Evidence map›Paper›PMID 32681188›Full record

ArticleArchives of toxicology2020

Microbially competent 3D skin: a test system that reveals insight into host-microbe interactions and their potential toxicological impact.

Lisa Lemoine, Ralf Dieckmann, Sascha Al Dahouk, Szilvia Vincze, Andreas Luch, Tewes Tralau

Open access · hybridAbstract read
In one paragraph

Article in Archives of toxicology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Engineered Tissue Models to Decode Host-Microbiota Interactions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. The Skin Microbiome: Current Landscape and Future Opportunities.International journal of molecular sciences · 2023
    Review
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Lisa LemoineDepartment of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Strasse 8-10, 10589, Berlin, Germany. Lisa.Lemoine@bfr.bund.de.ORCID 0000-0003-2492-7866
Ralf DieckmannDepartment of Biological Safety, German Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, 12277, Berlin, Germany.
Sascha Al DahoukDepartment of Biological Safety, German Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, 12277, Berlin, Germany.
Szilvia VinczeDepartment of Biological Safety, German Federal Institute for Risk Assessment (BfR), Diedersdorfer Weg 1, 12277, Berlin, Germany.
Andreas LuchDepartment of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Strasse 8-10, 10589, Berlin, Germany.
Tewes TralauDepartment of Food Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Strasse 8-10, 10589, Berlin, Germany.
Federal Institute for Risk Assessment · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The skin`s microbiome is predominantly commensalic, harbouring a metabolic potential far exceeding that of its host. While there is clear evidence that bacteria-dependent metabolism of pollutants modulates the toxicity for the host there is still a lack of models for investigating causality of microbiome-associated pathophysiology or toxicity. We now report on a biologically characterised microbial-skin tissue co-culture that allows studying microbe-host interactions for extended periods of time in situ. The system is based on a commercially available 3D skin model. In a proof-of-concept, this model was colonised with single and mixed cultures of two selected skin commensals. Two different methods were used to quantify the bacteria on the surface of the skin models. While Micrococcus luteus established a stable microbial-skin tissue co-culture, Pseudomonas oleovorans maintained slow continuous growth over the 8-day cultivation period. A detailed skin transcriptome analysis showed bacterial colonisation leading to up to 3318 significant changes. Additionally, FACS, ELISA and Western blot analyses were carried out to analyse secretion of cytokines and growth factors. Changes found in colonised skin varied depending on the bacterial species used and comprised immunomodulatory functions, such as secretion of IL-1α/β, Il-6, antimicrobial peptides and increased gene transcription of IL-10 and TLR2. The colonisation also influenced the secretion of growth factors such as VFGFA and FGF2. Notably, many of these changes have already previously been associated with the presence of skin commensals. Concomitantly, the model gained first insights on the microbiome's influence on skin xenobiotic metabolism (i.e., CYP1A1, CYP1B1 and CYP2D6) and olfactory receptor expression. The system provides urgently needed experimental access for assessing the toxicological impact of microbiome-associated xenobiotic metabolism in situ.

Indexed as

Host Microbial InteractionsAnti-Infective AgentsCytokinesGene Expression ProfilingHumansImmunomodulationIntercellular Signaling Peptides and ProteinsMicrococcus luteusModels, BiologicalPseudomonas oleovoransSkinSymbiosisTissue Culture TechniquesAnti-Infective AgentsCytokinesIntercellular Signaling Peptides and ProteinsCommensalsMethod developmentMicrobial–skin tissue co-cultureSkin modelTranscriptional changes

Identifiers

PMID32681188
PMCPMC7502063
OpenAlexW3042329125

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.