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The ketogenic diet (KD) is a popular option for managing body weight, though its influence on glucose and lipid metabolism was still inconclusive. Gut microbiota is modulated by dietary pattens and has been associated with the changes of metabolic homeostasis induced by KD. Here, we found that two types of KDs, KD1 (8.8% carbohydrate, 73.4% fat, 17.9% protein, 5.7 kcal/g) and KD2 (0.4% carbohydrate, 93.2% fat, 6.4% protein, 6.7 kcal/g), induced changes of gut microbiota and its metabolites, contributing to glucose intolerance but not lipid accumulation in mice. Following a 2-week intervention with KDs, mice fed on KD1 displayed symptoms related to obesity, whereas KD2-fed mice exhibited a decrease in body weight but had severe hepatic lipid accumulation and abnormal fatty acid metabolism, while both KDs led to significant glucose intolerance. Compared to the mice fed on a standard chow diet, the conventional mice fed on both KD1 and KD2 had significant shifted gut microbiota, lower levels of short chain fatty acids (SCFAs) and composition alteration of cecal bile acids. By using an antibiotic cocktail (ABX) to deplete most of the gut microbiota in mice, we found the disturbances induced by KDs in lipid metabolism were similar in the ABX-treated mice to their conventional companions, but the disturbances in glucose metabolism were absent in the ABX-treated mice. In conclusion, these findings suggest that ketogenic diets disrupted glucose and lipid metabolism, at least in mice, and highlight the gut microbial culprits associated with KD induced glucose intolerance rather than lipid accumulation. [ABSTRACT FROM AUTHOR]

The ketogenic diet (KD) is a popular option for managing body weight, though its influence on glucose and lipid metabolism was still inconclusive. Gut microbiota is modulated by dietary pattens and has been associated with the changes of metabolic homeostasis induced by KD. Here, we found that two types of KDs, KD1 (8.8% carbohydrate, 73.4% fat, 17.9% protein, 5.7 kcal/g) and KD2 (0.4% carbohydrate, 93.2% fat, 6.4% protein, 6.7 kcal/g), induced changes of gut microbiota and its metabolites, contributing to glucose intolerance but not lipid accumulation in mice. Following a 2-week intervention with KDs, mice fed on KD1 displayed symptoms related to obesity, whereas KD2-fed mice exhibited a decrease in body weight but had severe hepatic lipid accumulation and abnormal fatty acid metabolism, while both KDs led to significant glucose intolerance. Compared to the mice fed on a standard chow diet, the conventional mice fed on both KD1 and KD2 had significant shifted gut microbiota, lower levels of short chain fatty acids (SCFAs) and composition alteration of cecal bile acids. By using an antibiotic cocktail (ABX) to deplete most of the gut microbiota in mice, we found the disturbances induced by KDs in lipid metabolism were similar in the ABX-treated mice to their conventional companions, but the disturbances in glucose metabolism were absent in the ABX-treated mice. In conclusion, these findings suggest that ketogenic diets disrupted glucose and lipid metabolism, at least in mice, and highlight the gut microbial culprits associated with KD induced glucose intolerance rather than lipid accumulation. [ABSTRACT FROM AUTHOR]

The ketogenic diet (KD) is a popular option for managing body weight, though its influence on glucose and lipid metabolism was still inconclusive. Gut microbiota is modulated by dietary pattens and has been associated with the changes of metabolic homeostasis induced by KD. Here, we found that two types of KDs, KD1 (8.8% carbohydrate, 73.4% fat, 17.9% protein, 5.7 kcal/g) and KD2 (0.4% carbohydrate, 93.2% fat, 6.4% protein, 6.7 kcal/g), induced changes of gut microbiota and its metabolites, contributing to glucose intolerance but not lipid accumulation in mice. Following a 2-week intervention with KDs, mice fed on KD1 displayed symptoms related to obesity, whereas KD2-fed mice exhibited a decrease in body weight but had severe hepatic lipid accumulation and abnormal fatty acid metabolism, while both KDs led to significant glucose intolerance. Compared to the mice fed on a standard chow diet, the conventional mice fed on both KD1 and KD2 had significant shifted gut microbiota, lower levels of short chain fatty acids (SCFAs) and composition alteration of cecal bile acids. By using an antibiotic cocktail (ABX) to deplete most of the gut microbiota in mice, we found the disturbances induced by KDs in lipid metabolism were similar in the ABX-treated mice to their conventional companions, but the disturbances in glucose metabolism were absent in the ABX-treated mice. In conclusion, these findings suggest that ketogenic diets disrupted glucose and lipid metabolism, at least in mice, and highlight the gut microbial culprits associated with KD induced glucose intolerance rather than lipid accumulation. [ABSTRACT FROM AUTHOR]

Background: Polycystic ovary syndrome (PCOS) is a multifaceted disorder that impacts metabolism, reproduction, as well as endocrine function, characterized by excessive levels of androgen and insulin resistance. The gut microbiota has been implicated in the pathogenesis of PCOS. However, the precise mechanisms through which the gut microbiota influences PCOS still require further elucidation. Methods: The PCOS mouse model was established through the administration of letrozole to both conventional and antibiotics-treated mice. The evaluation of glucose metabolism, sex hormone levels, and ovarian morphology was conducted. Furthermore, the fecal samples from each group of mice were subjected to 16S rRNA gene sequencing, and functional prediction of gut microbiota was proceeded using PICRUSt2 to explore potential mechanisms. Results: By using letrozole-induced PCOS mice model, we manifested that antibiotic intervention significantly reduced the serum total testosterone level and ameliorated glucose intolerance. Antibiotic treatment reduced the number of amplicon sequence variants (ASVs), as well as the Shannon and Simpson index. Meanwhile, letrozole induced a significant increase in the Shannon and Simpson index instead of ASVs. Through random forest model analysis, the results revealed significant alterations in three distinct groups of microbiota, namely Clostridia_vadinBB60_group, Enterorhabdus, and Muribaculaceae after letrozole treatment. Further correlation analysis revealed a positive association between alterations in these microbiota and both serum total testosterone levels and the area under the curve (AUC) of blood glucose in IPGTT. The administration of antibiotics led to a decrease in the absolute abundance of 5 ASVs belonging to unclassified Clostridia_vadinBB60_group, unclassified Enterorhabdus, and unclassified Muribaculaceae, which exhibited a positive correlation with the levels of total testosterone in mice serum, as well as the area under the curve of blood glucose in IPGTT. Moreover, 25 functional pathways of gut microbiome were significantly discrepant between the letrozole-treated mice with and without antibiotics. Conclusion: These results suggest that disturbance of the gut microbiota may take participate in the progression of PCOS and manipulating the composition of the gut microbiota may be a therapeutic approach for managing PCOS. [ABSTRACT FROM AUTHOR]

Background: Huang Lian (HL), one of the traditional Chinese medicines (TCMs) that contains multiple active components including berberine (BBR), has been used to treat symptoms associated with diabetes for thousands of years. Compared to the monomer of BBR, HL exerts a better glucose-lowering activity and plays different roles in regulating gut microbiota. However, it remains unclear what role the gut microbiota plays in the anti-diabetic activity of HL. Methods: In this study, a type 2 diabetes mellitus (T2DM) mouse model was induced with a six-week high-fat diet (HFD) and a one-time injection of streptozotocin (STZ, 75 mg/kg). One group of these mice was administrated HL (50 mg/kg) through oral gavage two weeks after HFD feeding commenced and continued for four weeks; the other mice were given distilled water as disease control. Comprehensive analyses of physiological indices related to glycolipid metabolism, gut microbiota, untargeted metabolome, and hepatic genes expression, function prediction by PICRUSt2 were performed to identify potential mechanism. Results: We found that HL, in addition to decreasing body fat accumulation, effectively improved insulin resistance by stimulating the hepatic insulinmediated signaling pathway. In comparison with the control group, HL treatment constructed a distinct gut microbiota and bile acid (BA) profile. The HL-treated microbiota was dominated by bacteria belonging to Bacteroides and the Clostridium innocuum group, which were associated with BA metabolism. Based on the correlation analysis, the altered BAs were closely correlated with the improvement of T2DM-related markers. Conclusion: These results indicated that the anti-diabetic activity of HL was achieved, at least partly, by regulating the structure of the gut microbiota and the composition of BAs. [ABSTRACT FROM AUTHOR]

Context: Cardiovascular benefits of empagliflozin in patients with type 2 diabetes mellitus (T2DM) have been reported; however, the underlying mechanism remains unknown. Objective: We hypothesized that the cardiovascular benefits of empagliflozin are associated with altered gut microbiota and plasma metabolites, and that empagliflozin may be used as an initial treatment for patients with T2DM at risk of cardiovascular diseases (CVDs). Methods: This randomized, open-label, 3-month, 2-arm clinical trial included 76 treatment-naïve patients with T2DM and risk factors for CVD who were treated with either empagliflozin (10 mg/d, n = 40) or metformin (1700 mg/d, n = 36). We investigated changes in clinical parameters related to glucose metabolism and CVD risk factors, gut microbiota using 16S rRNA gene sequencing, and plasma metabolites using LC-MS. Results: We found significant and similar reduction in HbA1c levels and alleviation of glucose metabolism in both groups. However, only empagliflozin improved CVD risk factors. Empagliflozin significantly reshaped the gut microbiota after 1 month of treatment; this alteration was maintained until the end of the trial. Empagliflozin increased the levels of plasma metabolites such as sphingomyelin, but reduced glycochenodeoxycholate, cis-aconitate, and uric acid levels. Concurrently, empagliflozin elevated levels of short-chain fatty acid-producing bacteria such as species from Roseburia, Eubacterium, and Faecalibacterium, and reduced those of several harmful bacteria including Escherichia-Shigella, Bilophila, and Hungatella. Conclusion: Empagliflozin may be a superior initial therapy for patients with T2DM at risk of CVDs; its cardiovascular benefits may be associated with shifts in gut microbiota and plasma metabolites. [ABSTRACT FROM AUTHOR]

Dysbiotic gut microbiota contributes to genetically obese phenotype in human. However, the effect of genetic obesity-associated gut microbiota on host hepatic metabolic deteriorations remains largely unknown. Gut microbiota from a genetically obese human donor before and after a dietary weight loss program was transplanted into germ-free C57BL/6J male mice, grouped as PreM and PostM groups, respectively. The gut microbiome, liver pathology and transcriptome response in the gnotobiotic mice were evaluated. After being fed on normal chow diet for 4 weeks, PreM group developed liver macrovesicular steatosis accompanied with higher concentrations of hepatic triglyceride and cholesterol, while PostM group exhibited normal hepatic physiology. The gut microbiota in PreM and PostM groups was significantly different from each other and was more resembling with their respective donor. RNA-sequencing revealed that, in comparison with PostM group, PreM group showed a foregoing pro-steatotic transcriptional response in liver featuring by the repression of lipid beta-oxidation and the activation of lipid absorption and cholesterol uptake before the pathology of liver steatosis. Moreover, peroxisome proliferator-activated receptor alpha (PPARa), which was repressed in PreM group, may act as crucial regulator of the hepatic transcriptional profile of lipid metabolism between two groups. Our results show that gut microbiota from a genetically obese human promotes the onset of liver steatosis by impacting hepatic transcriptional profile of lipid metabolism in mice. This adds new evidence that gut microbiota may play a causative role in the development of non-alcoholic fatty liver disease. [ABSTRACT FROM AUTHOR]

Wind power industry plays an important role in promoting the development of low-carbon economic and energy transformation in the world. However, the randomness and volatility of wind speed series restrict the healthy development of the wind power industry. Accurate wind speed prediction is the key to realize the stability of wind power integration and to guarantee the safe operation of the power system. In this paper, combined with the Empirical Mode Decomposition (EMD), the Radial Basis Function Neural Network (RBF) and the Least Square Support Vector Machine (SVM), an improved wind speed prediction model based on Empirical Mode Decomposition (EMD-RBF-LS-SVM) is proposed. The prediction result indicates that compared with the traditional prediction model (RBF, LS-SVM), the EMDRBF-LS-SVM model can weaken the random fluctuation to a certain extent and improve the short-term accuracy of wind speed prediction significantly. In a word, this research will significantly reduce the impact of wind power instability on the power grid, ensure the power grid supply and demand balance, reduce the operating costs in the grid-connected systems, and enhance the market competitiveness of the wind power. [ABSTRACT FROM AUTHOR]

n view of the influence of cutting heat and cutting force on the machining precision of micro-machining, this paper carries out micro-milling temperature measurements and deformation measurement tests based on the theoretical model of temperature field distribution of workpiece and the simulation model of workpiece deformation, providing technical basis for the high-precision machining of precision micro-parts. A theoretical model for the description of the increase in the cutting temperature of the workpiece is established prior to using an inverse evaluation method for solving the heat source intensity iteratively. During the finite element analysis of the distribution of the temperature field and heat distortion, the process of the heat transfer is simplified as a process of applying a series surface heat source to workpiece. Besides, this paper carried on a series of micromilling experiments, used a fast-response thermocouple which has a property of self-renewal for the measurement of the change of the workpiece temperature, the response time of the applied thermocouple is within the magnitude of microsecond, and then, a high-frequency amplifier and an electric potential acquisition equipment were used to gain the transient temperature in the cutting area; meanwhile, a dynamometer is applied to measure the three-directional forces, and finally, the workpiece deformation would be measured by the Keyence microscope. Through the comparison of the simulated temperature and deformation with the experimental results, the simulation model showed considerable reliability. [ABSTRACT FROM AUTHOR]

Thanks to non-pollution and sustainability of wind energy, it has become the main source of power generation in the new era worldwide. However, the inherent random fluctuation and intermittency of wind power have negative effects on the safe and stable operation of power system and the quality of power. The key solving this problem is to improve the accuracy of wind speed prediction. In the paper, considering the forecasting accuracy is affected by many factors, we propose that, Principal Component Analysis (PCA) is combined with Independent Component Analysis (ICA) to process the sample, which can weaken the mutual interference between the various factors, extract accurately independent component reflected the characteristics of wind farm and achieve the purpose of improving the accuracy of wind speed prediction. At the same time, the adaptive and self-learning ability of neural network is more suitable for wind speed sequence prediction. The prediction results demonstrate that compared with the traditional neural network predicting model (RBF, BP, Elman), this model makes full use of the information provided by varieties of relevant factors, weakens the volatility of wind speed sequence and significantly enhances the short-term wind speed forecasting accuracy. The research work in the paper can help wind farm reasonably arrange the power dispatching plan, reduce the power operation cost and effectively boost the large-scale development and utilization of renewable energy. [ABSTRACT FROM AUTHOR]

Inflammasomes are involved in gut homeostasis and inflammatory pathologies, but the role of NLRP3 inflammasome in these processes is not well understood. Cryopyrin-associated periodic syndrome (CAPS) patients with NLRP3 mutations have autoinflammation in skin, joints, and eyes, but not in the intestine. Here we show that the intestines of CAPS model mice carrying an Nlrp3R258W mutation maintain homeostasis in the gut. Additionally, such mice are strongly resistant to experimental colitis and colorectal cancer; this is mainly through a remodelled gut microbiota with enhanced anti-inflammatory capacity due to increased induction of regulatory T cells (Tregs). Mechanistically, NLRP3R258W functions exclusively in the lamina propria mononuclear phagocytes to directly enhance IL-1β but not IL-18 secretion. Increased IL-1β boosts local antimicrobial peptides to facilitate microbiota remodelling. Our data show that NLRP3R258W-induced remodelling of the gut microbiota, induces local Tregs to maintain homeostasis and compensate for otherwise-detrimental intestinal inflammation. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the association between cardiorespiratory fitness and gut microbiota composition in premenopausal women. The participants consisted of 71 premenopausal Finnish women (aged 19-49 years). Gut microbiota were analyzed using flow cytometry, 16S rRNA gene hybridization and DNA-staining. Maximum oxygen uptake (VO2max) was assessed by respiratory gas analyzer and body composition by Bioimpdance. We found that participants with low VO2max had lower Bacteroides, but higher Eubacterium rectale-Clostridium coccoides than the high VO2max group (p < 0.05 for all). VO2max was inversely associated with EreC (r = -0.309, p = 0.01) but not with other bacteria. VO2max also negatively correlated with fat% (r = -0.755, p < 0.001), triglycerides (r = -0.274, p = 0.021) and leptin (r = -0.574, p < 0.001). By contrast, EreC was positively associated with fat% (r = 0.382, p = 0.002), dietary fat intake (r = 0.258, p = 0.034), triglycerides (r = 0.390, p = 0.002) and leptin (r = 0.424, p = 0.001), but negatively with carbohydrate intake (r = -0.252, p = 0.034) and HDL (r = -0.26, p = 0.028). After adjusting for age and dietary intake, all the significant associations remained. However, after adjusting for fat%, the associations between VO2max and EreC disappeared. Our results suggest that cardiorespiratory fitness is associated with gut microbiota composition, independent of age and carbohydrate or fat intake. The association between VO2max and EreC, however, appears to be mediated by body fatness. [ABSTRACT FROM AUTHOR]

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder in women. Gut microbiota has been implicated to play a critical role in metabolic diseases and may modulate the secretion of mediators of the brain-gut axis. Interaction between gut microbiota and the endocrine and biochemical disturbances in PCOS still remains elusive. Here, we showed an altered gut microbiota significantly correlated with PCOS phenotype. There were 33 patients with PCOS (non-obese PCOS individuals, PN, n = 12; obese PCOS individuals, PO, n = 21) as well as 15 control subjects (non-obese control individuals, CN, n = 9; obese control individuals, CO, n = 6) enrolled in our study. The plasma levels of serotonin, ghrelin, and peptide YY (PYY) were significantly decreased in patients with PCOS compared with controls, and have a significantly negative correlation with waist circumference and testosterone. Sequencing of the V3-V4 region of the 16S rRNA gene in fecal samples revealed the substantial differences of gut microbial species between the PCOS and non-obese controls. Bacterial species were clustered into 23 co-abundance groups (CAGs) based on the SparCC correlation coefficients of their relative abundance. The CAGs increased in PCOS, including the bacteria belonging to Bacteroides, Escherichia/Shigella and Streptococcus, were negatively correlated with ghrelin, and positively correlated with testosterone and BMI. Furthermore, the CAGs that were decreased in PCOS, including the bacteria from Akkermansia and Ruminococcaceae, showed opposite relationship with body-weight, sex-hormone, and brain-gut peptides. In conclusion, gut microbial dysbiosis in women with PCOS is associated with the disease phenotypes. [ABSTRACT FROM AUTHOR]

Increased evidences have demonstrated that gut microbiota targeted diet intervention can alleviate obesity and related metabolic disorders. The underlying mechanism of interactions among diet, microbiota, and host still remains unclear. Enterobacter cloacae B29, an endotoxin-producing strain dominated in the gut of a morbidly obese volunteer (weight 174.8 kg, BMI 58.8 kg m-2) was isolated and transplanted to germfree mice (inoculated 1010 cells of B29 per day for 1 week). Using deep mRNA sequencing technology, we compared different gene expression profiles in the colon samples of the germfree mice treated with/without B29 and/or high fat diet (HFD) for 16 weeks and identified 279 differential expressed genes in total, including up-regulated genes Apoa4 (fold change, 2.77), Ido1 (2.66), Cyp4a10 (7.01), and down-regulated genes Cyp2e1 (0.11), Cyp26b1 (0.34), Akr1b7 (0.42), Adipoq (0.36), Cyp1a1 (0.11), Apoa1 (0.44), Npc1l1 (0.37), Tff2 (0.13), Apoc1 (0.30), Ctla2a (0.34), Mttp (0.49), Lpl (0.48). Fifty-nine GO biological processes and five KEGG pathways, particularly the peroxisome proliferator-activated receptors signaling pathway, were significantly enriched in response to HFDCB29, which were mainly relevant to inflammation and the metabolism of lipid, lipoprotein, and sterols. These functional changes were consistent with the developed obesity, insulin-resistance, and aggravated inflammatory conditions of the HFDCB29 mice. This work provides insight into the gene expression changes in response to HFDCB29, helping to understand the mechanism of the interactions among HFD, B29 and the germfree mice. [ABSTRACT FROM AUTHOR]

The gut microbiota has been linked with metabolic diseases in humans, but demonstration of causality remains a challenge. The gut microbiota, as a complex microbial ecosystem, consists of hundreds of individual bacterial species, each of which contains many strains with high genetic diversity. Recent advances in genomic and metabolomic technologies are facilitating strain-level dissection of the contribution of the gut microbiome to metabolic diseases. Interventional studies and correlation analysis between variations in the microbiome and metabolome, captured by longitudinal sampling, can lead to the identification of specific bacterial strains that may contribute to human metabolic diseases via the production of bioactive metabolites. For example, high-quality draft genomes of prevalent gut bacterial strains can be assembled directly from metagenomic datasets using a canopy-based algorithm. Specific metabolites associated with a disease phenotype can be identified by nuclear magnetic resonance-based metabolomics of urine and other samples. Such multi-omics approaches can be employed to identify specific gut bacterial genomes that are not only correlated with detected metabolites but also encode the genes required for producing the precursors of those metabolites in the gut. Here, we argue that if a causative role can be demonstrated in follow-up mechanistic studies-for example, using gnotobiotic models-such functional strains have the potential to become biomarkers for diagnostics and targets for therapeutics. [ABSTRACT FROM AUTHOR]

Background: Emerging evidence supports novel roles for vitamin K in cardiometabolic health, some of which may be unique to the bacte-rially synthesized vitamin K forms known as menaquinones. However, factors influencing menaquinone biosynthesis by the gut microbiota and associations with cardiometabolic health have not been examined. Objective: The objective of this study was to identify associations between fecal menaquinone profiles, gut microbiota composition, and biomarkers of cardiometabolic health. Design: The menaquinone profile and gut microbiota structure were periodically measured in fecal samples collected from 77 overweight Chinese adults who consumed a prescribed diet previously shown to alter gut microbiota composition and to improve cardiometabolic biomarkers. Results: Co variance among menaquinones within individual fecal samples partitioned individuals into 2 distinct groups, herein introduced as menaquinotypes of the human gut. Menaquinotypes were characterized by differences in menaquinone (MK) 5 and MK9-MK13 and differences in the relative abundance of several operational taxonomic units (OTUs) delineated at the species level, predominantly within the genera Prevotella spp. and Bacteroides spp. Fecal MK4, MK6, and MK8 decreased during the intervention (P < 0.05); and longitudinal changes in the relative abundance of > 100 OTUs were associated with altered fecal content of ≥ 1 individual menaquinone. The strongest and most consistent relations were between Prevotella spp. and MK5 and MK11-MK13, between Bacteroides spp. and MK9 and MK10, and between Escherichia/Shigella spp. and MK8. Neither individual menaquinones nor menaquinotypes were longitudinally associated with markers of glycemia, insulin resistance, or inflammation. Conclusions: These findings suggest that variability in fecal menaquinone content is predominantly determined by relatively few genera within the gut microbiota and that diet-mediated alterations in gut microbiota composition may provide a feasible approach for altering gut menaquinone content. This trial was registered at the Chinese Clinical Trials Registry as ChiCTR-TRC-09000353. [ABSTRACT FROM AUTHOR]

Berberine, a major pharmacological component of the Chinese herb Coptis chinensis, which was originally used to treat bacterial diarrhea, has recently been demonstrated to be clinically effective in alleviating type 2 diabetes. In this study, we revealed that berberine effectively prevented the development of obesity and insulin resistance in high-fat diet (HFD)-fed rats, which showed decreased food intake. Increases in the levels of serum lipopolysaccharide- binding protein, monocyte chemoattractant protein-1, and leptin and decrease in the serum level of adiponectin corrected for body fat in HFD-fed rats were also significantly retarded by the co-administration of berberine at 100 mg/kg body weight. Bar-coded pyrosequencing of the V3 region of 16S rRNA genes revealed a significant reduction in the gut microbiota diversity of berberine-treated rats. UniFrac principal coordinates analysis revealed a marked shift of the gut microbiota structure in berberine-treated rats away from that of the controls. Redundancy analysis identified 268 berberine-responding operational taxonomic units (OTUs), most of which were essentially eliminated, whereas a few putative short-chain fatty acid (SCFA)-producing bacteria, including Blautia and Allobaculum, were selectively enriched, along with elevations of fecal SCFA concentrations. Partial least square regression models based on these 268 OTUs were established (Q²>0.6) for predicting the adiposity index, body weight, leptin and adiponectin corrected for body fat, indicating that these discrete phylotypes might have a close association with the host metabolic phenotypes. Taken together, our findings suggest that the prevention of obesity and insulin resistance by berberine in HFD-fed rats is at least partially mediated by structural modulation of the gut microbiota, which may help to alleviate inflammation by reducing the exogenous antigen load in the host and elevating SCFA levels in the intestine. [ABSTRACT FROM AUTHOR]

With the expanding availability of sequencing technologies, research previously centered on the human genome can now afford to include the study of humans’ internal ecosystem (human microbiome). Given the scale of the data involved in this metagenomic research (two orders of magnitude larger than the human genome) and their importance in relation to human health, it is crucial to guarantee (along with the appropriate data collection and taxonomy) proper tools for data analysis. We propose to adapt the approaches defined for the analysis of gene-expression microarray in order to infer information in metagenomics. In particular, we applied SAM, a broadly used tool for the identification of differentially expressed genes among different samples classes, to a reported dataset on a research model with mice of two genotypes (a high density lipoprotein knockout mouse and its wild-type counterpart). The data contain two different diets (high-fat or normal-chow) to ensure the onset of obesity, prodrome of metabolic syndromes (MS). By using 16S rRNA gene as a genomic diversity marker, we illustrate how this approach can identify bacterial populations differentially enriched among different genetic and dietary conditions of the host. This approach faithfully reproduces highly-relevant results from phylogenetic and standard statistical analyses, used to explain the role of the gut microbiome in relation to obesity. This represents a promising proof-of-principle for using functional genomic approaches in the fast growing area of metagenomics, and warrants the availability of a large body of thoroughly tested and theoretically sound methodologies to this exciting new field. [ABSTRACT FROM AUTHOR]

This study monitored structural shifts of gut microbiota of rats developing precancerous mucosal lesions induced by carcinogen 1,2-dimethyl hydrazine (DMH) treatment using PCR-denaturing gradient gel electrophoresis (DGGE) and 454 pyrosequencing on the 16S rRNA gene V3 region. Partial least square discriminant analysis of DGGE fingerprints showed that the gut microbiota structure of treated animals was similar to that of the controls 1 and 3 weeks after DMH treatments, but significantly different 7 weeks after DMH treatments, when a large number of aberrant crypt foci (ACF) developed in their colons. Martens' uncertainty test, followed byanova test ( P<0.05) identified Ruminococcus-like and Allobaculum-like bacteria as key variables for discrimination of DMH-treated rats from controls. Real-time PCR confirmed the significant increase of the Ruminococcus obeum and the Allobaculum-like bacteria in DMH-treated rats. UniFrac analysis based on V3 pyrosequencing further validated that the gut microbiota structures of treated and control animals were similar at an early stage, but segregated after ACF formation. Thirteen operational taxonomic units including Ruminococcus-like and Allobaculum-like bacteria were identified as key variables for the discrimination of DMH-treated rats from controls. Dynamic analysis of gut microbiota may become a noninvasive strategy for monitoring host health changes induced by carcinogen exposure. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study developed a new statistical strategy for analyzing clone library data to observe whether there is a defined pattern in structural responses of gut microbiota to environmental perturbations. A large clone library of genus Bacteroides was constructed with fecal samples for each subject in rotavirus-infected (Group R) and healthy children (Group H). In all, 665 clones of the 12 Group H subjects and 284 clones of the nine Group R subjects were sequenced and classified into 34 operational taxonomic units (OTUs) with a similarity cutoff at 98%. Partial least squares-discriminant analysis was used to observe the change of the Bacteroides spp. composition caused by rotavirus infection and to identify the most relevant species contributing to this shift. It was revealed that H subjects and R subjects were well separated. Bacteroides vulgatus, Bacteroides stercoris and Bacteroides fragilis were identified as the most important discriminating OTUs between two groups. The increased abundance of B. fragilis and the decreased populations of B. vulgatus and B. stercoris in infected guts observed in this study were in agreement with previous culture-based studies. The strategy developed in this work can be used to reveal patterns in structural responses of gut microbiota to environmental perturbations from large-scale 16S rRNA gene-based sequencing data. [ABSTRACT FROM AUTHOR]

Major histocompatibility complex class I genes are among the most polymorphic genes characterized. The high level of polymorphism is essential for generating host immune responses. In humans, three distinct genomic loci encode human leukocyte antigen (HLA) class I genes, allowing individuals to express up to six different HLA class I molecules. In cattle, the number of distinct genomic loci are currently at least six, and the number of different bovine leukocyte antigens (BoLA) class I molecules that are expressed in individual animals are variable. The extent of allele variation within the cattle population is unknown. In this study, the number and variety of BoLA class I sequences expressed by 36 individuals were determined from full-length BoLA class I cDNA clones. Twenty distinct BoLA class I alleles were identified, with only four being previously reported. The number of expressed BoLA class I alleles in individual animals ranged between one and four, with none of the animals having an identical complement of BoLA class I molecules. Variation existed in the number of BoLA class I alleles expressed as well as the composition of expressed alleles, however, several BoLA class I alleles were found in multiple individual animals. Polymorphic amino acid sites were analyzed for positive and negative selection using the ADAPTSITE program. In the antigen recognition sites (ARS), there were eight positions that were predicted to be under positive selection and three positions that were predicted to be under negative selection from 62 positions. In contrast, for non-antigen recognition sites (non-ARS), there were three positions that were predicted to be under positive selection and 20 that were predicted to be under negative selection from 278, indicating that positive selection of amino acids occurs at a greater frequency within the antigen recognition sites. [ABSTRACT FROM AUTHOR]

Hidden Markov models (HMMs) are one of various methods that have been applied to prediction of major histo-compatibility complex (MHC) binding peptide. In terms of model topology, a fully-connected HMM (fcHMM) has the greatest potential to predict binders, at the cost of intensive computation. While a profile HMM (pHMM) performs dramatically fewer computations, it potentially merges overlapping patterns into one which results in some patterns being missed. In a profile HMM a state corresponds to a position on a peptide while in an fcHMM a state has no specific biological meaning. This work proposes optimally-connected HMMs (ocHMMs), which do not merge overlapping patterns and yet, by performing topological reductions, a model's connectivity is greatly reduced from an fcHMM. The parameters of ocHMMs are initialized using a novel amino acid grouping approach called "multiple property grouping." Each group represents a state in an ocHMM. The proposed ocHMMs are compared to a pHMM implementation using HMMER, based on performance tests on two MHC alleles HLA (Human Leukocyte Antigen)-A*0201 and HLA-B*3501. The results show that the heuristic approaches can be adjusted to make an ocHMM achieve higher predictive accuracy than HMMER. Hence, such obtained ocHMMs are worthy of trial for predicting MHC-binding peptides. [ABSTRACT FROM AUTHOR]

A correction to the article "Interactions Between Gut Microbiota, Host Genetics & Diet Relevant to Development of Metabolic Syndromes in Mice" that was published in the October 29, 2009 issue is presented.