| Literature DB >> 28679656 |
Allyson L Byrd1,2,3, Clay Deming1, Sara K B Cassidy1, Oliver J Harrison3, Weng-Ian Ng1, Sean Conlan1, Yasmine Belkaid3,4, Julia A Segre5, Heidi H Kong6.
Abstract
The heterogeneous course, severity, and treatment responses among patients with atopic dermatitis (AD; eczema) highlight the complexity of this multifactorial disease. Prior studies have used traditional typing methods on cultivated isolates or sequenced a bacterial marker gene to study the skin microbial communities of AD patients. Shotgun metagenomic sequence analysis provides much greater resolution, elucidating multiple levels of microbial community assembly ranging from kingdom to species and strain-level diversification. We analyzed microbial temporal dynamics from a cohort of pediatric AD patients sampled throughout the disease course. Species-level investigation of AD flares showed greater Staphylococcus aureus predominance in patients with more severe disease and Staphylococcus epidermidis predominance in patients with less severe disease. At the strain level, metagenomic sequencing analyses demonstrated clonal S. aureus strains in more severe patients and heterogeneous S. epidermidis strain communities in all patients. To investigate strain-level biological effects of S. aureus, we topically colonized mice with human strains isolated from AD patients and controls. This cutaneous colonization model demonstrated S. aureus strain-specific differences in eliciting skin inflammation and immune signatures characteristic of AD patients. Specifically, S. aureus isolates from AD patients with more severe flares induced epidermal thickening and expansion of cutaneous T helper 2 (TH2) and TH17 cells. Integrating high-resolution sequencing, culturing, and animal models demonstrated how functional differences of staphylococcal strains may contribute to the complexity of AD disease.Entities:
Mesh:
Year: 2017 PMID: 28679656 PMCID: PMC5706545 DOI: 10.1126/scitranslmed.aal4651
Source DB: PubMed Journal: Sci Transl Med ISSN: 1946-6234 Impact factor: 17.956