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. 2024 Mar 5;12(6):4049-4062.
doi: 10.1002/fsn3.4061. eCollection 2024 Jun.

1H-NMR-based metabolomics reveals the preventive effect of Enteromorpha prolifera polysaccharides on diabetes in Zucker diabetic fatty rats

Jie Chen  1 , Shuting Wang  1 , Fuchuan Guo  1 , Yupeng Gong  1 , Tianbao Chen  2 , Chris Shaw  2 , Rencai Jiang  1 , Fang Huang  1 , Dai Lin  1
Affiliations

1H-NMR-based metabolomics reveals the preventive effect of Enteromorpha prolifera polysaccharides on diabetes in Zucker diabetic fatty rats

Jie Chen et al. Food Sci Nutr. .

Abstract

The primary objective of this investigation was to explore the beneficial impacts of Enteromorpha prolifera polysaccharide (EP) on dysglycemia in Zucker diabetic fatty (ZDF) rats, while also shedding light on its potential mechanism using 1H-NMR-based metabolomics. The results demonstrated a noteworthy reduction in fasting blood glucose (FBG, 46.3%), fasting insulin (50.17%), glycosylated hemoglobin A1c (HbA1c, 44.1%), and homeostatic model assessment of insulin resistance (HOMA-IR, 59.75%) following EP administration, while the insulin sensitivity index (ISI, 19.6%) and homeostatic model assessment of β-cell function (HOMA-β, 2.5-fold) were significantly increased. These findings indicate that EP enhances β-cell function, increases insulin sensitivity, and improves insulin resistance caused by diabetes. Moreover, EP significantly reduced serum lipid levels, suggesting improvement of dyslipidemia. Through the analysis of serum metabolomics, 17 metabolites were found to be altered in diabetic rats, 14 of which were upregulated and 3 of which were downregulated. Notably, the administration of EP successfully reversed the abnormal levels of 9 out of the 17 metabolites. Pathway analysis further revealed that EP treatment partially restored metabolic dysfunction, with notable effects observed in valine, leucine, and isoleucine metabolism; aminoacyl-transfer RNA (tRNA) biosynthesis; and ketone body metabolism. These findings collectively indicate the potential therapeutic efficacy of EP in preventing glycemic abnormalities and improving insulin resistance. Thus, EP holds promise as a valuable treatment option for individuals with diabetes.

Keywords: Enteromorpha prolifera polysaccharides; branched‐chain amino acid; glycemic abnormalities; metabolomics.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to exert influence on the research presented in this manuscript.

Figures

FIGURE 1
FIGURE 1
Effects of EP on biochemical parameters in ZDF rats. (a) Changes in fasting blood glucose over 9 weeks. (b) Curve and the area under the curve (AUC) of the oral glucose tolerance test (OGTT). (c) Glycosylated hemoglobin A1c (HbA1c). (d) Fasting serum insulin levels. (e) Homeostasis model assessment of insulin resistance (HOMA‐IR). (f) Homeostatic model assessment of β‐cell function (HOMA‐β). (g) Insulin sensitivity index (ISI). (h) Serum lipid profile. NC: control group (n = 9); DM: type 2 diabetic model group (n = 8), EP: intervention group (n = 10), gavaged with 200 mg/kg body weight EP. # p < .05 compared with the NC group; *p < .05 compared with the DM group.
FIGURE 2
FIGURE 2
Representative 1H‐NMR spectrum (0–10 ppm) for the detected metabolites in a serum sample. (1) 2‐Hydroxybutyrate; (2) 2‐Hydroxyisovalerate; (3) 2‐Oxoglutarate; (4) 2‐Oxoisocaproate; (5) 3‐Hydroxybutyrate; (6) 3‐Hydroxyisobutyrate; (7) 3‐Methyl‐2‐oxovalerate; (8) Acetate; (9) Acetoacetate; (10) Acetone; (11) Alanine; (12) Arginine; (13) Aspartate; (14) Betaine; (15) Carnitine; (16) Choline; (17) Citrate; (18) Creatine; (19) Creatinine; (20) Cytidine; (21) Dimethyl sulfone; (22) Ethanol; (23) Formate; (24) Fumarate; (25) Glucose; (26) Glutamate; (27) Glutamine; (28) Glycine; (29) Isoleucine; (30) Isopropanol; (31) Lactate; (32) Leucine; (33) Lysine: (34) Malate; (35) Mannose; (36) Methionine; (37) N6‐Acetyllysine; (38) O‐Acetylcarnitine; (39) Phenylalanine; (40) Proline; (41) Pyruvate; (42) Succinate; (43) Taurine; (44) Threonine; (45) Tryptophan; (46) Tyrosine; (47) Valine; (48) Myo‐inositol; (49) sn‐Glycero‐3‐phosphocholine; (50) τ‐Methylhistidine.
FIGURE 3
FIGURE 3
Principal component analysis (PCA) and PLS‐DA analysis of serum samples from three experimental groups. (a) PCA score plot. (b) Loading scatter plot of PCA. (c) PLS‐DA score plot. (d) Permutation test of PLS‐DA. (e) Loading scatter plot of PLS‐DA. NC: control group (n = 9); DM: type 2 diabetic model group (n = 8), EP: intervention group (n = 10), gavaged with 200 mg/kg body weight EP.
FIGURE 4
FIGURE 4
Box‐and‐whisker plots of differential metabolites among the three groups. (a) Leucine; (b) Isoleucine; (c) Valine; (d) 3‐Methyl‐2‐oxovalerate; (e) 2‐Oxoisocaproate; (f) 3‐Hydroxybutyrate; (g) O‐Acetylcarnitine; (h) Tryptophan; (i) Glucose. NC: control group (n = 9); DM: type 2 diabetic model group (n = 8), EP: intervention group (n = 10), gavaged with 200 mg/kg body weight EP. # p < .05 compared with the NC group; *p < .05 compared with the DM group.
FIGURE 5
FIGURE 5
Metabolic pathway impact prediction based on the KEGG database. (a) Alterative pathway between the DM group and NC group. (b) Alterative pathway between the EP group and DM group. NC: control group (n = 9); DM: type 2 diabetic model group (n = 8), EP: intervention group (n = 10), gavaged with 200 mg/kg body weight EP.
FIGURE 6
FIGURE 6
Summary of metabolic networks in diabetic and EP intervention rats. NC: control group (n = 9); DM: type 2 diabetic model group (n = 8), EP: intervention group (n = 10), gavaged with 200 mg/kg body weight EP.
FIGURE 7
FIGURE 7
Correlation analysis between metabolites and phenotypes of rats. NC: control group (n = 9); DM: type 2 diabetic model group (n = 8), EP: intervention group (n = 10), gavaged with 200 mg/kg body weight EP. *p < .05, ** p < .01.
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