Skip to content
1887

Abstract

The Karelian region, which spans the border between Finland and Russia, presents distinct environmental exposures and lifestyles on either side of the governmental border. In the more urbanized Finnish Karelia, allergic diseases are markedly more prevalent than in the more rural Russian Karelia. Prior studies, based on amplicon sequencing, have demonstrated major differences in skin microbiotas between the two populations. However, compositional differences in microbiota between sensitized and non-sensitized (NS) individuals have not been characterized. Here, in a selected population of 112 allergen-sensitized and NS adolescents, we used shotgun metagenomics to characterize the prokaryotic, eukaryotic and viral species in the skin potentially involved in allergic sensitization via distinct environmental exposures. In the more urban Finnish Karelia, the microbiome species composition was associated with IgE-mediated allergen sensitization status, while in the more rural Russian Karelia, the composition was associated with exposure to furry pets. Finnish participants showing high IgE-mediated sensitization to common allergens (allergen-specific IgE >7.5 kU/L) had less and in their skin and displayed weaker interconnectedness of the microbial co-occurrence network compared with NS participants. Moreover, strain-level differences were related to allergen sensitization in both Finnish and Russian participants. In summary, we found distinct skin microbiomes between allergen-sensitized and NS participants and tracked the bacterial and fungal species associated with the degree of allergic sensitization in the more urbanized part of the Karelian region. These findings provide new insights into the factors that shape the human skin microbiome and influence allergic diseases.

Funding
This study was supported by the:
  • Suomen Kulttuurirahasto (Award 210944)
    • Principal Award Recipient: MattiO Ruuskanen
  • Instrumentariumin Tiedesäätiö
    • Principal Award Recipient: MatildaRiskumäki
  • Yrjö Jahnssonin Säätiö
    • Principal Award Recipient: MatildaRiskumäki
  • Allergiasäätiö
    • Principal Award Recipient: MatildaRiskumäki
  • Academy of Finland (Award 338818)
    • Principal Award Recipient: MattiO Ruuskanen
  • Academy of Finland (Award 333178)
    • Principal Award Recipient: HannaSinkko
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.001527
2025-12-03
2025-12-16

Metrics

Loading full text...

Full text loading...

/deliver/fulltext/mgen/11/12/mgen001527.html?itemId=/content/journal/mgen/10.1099/mgen.0.001527&mimeType=html&fmt=ahah

References

  1. Riskumäki M, Ruuskanen MO, Mäenpää K, Ruokolainen L, Mäkelä MJ et al.Shotgun metagenomics reveals distinct skin microbial species in allergen sensitized individuals Microbiology Society Figshare 2025 [View Article]
    [Google Scholar]
  2. Tong S, Beggs PJ, Davies JM, Jiang F, Kinney PL et al. Compound impacts of climate change, urbanization and biodiversity loss on allergic disease. Int J Epidemiol 2023; 52:655–663 [View Article]
    [Google Scholar]
  3. Haahtela T, Holgate S, Pawankar R, Akdis CA, Benjaponpitak S et al. The biodiversity hypothesis and allergic disease: world allergy organization position statement. World Allergy Organ J 2013; 6:3 [View Article] [PubMed]
    [Google Scholar]
  4. von Hertzen L, Hanski I, Haahtela T. Natural immunity. Biodiversity loss and inflammatory diseases are two global megatrends that might be related. EMBO Rep 2011; 12:1089–1093 [View Article] [PubMed]
    [Google Scholar]
  5. Byrd AL, Belkaid Y, Segre JA. The human skin microbiome. Nat Rev Microbiol 2018; 16:143–155 [View Article] [PubMed]
    [Google Scholar]
  6. Fyhrquist N, Ruokolainen L, Suomalainen A, Lehtimäki S, Veckman V et al. Acinetobacter species in the skin microbiota protect against allergic sensitization and inflammation. J Allergy Clin Immunol 2014; 134:1301–1309 [View Article] [PubMed]
    [Google Scholar]
  7. Ahn J, Hayes RB. Environmental influences on the human microbiome and implications for noncommunicable disease. Annu Rev Public Health 2021; 42:277–292 [View Article] [PubMed]
    [Google Scholar]
  8. Haahtela T, Laatikainen T, Alenius H, Auvinen P, Fyhrquist N et al. Hunt for the origin of allergy - comparing the Finnish and Russian Karelia. Clin Exp Allergy 2015; 45:891–901 [View Article] [PubMed]
    [Google Scholar]
  9. Ruokolainen L, Paalanen L, Karkman A, Laatikainen T, von Hertzen L et al. Significant disparities in allergy prevalence and microbiota between the young people in Finnish and Russian Karelia. Clin Exp Allergy 2017; 47:665–674 [View Article] [PubMed]
    [Google Scholar]
  10. Koskinen J-P, Kiviranta H, Vartiainen E, Jousilahti P, Vlasoff T et al. Common environmental chemicals do not explain atopy contrast in the Finnish and Russian Karelia. Clin Transl Allergy 2016; 6:14 [View Article] [PubMed]
    [Google Scholar]
  11. Ruokolainen L, Fyhrquist N, Laatikainen T, Auvinen P, Fortino V et al. Immune-microbiota interaction in Finnish and Russian Karelia young people with high and low allergy prevalence. Clin Exp Allergy 2020; 50:1148–1158 [View Article] [PubMed]
    [Google Scholar]
  12. Moitinho-Silva L, Boraczynski N, Emmert H, Baurecht H, Szymczak S et al. Host traits, lifestyle and environment are associated with human skin bacteria. Br J Dermatol 2021; 185:573–584 [View Article] [PubMed]
    [Google Scholar]
  13. Hanski I, von Hertzen L, Fyhrquist N, Koskinen K, Torppa K et al. Environmental biodiversity, human microbiota, and allergy are interrelated. Proc Natl Acad Sci USA 2012; 109:8334–8339 [View Article] [PubMed]
    [Google Scholar]
  14. Akdis CA. Does the epithelial barrier hypothesis explain the increase in allergy, autoimmunity and other chronic conditions?. Nat Rev Immunol 2021; 21:739–751 [View Article] [PubMed]
    [Google Scholar]
  15. Ruuskanen MO, Vats D, Potbhare R, RaviKumar A, Munukka E et al. Towards standardized and reproducible research in skin microbiomes. Environ Microbiol 2022; 24:3840–3860 [View Article] [PubMed]
    [Google Scholar]
  16. Johnson JS, Spakowicz DJ, Hong B-Y, Petersen LM, Demkowicz P et al. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat Commun 2019; 10:5029 [View Article] [PubMed]
    [Google Scholar]
  17. von Hertzen L, Mäkelä MJ, Petäys T, Jousilahti P, Kosunen TU et al. Growing disparities in atopy between the Finns and the Russians: a comparison of 2 generations. J Allergy Clin Immunol 2006; 117:151–157 [View Article]
    [Google Scholar]
  18. Mäenpää K, Wang S, Ilves M, El-Nezami H, Alenius H et al. Skin microbiota of oxazolone-induced contact hypersensitivity mouse model. PLoS One 2022; 17:e0276071 [View Article] [PubMed]
    [Google Scholar]
  19. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 2011; 17:10 [View Article]
    [Google Scholar]
  20. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
    [Google Scholar]
  21. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012; 9:357–359 [View Article] [PubMed]
    [Google Scholar]
  22. Andrews S. FastQC: a quality control tool for high throughput sequence data; 2010 https://www.bioinformatics.babraham.ac.uk/projects/fastqc accessed 7 February 2025
  23. Blanco-Míguez A, Beghini F, Cumbo F, McIver LJ, Thompson KN et al. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nat Biotechnol 2023; 41:1633–1644 [View Article] [PubMed]
    [Google Scholar]
  24. Beghini F, McIver LJ, Blanco-Míguez A, Dubois L, Asnicar F et al. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. Elife 2021; 10:e65088 [View Article] [PubMed]
    [Google Scholar]
  25. Huang R, Soneson C, Ernst FGM, Rue-Albrecht KC, Yu G et al. TreeSummarizedExperiment: a S4 class for data with hierarchical structure. F1000Res 2021; 9:1246 [View Article]
    [Google Scholar]
  26. Team RC. R: a language and environment for statistical computing; 2023
  27. Truong DT, Tett A, Pasolli E, Huttenhower C, Segata N. Microbial strain-level population structure and genetic diversity from metagenomes. Genome Res 2017; 27:626–638 [View Article] [PubMed]
    [Google Scholar]
  28. Strimmer K, von Haeseler A. Likelihood-mapping: a simple method to visualize phylogenetic content of a sequence alignment. Proc Natl Acad Sci USA 1997; 94:6815–6819 [View Article] [PubMed]
    [Google Scholar]
  29. Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol 2020; 37:1530–1534 [View Article] [PubMed]
    [Google Scholar]
  30. Zhang J, Rimet F, Bouchez A, Franc A. CRP-Tree: a phylogenetic association test for binary traits. J R Stat Soc C Appl Stat 2024; 73:340–377 [PubMed]
    [Google Scholar]
  31. Oksanen J. vegan: community ecology package 2022
  32. Ernst FGM. mia: microbiome analysis 2023
  33. Ovaskainen O, Tikhonov G, Norberg A, Guillaume Blanchet F, Duan L et al. How to make more out of community data? A conceptual framework and its implementation as models and software. Ecol Lett 2017; 20:561–576 [View Article] [PubMed]
    [Google Scholar]
  34. Tikhonov G. Hmsc: hierarchical model of species communities 2022
  35. Zhou H, He K, Chen J, Zhang X. LinDA: linear models for differential abundance analysis of microbiome compositional data. Genome Biol 2022; 23:95 [View Article] [PubMed]
    [Google Scholar]
  36. Mallick H, Rahnavard A, McIver LJ, Ma S, Zhang Y et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput Biol 2021; 17:e1009442 [View Article] [PubMed]
    [Google Scholar]
  37. Csardi G, Nepusz T. The igraph software package for complex network research. InterJ 20061695
    [Google Scholar]
  38. Pons P, Latapy M. Computing communities in large networks using random walks. In Computer and Information Sciences - Iscis 2005, Proceedings 2005 pp 284–293
    [Google Scholar]
  39. Turner D, Kropinski AM, Adriaenssens EM. A roadmap for genome-based phage taxonomy. Viruses 2021; 13:506 [View Article] [PubMed]
    [Google Scholar]
  40. Lehtimäki J, Sinkko H, Hielm-Björkman A, Laatikainen T, Ruokolainen L et al. Simultaneous allergic traits in dogs and their owners are associated with living environment, lifestyle and microbial exposures. Sci Rep 2020; 10:21954 [View Article] [PubMed]
    [Google Scholar]
  41. Von Hertzen LC, Laatikainen T, Pennanen S, Mäkelä MJ, Haahtela T et al. ALLERGY Net: is house dust mite monosensitization associated with clinical disease?. Allergy 2008; 63:379–381 [View Article]
    [Google Scholar]
  42. Laatikainen T, von Hertzen L, Koskinen J-P, Mäkelä MJ, Jousilahti P et al. Allergy gap between Finnish and Russian Karelia on increase. Allergy 2011; 66:886–892 [View Article]
    [Google Scholar]
  43. Walker JA, McKenzie ANJ. TH2 cell development and function. Nat Rev Immunol 2018; 18:121–133 [View Article]
    [Google Scholar]
  44. van Ree R, Hummelshøj L, Plantinga M, Poulsen LK, Swindle E. Allergic sensitization: host-immune factors. Clin Transl Allergy 2014; 4:12 [View Article] [PubMed]
    [Google Scholar]
  45. Belkaid Y, Segre JA. Dialogue between skin microbiota and immunity. Science 2014; 346:954–959 [View Article]
    [Google Scholar]
  46. Riskumäki M, Tessas I, Ottman N, Suomalainen A, Werner P et al. Interplay between skin microbiota and immunity in atopic individuals. Allergy 2021; 76:1280–1284 [View Article]
    [Google Scholar]
  47. Yang Z, Chen Z, Lin X, Yao S, Xian M et al. Rural environment reduces allergic inflammation by modulating the gut microbiota. Gut Microbes 2022; 14:2125733 [View Article]
    [Google Scholar]
  48. Cahenzli J, Köller Y, Wyss M, Geuking MB, McCoy KD. Intestinal microbial diversity during early-life colonization shapes long-term IgE levels. Cell Host Microbe 2013; 14:559–570 [View Article] [PubMed]
    [Google Scholar]
  49. Wyss M, Brown K, Thomson CA, Koegler M, Terra F et al. Using precisely defined in vivo microbiotas to understand microbial regulation of IgE. Front Immunol 2019; 10:3107 [View Article] [PubMed]
    [Google Scholar]
  50. Jung J, Park W. Acinetobacter species as model microorganisms in environmental microbiology: current state and perspectives. Appl Microbiol Biotechnol 2015; 99:2533–2548 [View Article]
    [Google Scholar]
  51. Debarry J, Garn H, Hanuszkiewicz A, Dickgreber N, Blümer N et al. Acinetobacter lwoffii and Lactococcus lactis strains isolated from farm cowsheds possess strong allergy-protective properties. J Allergy Clin Immunol 2007; 119:1514–1521 [View Article] [PubMed]
    [Google Scholar]
  52. Allhorn M, Arve S, Brüggemann H, Lood R. A novel enzyme with antioxidant capacity produced by the ubiquitous skin colonizer Propionibacterium acnes. Sci Rep 2016; 6:36412 [View Article]
    [Google Scholar]
  53. Rozas M, Hart de Ruijter A, Fabrega MJ, Zorgani A, Guell M et al. From dysbiosis to healthy skin: major contributions of Cutibacterium acnes to skin homeostasis. Microorganisms 2021; 9:628 [View Article]
    [Google Scholar]
  54. Kistowska M, Meier B, Proust T, Feldmeyer L, Cozzio A et al. Propionibacterium acnes promotes Th17 and Th17/Th1 responses in acne patients. J Invest Dermatol 2015; 135:110–118 [View Article] [PubMed]
    [Google Scholar]
  55. Fyhrquist N, Muirhead G, Prast-Nielsen S, Jeanmougin M, Olah P et al. Microbe-host interplay in atopic dermatitis and psoriasis. Nat Commun 2019; 10:4703 [View Article]
    [Google Scholar]
  56. Grice EA, Dawson TLJ. Host-microbe interactions: Malassezia and human skin. Curr Opin Microbiol 2017; 40:81–87 [View Article] [PubMed]
    [Google Scholar]
  57. Thomas DS, Ingham E, Bojar RA, Holland KT. In vitro modulation of human keratinocyte pro- and anti-inflammatory cytokine production by the capsule of Malassezia species. FEMS Immunol Med Microbiol 2008; 54:203–214 [View Article] [PubMed]
    [Google Scholar]
  58. Kesavan S, Holland KT, Ingham E. The effects of lipid extraction on the immunomodulatory activity of Malassezia species in vitro. Med Mycol 2000; 38:239–247 [View Article] [PubMed]
    [Google Scholar]
  59. Glatz M, Bosshard PP, Hoetzenecker W, Schmid-Grendelmeier P. The role of Malassezia spp. in atopic dermatitis. J Clin Med 2015; 4:1217–1228 [View Article] [PubMed]
    [Google Scholar]
  60. Sparber F, De Gregorio C, Steckholzer S, Ferreira FM, Dolowschiak T et al. The skin commensal yeast Malassezia triggers a type 17 response that coordinates anti-fungal immunity and exacerbates skin inflammation. Cell Host Microbe 2019; 25:389–403 [View Article] [PubMed]
    [Google Scholar]
  61. Kneidinger B, O’Riordan K, Li J, Brisson J-R, Lee JC et al. Three highly conserved proteins catalyze the conversion of UDP-N-acetyl-D-glucosamine to precursors for the biosynthesis of O antigen in Pseudomonas aeruginosa O11 and capsule in Staphylococcus aureus type 5. Implications for the UDP-N-acetyl-L-fucosamine biosynthetic pathway. J Biol Chem 2003; 278:3615–3627 [View Article] [PubMed]
    [Google Scholar]
  62. Komaniecka I, Żebracki K, Mazur A, Suśniak K, Sroka-Bartnicka A et al. The absence of a very long chain fatty acid (VLCFA) in lipid A impairs Agrobacterium fabrum plant infection and biofilm formation and increases susceptibility to environmental stressors. Molecules 2025; 30:1080 [View Article] [PubMed]
    [Google Scholar]
  63. Bourassa DV, Kannenberg EL, Sherrier DJ, Buhr RJ, Carlson RW. The lipopolysaccharide lipid A long-chain fatty acid is important for Rhizobium leguminosarum growth and stress adaptation in free-living and nodule environments. Mol Plant Microbe Interact 2017; 30:161–175 [View Article] [PubMed]
    [Google Scholar]
  64. Furue M. Regulation of filaggrin, loricrin, and involucrin by IL-4, IL-13, IL-17A, IL-22, AHR, and NRF2: pathogenic implications in atopic dermatitis. Int J Mol Sci 2020; 21:15 [View Article] [PubMed]
    [Google Scholar]
  65. Hönzke S, Wallmeyer L, Ostrowski A, Radbruch M, Mundhenk L et al. Influence of Th2 cytokines on the cornified envelope, tight junction proteins, and ß-defensins in filaggrin-deficient skin equivalents. J Invest Dermatol 2016; 136:631–639 [View Article] [PubMed]
    [Google Scholar]
/content/journal/mgen/10.1099/mgen.0.001527
Loading
/content/journal/mgen/10.1099/mgen.0.001527
Loading

Data & Media loading...

Supplements

Loading data from figshare Loading data from figshare
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An error occurred
Approval was partially successful, following selected items could not be processed due to error