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Comparative Study
. 2019 Dec 31;14(12):e0226372.
doi: 10.1371/journal.pone.0226372. eCollection 2019.

Analysis of gut microbiota of obese individuals with type 2 diabetes and healthy individuals

Aftab Ahmad  1 , Wanwei Yang  2 , Guofang Chen  2 , Muhammad Shafiq  1 , Sundus Javed  1 , Syed Shujaat Ali Zaidi  1 , Ramla Shahid  1 , Chao Liu  2 , Habib Bokhari  1
Affiliations
Comparative Study

Analysis of gut microbiota of obese individuals with type 2 diabetes and healthy individuals

Aftab Ahmad et al. PLoS One. .

Abstract

Type 2 diabetes mellitus (T2DM) accounts for 90% of diabetes cases worldwide. The majority of T2DM patients are obese. Dysbiosis in the gut microflora is strongly associated with the pathogenesis of obesity and T2DM; however, the microbiome of obese-T2DM individuals in the Pakistani population remains unexplored. The gut microbiota signature of 60 Pakistani adults was studied using 16S rRNA sequencing targeting V3-V4 hypervariable regions. The sequence analysis revealed that bacteria from Firmicutes were predominant along with those from Clostridia and Negativicutes, whereas bacteria from Verrucomicrobia, Bacteroidetes, Proteobacteria, and Elusimicrobia were less abundant among the obese T2DM patients. These data distinctively vary from those in reports on the Indian population. The difference in gut microbiota could presumably be related to the distinct lifestyle and eastern dietary habits (high carbohydrate and fat intake, low fiber intake) and unregulated antibiotic consumption. This is the first study carried out to understand the gut microbiome and its correlation with individual life style of obese T2DM patients in the Pakistani population.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Alpha diversity between obese-T2DM patients.
(A) Comparison of Boxplots depicting OTU/Diversity between obese-T2DM patients (n = 40) and healthy participants (n = 20). (B) The Shannon Wiener index representing the number of species and uniformity of individual distribution between obese-T2DM patients (n = 40) and healthy participants (n = 20).
Fig 2
Fig 2. Beta-diversity of the gut microbial communities in obese-T2DM patients and healthy participants.
Principal Coordinates Analysis (PCoA) plot based on weighted and unweighted UniFrac distance. Each dot represents one sample from each group.
Fig 3
Fig 3. The relative abundance of gut bacteria in obese-T2DM patients and healthy participants using Kruskal-Wallis rank-sum tests.
(A) Relative percentage of most abundant phyla between obese-T2DM patients (n = 40) and healthy individuals (n = 20). (B) Relative percentage of most abundant phyla in each sample between obese-T2DM patients (n = 40) and healthy individuals. (C) Relative abundance of bacteria at class level in obese-T2DM patients (n = 40) and healthy participants (n = 20).
Fig 4
Fig 4. Correlations between fasting glucose and gut microbiota in fecal samples of participants.
Spearman’s rank correlation coefficient was used to analyze the correlation between obese-T2DM (n = 40) and healthy (n = 20). (A) Correlation between fasting glucose and phylum Actinobacteria. (B) Correlation between fasting glucose and phylum Firmicutes (ρ = 0.246, p = 0.05). (C) Correlation between fasting glucose and phylum Proteobacteria (ρ = -0.253, p = 0.05). (D) Correlation between fasting glucose and Bacteroidetes (ρ = -0.205, p = 0.11).
See this image and copyright information in PMC

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