Correlation Engine 2.0
Clear Search sequence regions

Sizes of these terms reflect their relevance to your search.

BACKGROUND Worldwide, the treatment of complications associated with type 2 diabetes mellitus, including diabetic foot ulcer (DFU), results in an economic burden for patients and healthcare systems. This study aimed to use high-throughput 16S rRNA gene sequencing to investigate the changes in foot skin microbiome of patients with diabetes mellitus from a single center in China. MATERIAL AND METHODS Fifty-two participants were divided into 4 study groups: healthy controls (n=13); patients with short-term diabetes (<2 years; n=13); patients with intermediate-term diabetes (5-8 years; n=13); and patients with long-term diabetes (>10 years; n=13). Swabs were analyzed from the intact skin of the foot arch using high-throughput 16S ribosomal RNA sequencing. RESULTS Microbiome phylogenic diversity varied significantly between the study groups (whole tree, P<0.01; Chao1, P<0.01), but were similar within the same group. The findings were supported by non-parametric multidimensional scaling (stress=0.12) and principal component analysis (principal component 1, 8.38%; principal component 2, 5.28%). In patients with diabetes mellitus, the dominant skin microbial phyla were Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes. CONCLUSIONS High-throughput 16S rRNA gene sequencing showed dynamic changes in the skin microbiome from the foot during the progression of diabetes mellitus. These findings support the importance of understanding the role of the skin microbiota in the pathogenesis of DFU.


Mengru Pang, Meishu Zhu, Xiaoxuan Lei, Caihong Chen, Zexin Yao, Biao Cheng. Changes in Foot Skin Microbiome of Patients with Diabetes Mellitus Using High-Throughput 16S rRNA Gene Sequencing: A Case Control Study from a Single Center. Medical science monitor : international medical journal of experimental and clinical research. 2020 May 02;26:e921440

Expand section icon Mesh Tags

Expand section icon Substances

PMID: 32358479

View Full Text