Microbiota and SCFA in Lean and Overweight Healthy Subjects

Obesity has recently been linked to the composition of human microbiota and the production of short chain fatty acids (SCFAs). However, these findings rely on experimental studies carried out using rather small and defined groups of volunteers or model animals. Our aim was to evaluate differences within the human intestinal microbiota and fecal SCFA concentration of lean and obese subjects. A total of 98 subjects volunteered to take part in this study. The BMI in kg/m² of 30 volunteers was within the lean range, 35 were overweight and 33 were obese. The fecal microbiota was characterized by real‐time PCR analyses. With the primers used herein we were able to cover 82.3% (interquartile range of 68.3–91.4%) of the total microbiota detectable with a universal primer. In addition, the concentration of SCFA was evaluated. The total amount of SCFA was higher in the obese subject group (P = 0.024) than in the lean subject group. The proportion of individual SCFA changed in favor of propionate in overweight (P = 0.019) and obese subjects (P = 0.028). The most abundant bacterial groups in faeces of lean and obese subjects belonged to the phyla Firmicutes and Bacteroidetes. The ratio of Firmicutes to Bacteroidetes changed in favor of the Bacteroidetes in overweight (P = 0.001) and obese subjects (P = 0.005). Our results are in line with previous reports suggesting that SCFA metabolism might play a considerable role in obesity. However, our results contradict previous reports with regard to the contribution of various bacterial groups to the development of obesity and this issue remains controversial.     

Sitting and Supine Esophageal Pressures in Overweight and Obese Subjects

Esophageal pressure (P_Es) can be used to approximate pleural pressure (P_pl) and might be clinically useful, particularly in the obese e.g., to guide mechanical ventilator settings in critical illness. However, mediastinal artifact (the difference between true P_pl and P_Es) may limit acceptance of the measurement, and reproducibility of P_Es measurements remains unknown. Therefore, we aimed to assess the effect of body posture on P_Es in a cohort of obese, but healthy subjects, some of whom had multiple measurements, to address the clinical robustness of esophageal manometry. Twenty‐five overweight and obese subjects (BMI > 25 kg/m²) and 11 control lean subjects (BMI < 25 kg/m²) underwent esophageal manometry with pressures measured seated and supine. Twenty overweight and obese subjects had measurements repeated after ～1 to 2 weeks. Anthropometric data and sitting and supine spirometry were recorded. The average end‐expiratory P_Es sitting and supine were greater in the overweight and obese group than the lean group (sitting ?0.1 ± 2.1 vs. ?3.3 ± 1.2 cmH₂O, supine 9.3 ± 3.3 vs. 6.9 ± 2.8 cmH₂O, respectively). The mean differences between repeated measurements were small (?0.3 ± 1.7 cmH₂O sitting and ?0.1 ± 1.5 cmH₂O supine). P_Es correlated with a number of anthropometric and spirometric variables. In conclusion, P_Es are slightly greater in overweight and obese subjects than lean subjects; but changes with position are similar in both groups. These data indicate that mediastinal weight and postural effects on P_Es are within a clinically acceptable range, and suggest that esophageal manometry can be used to inform clinical decision making across wide range of body types.     

Air Displacement Plethysmography: Validation in Overweight and Obese Subjects

Objective: Patients with moderate and severe obesity, because of their physical size, often cannot be evaluated with conventional body composition measurement systems. The BOD POD air displacement plethysmography (ADP) system can accommodate a large body volume and may provide an opportunity for measuring body density (D_b) in obese subjects. D_b can be used in two‐ or three‐compartment body composition models for estimating total body fat in patients with severe obesity. The purpose of this study was to compare D_b measured by ADP to D_b measured by underwater weighing (UWW) in subjects ranging from normal weight to severely obese. Research Methods and Procedures: D_b was measured with UWW and BOD POD in 123 subjects (89 men and 34 women; age, 46.5 ± 16.9 years; BMI, 31.5 ± 7.3 kg/m²); 15, 70, and 10 subjects were overweight (25 ≤ BMI < 30 kg/m²), obese (30 ≤ BMI < 40 kg/m²), and severely obese (BMI ≥ 40 kg/m²), respectively. Results: There was a strong correlation between D_b(kilograms per liter) measured by UWW and ADP (r = 0.94, standard error of the estimate = 0.0073 kg/L, p < 0.001). Similarly, percent fat estimates from UWW and ADP using the two‐compartment Siri equation were highly correlated (r = 0.94, standard error of the estimate = 3.58%, p < 0.001). Bland‐Altman analysis showed no significant bias between D_b measured by UWW and ADP. After controlling for D_b measured by ADP, no additional between‐subject variation in D_b by UWW was accounted for by subject age, sex, or BMI. Discussion: Body density, an important physical property used in human body composition models, can be accurately measured by ADP in overweight and obese subjects.     

Interplay Between Weight Loss and Gut Microbiota Composition in Overweight Adolescents

The aim of this study was to determine the influence of an obesity treatment program on the gut microbiota and body weight of overweight adolescents. Thirty‐six adolescents (13–15 years), classified as overweight according to the International Obesity Task Force BMI criteria, were submitted to a calorie‐restricted diet (10–40%) and increased physical activity (15–23 kcal/kg body weight/week) program over 10 weeks. Gut bacterial groups were analyzed by quantitative real‐time PCR before and after the intervention. A group of subjects (n = 23) experienced >4.0 kg weight loss and showed significant BMI (P = 0.030) and BMI z‐score (P = 0.035) reductions after the intervention, while the other group (n = 13) showed <2.0 kg weight loss. No significant differences in dietary intake were found between both groups. In the whole adolescent population, the intervention led to increased Bacteroides fragilis group (P = 0.001) and Lactobacillus group (P = 0.030) counts, and to decreased Clostridium coccoides group (P = 0.028), Bifidobacterium longum (P = 0.031), and Bifidobacterium adolescentis (P = 0.044) counts. In the high weight–loss group, B. fragilis group and Lactobacillus group counts also increased (P = 0.001 and P = 0.007, respectively), whereas C. coccoides group and B. longum counts decreased (P = 0.001 and P = 0.044, respectively) after the intervention. Total bacteria, B. fragilis group and Clostridium leptum group, and Bifidobacterium catenulatum group counts were significantly higher (P < 0.001–0.036) while levels of C. coccoides group, Lactobacillus group, Bifidobacterium, Bifidobacterium breve, and Bifidobacterium bifidum were significantly lower (P < 0.001–0.008) in the high weight–loss group than in the low weight–loss group before and after the intervention. These findings indicate that calorie restriction and physical activity have an impact on gut microbiota composition related to body weight loss, which also seem to be influenced by the individual's microbiota.     

Gut Microbiota Patterns Associated with Colonization of Different Clostridium difficile Ribotypes

C. difficile infection is associated with disturbed gut microbiota and changes in relative frequencies and abundance of individual bacterial taxons have been described. In this study we have analysed bacterial, fungal and archaeal microbiota by denaturing high pressure liquid chromatography (DHPLC) and with machine learning methods in 208 faecal samples from healthy volunteers and in routine samples with requested C. difficile testing. The latter were further divided according to stool consistency, C. difficile presence or absence and C. difficile ribotype (027 or non-027). Lower microbiota diversity was a common trait of all routine samples and not necessarily connected only to C. difficile colonisation. Differences between the healthy donors and C. difficile positive routine samples were detected in bacterial, fungal and archaeal components. Bifidobacterium longum was the single most important species associated with C. difficile negative samples. However, by machine learning approaches we have identified patterns of microbiota composition predictive for C. difficile colonization. Those patterns also differed between samples with C. difficile ribotype 027 and other C. difficile ribotypes. The results indicate that not only the presence of a single species/group is important but that certain combinations of gut microbes are associated with C. difficile carriage and that some ribotypes (027) might be associated with more disturbed microbiota than the others.     

Physical Activity Patterns in Normal-Weight and Overweight/Obese Pregnant Women

The aims of the present study were to assess the volume of physical activity (PA) throughout pregnancy in normal-weight vs overweight/obese women, and to investigate which factors may predict compliance to PA recommendations in these women throughout gestation. In 236 pregnant women, 177 normal-weight and 59 overweight/obese (median[IQR] BMI 21.2[19.9–22.8] vs 26.5[25.5–29.0] kg/m2, respectively), medical history, anthropometry and clinical data, including glucose tolerance, were recorded. In addition, pre-pregnancy PA was estimated by the Kaiser questionnaire, while total, walking and fitness/sport PA during pregnancy were assessed by the Physical Activity Scale for the Elderly (PASE) modified questionnaire, at 14–16, 24–28 and 30–32 weeks of gestation. PA volume was very low in the first trimester of pregnancy in both groups of women. However, it increased in the second and third trimester in normal-weight, but not in overweight/obese subjects. Higher pre-pregnancy PA was a statistically significant predictor of being physically active (>150 minutes of PA per week) during all trimesters of gestation. In conclusion, physical activity volume is low in pregnant women, especially in overweight/obese subjects. PA volume increases during pregnancy only in normal-weight women. Pre-pregnancy PA is an independent predictor of achieving a PA volume of at least 150 min per week during pregnancy.     

Prevalence of Unhealthy Lifestyle Patterns Among Overweight and Obese Adults

This study determined the prevalence of unhealthy eating, exercise, and coping pattern traits among a large sample of overweight and obese adults. We analyzed responses to a 53‐item lifestyle pattern questionnaire posted on a commercial weight loss program Web site collected from 2004 through 2008. Subjects included 446,608 healthy weight, overweight, and obese adults, 18–65 years old, average age 31.9 (s.d. = 11.8), average BMI 30.5 kg/m² (s.d. = 7.5). Categorically, 25.5% were healthy weight, 29.0% were overweight, 33.7% were class I–II obesity, and 11.8% class III obesity. A stratified random sample was used to estimate the prevalence of the 21 lifestyle patterns (7 eating, 7 exercise, and 7 coping) in the general population, and the prevalence of patterns in the complete dataset was further analyzed by gender, age, and BMI. Finally, we analyzed the odds ratio of the pattern prevalence for each BMI category. We found that unhealthy lifestyle patterns in diet, exercise, and coping were highly prevalent among this population. In general, the prevalence of these patterns rose with increasing BMI and is correlated with advancing age. Gender differences were seen with many of the patterns, most noticeably among the coping patterns. The odds ratio for 18 of the 21 patterns was >1.0 and steadily increased with higher BMI categories. We conclude that unhealthy lifestyle patterns in diet, exercise, and coping are highly prevalent among the overweight and obese population. Pattern recognition represents a new method to analyze the cluster of behaviors, attitudes, and traits seen among this population.     

Gut Microbiota Dynamics during Dietary Shift in Eastern African Cichlid Fishes

The gut microbiota structure reflects both a host phylogenetic history and a signature of adaptation to the host ecological, mainly trophic niches. African cichlid fishes, with their array of closely related species that underwent a rapid dietary niche radiation, offer a particularly interesting system to explore the relative contribution of these two factors in nature. Here we surveyed the host intra- and interspecific natural variation of the gut microbiota of five cichlid species from the monophyletic tribe Perissodini of lake Tanganyika, whose members transitioned from being zooplanktivorous to feeding primarily on fish scales. The outgroup riverine species Astatotilapia burtoni, largely omnivorous, was also included in the study. Fusobacteria, Firmicutes and Proteobacteria represented the dominant components in the gut microbiota of all 30 specimens analysed according to two distinct 16S rRNA markers. All members of the Perissodini tribe showed a homogenous pattern of microbial alpha and beta diversities, with no significant qualitative differences, despite changes in diet. The recent diet shift between zooplantkon- and scale-eaters simply reflects on a significant enrichment of Clostridium taxa in scale-eaters where they might be involved in the scale metabolism. Comparison with the omnivorous species A. burtoni suggests that, with increased host phylogenetic distance and/or increasing herbivory, the gut microbiota begins differentiating also at qualitative level. The cichlids show presence of a large conserved core of taxa and a small set of core OTUs (average 13–15%), remarkably stable also in captivity, and putatively favoured by both restricted microbial transmission among related hosts (putatively enhanced by mouthbrooding behavior) and common host constraints. This study sets the basis for a future large-scale investigation of the gut microbiota of cichlids and its adaptation in the process of the host adaptive radiation.     

Gut and Root Microbiota Commonalities

Animal guts and plant roots have absorption roles for nutrient uptake and converge in harboring large, complex, and dynamic groups of microbes that participate in degradation or modification of nutrients and other substances. Gut and root bacteria regulate host gene expression, provide metabolic capabilities, essential nutrients, and protection against pathogens, and seem to share evolutionary trends.     

Influences of Normobaric Hypoxia Training on Physical Fitness and Metabolic Risk Markers in Overweight to Obese Subjects

Previous studies suggested that hypoxia and exercise may have a synergistic effect on cardiovascular and metabolic risk factors. We conducted a single blind study in overweight to obese subjects to test the hypothesis that training under hypoxia (HG, n = 24, FiO₂ = 15%) results in similar or even greater improvement in body weight and metabolic risk markers compared with exercise under normoxia (NG, n = 21, FiO₂ = 21%). After an initial metabolic evaluation including incremental exercise testing, subjects trained in normoxic or hypoxic conditions thrice weekly over a 4‐week period at a heart rate corresponding to 65% of maximum oxygen uptake (VO_2max). The experimental groups were similar at the start of the investigation and weight stable during the training period. Subjects in the hypoxia group trained at a significantly lower workload (P < 0.05). Yet, both groups showed similar improvements in VO_2max and time to exhaustion. Respiratory quotient and lactate at the anaerobic threshold as well as body composition improved more in the hypoxia group. We conclude that in obese subjects, training in hypoxia elicits a similar or even better response in terms of physical fitness, metabolic risk markers, and body composition at a lower workload. The fact that workload and, therefore, mechanic strain can be reduced in hypoxia could be particularly beneficial in obese patients with orthopedic comorbidities.     

Effect of Glucose Tolerance Status on PAI‐1 Plasma Levels in Overweight and Obese Subjects

Objective: The aim of our study was to examine whether plasminogen activator inhibitor‐1 (PAI‐1) plasma levels varied as a function of differences in glucose tolerance status independently of body fatness, body‐fat distribution, and insulin sensitivity. Research Methods and Procedures: Plasma PAI‐1 antigen levels, along with insulin resistance [measured by homeostatic model assessment (HOMA_IR)], central fat accumulation, body composition, blood pressure, and fasting concentrations of glucose, insulin, and lipids, were measured in 229 overweight and obese [body mass index (BMI) ≥25 kg/m²) subjects with normal glucose tolerance (NGT) and in 44 age‐ and BMI‐matched subjects with impaired glucose tolerance (IGT). Results: Plasma PAI‐1 antigen levels were significantly higher in IGT than in NGT subjects. Log PAI‐1 was positively correlated with BMI, HOMA_IR, and log insulin, and inversely associated with high‐density lipoprotein‐cholesterol both in IGT and in NGT individuals. On the other hand, log PAI‐1 was positively correlated with waist circumference, fat mass (FM), fat‐free mass, systolic and diastolic blood pressure, and log triglycerides only in the NGT group. After multivariate analyses, the strongest determinants of PAI‐1 levels were BMI, FM, waist circumference, and high‐density lipoprotein cholesterol in the NGT group and only HOMA_IR in the IGT cohort. Discussion: This study demonstrates that PAI‐1 concentrations are higher in IGT than in NGT subjects. Furthermore, we suggest that the influences of total adiposity, central fat, and insulin resistance, main determinants of PAI‐1 concentrations, are different according to the degree of glucose tolerance.     

Decreased Glucagon‐like Peptide 1 Release after Weight Loss in Overweight/Obese Subjects

Objective: Postprandial glucagon‐like peptide 1 (GLP‐1) release seems to be attenuated in obese subjects. Results on whether weight loss improves GLP‐1 release are contradictory. The aim of this study was to further investigate the effect of weight loss on basal and postprandial GLP‐1 release in overweight/obese subjects. Research Methods and Procedures: Thirty‐two overweight/obese subjects participated in a repeated measurement design before (BMI, 30.3 ± 2.8 kg/m²; waist circumference, 92.6 ± 7.8 cm; hip circumference, 111.1 ± 7.4 cm) and after a weight loss period of 6 weeks (BMI, 28.2 ± 2.7 kg/m²; waist circumference, 85.5 ± 8.5 cm; hip circumference, 102.1 ± 9.2 cm). During weight loss, subjects received a very‐low‐calorie diet (Optifast) to replace three meals per day. Subjects came to the laboratory fasted, and after a baseline blood sample, received a standard breakfast (1.9 MJ). Postprandially, blood samples were taken every one‐half hour relative to intake for 120 minutes to determine GLP‐1, insulin, glucose, and free fatty acids from plasma. Appetite ratings were obtained with visual analog scales. Results: After weight loss, postprandial GLP‐1 concentrations at 30 and 60 minutes were significantly lower than before weight loss (p < 0.05). Glucose concentrations were also lower, and free fatty acids were higher compared with before weight loss. Ratings of satiety were increased, and hunger scores were decreased after weight loss (p < 0.05). Discussion: In overweight/obese subjects, GLP‐1 concentrations after weight loss were decreased compared with before weight loss, and nutrient‐related stimulation was abolished. This might be a response to a proceeding negative energy balance. Satiety and GLP‐1 seem to be unrelated in the long term.     

Body Compartment and Subcutaneous Adipose Tissue Distribution - Risk Factor Patterns in Obese Subjects

The purpose of this study was to investigate whether upper body obesity and/or visceral obesity are related to cardiovascular risk factors among severely obese subjects, phenomena that have previously been reported in more heterogeneous body weight distri -buttons. 2450 severely obese men and women aged 37 to 59 years, with a body mass index of 39 ± 4.5 kg/m² (mean ± SD) were examined cross-sectionally. Eight cardiovascular risk factors were studied in relation. to the following body composition indicators: four trunk and three limb circumferences, along with weight, height and sagittal trunk diameter. From the latter three measurements lean body mass (LBM, i.e., the non-adipose tissue mass) and the masses of subcutaneous and visceral adipose tissue were estimated by using sex-specific prediction equations previously calibrated by computed tomography. Two risk factor patterns could be distinguished: 1. One body compartment- risk factor pattern in which the subcutaneous adipose tissue (AT) mass and, in particular, the visceral AT mass were positively related to most risk factors while the lean body mass was negatively related to some risk factors. 2. One subcutaneous adipose tissue distribution- risk factor pattern in which the neck circumference was positively and the thigh circumference negatively related to several risk factors. It is concluded that lean body mass (LBM), visceral and subcutaneous adipose tissue masses as well as neck and thigh circumferences, used as indices of subcutaneous adipose tissue distribution, are independently related to cardiovascular risk factors in severely obese men and women.     

In Vitro Characterization of the Impact of Different Substrates on Metabolite Production,Energy Extraction and Composition of Gut Microbiota from Lean and Obese Subjects

The aim of this study was to investigate the effect of galacto-oligosaccharides, lactulose, apple fiber and sugar beet pectin on the composition and activity of human colonic microbiota of lean and obese healthy subjects using an in vitro model of the proximal colon: TIM-2. Substrate fermentation was assessed by measuring the production of short-chain and branched-chain fatty acids, lactate and ammonia and by studying the composition of the bacterial communities over time. The results suggest that energy harvest (in terms of metabolites) of lean and obese microbiotas is different and may depend on the fermentable substrate. For galacto-oligosaccharides and lactulose, the cumulative amount of short-chain fatty acids plus lactate produced in TIM-2 was lower in the fermentation experiments with the lean microbiota (123 and 155 mmol, respectively) compared to the obese (162 and 173 mmol, respectively). This was reversed for the pectin and the fiber. The absolute amount produced of short-chain fatty acids including lactate was higher after 72 h in the fermentation experiments with apple fiber-L (108 mmol) than with apple fiber-O (92 mmol). Sugar beet-L was also higher (130 mmol) compared to sugar beet-O (103 mmol). Galacto-oligosaccharides and lactulose boosted the balance of health-promoting over toxic metabolites produced by the microbiota from obese subjects. Firmicutes were more predominant in the inoculum prepared from feces of obese subjects compared to lean subjects. The average abundance at time zero was 92% and 74%, respectively. On the other hand, Bacteroidetes were more dominant in the microbiota prepared with homogenates from lean subjects with an average abundance of 22% compared with the microbiota prepared with homogenates from obese subjects (3.6%). This study brings evidence that different fermentable carbohydrates are fermented differently by lean and obese microbiotas, which contributes to the understanding of the role of diet and the microbiota in tackling obesity.     

High Fat Diet-Induced Gut Microbiota Exacerbates Inflammation and Obesity in Mice via the TLR4 Signaling Pathway

Background & Aims

While it is widely accepted that obesity is associated with low-grade systemic inflammation, the molecular origin of the inflammation remains unknown. Here, we investigated the effect of endotoxin-induced inflammation via TLR4 signaling pathway at both systemic and intestinal levels in response to a high-fat diet.

Methods

C57BL/6J and TLR4-deficient C57BL/10ScNJ mice were maintained on a low-fat (10 kcal % fat) diet (LFD) or a high–fat (60 kcal % fat) diet (HFD) for 8 weeks.

Results

HFD induced macrophage infiltration and inflammation in the adipose tissue, as well as an increase in the circulating proinflammatory cytokines. HFD increased both plasma and fecal endotoxin levels and resulted in dysregulation of the gut microbiota by increasing the Firmicutes to Bacteriodetes ratio. HFD induced the growth of Enterobecteriaceae and the production of endotoxin in vitro. Furthermore, HFD induced colonic inflammation, including the increased expression of proinflammatory cytokines, the induction of Toll-like receptor 4 (TLR4), iNOS, COX-2, and the activation of NF-κB in the colon. HFD reduced the expression of tight junction-associated proteins claudin-1 and occludin in the colon. HFD mice demonstrated higher levels of Akt and FOXO3 phosphorylation in the colon compared to the LFD mice. While the body weight of HFD-fed mice was significantly increased in both TLR4-deficient and wild type mice, the epididymal fat weight and plasma endotoxin level of HFD-fed TLR4-deficient mice were 69% and 18% of HFD-fed wild type mice, respectively. Furthermore, HFD did not increase the proinflammatory cytokine levels in TLR4-deficient mice.

Conclusions

HFD induces inflammation by increasing endotoxin levels in the intestinal lumen as well as in the plasma by altering the gut microbiota composition and increasing its intestinal permeability through the induction of TLR4, thereby accelerating obesity.     

Human Gut Microbiota and Gastrointestinal Cancer

Human gut microbiota play an essential role in both healthy and diseased states of humans. In the past decade, the interactions between microorganisms and tumors have attracted much attention in the efforts to understand various features of the complex microbial communities, as well as the possible mechanisms through which the microbiota are involved in cancer prevention, carcinogenesis, and anti-cancer therapy. A large number of studies have indicated that microbial dysbiosis contributes to cancer susceptibility via multiple pathways. Further studies have suggested that the microbiota and their associated metabolites are not only closely related to carcinogenesis by inducing inflammation and immune dysregulation, which lead to genetic instability, but also interfere with the pharmacodynamics of anticancer agents. In this article, we mainly reviewed the influence of gut microbiota on cancers in the gastrointestinal (GI) tract (including esophageal, gastric, colorectal, liver, and pancreatic cancers) and the regulation of microbiota by diet, prebiotics, probiotics, synbiotics, antibiotics, or the Traditional Chinese Medicine. We also proposed some new strategies in the prevention and treatment of GI cancers that could be explored in the future. We hope that this review could provide a comprehensive overview of the studies on the interactions between the gut microbiota and GI cancers, which are likely to yield translational opportunities to reduce cancer morbidity and mortality by improving prevention, diagnosis, and treatment.