Biomolecules (Jun 2023)

Combining 16S Sequencing and qPCR Quantification Reveals <i>Staphylococcus aureus</i> Driven Bacterial Overgrowth in the Skin of Severe Atopic Dermatitis Patients

  • Amedeo De Tomassi,
  • Anna Reiter,
  • Matthias Reiger,
  • Luise Rauer,
  • Robin Rohayem,
  • CK-CARE Study Group,
  • Claudia Traidl-Hoffmann,
  • Avidan U. Neumann,
  • Claudia Hülpüsch

DOI
https://doi.org/10.3390/biom13071030
Journal volume & issue
Vol. 13, no. 7
p. 1030

Abstract

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Atopic dermatitis (AD) is an inflammatory skin disease with a microbiome dysbiosis towards a high relative abundance of Staphylococcus aureus. However, information is missing on the actual bacterial load on AD skin, which may affect the cell number driven release of pathogenic factors. Here, we combined the relative abundance results obtained by next-generation sequencing (NGS, 16S V1-V3) with bacterial quantification by targeted qPCR (total bacterial load = 16S, S. aureus = nuc gene). Skin swabs were sampled cross-sectionally (n = 135 AD patients; n = 20 healthy) and longitudinally (n = 6 AD patients; n = 6 healthy). NGS and qPCR yielded highly inter-correlated S. aureus relative abundances and S. aureus cell numbers. Additionally, intra-individual differences between body sides, skin status, and consecutive timepoints were also observed. Interestingly, a significantly higher total bacterial load, in addition to higher S. aureus relative abundance and cell numbers, was observed in AD patients in both lesional and non-lesional skin, as compared to healthy controls. Moreover, in the lesional skin of AD patients, higher S. aureus cell numbers significantly correlated with the higher total bacterial load. Furthermore, significantly more severe AD patients presented with higher S. aureus cell number and total bacterial load compared to patients with mild or moderate AD. Our results indicate that severe AD patients exhibit S. aureus driven increased bacterial skin colonization. Overall, bacterial quantification gives important insights in addition to microbiome composition by sequencing.

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