摘要
AIM To analyze the bacterial community structure and distribution of intestinal microflora in people with and without metabolic syndrome and combined these data with clinical indicators to determine relationships between selected bacteria and metabolic diseases. METHODS Faecal samples were collected from 20 patients with metabolic syndrome and 16 controls at Cangnan People's Hospital, Zhejiang Province, China. DNA was extracted and the V3-V4 regions of the 16 S rRNA genes were amplified for high throughput sequencing. Clear reads were clustered at the 97% sequence similarity level. α and β diversity were used to describe the bacterial community structure and distribution in patients. Combined with the clinical indicators, further analysis was performed.RESULTS Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, Fusobacteria were the dominant phyla, and Prevotella, Bacteroides and Faecalibacterium was the top three genera in faecal samples. α diversity analysis showed that the species richness of metabolic syndrome samples(group D) was significantly higher than the control(group C)(P < 0.05), and the microbial diversity of group C was greater than that of group D. According to the principal co-ordinates analysis, the samples of group C clustered more tightly, indicating that the distribution of bacteria in healthy patients was similar. The correlation analysis showed that alkaline phosphatase was negatively correlated with the abundance of Prevotella(P < 0.05). There was a negative correlation between low-density lipoprotein and the abundance of Ruminococcus(P < 0.05) and a positive correlation between the high-density lipoprotein and the abundance of Ruminococcus(P < 0.05). The total protein and the alanine aminotransferase was positively correlated with the abundance of Peptostreptococcus(P < 0.05). CONCLUSION The changes microbial communities can be used as an indicator of metabolic syndrome, and Prevotella may be a target microorganism in patients with metabolic syndrome.
AIM To analyze the bacterial community structure and distribution of intestinal microflora in people with and without metabolic syndrome and combined these data with clinical indicators to determine relationships between selected bacteria and metabolic diseases. METHODS Faecal samples were collected from 20 patients with metabolic syndrome and 16 controls at Cangnan People's Hospital, Zhejiang Province, China. DNA was extracted and the V3-V4 regions of the 16 S rRNA genes were amplified for high throughput sequencing. Clear reads were clustered at the 97% sequence similarity level. α and β diversity were used to describe the bacterial community structure and distribution in patients. Combined with the clinical indicators, further analysis was performed.RESULTS Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, Fusobacteria were the dominant phyla, and Prevotella, Bacteroides and Faecalibacterium was the top three genera in faecal samples. α diversity analysis showed that the species richness of metabolic syndrome samples(group D) was significantly higher than the control(group C)(P < 0.05), and the microbial diversity of group C was greater than that of group D. According to the principal co-ordinates analysis, the samples of group C clustered more tightly, indicating that the distribution of bacteria in healthy patients was similar. The correlation analysis showed that alkaline phosphatase was negatively correlated with the abundance of Prevotella(P < 0.05). There was a negative correlation between low-density lipoprotein and the abundance of Ruminococcus(P < 0.05) and a positive correlation between the high-density lipoprotein and the abundance of Ruminococcus(P < 0.05). The total protein and the alanine aminotransferase was positively correlated with the abundance of Peptostreptococcus(P < 0.05). CONCLUSION The changes microbial communities can be used as an indicator of metabolic syndrome, and Prevotella may be a target microorganism in patients with metabolic syndrome.
基金
Supported by the Medical and Health Science and Technology Plan Project of Zhejiang Province,No.2015KY371
the Public Technology Application Research of Zhejiang Province Science and Technology Hall,No.2016C33242