Cited by 32Dermatology and Skin DiseasesContact Dermatitis and AllergiesNail Diseases and Treatments

Skin microbiota analysis in human 3D skin models—“Free your mice”

Open access
Emmert, Hila, Rademacher, Franziska, Gläser, Regine, Harder, Jürgen·2020·Experimental Dermatology

Abstract

In the May issue of Experimental Dermatology 2018, we published a review article focusing on human 3D skin models in the context of microbiota research. The principal intention was to provide an overview of present and future concepts to use skin models in microbiota analyses. With the present viewpoint, we would like to draw the reader's attention again to the use of human skin models in microbiota research with the aim to highlight the benefits and necessity of human skin models to analyse the human skin‐microbiota interaction. This is accompanied by a critical view on mice models that often are not suitable to analyse the functional impact of the human skin microbiota. In addition, we present novel and future concepts highlighting the benefits of human 3D skin models in microbiota research.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/exd.14164

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Rodent skin has its own microbiota that differs from human skin microbial communities, and attempts to model human microbiota on animal skin are prevented by competition from the native flora, in addition to intrinsic morphological differences with human skin.

    “Indeed, besides having intrinsic morphological differences with human skin, disadvantaging germ-free animal models, rodent skin is characterized by its own microbiota, which obviously differs from the microbial communities of human skin; thus, the attempts to model human microbiota on animal skin are prevented due to the competition exerted by the native flora [133,134].”

    From Recreating Human Skin In Vitro: Should the Microbiota Be Taken into Account? (2024) · cites this paper as [134]

    Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 54

  1. F. Rademacher, M. Simanski, R. Gläser, J. Harder, Exp. Dermatol. 2018, 27, 489.
  2. H. Niehues, J. A. Bouwstra, A. El Ghalbzouri, J. M. Brandner, P. Zeeuwen, E. H. van den Bogaard, Exp. Dermatol. 2018, 27, 501.
  3. A. Pupovac, B. Senturk, C. Griffoni, K. Maniura-Weber, M. Rottmar, S. L. McArthur, Adv. Healthc. Mater. 2018, 7, e1701405.
  4. P. A. Gerber, B. A. Buhren, H. Schrumpf, B. Homey, A. Zlotnik, P. Hevezi, Biol. Chem. 2014, 395, 577.
  5. E. A. Brettmann, C. de Guzman Strong, Exp. Dermatol. 2018, 27, 859.
  6. M. Pasparakis, I. Haase, F. O. Nestle, Nat. Rev. Immunol. 2014, 14, 289.
  7. J. Harder, J. M. Schröder, R. Gläser, Exp. Dermatol. 2013, 22, 1.
  8. K. Kwiecien, A. Zegar, J. Jung, P. Brzoza, M. Kwitniewski, U. Godlewska, B. Grygier, P. Kwiecinska, A. Morytko, J. Cichy, Cytokine Growth Factor Rev. 2019, 49, 70.
  9. F. Rademacher, M. Simanski, J. Harder, Int. J. Mol. Sci. 2016, 17, 560.
  10. V. Dimitrov, J. H. White, J. Steroid Biochem. Mol. Biol. 2016, 164, 246.
  11. S. Holtfreter, F. J. Radcliff, D. Grumann, H. Read, S. Johnson, S. Monecke, S. Ritchie, F. Clow, C. Goerke, B. M. Broker, J. D. Fraser, S. Wiles, PLoS One 2013, 8, e71142.
  12. N. Nagase, A. Sasaki, K. Yamashita, A. Shimizu, Y. Wakita, S. Kitai, J. Kawano, J. Vet. Med. Sci. 2002, 64, 245.
  13. A. A. Ross, K. M. Muller, J. S. Weese, J. D. Neufeld, Proc. Natl Acad. Sci. USA 2018, 115, E5786.
  14. F. Hugenholtz, W. M. de Vos, Cell Mol. Life Sci. 2018, 75, 149.
  15. H. K. Kim, D. Missiakas, O. Schneewind, J. Immunol. Methods 2014, 410, 88.
  16. A. Schulz, L. Jiang, L. de Vor, M. Ehrstrom, F. Wermeling, L. Eidsmo, K. Melican, Cell Rep. 2019, 29, 1074.
  17. P. A. Dimitriu, B. Iker, K. Malik, H. Leung, W. W. Mohn, G. G. Hillebrand, mBio 2019, 10(4):e00839-19. https://doi.org/10.1128/ mBio.00839 -19 · DOI
  18. H. J. Kim, J. J. Kim, N. R. Myeong, T. Kim, D. Kim, S. An, H. Kim, T. Park, S. I. Jang, J. H. Yeon, I. Kwack, W. J. Sul, Sci. Rep. 2019, 9, 16748.
  19. M. Brandwein, I. Katz, A. Katz, R. Kohen, Hum. Microbiome J. 2019, 13, 100063.
  20. R. Vongsa, D. Hoffman, K. Shepard, D. Koenig, BMC Microbiol. 2019, 19, 16.
  21. A. A. Ross, A. Rodrigues Hoffmann, J. D. Neufeld, Microbiome 2019, 7, 79.
  22. P. L. Zeeuwen, T. H. Ederveen, D. A. van der Krieken, H. Niehues, J. Boekhorst, S. Kezic, D. A. Hanssen, M. E. Otero, I. M. van Vlijmen- Willems, D. Rodijk-Olthuis, D. Falcone, E. H. van den Bogaard, M. Kamsteeg, H. D. de Koning, M. E. Zeeuwen-Franssen, M. A. van Steensel, M. Kleerebezem, H. M. Timmerman, S. A. van Hijum, J. Schalkwijk, J. Allergy Clin. Immunol. 2017, 139, 1368.
  23. N. Fyhrquist, G. Muirhead, S. Prast-Nielsen, M. Jeanmougin, P. Olah, T. Skoog, G. Jules-Clement, M. Feld, M. Barrientos-Somarribas, H. Sinkko, E. H. van den Bogaard, P. Zeeuwen, G. Rikken, J. Schalkwijk, H. Niehues, W. Daubener, S. K. Eller, H. Alexander, D. Pennino, S. Suomela, I. Tessas, E. Lybeck, A. M. Baran, H. Darban, R. S. Gangwar, U. Gerstel, K. Jahn, P. Karisola, L. Yan, B. Hansmann, S. Katayama, S. Meller, M. Bylesjo, P. Hupe, F. Levi-Schaffer, D. Greco, A. Ranki, J. M. Schroder, J. Barker, J. Kere, S. Tsoka, A. Lauerma, V. Soumelis, F. O. Nestle, B. Homey, B. Andersson, H. Alenius, Nat. Commun. 2019, 10, 4703.
  24. E. van den Bogaard, D. Ilic, S. Dubrac, M. Tomic-Canic, J. Bouwstra, A. Celli, T. Mauro, J. Invest. Dermatol. 2020. https://doi. org/10.1016/j.jid.2020.04.023 [Online ahead of print] · DOI
  25. H. Niehues, J. Schalkwijk, I. van Vlijmen-Willems, D. Rodijk-Olthuis, M. M. van Rossum, E. Wladykowski, J. M. Brandner, E. H. J. van den Bogaard, P. Zeeuwen, J Allergy Clin. Immunol. 1979, 2017, 139.
  26. W. David Boothe, J. A. Tarbox, M. B. Tarbox, Adv. Exp. Med. Biol. 2017, 1027, 21.
  27. S. Weidinger, N. Novak, Lancet 2016, 387, 1109.
  28. H. Baurecht, M. C. Ruhlemann, E. Rodriguez, F. Thielking, I. Harder, A. S. Erkens, D. Stolzl, E. Ellinghaus, M. Hotze, W. Lieb, S. Wang, F. A. Heinsen-Groth, A. Franke, S. Weidinger, J. Allergy Clin. Immunol. 2018, 141, 1668.
  29. M. Burian, B. Schittek, Int. J. Med. Microbiol. 2015, 305, 283.
  30. C. Tam, J. J. Mun, D. J. Evans, S. M. Fleiszig, J. Clin. Invest. 2012, 122, 3665.
  31. J. Ishikawa, H. Narita, N. Kondo, M. Hotta, Y. Takagi, Y. Masukawa, T. Kitahara, Y. Takema, S. Koyano, S. Yamazaki, A. Hatamochi, J. Invest. Dermatol. 2010, 130, 2511.
  32. S. Li, M. Villarreal, S. Stewart, J. Choi, G. Ganguli-Indra, D. C. Babineau, C. Philpot, G. David, T. Yoshida, M. Boguniewicz, J. M. Hanifin, L. A. Beck, D. Y. Leung, E. L. Simpson, A. K. Indra, Br. J. Dermatol. 2017, 177, e125.
  33. M. Mildner, J. Jin, L. Eckhart, S. Kezic, F. Gruber, C. Barresi, C. Stremnitzer, M. Buchberger, V. Mlitz, C. Ballaun, B. Sterniczky, D. Fodinger, E. Tschachler, J. Invest. Dermatol. 2010, 130, 2286.
  34. V. van Drongelen, E. M. Haisma, J. J. Out-Luiting, P. H. Nibbering, A. El Ghalbzouri, Clin. Exp. Allergy 2014, 44, 1515.
  35. D. Fangmann, E. M. Theismann, K. Turk, D. M. Schulte, I. Relling, K. Hartmann, J. K. Keppler, J. R. Knipp, A. Rehman, F. A. Heinsen, A. Franke, L. Lenk, S. Freitag-Wolf, E. Appel, S. Gorb, C. Brenner, D. Seegert, G. H. Waetzig, P. Rosenstiel, S. Schreiber, K. Schwarz, M. Laudes, Diab. Care 2018, 41, 398.
  36. D. Houghton, T. Hardy, C. Stewart, L. Errington, C. P. Day, M. I. Trenell, L. Avery, Diabetologia 2018, 61, 1700.
  37. V. Meslier, M. Laiola, H. M. Roager, F. De Filippis, H. Roume, B. Quinquis, R. Giacco, I. Mennella, R. Ferracane, N. Pons, E. Pasolli, A. Rivellese, L. O. Dragsted, P. Vitaglione, S. D. Ehrlich, D. Ercolini, Gut 2020, 69, 1258.
  38. C. Clemente, E. C. Pehrsson, M. J. Blaser, K. Sandhu, Z. Gao, B. Wang, M. Magris, G. Hidalgo, M. Contreras, Ó. Noya-Alarcón, O. Lander, J. McDonald, M. Cox, J. Walter, P. L. Oh, J. F. Ruiz, S. Rodriguez, N. Shen, S. J. Song, J. Metcalf, R. Knight, G. Dantas, M. G. Dominguez-Bello, Sci. Adv. 2015, 1, e1500183.
  39. Y. Nodake, S. Matsumoto, R. Miura, H. Honda, G. Ishibashi, I. Dekio, R. Sakakibara, J. Dermatol. Sci. 2015, 79, 119.
  40. A. Myles, N. J. Earland, E. D. Anderson, I. N. Moore, M. D. Kieh, K. W. Williams, A. Saleem, N. M. Fontecilla, P. A. Welch, D. A. Darnell, L. A. Barnhart, A. A. Sun, G. Uzel, S. K. Datta, JCI Insight 2018, 3, e120608.
  41. C. Schmidt, Nat. Biotechnol. 2020, 38, 392.
  42. B. Paetzold, J. R. Willis, J. Pereira de Lima, N. Knodlseder, H. Bruggemann, S. R. Quist, T. Gabaldon, M. Guell, Microbiome 2019, 7, 95.
  43. D. Hoeller, B. Huppertz, T. C. Roos, P. Poblete Gutierrez, H. F. Merk, J. Frank, F. K. Jugert, Exp. Dermatol. 2001, 10, 264.
  44. T. Wagner, M. Gschwandtner, A. Strajeriu, A. Elbe-Burger, J. Grillari, R. Grillari-Voglauer, G. Greiner, B. Golabi, E. Tschachler, M. Mildner, Sci. Rep. 2018, 8, 13434.
  45. N. Obara, S. Tohgi, Y. Mii, N. Hamada, R. Arakawa, S. R. Aki, R. M. Singh, Y. A. Hoffman, Sci. Rep. 2019, 9, 9326.
  46. A. Berroth, J. Kuhnl, N. Kurschat, A. Schwarz, F. Stab, T. Schwarz, H. Wenck, R. Fölster-Holst, G. Neufang, J. Allergy Clin. Immunol. 2013, 131, 1547.
  47. E. Desmet, A. Ramadhas, J. Lambert, M. Van Gele, Exp. Biol. Med. (Maywood) 2017, 242, 1158.
  48. E. H. van den Bogaard, G. S. Tjabringa, I. Joosten, M. Vonk-Bergers, E. van Rijssen, H. J. Tijssen, M. Erkens, J. Schalkwijk, H. Koenen, J. Invest. Dermatol. 2014, 134, 719.
  49. K. Ouwehand, S. W. Spiekstra, T. Waaijman, M. Breetveld, R. J. Scheper, T. D. de Gruijl, S. Gibbs, Eur. J. Cell Biol. 2012, 91, 765.
  50. V. Facy, V. Flouret, M. Regnier, R. Schmidt, Toxicol. In Vitro 2005, 19, 787.
  51. J. Lee, C. C. Rabbani, H. Gao, M. R. Steinhart, B. M. Woodruff, Z. E. Pflum, A. Kim, S. Heller, Y. Liu, T. Z. Shipchandler, K. R. Koehler, Nature 2020, 582, 399.
  52. S. Ishack, S. R. Lipner, Dermatol. Surg. 2020. https://doi.org/10.1097/ DSS.00000 00000 002378 [Online ahead of print] · DOI
  53. S. Xu, X. Zheng, L. Hu, W. Li, R. Li, Y. Parungao, Y. Wang, Y. Nie, T. Liu, K. Song, Polymers (Basel) 2020, 12, 1237.
  54. B. S. Kim, G. Gao, J. Y. Kim, D. W. Cho, Adv. Healthc. Mater. 2019, 8, e1801019. How to cite this article: Emmert H, Rademacher F, Gläser R, Harder J. Skin microbiota analysis in human 3D skin models- "Free your mice". Exp Dermatol. 2020;29:1133-1139. https:// doi.org/10.1111/exd.14164

Cited by

Sorted by citations

Authors
Emmert, H., Rademacher, F., Gläser, R., & Harder, J.
Affiliations
Christian-Albrechts-Universität zu Kiel (DE)
Corresponding author
Harder, Jürgen
Venue
Experimental Dermatology
Publisher
Wiley
Published
2020-08-27
Volume
29
Issue
11
Pages
1133-1139
ISSN
  • 0906-6705 (ISSN-L)
  • 1600-0625
OpenAlex
W3047285247
Cited by
32
References
6
Citations by year
2026: 5 · 2025: 7 · 2024: 6 · 2023: 7 · 2022: 4 · 2021: 3
FWCI
2.55
Type
journal article
Language
en
Open access
Locations
  • Experimental Dermatology (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Dermatology › Dermatology and Skin Diseases
  • Health Sciences › Medicine › Dermatology › Contact Dermatitis and Allergies
  • Health Sciences › Medicine › Epidemiology › Nail Diseases and Treatments
Keywords
skin microbiome, mouse model, animal model limitations, in vitro skin model
MeSH terms
Host Microbial Interactions, Animals, Humans, Models, Biological, Skin, Skin Physiological Phenomena, Biomedical Research, Mice, Precision Medicine, Microbiota

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review