week. All mice used were 4–6 months old unless otherwise indicated. For chronic SR 48692 treatment on HFD-fed mice, male C57BL/6 mice (2 months old) were obtained from Taconic. After 1 week acclimation, mice were placed in individual cages, started on HFD, and after 1 week were divided into two groups, one of which received SR 48692 (dissolved in sterile distilled H2O by brief sonication, 2.5 mg per kg body weight31,32,33 and the other vehicle twice a day (8 a.m. and 8 p.m.) by gavage. Body weight and food intake were measured weekly.

Human intestinal samples

Surgical samples of duodenum and colon were obtained from de-identified donors through the Markey Cancer Center Biospecimen and Tissue Procurement Shared Resource Facility. All samples were obtained after informed consent according to a protocol approved by the Institutional Review Board of the University of Kentucky Medical Center (UKMC). Tissues were processed within 1 h after resection; the mucosal layer was sharply dissected from the underlying seromuscular layer and collected in multiple 3–5 mm sections for western blotting.

Cell lines, transfection and treatment

FHs 74 Int human small intestinal epithelial cells34 were purchased from ATCC (Manassas, VA) and maintained in Hybri-Care Medium ATCC 46-X supplemented with 30 ng ml−1 epidermal growth factor (Sigma-Aldrich) and 10% FBS. RIE-1 rat intestinal epithelial cells35 were maintained in DMEM containing 2 mM l-glutamine, 4,500 mg l−1 glucose and 10% FBS. FHs 74 Int cells were tested for authentication via STR profiling in April 2015 by Genetica DNA Laboratories (LabCorp Speciality Testing Group; Burlington, NC) using the commercially available PowerPlex 16HS amplification kit (Promega Corporation) and GeneMapper ID v.3.2.1 software (Applied Biosystems). Authentication was confirmed by a 100% match in comparison to the reference STR profile from ATCC (FHs 74 Int; ATCC CCL-241). The cell lines are not listed in the International Cell Line Authentication Committee (ICLAC) database. In addition, both cell lines were tested for mycoplasma contamination via PCR (e-Myco Plus kit; iNtRON Biotechnology) and were found to be negative. Reverse transfection was performed using RNAiMAX (for siRNA) or LTX with PLUS (for plasmid) transfection reagents. Final siRNA concentrations were used at 20 (NTR3), 40 (LKB1, CAMKK2) or 100 (NTR1) nM. Cells were treated 72 h (siRNA) or 48 h (plasmid) after transfection. For combined treatment of oleate with NT, cells were pre-treated with BSA or NT (2 μM) or NT at various dosages in serum-free media as indicated in the figures for 30 min followed by oleate (0.1 mM) for 1 h or overnight. For treatment with oleate alone, cells were treated with BSA or oleate at different concentrations as indicated in the figures for 1 h in serum-free media.

Western blotting

Tissues and cells were lysed with lysis buffer (Cell Signaling Technology), and equal amounts of protein were resolved on 4–12% NuPAGE BisTris gels (Life Technologies), electrophoretically transferred to polyvinylidene difluoride (PVDF) membranes, and western blotting was performed as previously described36,37. p-AMPK expression was analysed by densitometry and normalized to total AMPK expression using NIH ImageJ software from three separate experiments. Data are presented as fold change.

Histology and immunohistochemistry

Tissues were fixed in 10% neutral-buffered formalin, embedded in paraffin, and sectioned (5 μm). H&E staining was performed using standard techniques. For H&E and oil red O (ORO) staining, liver tissues were collected from male Nt+/+ and Nt–/– mice fed a HFD for 24 weeks after weaning. For ORO staining, liver tissues were fixed in 10% neutral-buffered formalin, equilibrated in 30% sucrose, embedded in OCT compound and snap-frozen in liquid N2. Frozen sections were stained with ORO (Sigma-Aldrich) for lipid deposition using standard methods. Adipocyte size was measured as described previously38. Briefly, sections of epididymal adipose tissue from each mouse were photographed under ×100 magnification. In a square measuring 700 × 700 μm (x and y axis, respectively), adipocyte size and number were measured using NIS Elements BR.3.10 software. A criterion for inclusion of measurements was a circularity of adipocytes superior to 0.33 (shape of cells; from 0 (thin shape) to 1 (perfect circle)). Immunohistochemistry was performed and visualized by Dako EnVision Systems (Burlington, Ontario, Canada) following the product instruction.


Total RNA was isolated from cells using RNeasy Kit (Qiagen, Valencia, CA) according to the manufacturer’s instructions. RT–PCR analysis of NTR1, 2 and 3 was performed using cDNA synthesized from 1 μg of total RNA. β-Actin was used as the internal control. The primers included: human NTR1: 5′-TCATCGCCTTTGTGGTCTGCT-3′ and 5′-TGGTTGCTGGACACGCTGTCG-3′; human NTR2: 5′- GTCTCCTCAGCTTCATCGTAT-3′ and 5′-TCCCCAAAGCCTGAAGCTGTA-3′; human NTR3: 5′-AGAATGGTCGAGACTATGTTG-3′ and 5′-AAGAGCTATTCCAAGAGGTCC-3′; rat Ntr1: 5′-GAGAAGCCCCCAAAATTCTC-3′ and 5′-CAAGGACCCAGTGCAGGTAT-3′; rat Ntr2: 5′-ACTCGCTCATCTTCGCATTT-3′ and 5′-TGGGACCACACGAAGTTGTA-3′; rat Ntr3: 5′-TTTCAAGCTGTGCTTTGTGG-3′ and 5′-AGTTCTCTGAACGGGAGCAA-3′. β-Actin: 5′-TCACCAACTGGGACGACATG-3′ and 5′-ACCGGAGTCCATCACGATG-3′. The PCR products were analysed on a 2% agarose gel.

Glucose and insulin tolerance tests

Insulin (ITT) and glucose (GTT) tolerance tests were performed on 6-h-fasted male Nt+/+ and Nt–/– mice fed HFD for 24 weeks after weaning. Glucose values were measured using One Touch Ultra from LifeScan (Wayne, PA) by tail snip. Glucose (1.5 g per kg body weight) and human insulin (0.75 U per kg body weight) were injected intraperitoneally (i.p.) after baseline glucose levels were established in each mouse, and blood glucose levels were measured 15, 30, 60 and 120 min after injection.

Metabolic studies

Whole-body composition parameters were measured in male Nt+/+ and Nt–/– mice fed either a LFD or HFD for 24 weeks after weaning by EchoMRI-100 Whole Body Composition (Echo Medical System, Houston, TX) using magnetic resonance relaxometry to precisely measure total body fat, lean mass, body fluids and total body water in conscious mice. A TSE LabMaster indirect calorimetry system (TSE-Systems, Chesterfield, MO) was used to simultaneously quantify energy expenditure, energy intake, locomotor activity and respiratory exchange ratio (RER). Mice were acclimated to the chambers for 7 days, to permit recovery from the weight loss initially experienced by obese mice. Recordings were performed for 5 days, yielding three full 24-h periods of data. Feeding and activity data were collected continuously; O2 and CO2 levels for energy expenditure and RER calculations were collected at 30-min intervals. Resting energy expenditure values were calculated from data collected between 9 a.m. and 6 p.m., filtered to remove points at which activity was greater than 150 counts for that interval.

For hepatic TG and cholesterol measurements, liver tissues were collected from male Nt+/+ and Nt–/– mice fed a HFD for 24 weeks after weaning; TG and cholesterol were extracted as described previously39 and analysed by LC–MS coupled with electrospray ionization tandem using stable isotope dilution40 performed on AB Sciex 4000 Q-Trap instruments. Fasting plasma glucose was analysed using a Glucose Colorimetric Assay Kit II (BioVision) and insulin using a Mouse Insulin ELISA kit (Mercodia, Winston Salem, NC). To monitor insulin secretion in response to glucose stimulation, plasma insulin and glucose levels were measured in mice (fed standard chow after weaning) that had been fasted overnight and subsequently given glucose (2 g per kg body weight) by gavage (that is, oral GTT). Blood was collected from tail snip before (0 min) or 15, 30, 60 and 120 min after gavage. Insulin and glucose levels were measured using Glucose Colorimetric Assay Kit II and Mouse Insulin ELISA kit as described earlier. Plasma insulin levels were also determined in mice that were either fasted for 16 h or fasted for 16 h with refeeding for 4 h; blood was collected from the IVC. For faecal TG assay, mice were housed in individual cages for 4 days, day-4 faecal samples were dried and ground, lipid was extracted from 50 mg faeces, and TG was measured by LC–MS.

Body length measurements

Anal–nasal length was measured following isoflurane anaesthesia of male and female Nt+/+ and Nt–/– mice (7 months old).

Faecal weight measurements

Male Nt+/+ and Nt–/– mice fed either normal chow (NC) or a HFD for 24 weeks after weaning were separated into individual cages and faecal pellets were collected and weighed daily for 4 days. Faecal weights from day 4 were averaged for wild-type and NT-deficient mice.

Small intestinal characterization

The entire small intestine (SI), from the gastric pylorus to the ileocecal valve was dissected from anaesthetized male Nt+/+ and Nt–/– mice (7 months old). The SI length was measured and then opened longitudinally, washed in cold saline to clear the luminal contents, dried briefly on a paper towel and weighed. The SI was divided 5 cm distal from the pyloric junction and the jejunoileum was divided into equal proximal and distal fragments. Proximal fragments were fixed in 10% neutral-buffered formalin for 24 h, and ‘Swiss rolls’41 were sectioned (5 μm) for H&E staining. H&E-stained sections were imaged on an Aperio ScanScope XT slide scanner at ×20. Villus height and crypt counts were determined using Aperio ImageScope v. software. Crypts in a 1-mm field were counted; 10 fields were analysed per section. Villus height was measured from 10 well-oriented villi on each slide.

Lipid absorption studies

For olive oil administration and ORO analysis, male Nt+/+ and Nt–/– mice on NC were fasted overnight, fed olive oil (17 μl per g body weight) by gavage, and killed either before (control), or 30 min and 60 min after gavage. The intestine was resected from the ligament of Treitz to the ileocecal junction, divided into proximal, middle, and distal segments of equal length, washed with cold saline, and the proximal segment was processed for frozen sectioning and ORO staining using standard protocols.

For 13C18-OA experiments, male Nt+/+ and Nt–/– mice on NC were fasted overnight, fed 13C18-OA (480 μg per g body weight) mixed in olive oil (10 μl per g body weight) by gavage, killed either 0 or 30 min later, and proximal intestinal segments were collected as described earlier. To detect plasma level of 13C18-OA, mice were given 13C18-OA as described earlier and blood was collected from tail snip either before (0 h), or 1, 2 and 3 h after gavage. Lipid was extracted from proximal intestines and plasma42 and 13C18-OA levels were determined by direct infusion nanospray FT-MS (Orbitrap Fusion Tribrid Mass Spectrometer, Thermo Scientific, Waltham, MA) using a modification of a previous method43. Briefly, aliquots of the lipid extracts were diluted 20-fold in isopropanol:chloroform:methanol (4:2:1), introduced into the TriVersa NanoMate (Advion, Ithaca, NY) and analysed on the Orbitrap Fusion in negative-ion mode to estimate the appropriate amount of d34-OA to spike. Lipid extracts were then spiked with a known concentration of d34-OA and re-analysed. The nanospray conditions on the Nanomate were as follows: 15 μl of sample injection, 16 min of delivery time, 0.4 psi of gas pressure, and 1.5 kV of negative applied voltage. The Orbitrap Fusion MS analysis conditions were as follows: mass resolution setting of 450,000 with lock mass using internal calibrant, scan range of m/z 150–1,600, percentage S-Lens RF Level of 60, 1.0 × 105 for AGC Target, 100 ms maximum injection time, and 10 averaged microscans. The ion transfer tube temperature was 275 °C, and the experimental mass accuracy was ± ~1 p.p.m. The unlabelled, 13C-labelled, and d34-OA were assigned based on their respective accurate mass of 281.24860, 299.30899, and 314.45574; unlabelled and 13C-labelled OA were then quantified against the internal d34-OA standard using their respective peak intensity.

For NT ‘rescue’ experiments, male Nt+/+ and Nt–/– mice on NC were fasted overnight, fed saline or olive oil (17 μl per g body weight) by gavage, injected i.p. with saline or NT (3,600 nmol per kg body weight), and, after being killed 60 min later, proximal intestinal fragments were dissected as described earlier and further divided into proximal and distal halves that were either processed for ORO staining or used for TG quantification, respectively, as described previously with modifications44. Briefly, intestinal tissues were homogenized in 200 μl of 0.5% Tween-20 in PBS, heated for 5 min at 70 °C, homogenates were microcentrifuged (3 min), and TG measurements were performed on the supernatants using a Triglyceride Determination Kit (Sigma-Aldrich)44 according to the manufacturer’s instructions.

For in vitro fatty acid absorption or lipid accumulation studies, FHs 74 Int and RIE-1 cells (in serum-free medium) were incubated with either bovine serum albumin (BSA; fatty-acid-free) (Sigma-Aldrich) or BSA-conjugated BODIPY FL C16 (4,4-difluoro-5,7-dimethyl-4-bora-3a,4a-diaza-s-indacene-3-hexadecanoic acid) (Life Technologies) (5 μM) for 15 min and images were obtained using an FV1000 Olympus confocal microscope (Olympus, Tokyo, Japan) using a ×60, 1.35 numerical aperture (NA) oil objective, zoom 3 and analysed with Olympus FV10-ASW v.3.1b software. Florescence intensity was determined on a total of 30 cells from 3 fields (10 cells per field). Lipid accumulation, RIE-1 cells were pre-treated with or without NT for 30 min followed by combination treatment of BSA or oleate (0.1 mM) with or without NT overnight. Cells were homogenized and TG measured using Triglyceride Determination Kit as described earlier. Experiments were repeated at least three times.

For acute SR 48692 treatment, one experiment was performed on male wild-type C57BL/6 mice obtained from Taconic (Hudson, NY). Mice were acclimated for 1 week, randomly divided into control, olive oil, and olive oil plus SR 48692 groups and fasted overnight. SR 48692 was dissolved in dimethylsulfoxide (DMSO; 50 mg ml−1) and diluted 1:100 in saline just before use. Mice were injected i.p. with SR 48692 (2.5 mg per kg body weight)31,33 or vehicle 30 min before oral gavage of olive oil (10 μl per g body weight), killed after an additional 30 min, and the proximal intestine (see earlier) was used to determine TG content and for preparation of lysates for western blotting. This experiment was repeated in male Nt+/+ and Nt–/– mice (7 months old), and proximal intestinal TG was measured as described earlier.

Drosophila studies

Full-length human NT cDNA was inserted into an attB-UAST backbone45 and transgenic lines were generated using an attP2 locus and PhiC31 integration system. UAS-AMPK and UAS-AMPK-RNAi (v106200) lines have been described46,47. UAS-AMPK-RNAi line (TRiP #25931, Bloomington Stock Center) produced similar phenotypes to UAS-AMPK-RNAi (v106200) and was used for most experiments. The UAS-CG9918-RNAi line (TRiP #27539, Bloomington Stock Center) has been described48. Gr36C-Gal4, Myo1Ats-Gal4, voila-Gal4, and S106-Gal4 have been described49,50,51 (FlyBase). Myo1A-Gal4 is specifically expressed in enterocytes52. To constitutively express NT in gut enteroendocrine cells, a gut enteroendocrine-cell-specific TK promoter (2.0 kb)28,29 was cloned into attB-UAST lacking Gal4-binding sites followed by insertion of full-length NT cDNA and the resulting plasmid (TK-NT) was used to generate a transgenic line by insertion at the VK5 attP locus. To express NT in enteroendocrine cells and knock down CG9918 by RNAi in enterocytes, the following genotype was used: yw; Myo1A-Gal4/CG9918RNAi27539; TK-NT/+. tub-Gal80ts was used in combination with the Myo1A-Gal4 (resulting in Myots) to suppress Myo1A-Gal4-driven expression52, until shifting larvae to 29 °C (non-permissive temperature) 96 h after egg laying (AEL) or adult emerging. AMPK or AMPK RNAi were expressed in the fat body using the RU486-inducible GeneSwitch S106-Gal4 line. S106-AMPK or S106-AMPK-RNAi larvae (3rd instar) were grown on RU486- (200 μM, Mifepristone, Sigma-Aldrich) or vehicle-containing food and lipid droplet accumulation in fat body and oenocytes was examined by BODIPY (Invitrogen) and immunohistochemical (anti-HNF4 oenocyte marker53) staining. Midguts (3rd instar larvae, adult) were dissected, fixed in 4% formaldehyde in PBS for 20 min, permeabilized in 0.1% Triton X-100 in PBS, and processed for either immunohistochemistry using mouse anti-Pros (DSHB, MR1A) and rabbit anti-NT (Abcam, ab43833) primary antibodies or lipid staining using BODIPY, Nile Red, or ORO (larvae).

AMPK and p-AMPK were detected by western blot analysis using protein extracts from gastrointestinal tract (15 per sample) using anti-p-AMPK (Cell Signaling, #2535), anti-AMPK (Abcam, ab80039) and anti-β-tubulin control (DSHB, E7) primary antibodies and ECL as described.

Adult flies were fed a HFD or standard food (SDF, cornmeal yeast) as described25. Briefly, flies (5 days after emerging) were collected and maintained on SDF for an additional 5 days, split into two groups, and fed either SDF or SDF containing 20% (w/v) coconut oil (HFD) for a further 5 days, followed by dissection and lipid staining using BODIPY or Nile Red. voila-NT and voila-Gal4-w1118 control flies were fed a HFD or SDF as described earlier for TG measurement (25 flies per sample) as described44. Fluorescence signals were acquired on an Olympus confocal microscope and images processed with Olympus FV10-ASW v.3.1b.

Drosophila S2 cells54 were transfected with ub-Gal4, UAST-NT, and individual dsRNAs55 to inhibit the expression of NTR-like receptors CG9918 (nucleotides 11–570), CG8784 (nucleotides 72–478), CG8795 (nucleotides 203–343), Capa (nucleotides 1–455) or GFP control (nucleotides 6–606) using Effectene (Qiagen). Cells (6 × 106) were dissolved in lysis buffer (450 μl) 48 h post-transfection, microcentrifuged (12,000 r.p.m., 10 min), and supernatants were analysed by western blotting. For quantitative RT–PCR, cDNA was synthesized (SuperScript III First Strand Synthesis, Invitrogen) from 1.0 μg Trizol-extracted RNA and used for quantitative RT–PCR (95 °C, 30 s followed by 40 cycles, 95 °C, 5 s; 55 °C, 30 s; 72 °C, 15 s) using SYBR Green (Thermo-Fisher) and the ΔCt method (StepOnePlus Real-Time PCR System, Applied Biosystems). Primer pairs were as follows: CG9918, 5′-GAGTTTCAACGGCGGAGGAA-3′, 5′-AGCAGAGGAAGAAGCACACC-3′; CG8784, 5′-GGCGTGCTGGGTAATCTTAT-3′, 5′-CAAAGGTTGTACAGCTCCTG-3′; CG8795, 5′-GCTACGCCCTCATATTTATC-3′, 5′-GAGGTTATAGAGGTCCTGCG-3′; Capa, 5′-ATGAAATCTATGTTGGTC-3′, 5′-CCAACGCGCGGGAAGGC-3′; actin, 5′-GCGTCGGTCAATTCAATCTT-3′, 5′-AAGCTGCAACCTCTTCGTCA-3′. All S2 cell experiments were independently repeated at least three times.

NT enzyme immunoassay

Fifty microlitres of media from S2 cells transfected with ub-Gal4 and UAST-NT were used to measure NT levels using NT EIA Kit from Phoenix Pharmaceuticals (Burlingame, CA) as described previously36,37.

LC–MS/MS analysis of NT

NT was analysed by liquid chromatography tandem mass spectrometry (LC–MS/MS) using an LTQ-Orbitrap mass spectrometer (Thermo Fisher Scientific, Waltham, MA) coupled with an Eksigent Nanoflex cHiPLC system (Eksigent, Dublin, CA) through a nano-electrospray ionization source56. NT in the NT EIA kit (Phoenix Pharmaceutical) was used as standard. S2 cells were transfected with ub-Gal4 and UAST-NT or the UAST vector control, and conditioned medium was harvested after 48 h for analysis. GI tracts (350 per genotype) were dissected from wild-type (w1118) or Gr36C-NT 3rd instar larvae, methanol extracted57, extracts were dried, and dissolved in 20 μl 0.1% (v/v) formic acid in water for analysis. Samples were separated by reversed-phase cHiPLC (ChromXP C18 column, 75 μm I.D. × 15 cm length, Eksigent catalogue no. 804-00001; mobile phase A and B were 0.1% (v/v) formic acid in either water or acetonitrile, respectively; flow rate, 300 nl min−1). LC–MS/MS data were acquired in an automated data-dependent acquisition mode consisting of an Orbitrap MS scan (300−1,800 m/z, 60,000 resolutions) followed by MS/MS for fragmentation of the seven most abundant ions with the collision-induced dissociation method.

MS/MS fragments corresponding to NT1,2,3,4,5,6,7,8,9,10,11,12,13 were identified by comparison with the NT standard, and quantified using the intensity of the NT3+ peak and NT standards (0.05, 0.1, 0.2, 0.5 fmol)57.

Human population studies

The Malmö Diet and Cancer (MDC) study is a population-based, prospective epidemiological cohort of 28,449 men (born 1923–1945) and women (born 1923–1950) from the city of Malmö in southern Sweden who underwent baseline examinations between 1991 and 199658. From this cohort, 6,103 persons were randomly selected to participate in the MDC Cardiovascular Cohort (MDC-CC), which was designed to investigate the epidemiology of carotid artery disease, between 1991 and 199459. Fasted plasma samples at the baseline examination were available for analysis of pro-NT and successfully measured in a total of 4,632 participants in the MDC-CC. Of those, complete data were available for BMI in 4,626, for waist circumference on 4,625, and for estimated degree of insulin resistance using the homeostasis model assessment of insulin resistance (HOMA-IR) (fasting blood glucose concentration × fasting plasma insulin concentration/22.5)60 in 4,468 participants. BMI was defined as body weight in kilograms divided by the square of height in meters and obesity as a BMI ≥ 30 kg m−2. Abdominal obesity was defined as a waist circumference of ≥94 cm in males and ≥80 cm in females, according to the International Diabetes Federation definition61. Insulin resistance was regarded present in subjects belonging to the top 25% of HOMA-IR values in the MDC-CC. ‘New-onset obesity’ is defined as obesity development among non-obese MDC-CC participants who were re-examined and diagnosed with obesity after an average follow-up time of 16.5 ± 1.5 years. Pro-NT was measured in stored fasting plasma specimens (all samples were assayed in 2010) that were immediately frozen to −80 °C at the MDC-CC baseline examination using a chemiluminometric sandwich immunoassay to detect a pro-NT precursor fragment (pro-NT 1–117) as described previously62. Analyses of blood glucose and plasma insulin were carried out at the time of baseline examination at the Department of Clinical Chemistry, Malmö University Hospital, which is attached to a national standardization and quality control system63. Of the 4,626 subjects with baseline data on BMI and pro-NT, 2,900 subjects were re-examined with a new measurement of BMI after a mean follow-up of 16.5 ± 1.5 years. In analyses of incident obesity, we excluded 306 subjects who were obese already at the baseline examination, leaving a total of 2,594 non-obese subjects for analysis of pro-NT in relation to incident obesity. All participants gave written informed consent, and the study was approved by the Ethical Committee at Lund University, Lund, Sweden.

Statistical analysis

Descriptive statistics including means and standard deviations were calculated and represented using bar or line graphs. Linear mixed models were implemented to compare body weight and food intake levels over time as well as comparisons at each time point for other endpoints from in vivo experiments involving repeat measurements. Specifically, body weight growth curves were compared using linear mixed models with fixed effects for linear and quadratic terms for time and their interaction with genotype and random effects for the intercept and time factors. Contrast statements for the interaction terms in the model were used to assess differences in growth curves between genotypes. Likewise, linear mixed models were employed for body weight growth curve comparisons between vehicle versus SR 48692 with the same fixed and random effects terms as earlier along with baseline weight as a covariate. Total food consumption for 22 weeks was calculated and compared between genotypes and between vehicle versus SR 48692 treatment using two-sample t-tests. Furthermore, weekly food intake levels were analysed using linear mixed models. However, since there is no clear trend in weekly food intake over time, an overall comparison of trend was not employed. Instead, a linear mixed model with fixed effects for genotype, time and their interaction and a random effect for the intercept term was employed in order to perform individual comparisons at each time point. A P-value adjustment due to multiple testing at each time point was performed using the Holm’s step-down procedure. We used the Akaike information criterion (AIC) to evaluate the goodness-of-fit of the above linear mixed models. Two-sided, two-sample Student’s t-test was employed for cell culture and in vivo studies involving two independent groups. One-way or two-way analysis of variance models with test for interaction between two factors was employed for multiple group comparisons of diet (LFD, HFD), mouse genotype, feeding and fasting groups, different time points of measurement, varying doses of NT treatment, SR48692 and AICAR treatments with Holm’s P-value adjustment for multiple pairwise comparisons. ANCOVA was employed to compare genotype and diet with adjustment for the confounding effect of mouse body weight for fat composition and energy metabolism endpoints (energy expenditure, locomotor activity, energy intake, respiratory ratio). Model building was performed to assess equality of slopes using two-way interactions between each of genotype and diet with the body weight covariate as well as genotype and diet interactions.

For the animal studies, sufficient sample sizes were used to provide at least 80% power to detect large effect sizes (1.0 to 3.0 mean differences in s.d. units) based on two-sided, two-sample t-tests with 5% significance level. Some experiments including body weight and food intake were measured repeatedly, thus affording larger statistical power. No replicate samples from in vitro studies were excluded in the analysis. All data from animal studies with measurement of study endpoints were included in the analysis. Experiments with slight differences in animal numbers per group were due to the number of animals that were successfully bred and not due to exclusion of certain animals and their data points. Mice within a cage were randomized to all groups in an experiment to ensure balance in treatment group assignments across all cages. The animals were randomly selected for group assignment without preference to size or other confounding factors. A different individual performed measurements on study endpoints to ensure blinding from group assignment. Furthermore, only animal IDs without information on group assignment were available to staff performing the endpoint evaluation. Parametric tests were used after evaluating distribution of data (for example, percentiles, mean and median levels), test for normality (for example, Kolmogorov–Smirnov test, if sufficient sample sizes) and test for homogeneity of variance assumptions across groups. Otherwise, data log transformation or nonparametric tests were used. Appropriateness of other statistical models including linear mixed models was evaluated for goodness-of-fit using the AIC and equality of slopes between groups was evaluated for the ANCOVA models.

All subjects at the MDC-CC baseline examination were divided into ascending quartiles according to their value of fasting pro-NT. BMI, waist circumference and HOMA-IR were analysed as dichotomous outcome variables as defined earlier. In cross-sectional analyses, we related baseline quartile of pro-NT to the dichotomous outcome of obesity, abdominal obesity, and insulin resistance using age- and sex-adjusted logistic regression models. In the analyses of incident obesity, we related baseline quartile of pro-NT to the dichotomous outcome of incident obesity using logistic regression adjusted for baseline age, sex and BMI. Data are presented as odds ratios (95% confidence intervals), and subjects belonging to the lowest quartile of pro-NT were defined as the referent group (odds ratio = 1). ‘P for trend’ denotes the P value for linear trend over quartiles 1–4. For code availability, statistical analysis codes in SAS version 9.4 were used for analysis of in vivo and in vitro studies and SPSS version 22.0 for analysis of human data and can be accessed by contacting B.M.E.


  1. 1.

    , , & The epidemiology of obesity. Gastroenterology 132, 2087–2102 (2007)

  2. 2.

    Obesity as a medical problem. Nature 404, 635–643 (2000)

  3. 3.

    et al. The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis. BMC Public Health 9, 88 (2009)

  4. 4.

    et al. Specific localisation of neurotensin to the N cell in human intestine by radioimmunoassay and immunocytochemistry. Nature 270, 183–184 (1977)

  5. 5.

    , & Elevation of plasma neurotensin during lipid perfusion of rat small intestine. Peptides 2 (suppl. 2), 263–266 (1981)

  6. 6.

    , , & Neurotensin stimulates [3H]oleic acid translocation across rat small intestine. Am. J. Physiol. 251, G823–G829 (1986)

  7. 7.

    Neurotensin and growth of normal and neoplastic tissues. Peptides 27, 2424–2433 (2006)

  8. 8.

    , & Neurotensin and neurotensin receptors. Trends Pharmacol. Sci. 20, 302–309 (1999)

  9. 9.

    et al. Plasma proneurotensin and incidence of diabetes, cardiovascular disease, breast cancer, and mortality. J. Am. Med. Assoc. 308, 1469–1475 (2012)

  10. 10.

    , , , & Neurotensin-deficient mice show altered responses to antipsychotic drugs. Proc. Natl Acad. Sci. USA 98, 8048–8053 (2001)

  11. 11.

    et al. Neurotensin increases mortality and mast cells reduce neurotensin levels in a mouse model of sepsis. Nature Med. 14, 392–398 (2008)

  12. 12.

    , & Evidence that neurotensin mediates the central effect of leptin on food intake in rat. Brain Res. 888, 343–347 (2001)

  13. 13.

    et al. A novel neurotensin peptide analog given extracranially decreases food intake and weight in rodents. Brain Res. 865, 35–44 (2000)

  14. 14.

    et al. Peripheral and central administration of xenin and neurotensin suppress food intake in rodents. Obesity (Silver Spring) 17, 1135–1143 (2009)

  15. 15.

    , , & Neurotensin receptor-1 and -3 complex modulates the cellular signaling of neurotensin in the HT29 cell line. Gastroenterology 123, 1135–1143 (2002)

  16. 16.

    et al. Sortilin deficiency improves the metabolic phenotype and reduces hepatic steatosis of mice subjected to diet-induced obesity. J. Hepatol. 62, 175–181 (2015)

  17. 17.

    , & AMPK as a mediator of hormonal signalling. J. Mol. Endocrinol. 44, 87–97 (2010)

  18. 18.

    & AMPK integrates nutrient and hormonal signals to regulate food intake and energy balance through effects in the hypothalamus and peripheral tissues. J. Physiol. 574, 73–83 (2006)

  19. 19.

    AMPK: positive and negative regulation, and its role in whole-body energy homeostasis. Curr. Opin. Cell Biol. 33, 1–7 (2015)

  20. 20.

    & Calcium/calmodulin-dependent protein kinase kinase 2: roles in signaling and pathophysiology. J. Biol. Chem. 287, 31658–31665 (2012)

  21. 21.

    & The LKB1–AMPK pathway: metabolism and growth control in tumour suppression. Nature Rev. Cancer 9, 563–575 (2009)

  22. 22.

    & Heterogeneous expression of Drosophila gustatory receptors in enteroendocrine cells. PLoS ONE 6, e29022 (2011)

  23. 23.

    & Evidence that stem cells reside in the adult Drosophila midgut epithelium. Nature 439, 475–479 (2006)

  24. 24.

    & The adult Drosophila posterior midgut is maintained by pluripotent stem cells. Nature 439, 470–474 (2006)

  25. 25.

    et al. High-fat-diet-induced obesity and heart dysfunction are regulated by the TOR pathway in Drosophila. Cell Metab. 12, 533–544 (2010)

  26. 26.

    & Neuropeptides and neuropeptide receptors in the Drosophila melanogaster genome. Genome Res. 11, 1126–1142 (2001)

  27. 27.

    , & Identification of G protein-coupled receptors for Drosophila PRXamide peptides, CCAP, corazonin, and AKH supports a theory of ligand-receptor coevolution. Proc. Natl Acad. Sci. USA 99, 11423–11428 (2002)

  28. 28.

    , & Control of lipid metabolism by tachykinin in Drosophila. Cell Reports 9, 40–47 (2014)

  29. 29.

    et al. Enteroendocrine cells support intestinal stem-cell-mediated homeostasis in Drosophila. Cell Reports 9, 32–39 (2014)

  30. 30.

    et al. Hypothalamic CaMKK2 contributes to the regulation of energy balance. Cell Metab. 7, 377–388 (2008)

  31. 31.

    , & Amphetamine-elicited striatal Fos expression is attenuated in neurotensin null mutant mice. Neurosci. Lett. 402, 97–101 (2006)

  32. 32.

    et al. SR 48692, a non-peptide neurotensin receptor antagonist differentially affects neurotensin-induced behaviour and changes in dopaminergic transmission. Neuroscience 59, 921–929 (1994)

  33. 33.

    , & The neurotensin antagonist SR 48692 attenuates haloperidol-induced striatal Fos expression in the rat. Neurosci. Lett. 303, 17–20 (2001)

  34. 34.

    , , & Epithelial cell cultures from normal and cancerous human tissues. J. Natl. Cancer Inst. 56, 843–849 (1976)

  35. 35.

    , , , & Protein kinase D protects against oxidative stress-induced intestinal epithelial cell injury via Rho/ROK/PKC-δ pathway activation. Am. J. Physiol. Cell Physiol. 290, C1469–C1476 (2006)

  36. 36.

    et al. mTORC1 inhibition increases neurotensin secretion and gene expression through activation of the MEK/ERK/c-Jun pathway in the human endocrine cell line BON. Am. J. Physiol. Cell Physiol. 301, C213–C226 (2011)

  37. 37.

    et al. Cyclic adenosine 5′-monophosphate-stimulated neurotensin secretion is mediated through Rap1 downstream of both Epac and protein kinase A signaling pathways. Mol. Endocrinol. 21, 159–171 (2007)

  38. 38.

    et al. Adipocyte-specific deficiency of angiotensinogen decreases plasma angiotensinogen concentration and systolic blood pressure in mice. Am. J. Physiol. Regul. Integr. Comp. Physiol. 302, R244–R251 (2012)

  39. 39.

    et al. Mechanism of rapid elimination of lysophosphatidic acid and related lipids from the circulation of mice. J. Lipid Res. 54, 2775–2784 (2013)

  40. 40.

    et al. Efficient use of exogenous isoprenols for protein isoprenylation by MDA-MB-231 cells is regulated independently of the mevalonate pathway. J. Biol. Chem. 288, 27444–27455 (2013)

  41. 41.

    & The “Swiss roll”: a simple technique for histological studies of the rodent intestine. Lab. Anim. 15, 57–59 (1981)

  42. 42.

    , , & Stable isotope resolved metabolomics of lung cancer in a SCID mouse model. Metabolomics 7, 257–269 (2011)

  43. 43.

    , , , & Isotopomer analysis of lipid biosynthesis by high resolution mass spectrometry and NMR. Anal. Chim. Acta 651, 201–208 (2009)

  44. 44.

    , , & Drosophila HNF4 regulates lipid mobilization and β-oxidation. Cell Metab. 9, 228–239 (2009)

  45. 45.

    , , & PP4 and PP2A regulate Hedgehog signaling by controlling Smo and Ci phosphorylation. Development 136, 307–316 (2009)

  46. 46.

    On why decreasing protein synthesis can increase lifespan. Mech. Ageing Dev. 128, 412–414 (2007)

  47. 47.

    et al. Adenosine nucleotide biosynthesis and AMPK regulate adult life span and mediate the longevity benefit of caloric restriction in flies. Cell Metab. 17, 101–112 (2013)

  48. 48.

    et al. Suppression of insulin production and secretion by a decretin hormone. Cell Metab. 21, 323–333 (2015)

  49. 49.

    & A systematic analysis of Drosophila gustatory receptor gene expression in abdominal neurons which project to the central nervous system. Mol. Cells 32, 375–381 (2011)

  50. 50.

    et al. Local control of intestinal stem cell homeostasis by enteroendocrine cells in the adult Drosophila midgut. Curr. Biol. 24, 1199–1211 (2014)

  51. 51.

    & Regulation of intestinal stem cells in mammals and Drosophila. J. Cell. Physiol. 222, 33–37 (2010)

  52. 52.

    & EGFR signaling regulates the proliferation of Drosophila adult midgut progenitors. Development 136, 483–493 (2009)

  53. 53.

    et al. Proneural and abdominal Hox inputs synergize to promote sensory organ formation in the Drosophila abdomen. Dev. Biol. 348, 231–243 (2010)

  54. 54.

    et al. Hedgehog-regulated atypical PKC promotes phosphorylation and activation of Smoothened and Cubitus interruptus in Drosophila. Proc. Natl Acad. Sci. USA 111, E4842–E4850 (2014)

  55. 55.

    , , & Fused–Costal2 protein complex regulates Hedgehog-induced Smo phosphorylation and cell-surface accumulation. Genes Dev. 21, 1949–1963 (2007)

  56. 56.

    , , & Self-assembled FUS binds active chromatin and regulates gene transcription. Proc. Natl Acad. Sci. USA 111, 17809–17814 (2014)

  57. 57.

    et al. Peptidomics and peptide hormone processing in the Drosophila midgut. J. Proteome Res. 10, 1881–1892 (2011)

  58. 58.

    Minisymposium: The Malmö Diet and Cancer Study. Design, biological bank and biomarker programme. J. Intern. Med. 233, 39–79 (1993)

  59. 59.

    , , & Lp-PLA2 activity and mass are associated with increased incidence of ischemic stroke: a population-based cohort study from Malmö, Sweden. Atherosclerosis 200, 191–198 (2008)

  60. 60.

    et al. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28, 412–419 (1985)

  61. 61.

    , & Metabolic syndrome—a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet. Med. 23, 469–480 (2006)

  62. 62.

    , & Proneurotensin 1–117, a stable neurotensin precursor fragment identified in human circulation. Peptides 27, 1787–1793 (2006)

  63. 63.

    et al. Plasma copeptin and the risk of diabetes mellitus. Circulation 121, 2102–2108 (2010)

  64. 64.

    et al. PI3K p110α/Akt signaling negatively regulates secretion of the intestinal peptide neurotensin through interference of granule transport. Mol. Endocrinol. 26, 1380–1393 (2012)

Download references


We thank D. A. Gilbreath, C. E. Anthony, H. N. Russell-Simmons and J. F. Rogers for manuscript preparation; D. Napier for tissue sectioning and staining; G. Epperly for intestinal crypt measurements and the use of the Aperio ScanScope; E. Y. Lee for consultation and assessment of histological sections and immunohistochemistry; R. Carraway and P. Forgez for their suggestions and helpful advice; J. Ambati and K. Grzech for their review of the manuscript; J. Young Kwon for the Gr36C-Gal4 line, M. Vidal for the voila-Gal4 line, N. Perrimon and T. Ip for the TKg-Gal4 line, and S. Hou for MyoIA-Gal4 and Esg-Gal4 lines; the Bloomington Stock Center, Vienna Drosophila RNAi Center (VDRC) and TRiP at Harvard Medical School for fly stocks; the Developmental Studies Hybridoma Bank (DSHB) for antibodies; B. Gebelein for the anti-HNF4 antibody; the Biospecimen and Tissue Procurement, Redox Metabolism, and Biostatistics and Bioinformatics Shared Resource Facilities of the University of Kentucky Markey Cancer Center (supported by National Cancer Institute grant P30 CA177558). This study was further supported by National Institutes of Health (NIH) grants R37 AG10885 and R01 DK048498 to B.M.E.; R01 GM079684 to J.J.; U24 DK097215, R01 ES022191, P01 CA163223 and P20 GM103527 to T.W.-M.F. and R.M.H.; R01 HL120507 to A.J.M.; RO1 NS077284 to H.Z.; R01 HL073085 and P20 GM103527 to L.A.C. O.M., P.M.N. and M.O.-M. are funded by the Swedish National Research Council; the Swedish Heart-Lung Foundation; Novo Nordisk Foundation; Swedish Diabetes Association; Region Skåne, ALF; and European Research Council grant StG-2011-282255. B.M.E. is also supported by the Markey Cancer Foundation. Y.Y.Z. and J.W.H. are supported by NIH postdoctoral training grants T32 CA165990 and T32 CA160003, respectively. The LC-MS/MS equipment was acquired using a National Center for Research Resources High-End Instrumentation grant (S10 RR029127 to H.Z.).

Author information

Author notes

    • Jun Song
    •  & Yekaterina Y. Zaytseva

    These authors contributed equally to this work.

    • Jianhang Jia
    •  & B. Mark Evers

    These authors jointly supervised this work.


  1. Department of Surgery, University of Kentucky, Lexington, Kentucky 40536, USA

    • Jing Li
    • , Jun Song
    • , Piotr Rychahou
    • , Marlene E. Starr
    • , Ji Tae Kim
    • , Jennifer W. Harris
    •  & B. Mark Evers
  2. Markey Cancer Center, University of Kentucky, Lexington, Kentucky 40536, USA

    • Jing Li
    • , Jun Song
    • , Yekaterina Y. Zaytseva
    • , Yajuan Liu
    • , Piotr Rychahou
    • , Kai Jiang
    • , Ji Tae Kim
    • , Jennifer W. Harris
    • , Timothy Fahrenholz
    • , Richard M. Higashi
    • , Tianyan Gao
    • , Teresa W. -M. Fan
    • , Heidi L. Weiss
    • , Jianhang Jia
    •  & B. Mark Evers
  3. Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, Kentucky 40536, USA

    • Yekaterina Y. Zaytseva
    • , Timothy Fahrenholz
    • , Richard M. Higashi
    •  & Teresa W. -M. Fan
  4. Department of Pharmacology and Nutritional Sciences, University of Kentucky, Lexington, Kentucky 40536, USA

    • Frederique B. Yiannikouris
    • , Wendy S. Katz
    •  & Lisa A. Cassis
  5. Department of Clinical Sciences, Lund University, Malmö, 221 00 Lund, Sweden

    • Peter M. Nilsson
    • , Marju Orho-Melander
    •  & Olle Melander
  6. Department of Internal Medicine, Skåne University Hospital, Malmö, 205 02 Malmö, Sweden

    • Peter M. Nilsson
    •  & Olle Melander
  7. Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, Kentucky 40536, USA

    • Jing Chen
    • , Haining Zhu
    • , Tianyan Gao
    •  & Jianhang Jia
  8. Center for Structural Biology, University of Kentucky, Lexington, Kentucky 40536, USA

    • Jing Chen
    •  & Haining Zhu
  9. Center for Environmental and Systems Biochemistry, University of Kentucky, Lexington, Kentucky 40536, USA

    • Timothy Fahrenholz
    • , Richard M. Higashi
    •  & Teresa W. -M. Fan
  10. Division of Cardiovascular Medicine, Gill Heart Institute, University of Kentucky and Lexington Veterans Affairs Medical Center, Lexington, Kentucky 40536, USA

    • Andrew J. Morris
  11. Department of Biostatistics, University of Kentucky, Lexington, Kentucky 40536, USA

    • Heidi L. Weiss
  12. Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts 01655, USA

    • Paul R. Dobner


  1. Search for Jing Li in:

  2. Search for Jun Song in:

  3. Search for Yekaterina Y. Zaytseva in:

  4. Search for Yajuan Liu in:

  5. Search for Piotr Rychahou in:

  6. Search for Kai Jiang in:

  7. Search for Marlene E. Starr in:

  8. Search for Ji Tae Kim in:

  9. Search for Jennifer W. Harris in:

  10. Search for Frederique B. Yiannikouris in:

  11. Search for Wendy S. Katz in:

  12. Search for Peter M. Nilsson in:

  13. Search for Marju Orho-Melander in:

  14. Search for Jing Chen in:

  15. Search for Haining Zhu in:

  16. Search for Timothy Fahrenholz in:

  17. Search for Richard M. Higashi in:

  18. Search for Tianyan Gao in:

  19. Search for Andrew J. Morris in:

  20. Search for Lisa A. Cassis in:

  21. Search for Teresa W. -M. Fan in:

  22. Search for Heidi L. Weiss in:

  23. Search for Paul R. Dobner in:

  24. Search for Olle Melander in:

  25. Search for Jianhang Jia in:

  26. Search for B. Mark Evers in:


J.L., J.J., P.R.D., O.M. and B.M.E. designed the research; J.L., J.S., Y.Y.Z., Y.L., P.R. and K.J. performed experiments; J.T.K. assisted with experiments; M.E.S. and J.W.H. assisted with the animal work; W.S.K., F.B.Y. and L.A.C. performed indirect metabolism and adipocyte size analyses; J.C. and H.Z. designed and performed the proteomics studies using liquid chromatography tandem mass spectrometry (LC–MS/MS) for NT analysis of the Drosophila samples; A.J.M. performed LC–MS analysis; T.W.-M.F. and R.M.H. designed the 13C-OA tracer study, reviewed the manuscript, and together with T.F. performed FT-MS data analyses; H.L.W. performed statistical analyses; P.R.D. provided NT-knockout mice and reviewed the manuscript; T.G. reviewed the manuscript and provided comments and suggestions; P.M.N., M.O.-M. and O.M. performed and analysed human studies; J.L., J.J., H.L.W. and B.M.E. reviewed and interpreted data; J.L., J.J., P.R.D. and B.M.E. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to B. Mark Evers.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains the uncropped scans with size marker indications.

About this article

Publication history






Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.