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A Metagenomic Analysis Provides a Culture-Independent Pathogen Detection for Atopic Dermatitis
Min Hye Kim1, Mina Rho2, Jun Pyo Choi3
1Department of Internal Medicine, Ewha Womans University School of Medicine, Seoul, Korea.
Purpose:
Atopic dermatitis (AD) is an inflammatory skin disease, significantly affecting the quality of life. Using AD as a model system, we tested a successive identification of AD-associated microbes, followed by a culture-independent serum detection of the identified microbe.
Methods:
A total of 43 genomic DNA preparations from washing fluid of the cubital fossa of 6 healthy controls, skin lesions of 27 AD patients, 10 of which later received treatment (post-treatment), were subjected to high-throughput pyrosequencing on a Roche 454 GS-FLX platform.
Results:
Microbial diversity was decreased in AD, and was restored following treatment. AD was characterized by the domination of Staphylococcus, Pseudomonas, and Streptococcus, whereas Alcaligenaceae (f), Sediminibacterium, and Lactococcus were characteristic of healthy skin. An enzyme-linked immunosorbent assay (ELISA) showed that serum could be used as a source for the detection of Staphylococcus aureus extracellular vesicles (EVs). S. aureus EV-specific immunoglobulin G (IgG) and immunoglobulin E (IgE) were quantified in the serum.
Conclusions:
A metagenomic analysis together with a serum detection of pathogen-specific EVs provides a model for successive identification and diagnosis of pathogens of AD.
Insights
This study identifies key microbes in atopic dermatitis (AD) and demonstrates that detecting Staphylococcus aureus extracellular vesicles (EVs) in serum can aid in diagnosis. This approach offers a new model for identifying AD-associated pathogens.
Area of Science:
- Microbiology
- Immunology
- Dermatology
Background:
- Atopic dermatitis (AD) is a prevalent inflammatory skin condition impacting patient quality of life.
- Understanding the microbial landscape in AD is crucial for developing effective diagnostic and therapeutic strategies.
Purpose of the Study:
- To identify microbes associated with atopic dermatitis (AD) using metagenomic analysis.
- To develop a culture-independent method for detecting AD-associated microbes via serum analysis.
- To establish a model system for successive identification and diagnosis of AD pathogens.
Main Methods:
- High-throughput pyrosequencing of genomic DNA from skin swabs of healthy controls and AD patients.
- Metagenomic analysis to compare microbial diversity between groups.
- Enzyme-linked immunosorbent assay (ELISA) to detect Staphylococcus aureus extracellular vesicles (EVs) and specific antibodies (IgG, IgE) in serum.
Main Results:
- Microbial diversity was reduced in AD patients and restored after treatment.
- AD skin lesions were dominated by Staphylococcus, Pseudomonas, and Streptococcus.
- Healthy skin showed a higher prevalence of Alcaligenaceae, Sediminibacterium, and Lactococcus.
- Serum detection of Staphylococcus aureus EVs and specific IgG/IgE antibodies was feasible.
Conclusions:
- Metagenomic analysis combined with serum detection of pathogen-specific EVs offers a novel model for AD pathogen identification and diagnosis.
- This approach facilitates the successive identification of microbes linked to atopic dermatitis.
- The findings support the potential of using microbial EVs in serum for diagnosing inflammatory skin diseases like AD.
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