2022bioRxiv (Cold Spring Harbor Laboratory)Open access

An attempt to find the correlations between body weight and the composition of gut microbiota in Zhejiang and Shanghai

Yihan Xia, Ziying Jin

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Abstract

Abstract Previous studies showed that the human gut microbiota was associated with metabolic diseases, but the interaction and mechanism between the gut microbiota and metabolic disease are still unclear. In this study, the gut microbiota of 58 persons living in Zhejiang and Shanghai area will be analyzed. Then, the potential contribution of the human gut microbiota to obesity/high Body Mass Index (BMI) will be explored. The gut microbiota was studied by high throughput sequencing analysis of bacterial 16S rRNA gene fragments, and the gut microbiota samples with different BMI were compared. Meanwhile, some gut microorganisms from faeces of a healthy individual were cultivated and isolated, and the classification was identified by 16S rRNA sequencing. The main microbes in human gut microbiota were assigned to the phyla of Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Moreover, four strains were isolated from an individual fecal sample, of which one species was assigned to Escherichia fergusonii and the other three strains were assigned to Weissella cibaria . These four species belong to both abundant and low-abundant species revealed by high throughput sequencing. It was found that individuals with different BMI have different gut microbiota; while the differences are not significant. Also, the Firmicutes/Bacteroidetes ratio increases with the decrease of BMI, which is corresponding to previous results. In the future, more cohort gut microbiota in Zhejiang and Shanghai area will be collected and recovered, and the gut microbiota database of Zhejiang and Shanghai area will be built up in order to provide the basis for future gut microbiota modulation in this area.

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Abstract Previous studies showed that the human gut microbiota was associated with metabolic diseases, but the interaction and mechanism between the gut microbiota and metabolic disease are still unclear. In this study, the gut microbiota of 58 persons living in Zhejiang and Shanghai area will be analyzed. Then, the potential contribution of the human gut microbiota to obesity/high Body Mass Index (BMI) will be explored. The gut microbiota was studied by high throughput sequencing analysis of bacterial 16S rRNA gene fragments, and the gut microbiota samples with different BMI were compared. Meanwhile, some gut microorganisms from faeces of a healthy individual were cultivated and isolated, and the classification was identified by 16S rRNA sequencing. The main microbes in human gut microbiota were assigned to the phyla of Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Moreover, four strains were isolated from an individual fecal sample, of which one species was assigned to Escherichia fergusonii and the other three strains were assigned to Weissella cibaria . These four species belong to both abundant and low-abundant species revealed by high throughput sequencing. It was found that individuals with different BMI have different gut microbiota; while the differences are not significant. Also, the Firmicutes/Bacteroidetes ratio increases with the decrease of BMI, which is corresponding to previous results. In the future, more cohort gut microbiota in Zhejiang and Shanghai area will be collected and recovered, and the gut microbiota database of Zhejiang and Shanghai area will be built up in order to provide the basis for future gut microbiota modulation in this area.

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Available abstract

Abstract Previous studies showed that the human gut microbiota was associated with metabolic diseases, but the interaction and mechanism between the gut microbiota and metabolic disease are still unclear. In this study, the gut microbiota of 58 persons living in Zhejiang and Shanghai area will be analyzed. Then, the potential contribution of the human gut microbiota to obesity/high Body Mass Index (BMI) will be explored. The gut microbiota was studied by high throughput sequencing analysis of bacterial 16S rRNA gene fragments, and the gut microbiota samples with different BMI were compared. Meanwhile, some gut microorganisms from faeces of a healthy individual were cultivated and isolated, and the classification was identified by 16S rRNA sequencing. The main microbes in human gut microbiota were assigned to the phyla of Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Moreover, four strains were isolated from an individual fecal sample, of which one species was assigned to Escherichia fergusonii and the other three strains were assigned to Weissella cibaria . These four species belong to both abundant and low-abundant species revealed by high throughput sequencing. It was found that individuals with different BMI have different gut microbiota; while the differences are not significant. Also, the Firmicutes/Bacteroidetes ratio increases with the decrease of BMI, which is corresponding to previous results. In the future, more cohort gut microbiota in Zhejiang and Shanghai area will be collected and recovered, and the gut microbiota database of Zhejiang and Shanghai area will be built up in order to provide the basis for future gut microbiota modulation in this area.

Key concepts: Firmicutes, Gut flora, Bacteroidetes, Biology, Proteobacteria, Feces, Actinobacteria, 16S ribosomal RNA

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