Research article
Comparison of serum metabolite compositions between obese and lean growing pigs using an NMR-based metabonomic approach

https://doi.org/10.1016/j.jnutbio.2010.11.007Get rights and content

Abstract

Childhood obesity has become a prevalent risk to health of children and teenagers. To develop biomarkers in serum for altered lipid metabolism, genetically obese (Ningxiang strain) and lean (Duroc×Landrace×Large Yorkshire strain) growing pigs were used as models to identify potential differences in the serum metabonome between the two strains of pigs after consuming the same diet for 46 days. At the end of the study, pigs were euthanized for analysis of the serum metabonome and determination of body composition. Obese pigs had higher fat mass (42.3±8.8% vs. 21.9±4.5%) and lower muscle mass (35.4±4.5% vs. 58.9±2.5%) than lean pigs (P<.01). Serum concentrations of insulin and glucagon were higher (P<.02) in obese than in lean pigs. With the use of an NMR-based metabonomic technology, orthogonal projection to latent structure with discriminant analysis showed that serum HDL, VLDL, lipids, unsaturated lipids, glycoprotein, myo-inositol, pyruvate, threonine, tyrosine and creatine were higher in obese than in lean pigs (P<.05), while serum glucose and urea were lower in obese pigs (P<.05). In addition, changes in gut microbiota-related metabolites, including trimethylamine-N-oxide and choline, were observed in sera of obese pigs relatively to lean pigs (P<.05). These novel findings indicate that obese pigs have distinct metabolism, including lipogenesis, lipid oxidation, energy utilization and partition, protein and amino acid metabolism, and fermentation of gastrointestinal microbes, compared with lean pigs. The obese Ningxiang pig may be a useful model for childhood obesity research.

Introduction

Obesity is one of the greatest public health challenges of the 21st century [1]. Obesity and overweight pose a major risk for serious diet-related chronic diseases, including type 2 diabetes, cardiovascular diseases, hypertension, stroke, certain forms of cancer, and other obesity-associated problems [2]. The prevalence of obesity increases with age, and there is a greater likelihood that obesity beginning in early childhood will persist through the life span [3]. However, experimental animal models to study childhood obesity are not fully established. Obesity and related health risks were presumably attributable to an excess of energy substrates from overeating [3]. However, the gut microbiota, lifestyle and genetic background also influence this process [4]. To enhance the understanding of relationships between these factors and obesity in humans, some animal species have been evaluated as experimental models for obesity research. Those animal models included C57BL/KsJ db/db mice [5], [6], [7], obese Zucker diabetic fatty rats [8], obese fatty (fa/fa) Zucker rats [9], rabbits [10], Ossabaw pigs [11] and primates [12]. Because of similarities in nutrition and metabolism between pigs and humans [13], [14], genetically obese and lean pigs are useful in childhood obesity research to understand the mechanisms responsible for development of adiposity [6], [15].

Metabonomics provides a useful systems approach to understanding global changes in metabolites in animals in response to alterations in genetics, nutrition, environments and gut microbiota [16], [17], [18], [19]. Despite many studies on obese and lean pigs [20], [21], a comprehensive analysis of metabonomes as potential indicators for the utilization of glucose and amino acids, lipid synthesis, as well as the turnover and storage of fat and protein in obese and lean pigs has not been performed, to the best of our knowledge. The serum metabonome could be used to develop biomarkers to identify early obesity and other associated health risks to facilitate prevention and treatment of obesity.

The Ningxiang pig is a regional swine strain in China and has excessive fat deposition genetically [22], [23]. In contrast, the Duroc×Landrace×Large Yorkshire (DLL) hybrid pig is recognized as a genetically lean strain [23]. The present study was designed to compare serum metabonome between the genetically obese and lean pigs using a nuclear magnetic resonance (NMR)-based metabonomic method.

Section snippets

Pigs, diets, housing and experimental design

Ten castrated male Ningxiang growing pigs (obese type pig) at 4 months of age with an average body weight of 55±6 kg and eight castrated male DLL growing pigs (lean type pig) at 4 months of age with an average body weight of 47±4 kg were obtained from two local commercial swine herds, respectively. They were fed the same corn- and soybean meal-based diet (Table 1) (Tianke Company, Guangzhou, China), which met or exceeded the nutrient recommendations of National Research Council [24]. Pigs were

1H NMR Spectra of serum samples

Examples of a 1H NMR CPMG (Fig. 1A), standard 1D (Fig. 1B) and BPP-LED (Fig. 1C) spectrum from an obese pig are illustrated in Fig. 1. From these spectra, 34 metabolites were unambiguously assigned, and their chemical shifts and peak multiplicity are given in Table 2 along with the corresponding 1H NMR chemical shifts and signal multiplicities. Assignment of metabolites was made by comparison with the published literature [27], [36], [37], [38], [39], [40], [41], [42] and confirmed by

Discussion

Obesity has become a serious and growing public health problem. Childhood obesity is attributable to a variety of nutritional, psychological, familial and physiological factors. However, heredity has been reported to influence fatness, regional fat distribution and response to overfeeding [43]. The objectives of the present study were to investigate metabonomic differences in the serum of genetically obese and lean growing pigs and to explore the feasibility of using the obese Ningxiang pig as

Acknowledgment

We acknowledge the financial supports in part from the National Basic Research Program of China (2007CB914701, 2009CB118800), National Natural Science Foundation of China (30901040, 30901041, 30928018, 30828025, 30771558, 31001015, 31001016 and 31072042), the Knowledge Innovation Program of the Chinese Academy of Sciences (KZCX2-EW-412, KSCX1-YW-02, KSCX2-YW-N-051, Y022042020), CAS/SAFEA International Partnership Program for Creative Research Teams (20100491005-8 and KZCX2-YW-T07), Changsha

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