Interaction of B⁰AT1 Deficiency and Diet on Metabolic Function and Diabetes Incidence in Male Nonobese Diabetic Mice

Abstract

Context

The obesity epidemic parallels an increasing type 1 diabetes incidence, such that westernized diets, containing high fat, sugar, and/or protein, through inducing nutrient-induced islet β-cell stress, have been proposed as contributing factors. The broad-spectrum neutral amino acid transporter (B⁰AT1), encoded by Slc6a19, is the major neutral amino acids transporter in intestine and kidney. B⁰AT1 deficiency in C567Bl/6J mice causes aminoaciduria, lowers insulinemia, and improves glucose tolerance.

Objective

We investigated the effects of standard rodent chow (chow), high-fat high-sucrose (HFHS), and high-fat high-protein (HFHP) diets, in addition to B⁰AT1 deficiency, on the diabetes incidence of male nonobese diabetic (NOD/ShiLtJArc (NOD)) mice.

Methods

Male NOD.Slc6a19^+/+ and NOD.Slc6a19^−/− mice were fed chow, HFHS and HFHP diets from 6 to 24 weeks of age. A separate cohort of male NOD mice were fed the three diets from 6-30 weeks of age. Body weight and fed-state blood glucose and plasma insulin were monitored, and urinary amino-acid profiles, intraperitoneal glucose tolerance, diabetes incidence, pancreatic islet number, insulitis scores and beta-cell mass were measured.

Results

The incidence of diabetes and severe glucose intolerance was 3.8% in HFHS-fed, 25.0% in HFHP-fed, and 14.7% in chow-fed mice, with higher pancreatic islet number and lower insulitis scores in HFHS-fed mice. B⁰AT1 deficiency had no effect on diabetes incidence, but curtailed HFHS-induced excessive weight gain, adipose tissue expansion, and hyperinsulinemia. In HFHP-fed mice, B⁰AT1 deficiency significantly increased pancreatic β-cell clusters and small islets. Male NOD mice that did not develop autoimmune diabetes were resistant to diet-induced hyperglycemia.

Conclusion

Dietary composition does, but B⁰AT1 deficiency does not, affect autoimmune diabetes incidence in male NOD mice. B⁰AT1 deficiency, however, reduces diet-induced metabolic dysfunction and in HFHP-fed mice increases pancreatic β-cell clusters and small islets.

Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic islet β cells are destroyed by the immune system, causing insulin deficiency and hyperglycemia (1, 2). The global incidence of T1D in people younger than 20 years was steadily increasing until the late 1990s (3), with increases continuing in some countries (3-5). While genetic predisposition to T1D places people at risk, the rising incidence is being attributed to environmental factors, including viral infections, early-life dietary exposures, low vitamin D, and overweight/obesity and insulin resistance (6-9). The “accelerator hypothesis,” suggested in the early 2000s, proposes a link between the obesity epidemic and increasing T1D incidence and suggests a reason for more people with lower genetic risk developing T1D (10-14). Nutrient-induced stress on islet β cells, increasing the generation of hybrid insulin peptides that become neoautoantigens, is a potential mechanism (6, 15, 16). Islet susceptibility to nutrient-induced stress may also underpin an increasingly reported overlap in T1D and type 2 diabetes (T2D) (17-19).

Nonobese diabetic (NOD) mice spontaneously develop autoimmune diabetes, with a greater incidence in females (80%-90%) than males (10%-40%) (20). Compared to a standard chow diet (unrefined nutrient sources and low in fat), semi-purified high-fat normal-protein (HFNP) diets have been shown to reduce the incidence of diabetes in female NOD mice (21, 22). However, compared to a semi-purified low-fat diet, semi-purified HFNP and high-fat high-protein (HFHP) diets increased the incidence of diabetes in female NOD mice (22, 23).

Unbalanced Western diets with high protein content, and elevated concentrations of branch chain amino acid levels in the blood, have been linked to poor metabolic health and T2D risk (24, 25). Differing patterns of circulating nutrients, including amino acids, have been associated with different stages of T1D development (26, 27). The broad-spectrum neutral amino acid transporter (B⁰AT1), encoded by the Slc6a19 gene, is the major epithelial transporter for neutral amino acids in the intestine and kidney (28). Global knockout of Slc6a19 in C57Bl/6J mice results in marked aminoaciduria, improved glucose tolerance, lowered insulinemia, and higher circulating fibroblast growth factor 21 and glucagon-like peptide 1 (GLP-1) concentrations (29), suggesting that development of inhibitors to B⁰AT1 for metabolic disease may be worthwhile (30, 31). Previously we reported that genetic B⁰AT1 deficiency did not protect chow-fed female NOD mice from developing autoimmune diabetes (32).

The first main aim of the present study was to determine the effects of high-fat high-sucrose (HFHS) and HFHP diets on autoimmune diabetes incidence in male NOD mice, considering that male mice are more prone to develop nonimmune diabetes through greater propensity to nutrient-induced islet β-cell stress (33, 34). The second main aim was to determine if genetic B⁰AT1 deficiency in male NOD mice on chow, HFHS, or HFHP diets could prevent them from developing autoimmune diabetes.

Materials and Methods

Animals

All mice experiments were approved by the Animal Experimentation Ethics Committee of the Australian National University (protocols: A2014/24, A2017/25, A2020/43). NOD/ShiLtJArc mice (herein referred to as NOD mice) were sourced from the Animal Resources Centre (Canning Vale). NOD/Lt-Slc6a19^em1Anu/Anu mice globally deficient in a functional Slc6a19 gene (herein referred to as NOD.Slc6a19 mice) were generated using the CRISPR-Cas9 gene editing system, as described previously (32). The mutant Slc6a19 allele has a compound 7-bp deletion and 2-bp insertion in exon 2 (wild-type allele, 5′- CATCGGTCAGAGGCTACGCAAGG −3′; mutated allele 5′-CATCGGTCAG——-TGGCAAGG −3′), and B⁰AT1 functional deficiency has been confirmed in NOD.Slc6a19^−/− mice, which exhibit marked aminoaciduria (32). Male NOD.Slc6a19^+/+ and NOD.Slc6a19^−/− experimental littermates were generated through mating of male and female NOD.Slc6a19^+/− mice. Genotyping of mice was performed by polymerase chain reaction using DNA extracted from ear punch samples. All mice were housed within the Australian Phenomics Facility at the Australian National University in a temperature and humidity-controlled environment on a 12-hour light/dark cycle.

Experimental Diets

The composition of the experimental diets is provided in Table 1. Standard rodent chow diet (chow) containing 58%, 26%, and 16% of digestible energy from carbohydrate, protein, and lipid, respectively, was purchased from Gordon's Specialty Stockfeed. The HFHS diet (SF03-020, Semi-Pure Rodent Diet) containing 40%, 17%, and 43% of digestible energy from carbohydrate (predominantly sucrose), protein (predominantly casein), and lipid (from canola oil, cocoa butter, and hydrogenated vegetable oil), respectively, was purchased from Specialty Feeds. The HFHP diet (SF16-050, Semi-Pure Rodent Diet) containing 19%, 38%, and 43%, respectively, from carbohydrate, protein, and lipid, with the main sources of macronutrients similar to the HFHS diet, was purchased from Specialty Feeds.

Table 1.

Composition of study diets

	Chowa	HFHSb	HFHPc
Energy content, MJ/kg	13	20	19.9
Total digestible energy, %
Carbohydrate	58%	40%	19%
Protein	26%	17%	38%
Lipids	16%	43%	43%
Content, g/kg
Sugars	6.6	424 (sucrose)	177 (sucrose)
Starch	272.4	50	50
Crude fiber	4.0	4.7	4.7
Saturated fat	14.9	149	165
Monounsaturated fat	1.8	5.9	5.4
Polyunsaturated fat	0.7	22.4	20.3
Cholesterol	n/a	1.9	1.9
Arginine	12.1	n/a	n/a
Histidine	5.0	6.0	11.7
Isoleucine	8.0	9.0	21.1
Leucine	15.2	18.0	38.3
Lysine	9.8	15	31.7
Methionine and cysteine	5.9	8.6	16.6
Phenylalanine and tyrosine	16.4	20.0	42.9
Threonine	8.4	8.0	17.6
Tryptophan	3.7	3.0	3.8
Valine	10.2	12.6	11.7

Abbreviation: n/a, not available.

^a Chow: standard rodent chow diet (Gordon's Specialty Stockfeed).

^b HFHS: high-fat high-sucrose diet (SF03-020, Semi-Pure Rodent Diet, Specialty Feeds).

^c HFHP: high-fat high-protein diet (SF16-050, Semi-Pure Rodent Diet, Specialty Feeds).

Experimental Design

All mice were fed a chow diet to age 6 weeks. Two series of studies were performed: the first in NOD.Slc6a19 mice, the second in NOD mice.

Male NOD.Slc6a19 Study

At age 6 weeks, male littermate NOD.Slc6a19^+/+ and Slc6a19^−/− mice were randomly allocated to chow, HFHS, and HFHP diets, creating 6 experimental groups. Serial 9 Am fed-state body weight and tail blood plasma glucose were measured at ages 6, 10, 14, 16, 20, and 24 weeks using a glucose meter (StatStrip Xpress, Nova Biomedical), or until the diagnosis of diabetes (plasma glucose ≥20 mM for 2 consecutive days). Plasma insulin was measured at ages 6, 10, 16, 20, and 24 weeks from tail blood samples (30 μL) collected into EDTA-rinsed microfuge tubes, stored on ice prior to centrifugation and plasma separation, followed by storage at −80 °C for later measurement of insulin by radioimmunoassay (Millipore catalog No. EZRMI-13 K, RRID:AB_2783856, Abacus). At age 13 and 23 weeks, intraperitoneal glucose tolerance tests (ipGTTs) were performed and insulin resistance was assessed by the homeostatic model assessment for insulin resistance (HOMA-IR) method, as described later.

A urine sample was also collected between ages 12 and 16 weeks for measurement of urine amino acid abundance using a gas chromatography–mass spectroscopy (GC-MS) method, after standardization for osmolality, as previously described (31).

At age 24 weeks, or following confirmation of diabetes, the mice were euthanized and tissues harvested for weighing and histological assessment, as described later.

Male Nonobese Diabetic Diet Study

At age 6 weeks, male NOD mice were randomly allocated to 1 of 3 experimental groups: chow-fed, HFHS-fed, and HFHP-fed. Serial fed-state body weight and tail vein plasma glucose were measured at 9 to 10 Am weekly to age 30 weeks, or until diabetes diagnosis (plasma glucose ≥20 mM for 2 consecutive days).

At age 10, 18, and 26 weeks, the mice were fasted overnight for 14 hours (18:00-08:00), then refed their allocated diets for a period of 4 hours. At the end of the fast and after 4 hours of refeeding, plasma glucose was measured and a blood sample (30 μL) was collected for measurement of insulin, as described above. Refeeding food intake was measured.

An ipGTT was performed and insulin resistance assessed by HOMA-IR at age 24 weeks.

At age 30 weeks, or following confirmation of diabetes, the mice were euthanized and tissues harvested for weighing and histological assessment.

Intraperitoneal Glucose Tolerance Testing and Insulin Resistance Assessment

ipGTTs were performed in conscious mice after fasting for 6 hours (08:00-14:00). Tail vein fasting plasma glucose by glucose meter and a blood sample (30 μL) were collected for plasma insulin (time 0 minutes), followed by the administration of 1 g/kg 25% glucose solution via intraperitoneal injection. Tail vein plasma glucose was then measured at 5, 15, 30, 60, 90, 120 minutes, and additional blood samples (30 μL) for plasma insulin were taken at 15 and 90 minutes. Area under the curve (AUC) for ipGTT glucose and insulin used the trapezoid method. HOMA-IR was used for assessment of insulin resistance from fasting blood glucose and insulin measurements according to the formula (fasting glucose in mmol/L × fasting insulin in μIU/mL)/22.5) (35).

Tissue Collection and Histology

All mice were euthanized by cervical dislocation at the end of the experimental period. Liver, pancreas, and epidydimal fat pads (white adipose tissue [WAT]) were quickly excised, weighed, and fixed in 10% neutral buffered formalin solution before embedding in paraffin using routine laboratory protocols. Histological analysis of pancreas was conducted on 4-µm-thick sections stained with hematoxylin and eosin. Islets per whole pancreas section were counted and individually graded for insulitis using a method previously described, and shown in Fig. 5A, with scores of 0 = no insulitis, 1 = peri-islet insulitis, 2 = invasive insulitis less than 50%, 3 = invasive insulitis 50% or greater, and 4 = invasive insulitis 100% (36). Pancreas islet scoring was performed by 2 blinded observers.

Figure 5.

High-fat high-sucrose (HFHS)-fed compared to chow-fed male NOD.Slc6a19 mice have greater numbers of insulitis stage 0 islets. A, Representative hematoxylin-eosin stain; image examples using in insulitis scoring, 0 = no insulitis, 1 = peri-islet insulitis, 2 = invasive insulitis less than 50%, 3 = invasive insulitis 50% or greater, and 4 = invasive insulitis 100%. B, Number of islets at each grade of insulitis (grades 0-4) per pancreas section. C, Insulitis average score per pancreas section. B and C, Data are presented as means ± SEM of 8 to 14 mice per group. B, Three-way analysis of variance (ANOVA) with Tukey post hoc testing for diet effect; for insulitis score 0, chow vs HFHS, P less than .0001; chow vs high-fat high-protein (HFHP), P less than .001; HFHS vs HFHP, P less than .001. C, Two-way ANOVA; n.s., not significant.

Insulin Immunohistochemistry

Immunohistochemistry was performed on the Ventana automated system (BenchMark ULTRA), following a standard protocol. Briefly, 2 pancreatic sections per mouse (3-µm thick, 200 µm apart) were dried in an oven at 60 °C for 20 minutes. Heat retrieval was performed for 32 minutes at 100 °C in cell condition solution (CC1) buffer (Ventana) followed by blocking with 0.1% solution of hydrogen peroxidase for 8 minutes. The sections were stained with 1:60 000 dilution of insulin and proinsulin (Abcam catalog No. ab8304, RRID:AB_2126399) monoclonal antibody incubated for 16 minutes at 36 °C. Optiview DAB IHC Detection Kit (Ventana) was used to amplify and visualize the signals. Nuclei were visualized by counterstaining with hematoxylin.

β-Cell Mass Measurement

Pancreas sections immunostained for insulin were scanned using an Axio Scan.Z1 scanning microscope (Carl Zeiss Microscopy) and analyzed using bioimaging software QuPath v0.5.1 (37). The whole tissue area was measured automatically, whereas the areas of nonpancreatic tissue and insulin-stained cells within clusters and pancreatic islets were manually detected by a blinded observer. β-Cell mass for each was calculated as the proportion of the pancreas tissue occupied by insulin staining cells multiplied by the pancreas weight (average of 2 sections). Size distribution of insulin-stained cell clusters and insulin-stained cells within islets was also determined.

Statistical Analyses

Statistical tests were carried out using R (v4.3.1), RStudio (v2023.03.0 + 386), and GraphPad Prism (v10.0.3). No data were excluded from assessments of diabetes-free survival and insulitis. Data points from the time mice developed diabetes, or from the time when markedly elevated plasma glucose concentrations developed (>2 SD above the mean), including during ipGTT testing, were excluded from analyses of diet effects on metabolism. Results are presented as mean ± SEM. All time-course data were tested using linear regression mixed models. Diabetes-free survival was assessed using the Gehan-Breslow-Wilcoxon test. Other group comparisons were by 1-way analysis of variance (ANOVA), 2-way ANOVA, 3-way ANOVA, and nonparametric tests as indicated. Post hoc testing for multiple comparisons is as indicated. Statistical significance was set at P less than .05. Thirty-two mice per group were estimated to provide 80% power to detect a change in diabetes-free survival from 85% to 50% with an α of 5%.

Results

B⁰AT1 Deficiency in Male NOD.Slc6a19^−/− Mice Confirmed by aminoaciduria

Urine amino acid profiles are shown in Table 2. In male NOD.Slc6a19^−/− mice, at age 12 to 16 weeks, marked urinary loss of neutral amino acids was confirmed. In chow Slc6a19^−/− compared to chow Slc6a19^+/+ mice, the increases in urine neutral amino acid abundance ranged from 21-fold for phenylalanine to greater than 100-fold for glutamine and threonine (see Table 2). Of note, the urinary abundance of the acidic amino acid glutamic acid and the basic amino acid lysine were, respectively, 5-fold and 4-fold higher in chow Slc6a19^−/− compared to chow Slc6a19^+/+ mice. For 10 of 12 neutral amino acids profiles assessed, the urinary abundance was less in HFHS Slc6a19^−/− mice compared to chow Slc6a19^−/− mice. Lower neutral amino acid abundance was found in only 3 of 12 neutral amino acids in HFHP Slc6a19^−/− mice compared to chow Slc6a19^−/− mice (see Table 2).

Table 2.

Urinary amino acid abundance

	Urinary amino acid abundance (log10 of arbitrary units)						2-way ANOVA
Genotype	NOD.Slc6a19+/+			NOD.Slc6a19−/−			Diet effect P	Genotype effect P	Diet × Gen Interaction P
Diet	Chow	HFHS	HFHP	Chow	HFHS	HFHP
Asparagine	4.56 ± 0.07	4.51 ± 0.05	4.21 ± 0.08	5.87 ± 0.11	5.16 ± 0.19b	5.63 ± 0.17d	<.05	<.0001	<.05
Glutamate	4.97 ± 0.07	5.15 ± 0.09	4.85 ± 0.08	5.70 ± 0.05	5.50 ± 0.09	5.46 ± 0.06	n.s.	<.0001	n.s.
Glutamine	5.11 ± 0.07	5.28 ± 0.04	5.01 ± 0.07	7.26 ± 0.08	6.65 ± 0.39	7.02 ± 0.10	n.s.	<.0001	n.s.
Glycine	5.57 ± 0.08	5.78 ± 0.06	5.70 ± 0.07	7.11 ± 0.07	6.39 ± 0.14c	6.62 ± 0.13b	<.05	<.0001	<.001
Isoleucine	4.95 ± 0.08	4.96 ± 0.05	4.82 ± 0.11	6.50 ± 0.12	5.68 ± 0.26b	6.26 ± 0.15d	<.05	<.0001	<.05
Leucine	5.23 ± 0.07	5.60 ± 0.04	5.4 ± 0.07	6.94 ± 0.09	6.26 ± 0.21b	6.79 ± 0.11d	n.s.	<.0001	<.001
Lysine	5.31 ± 0.07	5.56 ± 0.10	5.30 ± 0.05	5.92 ± 0.03	5.84 ± 0.11	6.09 ± 0.01	n.s.	<.0001	<.01
Methionine	4.78 ± 0.06	5.19 ± 0.06	4.89 ± 0.12	6.13 ± 0.12	5.92 ± 0.24	6.21 ± 0.14	n.s.	<.0001	<.05
Phenylalanine	4.66 ± 0.17	4.66 ± 0.05	4.30 ± 0.05	6.01 + 0.13	5.16 ± 0.13c	5.55 ± 0.17a	<.01	<.0001	<.01
Serine	4.85 ± 0.07	5.04 + 0.04	4.63 ± 0.04	6.78 ± 0.10	5.82 ± 0.29c	6.30 ± 0.16	<.05	<.0001	<.01
Threonine	4.78 ± 0.07	5.10 ± 0.02	4.79 ± 0.03	6.90 ± 0.07	6.21 ± 0.41a	6.80 ± 0.10	n.s.	<.0001	<.05
Tryptophan	4.43 ± 0.12	4.68 ± 0.07	4.2 ± 0.09	5.92 ± 0.14	5.25 ± 0.15b	5.39 ± 0.20a	<.05	<.0001	<.01
Tyrosine	4.52 ± 0.08	4.39 ± 0.03	4.23 ± 0.05	6.12 ± 0.12	5.37 ± 0.31b	5.99 ± 0.15d	<.05	<.0001	<.05
Valine	5.02 ± 0.06	5.24 ± 0.03	5.10 ± 0.07	6.91 ± 0.10	5.99 ± 0.25c	6.55 ± 0.14d	<.05	<.0001	<.01

n = 4 mice per group; 2-way analysis of variance with Tukey post hoc testing.

Abbreviations: HFHP, high-fat high-protein; HFHS, high-fat high-sucrose; n.s., not significant.

^a P less than .05 vs Slc6a19^−/− chow diet group.

^b P less than .01 vs Slc6a19^−/− chow diet group.

^c P less than .001 vs Slc6a19^−/− chow diet group.

^d P less than .05 vs Slc6a19^−/− HFHS diet group.

Diabetes Incidence in Male NOD.Slc6a19 Mice Is Affected by Diet, but not by Slc6a19 Genotype

The overall incidence of diabetes was low, with only 8 of 64 (12.5%) mice developing diabetes by age 24 weeks (Fig. 1A). Diabetes-free survival results are shown in Fig. 1B to 1D according to effects of genotype and diet (see Fig. 1B), genotype only (Fig. 1C), and diet only (see Fig. 1D). In considering the effects of Slc6a19 genotype, irrespective of diet, 9.4% (3/32) of Slc6a19^+/+ mice and 15.6% (5/32) of Slc6a19^−/− mice developed diabetes (P = .45) (see Fig. 1C). In contrast, in considering the effects of diet, irrespective of Slc6a19 genotype, 16.0% (3/26) of chow mice, 0% (0/18) HFHS mice, and 25% (5/20) HFHP mice developed diabetes (P = .049) (see Fig. 1D). In post hoc testing, a difference in diabetes incidences between HFHS (0%) and HFHP (25%) diet groups was not observed (P = .075).

Figure 1.

Diabetes incidence in male NOD.Slc6a19 mice is affected by diet, but not Slc6a19 genotype. A, Serial 9 Am fed plasma glucose (individual mice results shown). B, Diabetes-free survival in NOD.Slc6a19 mice according to diet and genotype (n = 9-14 mice per group; Gehan-Breslow-Wilcoxon test; P = .25). C, Diabetes-free survival according to genotype only (Slc6a19^+/+ n = 32 mice, Slc6a19^−/− n = 32 mice; Gehan-Breslow-Wilcoxon test; P = .45). D, Diabetes-free survival according to diet only (chow n = 26 mice, high-fat high-sucrose [HFHS] n = 18 mice, high-fat high-protein [HFHP] n = 20 mice; Gehan-Breslow-Wilcoxon test; P = .049; Bonferroni post hoc testing chow vs HFHS; P = .41; chow vs HFHP; P = .28; HFHS vs HFHP; P = .075).

B⁰AT1 Deficiency Attenuates High-Fat High-Sucrose Diet-Induced Weight Gain and Fed-State Hyperinsulinemia in Male NOD.Slc6a19 mice

HFHS feeding and HFHP feeding accelerated weight gain compared to chow feeding (P < .001 and P < .05, respectively) in NOD.Slc6a19 mice (Fig. 2A). Lower 9 Am fed-state glycemia was found in HFHP compared to chow and HFHS-fed mice (P < .05 and P < .01, respectively) (Fig. 2B). Fed-state insulinemia increased both in HFHS and HFHP mice compared to chow NOD.Slc6a19 mice (P < .0001 and P < .01, respectively) (Fig. 2C). B⁰AT1 deficiency curtailed both HFHS diet-induced accelerated weight gain and hyperinsulinemia (P < .05 for both post hoc comparisons), without significantly affecting these parameters in chow or HFHP mice (see Fig. 2A and 2C).

Figure 2.

Slc6a19 deficiency attenuates accelerated weight gain and the development of hyperinsulinemia in high-fat high-sucrose (HFHS)-fed male NOD.Slc6a19 mice. A, Serial 9 Am fed body weight; B, plasma glucose; and C, plasma insulin. Data are presented as means ± SEM of 9 to 14 mice per group. Linear mixed model Tukey post hoc testing of diet effect: A, chow vs HFHS, P < .001; chow vs high-fat high-protein (HFHP), P < .05; HFHS vs HFHP, n.s.; B, chow vs HFHS, n.s.; chow vs HFHP, P < .05; HFHS vs HFHP, P < .01; and C, chow vs HFHS, P < .0001; chow vs HFHP, P < .01; HFHS vs HFHP, n.s. Linear mixed model Tukey post hoc testing of genotype effect: A, Slc6a19^+/+ chow vs Slc6a19^−/− chow, n.s.; Slc6a19^+/+ HFHS vs Slc6a19^−/− HFHS, P < .05; Slc6a19^+/+ HFHP vs Slc6a19^−/− HFHP, n.s.; C, Slc6a19^+/+ chow vs Slc6a19^−/− chow, n.s.; Slc6a19^+/+ HFHS vs Slc6a19^−/− HFHS, P < .05; Slc6a19^+/+ HFHP vs Slc6a19^−/− HFHP n.s. n.s., not significant.

B⁰AT1 Deficiency Improves Glycemia at Age 13 Weeks and Lowers Insulinemia at Age 23 Weeks in High-Fat High-Sucrose–Fed Male NOD.Slc6a19 Mice During Glucose Tolerance Testing

At age 13 weeks the HFHS diet caused mild glucose intolerance compared to the chow and HFHP diets (P < .05 for both comparisons; Fig. 3A; P < .01 for both glucose AUC comparisons; Fig. 3C), which was mitigated in the Slc6a19^−/− genotype (P < .05) (see Fig. 3A and 3C). The HFHS and HFHP compared to chow diets elevated insulin levels during the ipGTTs (P < .01 and P < .05, respectively) (Fig. 3B), which was unaffected by Slc6a19 deficiency (see Fig. 3B and 3D). HOMA-IR was elevated 1.9-fold in HFHS Slc6a19^+/+ mice compared to Chow Slc6a19^+/+ mice (P < .01), which again was not altered by Slc6a19 deficiency (Fig. 3E).

Figure 3.

Scl6a19 deficiency reduces high-fat high-sucrose (HFHS)-induced hyperinsulinemia without deterioration in glycemia in male NOD.Scl6a19 mice. A to J, A and F, Intraperitoneal glucose tolerance test plasma glucose; B and G, insulin; C and H, area under the curve (AUC) glucose; D and I, AUC insulin; and E and J, homeostatic model of insulin resistance (HOMA-IR) at A to E, age 13 weeks and F to J, age 26 weeks of age. Data presented as means ± SEM of A to E, n = 6-14 and of F to J, n = 6-9 mice per group. Linear mixed model Tukey post hoc testing diet effect: A, chow vs HFHS, P < .05; chow vs high-fat high-protein (HFHP), n.s.; HFHS vs HFHP, P < .05; B, chow vs HFHS, P < .01; chow vs HFHP, P < .05; HFHS vs HFHP, n.s.; F, chow vs HFHS, n.s.; chow vs HFHP, n.s.; HFHS vs HFHP, n.s.; G, chow vs HFHS, P < .0001; chow vs HFHP P < .01; HFHS vs HFHP, n.s. Linear mixed model Tukey post hoc testing genotype effect: A, Slc6a19^+/+ chow vs Slc6a19^−/− chow, n.s.; Slc6a19^+/+ HFHS vs Slc6a19^−/− HFHS, P < .05; Slc6a19^+/+ HFHP vs Slc6a19^−/− HFHP, n.s.; G, Slc6a19^+/+ chow vs Slc6a19^−/− chow, n.s.; Slc6a19^+/+ HFHS vs Slc6a19^−/− HFHS, P < .05; Slc6a19^+/+ HFHP vs Slc6a19^−/− HFHP, n.s.; C to E and H to J, 2-way analysis of variance with Tukey post hoc testing; *P less than .05 vs Slc6a19^+/+ on same diet; ^#P less than .05, ^##P less than .01 vs chow of the same genotype group; ^†P less than .05, ^††P less than .01 vs HFHS of same genotype group; n.s., not significant.

At age 23 weeks, glucose tolerance was affected by diet, but statistically significant differences between groups on post hoc testing were not found (Fig. 3F and 3H). However, higher insulin levels during the ipGTTs of HFHS and HFHP mice compared to chow mice were found (P < .0001 and P < .01, respectively; Fig. 3G, and for the insulin AUCs P < .001 and P < .05, respectively; Fig. 3I). At this time point, HOMA-IR was 3.8-fold higher in HFHS Slc6a19^+/+ mice compared to Chow Slc6a19^+/+ mice (P < .05), again not being significantly curtailed by Slc6a19 deficiency (Fig. 3J). However, Slc6a19 deficiency was successful in reducing the ipGTT insulinemia in HFHS mice (P < .05) (see Fig. 3G and 3I).

B⁰AT1 Deficiency Curtails White Adipose Tissue Expansion in High-Fat High-Sucrose–Fed Mice

HFHS and HFHP feeding similarly expanded absolute epidydimal WAT depot weights compared to chow feeding in NOD.Slc6a19 mice (P < .0001 and P < .01 in Slc6a19^+/+ genotype mice, respectively), which in this study was substantially curtailed by Slc6a19 deficiency (P < .01) (Fig 4A). Of note, absolute liver weights did not increase in either the HFHS or HFHP mice compared to chow mice (Fig 4B). However, when liver weights were expressed as a percentage of body weight, Slc6a19 deficiency resulted in slightly heavier liver weights in mice fed the same high-fat diets (P < .05 for both) (Fig. 4E). Absolute pancreas weights of Slc6a19^+/+ mice were lower in HFHS compared to chow mice (P < .01); however, this difference was not found in Slc6a19^−/− mice (P < .01) (Fig. 4C). When pancreas weights were expressed as a percentage of body weight, the findings were similar (Fig. 4F).

Figure 4.

Effects of chow, high-fat high-sucrose (HFHS), and high-fat high-protein (HFHP) diets on white adipose tissue (WAT), liver, and pancreas tissue weights. A to C, Absolute tissue weights of A, epididymal WAT; B, liver; and C, pancreas at age 30 weeks. D to F, Corresponding tissue weights as a percentage of body weight of D, epididymal WAT; E, liver; and F, pancreas. Data are presented as means ± SEM of 6 to 14 mice per group; A to F, 2-way analysis of variance with Tukey post hoc testing; *P less than .05, **P less than .01 vs Slc6a19^+/+ on same diet; ^#P less than .05, ^##P less than .01, ^###P less than .001, ^####P less than .0001 vs chow of the same genotype group; ^†P less than .05, ^††P less than .01 vs HFHS of same genotype group; n.s., not significant.

Differential Effect of Diet, but not B⁰AT1 Deficiency, on Insulitis Scores

Severity of insulitis was scored 0 to 4 according to the examples shown in Fig. 5A. There was a strong diet and insulitis score interaction, with a much greater number of islets scoring 0 in the HFHS-fed mice (Fig. 5B). There was a statistically significant diet main effect on insulitis average scores, with a trend for these to be, respectively, lower in the HFHS mice (Fig. 5C). However, statistical differences in the average insulitis score between diet groups were not found on post hoc testing (see Fig. 5C). Slc6a19 genotype had no effect on insulitis severity scores (see Fig. 5B and 5C).

B⁰AT1 Deficiency Increases the Number of Small Islets and β-Cell Clusters in High-Fat High-Sucrose–Fed Male NOD.Scl6a19 mice

Pancreas sections immunostained for insulin were used to assess β-cell mass as well as islet number and size distribution. Representative images are shown in Fig. 6A to 6C showing a normal size islet without evidence of insulitis (see Fig. 6A), a small cluster of insulin-staining cells (see Fig. 6B), and 2 large islets with invasive insulitis of less than 10% and close to 50% of the islet areas (see Fig. 6C). A greater number of islets was evident in HFHS compared to chow-fed Slc6a19^+/+ mice (P < .05); however, B⁰AT1 deficiency had no effect on the islet number of these two mice groups (see Fig. 6D). B⁰AT1 deficiency, however, was associated with a 2.2-fold increase in islet number in the HFHP-fed mice (P < .01) (Fig. 6G). A diet main effect was noted with respect to β-cell area, although post hoc testing did not reveal statistically significant differences between the groups (Fig. 6E). No differences between groups was found for β-cell mass measurements (Fig. 6F). Of note, in analysis of islet size distributions, the differences in islet cell numbers between the two Slc6a19 genotypes of HFHP fed mice were predominantly determined by greater β-cell cell cluster (<5000 μm²) and small islet (≥5000 and <20 000 μm²) counts (P < .001 and P < .01, respectively) in the Slc6a19^−/− mice (see Fig. 6G).

Figure 6.

B⁰AT1 deficiency increases the number of small islets and β-cell clusters in high-fat high-protein (HFHP)-fed male NOD.Slc6a19 mice. A to C, Representative micrographs showing insulin immunohistochemistry examples. A, Normal size islet (≥20 000 and <50 000 μm²) without evidence of insulitis; B, small cluster of insulin immune-stained cells (<5000 μm²); C, 2 large islets (50 000 μm²) with insulitis scores of 2, one with less than 10% invasion and one at just under 50% inflammatory infiltrate invasion. D to G, D, Number of islets per pancreas section; E, percentage of pancreas area occupied by β cells; F, β-cell mass; and G, islet size distribution. Data presented as means ± SEM of n = 8 to 14 mice per group. D to F, Two-way analysis of variance (ANOVA) with Tukey post hoc testing; **P less than .01 vs Slc6a19^+/+ on same diet; ^#P less than .05 vs chow of the same genotype group; ^††P less than .01 vs high-fat high-sucrose (HFHS) of same genotype group; n.s., not significant. G, Three-way ANOVA with Tukey post hoc testing for diet effect; for islet category less than 5000 μm², chow vs HFHS, P < .0001; chow vs HFHP, n.s.; HFHS vs HFHP, P less than .05; for genotype effect; **P less than .01, ***P less than .001 vs Slc6a19^+/+ on same diet.

Findings in Chow, High-Fat High-Sucrose, and High-Fat High-Protein Feeding of Male Nonobese Diabetic Mice Aged to 30 Weeks

By age 30 weeks, the incidence of diabetes was again low, with no differences seen between groups. Of 24 mice that began this second study, only 3 developed diabetes with incidences of 25% (2/8), 12.5% (1/8), and 0% (0/8) in, respectively, the chow, HFHS, and HFHP groups (P = .33) (Fig. 7A and 7B). As in the NOD.Slc6a19^+/+ mice, HFHS-fed NOD mice were more prone to metabolic dysfunction than the other two diet groups, as shown in Supplementary Results and Supplementary Fig. S1 to S3 (38). Of note, male NOD mice after fasting and refeeding had reduced postfeeding glycemia and insulinemia (see Supplementary Fig. S2) (38). HFHP-fed mice had fewer islets, with insulitis scores of 1 and 2 compared to the HFHS-fed mice (see Supplementary Fig. S3) (38).

Figure 7.

Combining studies, high-fat high-sucrose (HFHS) feeding of male NOD and NOD.Slc6a19 mice increases total number of islets per pancreas and lowers the insulitis average score compared to chow fed mice. A, Serial 9 Am fed plasma glucose of male NOD mice fed chow, HFHS, and high-fat high-protein (HFHP) diets (individual mice results shown, n = 8 mice per group). B, Diabetes-free survival in male NOD mice. Total number of islets counted per pancreas section (Gehan-Breslow-Wilcoxon test, n = 8 mice per group). C, Total number of islets counted per pancreas section, D, insulitis average score per pancreas section in male NOD and NOD.Slc6a19 mice. E, Total number of islets counted per pancreas section, F, insulitis average score per pancreas section in male NOD and NOD.Slc6a19 mice after removal of mice pancreas results of diabetic mice, including severely glucose-intolerant mice. C and D, Chow n = 33 mice, HFHS n = 25 mice, HFHP n = 26 mice; E and F, chow n = 29 mice, HFHS n = 24 mice, HFHP n = 20 mice; one-way analysis of variance with Bonferroni post hoc testing; *P less than .05; **P less than .01. G, Diabetes-free survival all male NOD and NOD.Slc6a19 mice. Chow n = 34, HFHS n = 26, HFHP n = 28; Gehan-Breslow-Wilcoxon test; P = .024; Bonferroni post hoc tests chow vs HFHS; P = .22; chow vs HFHP; P = .52; HFHS vs HFHP; P = .024.

High-Fat High-Protein–Fed Mice With Severe Glucose Intolerance Not Meeting Criteria for Diabetes

One mouse in the HFHP group of the NOD study and one mouse in the HFHP Slc6a19^+/+ group in the NOD.Slc6a19 study had severe glucose intolerance when tested at age 23 to 24 weeks, but neither progressed to meet the criteria of diabetes. The ipGTT glucose and insulin, and serial 9 Am-fed glucose concentrations, including those of the other mice of the same groups, are shown in Supplementary Fig. S4 (38). As they were clear outliers, the ipGTT results were not included in the results presented earlier.

Beneficial Effects of High-Fat High-Sucrose Feeding on Pancreatic Islet Number, Insulitis Scores, and Diabetes Incidence Shown by Combining Nonobese Diabetic and NOD.Slc6a19 Male Mice Results

Considering that B⁰AT1 deficiency had no effect on diabetes incidence, we have combined all mice from the 2 studies to further assess diet-only effects. Islet number per pancreas section was 63% and 49% higher in HFHS mice compared to, respectively, chow- and HFHP-fed mice (P < .01 and P < .05) (Fig. 7C). The average insulitis score was 48% lower in HFHS mice compared to chow mice (P < .01) (Fig. 7D). As mice that developed diabetes, and the outliers with severe glucose intolerance, had low islet number and higher insulitis scores, their results were removed in a sensitivity analysis. Statistical differences in islet number and insulitis scores between normoglycemic HFHS and chow-fed mice remained (Fig. 7E and 7F). In a final analysis, diabetes-free survival was assessed in all mice in which the threshold for diabetes diagnosis was modified to include severe glucose intolerance. Diabetes incidence was 14.7% (5/34) in chow-fed mice, 3.8% (1/26) in HFHS, and 25% (7/28) in HFHP-fed mice with post hoc testing showing a diabetes-free survival advantage in HFHS compared to HFHP mice (P < .02) (Fig. 7G).

Discussion

This study highlights the importance of dietary composition, but not amino acid availability, in the development of autoimmune diabetes in male NOD mice. Combining male NOD and NOD.Slc6a19 mice together, the semi-purified HFHS diet mice had the lowest, while the semi-purified HFHP diet had the highest, incidence of autoimmune diabetes. B⁰AT1 deficiency had no effect on the incidence of autoimmune diabetes in male NOD.Slc6a19 mice, whether fed chow, HFHS, or HFHP diets. B⁰AT1 deficiency, however, attenuated excess body weight gain and the development of hyperinsulinemia in the fed state and during ipGTT testing in male NOD.Slc6a19 mice. Unexpectedly, B⁰AT1 deficiency in NOD.Slc6a19 mice fed the HFHP diet was associated with a 2.2-fold increase in small islets and β-cell clusters per pancreas section.

Considering the low incidence of autoimmune diabetes in the mice overall, caution is required in interpreting differences in diabetes rates between the groups. However, the pancreatic islet findings, together with those of diabetes incidence, do suggest a diabetes-protective effect of the HFHS diet. HFHS mice, with the lowest diabetes incidence, had overall the highest islet number and the lowest average insulitis scores. This finding in HFHS-fed mice is consistent with previous studies of female NOD mice, in which semi-purified HFNP diets were compared to unrefined standard rodent chow diets (21, 22). Increased islet β-cell proliferation and mass were reported in HFNP-fed mice (a similar diet to the HFHS diet of the present study) compared to unrefined chow-fed female NOD mice, suggesting that the beneficial effect of HFHS feeding is its ability to induce β-cell mass expansion (22). Batdorf et al (21) showed higher diabetes incidence in female mice fed a semi-purified HFNP compared to a semi-purified diet with low-fat normal-protein (LFNP) content and concluded it was a consequence of the high fat. The HFNP and LFNP diets in that study, however, while being equivalent in protein and sucrose content, were not equivalent in carbohydrate content, as the LFNP diet contained much more corn starch (21). The higher unrefined carbohydrate content of the LFNP diet may have in fact been beneficial, rather than the high fat content being harmful (21). Our finding that the HFHP diet (19% carbohydrate content) resulted in a higher incidence of diabetes compared to the HFHS diet (40% carbohydrate content) could be explained by its lower sucrose content. This could also be an explanation for the higher diabetes incidence in female NOD mice fed a semi-purified HFHP diet compared to a semi-purified LFNP, as the latter diet had greater content of maize starch and sucrose (23). Previously we showed in New Zealand Obese mice that a low-carbohydrate high-fat diet did not increase islet β-cell mass, indicative of the importance of carbohydrate content in Western diets for β-cell mass expansion (39). To summarize, high-fat diets with higher sucrose have a protective effect against autoimmune diabetes in NOD mice, possibly due to an effect of simple carbohydrate with fat to increase pancreatic islet number and to expand β-cell mass. This protective effect is not seen in diets high in fat and protein with low carbohydrate content.

The fed-state glucose levels and glucose and insulin levels in response to refeeding were lowest in the HFHP-fed male NOD and NOD.Slc6a19 mice, consistent with its low carbohydrate content. Thus, the HFHP diet exerts a lower glycemic load on islet β cells; however, this did not protect them from autoimmune diabetes, against nutrient-induced islet stress being a contributor to this diet's effect on diabetes incidence.

Islet size, number, β-cell area, and mass were measured in the NOD.Slc6a19 mice of the present study. Most striking were the effects of diet on islet number rather than mass, particularly small islets, which the HFHS diet clearly increased in the wild-type mice. This would be consistent with the protective effect of the HFHS diet against autoimmune diabetes being by islet β-cell neogenesis and proliferation. Unexpected was the increase in small islets and β-cell clusters in the HFHP B⁰AT1-deficient mice, but this was not protective against autoimmune diabetes. We have previously shown that plasma GLP-1 levels are increased by B⁰AT1 deficiency, likely due to an increased amino acid load reaching the ileum to stimulate GLP-1 production from intestinal L cells (29). The relevance of these findings to the human is uncertain though, as β-cell proliferation and/or replication is much less in humans than it is mice. High glucose, however, has been shown to increase β-cell replication in human islets transplanted to immunodeficient mice (40).

Despite HFHS feeding having only mild metabolic effects on male NOD.Slc6a19 mice, B⁰AT1 deficiency was able to curtail HFHS diet–induced accelerated weight gain, epididymal WAT adipose expansion, and fed-state and ipGTT insulinemia. This is consistent with our previous findings of beneficial effects of B⁰AT1 deficiency on metabolic parameters in C57Bl/6J mice, and together with the effects on increasing islet number, supports our ongoing work investigating B⁰AT1 as a therapeutic target for the prevention and treatment of cardiometabolic diseases (29-31). Of note, an oral inhibitor of B⁰AT1 (JNT-517) has been assessed in a phase 1 clinical trial with consideration of developing it for the treatment of phenylketonuria (41).

A major limitation in determining the relevance of the findings of this study to human T1D is an apparent resistance of the NOD islet β-cell to nutrient-induced stress. On removing the mice that developed autoimmune diabetes, the effects of the HFHS diet on the male NOD metabolic phenotype could be evaluated. HFHS feeding increased body weight, increased epididymal WAT mass, modestly increased fed-state and ipGTT plasma insulin, but did not increase liver weight or fed-state glucose concentrations (6.6 ± 1.2 mM in HFHS NOD mice after 30 weeks, 6.4 ± 0.9 mM in HFHS NOD.Slc6a19 mice after 24 weeks). Effects on ipGTT glucose concentrations were also minimal. NOD/ShiLtJArc mice in these studies, therefore, were resistant to developing a T2D-like phenotype. Thus, this strain of mice may not be prone to Western diet–induced islet β-cell stress, consistent with the heterogeneity in islet characteristics of multiple mice strains, as previously reported (42). This could also be an explanation for the lack of effect of B⁰AT1 deficiency on autoimmune diabetes incidence in our previous study of female mice and the present study of male NOD mice (32).

Other mechanisms by which the different diets and Slc6a19 deficiency could affect autoimmune diabetes and metabolic function that we did not investigate include changes in the gut microbiome and the intestinal neurohormonal system (43, 44).

In conclusion, the findings of this study support a potential role for B⁰AT1 inhibitors in treating cardiometabolic disease. The novel finding of an interaction of HFHP feeding and B⁰AT1 deficiency in increasing the presence of pancreatic β cell clusters and small islets clearly warrants further investigation. B⁰AT1 deficiency, however, failed to prevent autoimmune diabetes in the male NOD mice, and in contravention to the accelerator hypothesis, HFHS feeding was protective. The failure of these Western diets to increase autoimmune diabetes incidence in NOD/ShiLtJArc may be due to this mice strain being minimally prone to nutrient-induced islet β-cell stress. Humans are very heterogeneous with respect to islet β-cell susceptibility to stressors. In individuals more prone to nutrient-induced stress, targeting B⁰AT1 with inhibitors may still have a future role.

Abbreviations

ANOVA

analysis of variance

AUC

area under the curve

GLP-1

glucagon-like peptide 1

HFHP

high-fat high-protein

HFHS

high-fat high-sucrose

HFNP

high-fat normal-protein

HOMA-IR

homeostatic model assessment for insulin resistance

ipGTT

intraperitoneal glucose tolerance test

LFNP

low-fat normal-protein

NOD

nonobese diabetic

T1D

type 1 diabetes

T2D

type 2 diabetes

WAT

white adipose tissue

Funding

This work was funded by a project grant (APP1128442, CJN) from the National Health and Medical Research Council, Australia and a grant from the Canberra Hospital Private Practice Fund. G.B. received funding from the National Collaborative Research Infrastructure (NCRIS ) via the Australian Phenomics Network.

Disclosures

The authors have no conflicts of interest to declare.

Data Availability

Original data generated and analyzed during this study are included in this published article, including in the Supplementary Results and Supplementary Figures (38).