Correlation Analysis of the Risk Degree of Diabetic Foot with Skin Microbiota Based on 16S rRNA Sequencing

doi:10.12114/j.issn.1007-9572.2024.0382

Chinese General Practice ›› 2026, Vol. 29 ›› Issue (21): 3004-3011.DOI: 10.12114/j.issn.1007-9572.2024.0382

• Article·Specific Research·Diabetes • Previous Articles

Correlation Analysis of the Risk Degree of Diabetic Foot with Skin Microbiota Based on 16S rRNA Sequencing

1. Department of Endocrinology, the Second Affiliated Hospital of Zunyi Medical University, Zunyi 563006, China
2. Zunyi Medical University, Zunyi 563006, China
3. Department of Endocrinology, Kweichow Moutai Hospital, Zunyi 564599, China
4. Department of Endocrinology and Metabolism, Affiliated Hospital of Zunyi Medical University, Zunyi 563099, China

Received:2025-03-10 Revised:2025-09-20 Published:2026-07-20 Online:2026-06-03
Contact: CAI Yulan

基于16S rRNA测序探讨不同糖尿病足危险程度与皮肤菌群的相关性研究

1．563006　贵州省遵义市，遵义医科大学第二附属医院内分泌科
2．563006　贵州省遵义市，遵义医科大学
3．564599　贵州省遵义市，贵州茅台医院内分泌科
4．563099　贵州省遵义市，遵义医科大学附属医院内分泌与代谢病科

通讯作者: 蔡玉兰
作者简介:
作者贡献：
赵曼鹭、杨奔奔、朱秋瑾、蔡玉兰提出主要研究目标，负责研究的构思与设计，研究的实施，撰写论文；赵曼鹭、李昌露、上官怡涵进行数据的收集与整理，统计学处理，图、表的绘制与展示；赵曼鹭、陈霞、蔡玉兰进行论文的修订；蔡玉兰负责文章的质量控制与审查，对文章整体负责，监督管理。
基金资助:
国家自然科学基金资助项目(82460167，82260167); 贵州省科技计划项目(黔科合基础-ZK〔2022〕一般639); 贵州省科学技术协会青年科技人才托举工程(NO.GASTYESS202434); 贵州茅台医院科技创新项目(MTyk2022-42); 遵义市科技计划项目(遵市科合HZ字〔2022〕279号)

Abstract

Abstract:

Background

Diabetic foot (DF) is a common and severe chronic complication of diabetes mellitus, characterized by high incidence, high disability rate, and high recurrence rate. It severely affects the quality of life of affected people. Recent studies suggest that dysbiosis of the skin microbiota may play a critical role in the development of DF.

Objective

To investigate the differences in plantar skin microbiota composition among patients with varying risk degrees of DF using 16S rRNA gene sequencing, and to explore the association between microbiota imbalance and DF risk, thereby providing a microbial basis for early warning and intervention strategies.

Methods

A total of 64 patients with diabetes mellitus treated in the Second Affiliated Hospital of Zunyi Medical University from June 2023 to March 2024, and 16 healthy adults during the same period, were enrolled. According to the International Working Group on the Diabetic Foot (IWGDF) risk classification, participants were divided into five groups: control group (n=16), very low-risk group (VL, n=16), low-risk group (L, n=15), moderate-risk group (M, n=16), and high-risk group (H, n=17). Plantar skin swab samples were collected for DNA extraction. The V3-V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq platform. Operational taxonomic unit (OTU) clustering and annotation were performed using QIIME 2. Microbiota differences among groups were analyzed using the Linear discriminant analysis Effect Size (LEfSe) and Metastats methods.

Results

The α-diversity indices (Chao1, ACE, Shannon, and Simpson) of plantar skin microbiota were significantly different among the five groups with varying risk levels of DF (P<0.001). Principal coordinate analysis (PCoA) based on Bray-Curtis distances revealed a significant separation of microbiota structures among groups (P=0.001). At the phylum level, the relative abundances of Bacteroidetes and Proteobacteria sequentially increased than the previous low-risk group, whereas those of Firmicutes and Actinobacteria sequentially decreased than the previous low-risk group (P<0.001). At the genus level, the abundances of Corynebacterium, Streptococcus, and Bacteroides significantly sequentially increased than the previous low-risk group, while the abundance of Staphylococcus gradually decreased than the previous low-risk group (P<0.001). LEfSe analysis identified group-specific biomarker genera, namely the Aquabacterium (VL), Bacteroides (L), Gardnerella (M), and Corynebacterium (H)(P<0.05).

Conclusion

The composition of plantar skin microbiota in diabetes mellitus patients is closely associated with the risk degree of DF. With the increasing DF risk, microbiota α-diversity significantly increases and microbial community structure diverges. High-risk patients exhibit elevated levels of Gram-negative bacteria like Bacteroidetes, Proteobacteria, and Bacteroides, along with reduced levels of Gram-positive bacteria like Firmicutes, Actinobacteria, and Staphylococcus, reflecting marked microbiota dysbiosis. Distinct microbial biomarkers are observed across DF risk levels, suggesting that microbial characteristics may serve as potential targets for DF risk assessment and intervention.

Key words: Diabetic foot, Microbiota, 16S rRNA sequencing, Risk level

摘要：

背景

糖尿病足（DF）是糖尿病患者常见且严重的慢性并发症之一，具有高发病率、高致残率和高复发率等特点，严重影响了患者的生活质量。近年来研究发现，皮肤微生态失衡可能在DF的发生中发挥重要作用。

目的

采用16S rRNA测序技术，分析不同DF危险程度患者足底皮肤菌群组成差异，探讨菌群失衡与DF发生风险之间的关系，为DF的早期预警和干预提供微生态依据。

方法

纳入2023年6月—2024年3月在遵义医科大学第二附属医院就诊的糖尿病患者64例及健康成年人16例，依据国际糖尿病足工作组（IWGDF）分级标准，将研究对象分为5组：对照组（16例）、极低风险组（VL组，16例）、低风险组（L组，15例）、中等风险组（M组，16例）及高风险组（H组，17例）。采集患者足底皮肤试纸样本，提取DNA，对16S rRNA基因V3~V4区扩增并通过Illumina Miseq平台进行高通量测序。使用Qiime 2软件进行OTU聚类和注释，结合线性判别分析效应量（LEfSe）及Metastats检验方法分析菌群差异。

结果

5组DF不同危险程度患者的足部皮肤菌群α多样性（Chao1、ACE、Shannon及Simpson指数）比较，差异均有统计学意义（P<0.001）。基于Bray-Curtis距离的主坐标分析（PCoA）显示，菌群结构在不同组间明显分离（P=0.001）。随着DF危险程度的升高，VL组、L组、M组及H组拟杆菌门和变形菌门丰度依次较前一个较低风险组增加，厚壁菌门和放线菌门丰度依次较前一个低风险组减少（P<0.001）。属水平上，VL组、L组、M组及H组棒状杆菌属、链球菌属、拟杆菌属丰度依次较前一个较低风险组增加，而葡萄球菌属丰度依次较前一个较低风险组减少（P<0.001）。LEfSe分析显示VL、L、M、H组的标志菌分别为栖水菌属、拟杆菌属、加德纳菌属和棒状杆菌属（P<0.05）。

结论

糖尿病患者足底皮肤菌群组成与DF危险程度密切相关。随着危险程度增加，菌群α多样性明显升高，菌群结构明显分离。DF高危患者表现出拟杆菌门、变形菌门及拟杆菌属等革兰氏阴性菌丰度升高，厚壁菌门、放线菌门及葡萄球菌属等革兰氏阳性菌明显减少，而低危患者则表现出相反的菌群变化，反映出明显的菌群失衡。不同DF危险程度患者足底具有特异性标志菌，提示菌群特征可作为DF风险评估与干预的潜在靶点。

关键词: 糖尿病足, 菌群, 16S rRNA测序, 危险程度

ZHAO Manlu,YANG Benben,ZHU Qiujin, et al. Correlation Analysis of the Risk Degree of Diabetic Foot with Skin Microbiota Based on 16S rRNA Sequencing[J]. Chinese General Practice, 2026, 29(21): 3004-3011. DOI: 10.12114/j.issn.1007-9572.2024.0382.
赵曼鹭,杨奔奔,朱秋瑾等. 基于16S rRNA测序探讨不同糖尿病足危险程度与皮肤菌群的相关性研究[J]. 中国全科医学, 2026, 29(21): 3004-3011. DOI: 10.12114/j.issn.1007-9572.2024.0382.

Figures/Tables 8

References 37

[1]	Wukich D K, Schaper N C, Gooday C, et al. Guidelines on the diagnosis and treatment of active Charcot neuro-osteoarthropathy in persons with diabetes mellitus (IWGDF 2023)[J]. Diabetes Metab Res Rev, 2024, 40(3): e3646. DOI: 10.1002/dmrr.3646.
[2]	Guo L X, Xiao X H. Guideline for the management of diabetes mellitus in the elderly in China (2024 edition)[J]. Aging Med (Milton), 2024, 7(1): 5-51. DOI: 10.1002/agm2.12294.
[3]	Luxenburg C, Zaidel-Bar R. From cell shape to cell fate via the cytoskeleton—insights from the epidermis[J]. Exp Cell Res, 2019, 378(2): 232-237. DOI: 10.1016/j.yexcr.2019.03.016.
[4]	Nguyen A V, Soulika A M. The dynamics of the skin's immune system[J]. Int J Mol Sci, 2019, 20(8): 1811. DOI: 10.3390/ijms20081811.
[5]	Maheswary T, Nurul A A, Fauzi M B. The insights of microbes' roles in wound healing: a comprehensive review[J]. Pharmaceutics, 2021, 13(7): 981. DOI: 10.3390/pharmaceutics13070981.
[6]	张玉萍, 徐文阁. 糖尿病皮肤感染与微生物菌群关系的研究进展[J]. 中国微生态学杂志, 2013, 25(11): 1364-1365. DOI: 10.13381/j.cnki.cjm.2013.11.029.
[7]	Luqman A, Götz F. The ambivalent role of skin microbiota and adrenaline in wound healing and the interplay between them[J]. Int J Mol Sci, 2021, 22(9): 4996. DOI: 10.3390/ijms22094996.
[8]	Jnana A, Muthuraman V, Varghese V K, et al. Microbial community distribution and core microbiome in successive wound grades of individuals with diabetic foot ulcers[J]. Appl Environ Microbiol, 2020, 86(6): e02608-19. DOI: 10.1128/AEM.02608-19.
[9]	蔡玉兰, 阳琰, 岳瑜, 等. 糖尿病足严重程度连续分级创面菌群组成[J]. 中国老年学杂志, 2024, 44(5): 1079-1083.
[10]	Bus S A, Lavery L A, Monteiro-Soares M, et al. Guidelines on the prevention of foot ulcers in persons with diabetes (IWGDF 2019 update)[J]. Diabetes Metab Res Rev, 2020, 36(Suppl 1): e3269. DOI: 10.1002/dmrr.3269.
[11]	Chinese Diabetes Society. 中国2型糖尿病防治指南(2020年版)(上)[J]. 中国实用内科杂志, 2021, 41(8): 668-695. DOI: 10.19538/j.nk2021080106.
[12]	Armstrong D G, Tan T W, Boulton A J M, et al. Diabetic foot ulcers: a review[J]. JAMA, 2023, 330(1): 62-75. DOI: 10.1001/jama.2023.10578.
[13]	李海燕, 单国林, 黄生才, 等. 糖尿病足患者感染特征与下肢血管病变及免疫功能关系的研究[J]. 中华医院感染学杂志, 2019, 29(4): 574-577, 581.
[14]	洪旺兵, 刘名倬, 郭光华. 糖尿病足溃疡危险因素的研究进展[J]. 感染、炎症、修复, 2020, 21(4): 242-244.
[15]	Harris-Tryon T A, Grice E A. Microbiota and maintenance of skin barrier function[J]. Science, 2022, 376(6596): 940-945. DOI: 10.1126/science.abo0693.
[16]	郁天泽, 李巍. 皮肤菌群参与维持皮肤屏障功能[J]. 中华临床免疫和变态反应杂志, 2022, 16(4): 444-445.
[17]	Uberoi A, Mccready-Vangi A, Grice E A. The wound microbiota: microbial mechanisms of impaired wound healing and infection[J]. Nat Rev Microbiol, 2024, 22(8): 507-521. DOI: 10.1038/s41579-024-01035-z.
[18]	Pang M R, Zhu M S, Lei X X, et al. 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[J]. Med Sci Monit, 2020, 26: e921440. DOI: 10.12659/MSM.921440.
[19]	Balaji S K, Khuwaja W M, Hossain M L, et al. Neuroimmune interactions between itch neurons and skin microbes[J]. Semin Immunol, 2025, 78: 101933. DOI: 10.1016/j.smim.2025.101933.
[20]	Grice E A, Kong H H, Conlan S, et al. Topographical and temporal diversity of the human skin microbiome[J]. Science, 2009, 324(5931): 1190-1192. DOI: 10.1126/science.1171700.
[21]	Alonzo F 3rd. Toward uncovering the complexities of bacterial interspecies communication and competition on the skin[J]. mBio, 2022, 13(4): e0132022. DOI: 10.1128/mbio.01320-22.
[22]	Williams P, Hill P, Bonev B, et al. Quorum-sensing, intra- and inter-species competition in the staphylococci[J]. Microbiology (Reading), 2023, 169(8): 001381. DOI: 10.1099/mic.0.001381.
[23]	Ridaura V K, Bouladoux N, Claesen J, et al. Contextual control of skin immunity and inflammation by Corynebacterium[J]. J Exp Med, 2018, 215(3): 785-799. DOI: 10.1084/jem.20171079.
[24]	Huang Y, Xiao Z Z, Cao Y, et al. Rapid microbiological diagnosis based on 16S rRNA gene sequencing: a comparison of bacterial composition in diabetic foot infections and contralateral intact skin[J]. Front Microbiol, 2022, 13: 1021955. DOI: 10.3389/fmicb.2022.1021955.
[25]	Swaney M H, Nelsen A, Sandstrom S, et al. Sweat and sebum preferences of the human skin microbiota[J]. Microbiol Spectr, 2023, 11(1): e0418022. DOI: 10.1128/spectrum.04180-22.
[26]	Nakatsuji T, Brinton S L, Cavagnero K J, et al. Competition between skin antimicrobial peptides and commensal bacteria in type 2 inflammation enables survival of S. aureus[J]. Cell Rep, 2023, 42(5): 112494. DOI: 10.1016/j.celrep.2023.112494.
[27]	Orosz L, Lengyel G, Makai K, et al. Prescription of rifampicin for Staphylococcus aureus infections increased the incidence of Corynebacterium striatum with decreased susceptibility to rifampicin in a Hungarian clinical center[J]. Pathogens, 2023, 12(3): 481. DOI: 10.3390/pathogens12030481.
[28]	Gladysheva I V, Stroganova E A, Chertkov K L, et al. Antimicrobial activity of corynebacterium amycolatum ICIS 53 and Corynebacterium amycolatum ICIS 82 against urogenital isolates of multidrug-resistant staphylococcus aureus[J]. Curr Microbiol, 2024, 81(12): 426. DOI: 10.1007/s00284-024-03936-x.
[29]	Tamkin E, Lorenz B P, Mccarty A, et al. Airway Corynebacterium interfere with Streptococcus pneumoniae and Staphylococcus aureus infection and express secreted factors selectively targeting each pathogen[J]. Infect Immun, 2025, 93(2): e0044524. DOI: 10.1128/iai.00445-24.
[30]	Silva-Santana G, Baêta Júnior E S, Silva Conceição G M, et al. Intervention of Corynebacterium striatum in the sessile lifestyle of Staphylococcus aureus wild-type and mutants for Ica genes in polymicrobial biofilms[J]. Microb Pathog, 2025, 204: 107577. DOI: 10.1016/j.micpath.2025.107577.
[31]	Zhang S, Liu H Y, Li W, et al. Polysaccharide-based hydrogel promotes skin wound repair and research progress on its repair mechanism[J]. Int J Biol Macromol, 2023, 248: 125949. DOI: 10.1016/j.ijbiomac.2023.125949.
[32]	Larsbrink J, Mckee L S. Bacteroidetes bacteria in the soil: glycan acquisition, enzyme secretion, and gliding motility[J]. Adv Appl Microbiol, 2020, 110: 63-98. DOI: 10.1016/bs.aambs.2019.11.001.
[33]	An J, Kwon H, Kim Y J. The firmicutes/bacteroidetes ratio as a risk factor of breast cancer[J]. J Clin Med, 2023, 12(6): 2216. DOI: 10.3390/jcm12062216.
[34]	Yañez C M, Hernández A M, Sandoval A M, et al. Prevalence of Blastocystis and its association with Firmicutes/Bacteroidetes ratio in clinically healthy and metabolically ill subjects[J]. BMC Microbiol, 2021, 21(1): 339. DOI: 10.1186/s12866-021-02402-z.
[35]	Xiao X, Xiao X, Hu X, et al. The role of short-chain fatty acids in inflammatory skin diseases[J]. Front Microbiol, 2022, 13: 1083432. DOI: 10.3389/fmicb.2022.1083432.
[36]	Stojanov S, Berlec A, Štrukelj B. The influence of probiotics on the firmicutes/bacteroidetes ratio in the treatment of obesity and inflammatory bowel disease[J]. Microorganisms, 2020, 8(11): 1715. DOI: 10.3390/microorganisms8111715.
[37]	Walker A W, Sanderson J D, Churcher C, et al. High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease[J]. BMC Microbiol, 2011, 11: 7. DOI: 10.1186/1471-2180-11-7.

组别	例数	Chao1指数	ACE指数	Shannon指数	Simpson指数
对照组	16	29.25±2.09	28.34±2.43	2.35±0.12	0.87±0.02
VL组	16	30.75±1.56	31.17±1.95^a	2.46±0.04^a	0.89±0.01^a
L组	15	34.03±1.77^ab	35.30±2.54^ab	2.64±0.052^ab	0.92±0.00^ab
M组	16	36.54±1.93^abc	38.01±1.48^abc	2.93±0.07^abc	0.93±0.01^abc
H组	17	41.64±1.94^abcd	41.05±0.93^abcd	3.13±0.06^abcd	0.95±0.01^abcd
F值		86.840	81.799	232.976	111.584
P值		<0.001	<0.001	<0.001	<0.001

组别	例数	Chao1指数	ACE指数	Shannon指数	Simpson指数
对照组	16	29.25±2.09	28.34±2.43	2.35±0.12	0.87±0.02
VL组	16	30.75±1.56	31.17±1.95^a	2.46±0.04^a	0.89±0.01^a
L组	15	34.03±1.77^ab	35.30±2.54^ab	2.64±0.052^ab	0.92±0.00^ab
M组	16	36.54±1.93^abc	38.01±1.48^abc	2.93±0.07^abc	0.93±0.01^abc
H组	17	41.64±1.94^abcd	41.05±0.93^abcd	3.13±0.06^abcd	0.95±0.01^abcd
F值		86.840	81.799	232.976	111.584
P值		<0.001	<0.001	<0.001	<0.001

组别	例数	厚壁菌门	拟杆菌门	变形菌门	放线菌门
对照组	16	0.67（0.63，0.79）	0.08（0.05，0.10）	0.08（0.07，0.11）	0.15（0.08，0.17）
VL组	16	0.41（0.40，0.48）	0.19（0.17，0.20）	0.25（0.23，0.31）^a	0.11（0.08，0.13）
L组	15	0.25（0.19，0.30）^ab	0.37（0.36，0.39）^ab	0.29（0.24，0.39）^a	0.10（0.07，0.10）
M组	16	0.28（0.27，0.30）^a	0.41（0.34，0.44）^ab	0.26（0.21，0.29）^a	0.04（0.03，0.04）^abc
H组	17	0.16（0.15，0.18）^abd	0.45（0.41，0.47）^ab	0.34（0.33，0.39）^ac	0.01（0.01，0.02）^abc
H值		69.391	63.517	48.938	55.815
P值		<0.001	<0.001	<0.001	<0.001

组别	例数	厚壁菌门	拟杆菌门	变形菌门	放线菌门
对照组	16	0.67（0.63，0.79）	0.08（0.05，0.10）	0.08（0.07，0.11）	0.15（0.08，0.17）
VL组	16	0.41（0.40，0.48）	0.19（0.17，0.20）	0.25（0.23，0.31）^a	0.11（0.08，0.13）
L组	15	0.25（0.19，0.30）^ab	0.37（0.36，0.39）^ab	0.29（0.24，0.39）^a	0.10（0.07，0.10）
M组	16	0.28（0.27，0.30）^a	0.41（0.34，0.44）^ab	0.26（0.21，0.29）^a	0.04（0.03，0.04）^abc
H组	17	0.16（0.15，0.18）^abd	0.45（0.41，0.47）^ab	0.34（0.33，0.39）^ac	0.01（0.01，0.02）^abc
H值		69.391	63.517	48.938	55.815
P值		<0.001	<0.001	<0.001	<0.001

组别	例数	棒状杆菌属	葡萄球菌属	链球菌属	拟杆菌属
对照组	16	0.08（0.05，0.10）	0.46（0.43，0.53）	0.02（0.00，0.03）	0.00（0.00，0.00）
VL组	16	0.18（0.17，0.20）	0.17（0.10，0.21）^a	0.05（0.04，0.06）	0.00（0.00，0.01）
L组	15	0.27（0.28，0.30）^a	0.11（0.09，0.13）^a	0.05（0.04，0.08）^a	0.01（0.00，0.01）^a
M组	16	0.29（0.28，0.30）^ab	0.10（0.07，0.11）^a	0.09（0.06，0.11）^a	0.13（0.13，0.14）^abc
H组	17	0.35（0.34，0.36）^abc	0.03（0.01，0.04）^abcd	0.11（0.10，0.12）^abc	0.13（0.07，0.14）^ab
H值		72.060	64.263	49.133	63.995
P值		<0.001	<0.001	<0.001	<0.001

Correlation Analysis of the Risk Degree of Diabetic Foot with Skin Microbiota Based on 16S rRNA Sequencing

基于16S rRNA测序探讨不同糖尿病足危险程度与皮肤菌群的相关性研究

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组别	例数	拟杆菌门	厚壁菌门	葡萄球菌属	棒状杆菌属
对照组	16	13.59±0.47	16.99±0.38	11.33±0.06	8.98±0.04
VL组	16	15.02±0.34^a	16.03±0.27^a	11.31±0.01^a	9.21±0.09^a
L组	15	14.91±0.27^a	15.05±0.45^ab	11.29±0.07^ab	9.38±0.03^ab
M组	16	14.90±0.36^a	14.94±0.36^ab	11.27±0.05^abc	9.49±0.06^abc
H组	17	14.97±0.39^a	14.40±0.61^abcd	11.26±0.01^abcd	9.53±0.04^abcd
F值		40.426	88.453	190.594	253.290
P值		<0.001	<0.001	<0.001	<0.001

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