Linking gut microbiota, metabolic syndrome and economic status based on a population-level analysis.

BACKGROUND: The metabolic syndrome (MetS) epidemic is associated with economic development, lifestyle transition and dysbiosis of gut microbiota, but these associations are rarely studied at the population scale. Here, we utilised the Guangdong Gut Microbiome Project (GGMP), the largest Eastern population-based gut microbiome dataset covering individuals with different economic statuses, to investigate the relationships between the gut microbiome and host physiology, diet, geography, physical activity and socioeconomic status. RESULTS: At the population level, 529 OTUs were significantly associated with MetS. OTUs from Proteobacteria and Firmicutes (other than Ruminococcaceae) were mainly positively associated with MetS, whereas those from Bacteroidetes and Ruminococcaceae were negatively associated with MetS. Two hundred fourteen OTUs were significantly associated with host economic status (140 positive and 74 negative associations), and 157 of these OTUs were also MetS associated. A microbial MetS index was formulated to represent the overall gut dysbiosis of MetS. The values of this index were significantly higher in MetS subjects regardless of their economic status or geographical location. The index values did not increase with increasing personal economic status, although the prevalence of MetS was significantly higher in people of higher economic status. With increased economic status, the study population tended to consume more fruits and vegetables and fewer grains, whereas meat consumption was unchanged. Sedentary time was significantly and positively associated with higher economic status. The MetS index showed an additive effect with sedentary lifestyle, as the prevalence of MetS in individuals with high MetS index values and unhealthy lifestyles was significantly higher than that in the rest of the population. CONCLUSIONS: The gut microbiome is associated with MetS and economic status. A prolonged sedentary lifestyle, rather than Westernised dietary patterns, was the most notable lifestyle change in our Eastern population along with economic development. Moreover, gut dysbiosis and a Western lifestyle had an additive effect on increasing MetS prevalence.

Author Correction: Regional variation limits applications of healthy gut microbiome reference ranges and disease models.

In the version of this article originally published, in the sentence "Applying the same approach to obesity (Fig. 2b), MetS (Fig. 2c) and fatty liver (Fig. 2d) yielded similar results," two figure panels were cited incorrectly. The data for obesity are in Fig. 2c, and the data for MetS are in Fig. 2b. The sentence has been updated with the correct citations in the print, PDF and HTML versions of the article.

Regional variation limits applications of healthy gut microbiome reference ranges and disease models.

Dysbiosis, departure of the gut microbiome from a healthy state, has been suggested to be a powerful biomarker of disease incidence and progression1-3. Diagnostic applications have been proposed for inflammatory bowel disease diagnosis and prognosis4, colorectal cancer prescreening5 and therapeutic choices in melanoma6. Noninvasive sampling could facilitate large-scale public health applications, including early diagnosis and risk assessment in metabolic7 and cardiovascular diseases8. To understand the generalizability of microbiota-based diagnostic models of metabolic disease, we characterized the gut microbiota of 7,009 individuals from 14 districts within 1 province in China. Among phenotypes, host location showed the strongest associations with microbiota variations. Microbiota-based metabolic disease models developed in one location failed when used elsewhere, suggesting that such models cannot be extrapolated. Interpolated models performed much better, especially in diseases with obvious microbiota-related characteristics. Interpolation efficiency decreased as geographic scale increased, indicating a need to build localized baseline and disease models to predict metabolic risks.

[Effect of intermittent fasting on physiology and gut microbiota in presenium rats].

OBJECTIVE: To investigate the effect of intermittent fasting on metabolize and gut microbiota in obese presenium rats fed with high-fat-sugar-diet. METHODS: We fed the Wistar rats with high-fat and high-sugar diet to induce adiposity, and the rats for intermittent fasting were selected base on their body weight. The rats were subjected to fasting for 72 h every 2 weeks for 18 weeks. OGTT test was performed and fasting blood samples and fecal samples were collected for measurement of TC, TG, HDL-C and LDL-C and sequence analysis of fecal 16S rRNA V4 tags using Illumina. Gut microbial community structure was analyzed with QIIME and LEfSe. RESULTS: After the intervention, the body weight of the fasting rats was significantly lower than that in high-fat diet group (P<0.01). OGTT results suggested impairment of sugar tolerance in the fasting group, which showed a significantly larger AUC than compared with the high-fat diet group (P<0.05). Intermittent fasting significantly reduced blood HDL-C and LDL-C levels (P<0.05) and partially restored liver steatosis, and improved the gut microbiota by increasing the abundance of YS2, RF32 and Helicobacteraceae and reducing Lactobacillus, Roseburia, Erysipelotrichaceae and Ralstonia. Bradyrhizobiaceae was found to be positively correlated with CHOL and HDL-C, and RF39 was inversely correlated with the weight of the rats. CONCLUSION: Intermittent fasting can decrease the body weight and blood lipid levels and restore normal gut microbiota but can cause impairment of glucose metabolism in obese presenium rats.

Sputum Bacterial and Fungal Dynamics during Exacerbations of Severe COPD.

The changes in the microbial community structure during acute exacerbations of severe chronic obstructive pulmonary disease (COPD) in hospitalized patients remain largely uncharacterized. Therefore, further studies focused on the temporal dynamics and structure of sputum microbial communities during acute exacerbation of COPD (AECOPD) would still be necessary. In our study, the use of molecular microbiological techniques provided insight into both fungal and bacterial diversities in AECOPD patients during hospitalization. In particular, we examined the structure and varieties of lung microbial community in 6 patients with severe AECOPD by amplifying 16S rRNA V4 hyper-variable and internal transcribed spacer (ITS) DNA regions using barcoded primers and the Illumina sequencing platform. Sequence analysis showed 261 bacterial genera representing 20 distinct phyla, with an average number of genera per patient of >157, indicating high diversity. Acinetobacter, Prevotella, Neisseria, Rothia, Lactobacillus, Leptotrichia, Streptococcus, Veillonella, and Actinomyces were the most commonly identified genera, and the average total sequencing number per sputum sample was >10000 18S ITS sequences. The fungal population was typically dominated by Candia, Phialosimplex, Aspergillus, Penicillium, Cladosporium and Eutypella. Our findings highlight that COPD patients have personalized structures and varieties in sputum microbial community during hospitalization periods.