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Yin X.,Shanghai JiaoTong University | Peng J.,Shanghai University of Traditional Chinese Medicine | Zhao L.,Shanghai JiaoTong University | Zhao L.,Shanghai Center for Systems Biomedicine | And 7 more authors.
Systematic and Applied Microbiology | Year: 2013

Accumulating evidence indicates that disruption of the gut microbiota by a high-fat diet (HFD) may play a pivotal role in the progression of metabolic disorders such as non-alcoholic fatty liver disease (NAFLD). In this study, the structural changes of gut microbiota were analyzed in an HFD-induced NAFLD rat model during treatment with an ancient Chinese herbal formula (CHF) used in clinical practice - Qushi Huayu Fang. CHF treatment significantly reduced body weight, alleviated hepatic steatosis, and decreased the content of triglycerides and free fatty acids in the livers of the rats. Gut microbiota of treated and control rats were profiled with polymerase chain reaction-denaturing gradient gel electrophoresis and bar-coded pyrosequencing of the V3 region of 16S rRNA genes. Both analyses indicated that the CHF-treated group harbored significantly different gut microbiota from that of model rats. Partial least squares discriminant analysis and taxonomy-based analysis were further employed to identify key phylotypes responding to HFD and CHF treatment. Most notably, the genera Escherichia/. Shigella, containing opportunistic pathogens, were significantly enriched in HFD-fed rats compared to controls fed normal chow (P< 0.05) but they decreased to control levels after CHF treatment. Collinsella, a genus with short chain fatty acid producers, was significantly elevated in CHF-treated rats compared to HFD-fed rats (P< 0.05). The results revealed that the bacterial profiles of HFD-induced rats could be modulated by the CHF. Elucidation of these differences in microbiota composition provided a basis for further understanding the pharmacological mechanism of the CHF. © 2013 Elsevier GmbH. Source


Yang Y.,Shanghai Maritime University | Lu B.-L.,Shanghai JiaoTong University | Lu B.-L.,Shanghai Center for Systems Biomedicine | Lu B.-L.,Microsoft
International Journal of Neural Systems | Year: 2010

Prediction of protein subcellular localization is an important issue in computational biology because it provides important clues for the characterization of protein functions. Currently, much research has been dedicated to developing automatic prediction tools. Most, however, focus on mono-locational proteins, i.e., they assume that proteins exist in only one location. It should be noted that many proteins bear multi-locational characteristics and carry out crucial functions in biological processes. This work aims to develop a general pattern classifier for predicting multiple subcellular locations of proteins. We use an ensemble classifier, called the min-max modular support vector machine (M3-SVM), to solve protein subcellular multi-localization problems; and, propose a module decomposition method based on gene ontology (GO) semantic information for M3-SVM. The amino acid composition with secondary structure and solvent accessibility information is adopted to represent features of protein sequences. We apply our method to two multi-locational protein data sets. The M3-SVMs show higher accuracy and efficiency than traditional SVMs using the same feature vectors. And the GO decomposition also helps to improve prediction accuracy. Moreover, our method has a much higher rate of accuracy than existing subcellular localization predictors in predicting protein multi-localization. © 2010 World Scientific Publishing Company. Source


Zhang C.,Shanghai JiaoTong University | Li S.,Chinese Academy of Sciences | Yang L.,Chinese Academy of Sciences | Huang P.,Chinese Academy of Sciences | And 9 more authors.
Nature Communications | Year: 2013

Calorie restriction has been regarded as the only experimental regimen that can effectively lengthen lifespan in various animal models, but the actual mechanism remains controversial. The gut microbiota has been shown to have a pivotal role in host health, and its structure is mostly shaped by diet. Here we show that life-long calorie restriction on both high-fat or low-fat diet, but not voluntary exercise, significantly changes the overall structure of the gut microbiota of C57BL/6 J mice. Calorie restriction enriches phylotypes positively correlated with lifespan, for example, the genus Lactobacillus on low-fat diet, and reduces phylotypes negatively correlated with lifespan. These calorie restriction-induced changes in the gut microbiota are concomitant with significantly reduced serum levels of lipopolysaccharide-binding protein, suggesting that animals under calorie restriction can establish a structurally balanced architecture of gut microbiota that may exert a health benefit to the host via reduction of antigen load from the gut. © 2013 Macmillan Publishers Limited. All rights reserved. Source


Xiao S.,Shanghai JiaoTong University | Zhao L.,Shanghai JiaoTong University | Zhao L.,Shanghai Center for Systems Biomedicine
FEMS Microbiology Ecology | Year: 2014

In the face of the global epidemic of metabolic syndrome (MetS) and its strong association with the increasing rate of cardiovascular morbidity and mortality, it is critical to detect MetS at an early stage in the clinical setting to implement preventive intervention long before the complications arise. Lipopolysaccharide, the cell wall component of Gram-negative bacteria produced from diet-disrupted gut microbiota, has been shown to induce metabolic endotoxemia, chronic low-grade inflammation, and ultimately insulin resistance. Therefore, ameliorating the inflammation and insulin resistance underlying MetS by gut microbiota-targeted, dietary intervention has gained increasing attention. In this review, we propose using dynamic monitoring of a set of translational biomarkers related with the etiological role of gut microbiota, including lipopolysaccharide binding protein (LBP), C-reactive protein (CRP), fasting insulin, and homeostasis model assessment of insulin resistance (HOMA-IR), for early detection and prevention of MetS via nutritional modulation. LBP initiates the recognition and monomerization of lipopolysaccharide and amplifies host immune responses, linking the gut-derived antigen load and inflammation indicated by the plasma levels of CRP. Fasting plasma insulin and HOMA-IR are measured to evaluate insulin sensitivity that is damaged by pro-inflammatory cytokines. The dynamic monitoring of these biomarkers in high-risk populations may provide translational methods for the quantitative and dynamic evaluation of dysbiosis-induced insulin resistance and the effectiveness of dietary treatment for MetS. Monitoring of gut microbiota-based host biomarkers to prevent MetS and evaluate the effectiveness of dietary intervention. © 2014 Federation of European Microbiological Societies. Source


Zhang C.,Shanghai JiaoTong University | Zhang M.,Shanghai JiaoTong University | Wang S.,Chinese National Human Genome Sequencing Center | Han R.,CAS Shanghai Institutes for Biological Sciences | And 10 more authors.
ISME Journal | Year: 2010

Both genetic variations and diet-disrupted gut microbiota can predispose animals to metabolic syndromes (MS). This study assessed the relative contributions of host genetics and diet in shaping the gut microbiota and modulating MS-relevant phenotypes in mice. Together with its wild-type (Wt) counterpart, the Apoa-I knockout mouse, which has impaired glucose tolerance (IGT) and increased body fat, was fed a high-fat diet (HFD) or normal chow (NC) diet for 25 weeks. DNA fingerprinting and bar-coded pyrosequencing of 16S rRNA genes were used to profile gut microbiota structures and to identify the key population changes relevant to MS development by Partial Least Square Discriminate Analysis. Diet changes explained 57% of the total structural variation in gut microbiota, whereas genetic mutation accounted for no more than 12%. All three groups with IGT had significantly different gut microbiota relative to healthy Wt/NC-fed animals. In all, 65 species-level phylotypes were identified as key members with differential responses to changes in diet, genotype and MS phenotype. Most notably, gut barrier-protecting Bifidobacterium spp. were nearly absent in all animals on HFD, regardless of genotype. Sulphate-reducing, endotoxin-producing bacteria of the family, Desulfovibrionaceae, were enhanced in all animals with IGT, most significantly in the Wt/HFD group, which had the highest calorie intake and the most serious MS phenotypes. Thus, diet has a dominating role in shaping gut microbiota and changes of some key populations may transform the gut microbiota of Wt animals into a pathogen-like entity relevant to development of MS, despite a complete host genome. Source

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