Analyze Diet
Microorganisms2025; 14(1); 57; doi: 10.3390/microorganisms14010057

High-Altitude Extreme Environments Drive Convergent Evolution of Skin Microbiota in Humans and Horses.

Abstract: Unique skin microbial communities have been shaped by the harsh climatic conditions in high-altitude areas, such as intense ultraviolet radiation and low oxygen concentration. However, it is unknown whether high altitude contributes to shaping common microbiota inhabiting the skin across different mammals. The skin microbial communities of humans and horses living in high-altitude (Tibetan) and low-altitude areas were analyzed using full-length 16S rRNA sequencing technology. Alpha diversity differed between high- and low-altitude groups ( < 0.01). Skin microbial community composition also differed between high- and low-altitude areas ( < 0.05). Some of the common taxa present in the skin of humans and horses in high-altitude areas were identified as extreme microorganisms capable of adapting to the harsh high-altitude environment. Five bacterial taxa, including the genera , , and , as well as the species and , were significantly enriched ( < 0.01) on the skin of both humans and horses in high-altitude areas. Meanwhile, some taxa enriched on the skin surface at the same altitude showed preferences for mammalian species. , , and were significantly enriched ( < 0.05) in the skin of humans at both high and low altitudes, whereas and , and were significantly enriched ( < 0.05) in the skin of horses at both high and low altitudes. In the network analyses, a positive correlation ( < 0.01) was shown between the skin taxa enriched in high-altitude areas and each other, while a negative correlation ( < 0.01) was found between the skin microorganisms enriched in high-altitude areas and those enriched in low-altitude areas. Overall, our findings indicate that high-altitude extreme environments drive convergent evolution of skin microbiota across mammals, reflecting the joint effects of environmental selection and host-related filtering on community assembly. This cross-species comparison provides a framework for understanding skin microbiome responses to extreme environments in plateau mammals.
Publication Date: 2025-12-26 PubMed ID: 41597577PubMed Central: PMC12843950DOI: 10.3390/microorganisms14010057Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

Overview

  • This study investigates how the extreme environmental conditions at high altitudes influence the skin microbiota of humans and horses.
  • It identifies common microbial communities on the skin of both species that have evolved convergently to survive harsh conditions like intense UV radiation and low oxygen, indicating similar environmental pressures shape skin microbiomes across different mammals.

Background and Purpose

  • High-altitude environments present unique challenges such as intense ultraviolet (UV) radiation, low oxygen levels, and extreme climatic variations.
  • Previous knowledge shows skin microbiota diversity can be influenced by environmental factors, but it is unclear whether such extreme environments drive similar microbial adaptations across different mammalian species.
  • The study aims to analyze and compare the skin microbiota of humans and horses living at high altitudes (Tibetan Plateau) versus low altitudes, to reveal whether convergent evolution of skin microbiota occurs due to these environments.

Methods

  • Sample collection from the skin of humans and horses living in both high-altitude (Tibet) and low-altitude regions.
  • Use of full-length 16S rRNA gene sequencing technology, which allows detailed identification and quantification of bacterial species on the skin.
  • Analysis of alpha diversity (variation within samples) and community composition differences between groups.
  • Statistical evaluation of the abundance of bacterial taxa enriched in different altitude groups and between species.
  • Network analyses to investigate relationships and interactions among bacterial taxa enriched in different environments and species.

Key Findings

  • Diversity Differences: Alpha diversity significantly differed between high- and low-altitude groups, indicating that microbial richness or evenness changes with altitude (<0.01 significance).
  • Community Composition: The overall skin microbial community composition also significantly differed between altitudes (<0.05 significance), suggesting altitude shapes which microbes dominate.
  • Common High-Altitude Microbes: Identification of several bacterial taxa enriched on both humans and horses at high altitudes, including genera and species known to be extremophiles capable of surviving harsh UV, low oxygen, and other stressors.
  • Specific Taxa Enriched in Both Species: Five bacterial taxa including certain genera and species were significantly more abundant on the skin of both humans and horses living at high altitudes (p < 0.01).
  • Host-Specific Preferences: Despite convergence driven by environmental factors, some taxa showed preferences for a particular host species regardless of altitude:
    • Humans had enrichment of specific genera regardless of altitude.
    • Horses had other specific taxa enriched on their skin at both altitudes.
  • Microbial Network Correlations:
    • Positive correlations among high-altitude enriched taxa indicate these bacteria may interact synergistically or share adaptation strategies.
    • Negative correlations between high-altitude and low-altitude enriched taxa suggest competitive or mutually exclusive relationships influenced by the environment.

Conclusions

  • The harsh, extreme environment at high altitudes acts as a strong selective force that drives convergent evolution of the skin microbiota across different mammalian species.
  • Both environmental pressures (like UV radiation, oxygen levels) and host-related biological filtering shape which microbial communities assemble on the skin in these regions.
  • The findings reveal that despite differences in host species, environmental extremes can lead to similar microbial adaptations, reflecting a broader ecological principle of convergence.
  • This cross-species approach improves understanding of how skin microbiomes respond and adapt to extreme environments, particularly in plateau mammals.

Implications and Future Directions

  • This study suggests potential for identifying microbial species with unique adaptations that could be harnessed for biotechnological or medical purposes, such as UV protection or oxygen stress mitigation.
  • Understanding microbial convergence may help in managing skin health in humans and animals living at high altitudes.
  • Future research could explore functional genomics of these extremophile skin microbes to detail the mechanisms of adaptation.
  • Comparative studies including more mammalian species or other high-altitude regions could generalize these findings further.

Cite This Article

APA
Zhang Y, Zhang M, Zhao Z, Peng Y, Deng F, Jiang H, Zhang M, Song B, Kim JK, Pan JH, Chai J, Li Y. (2025). High-Altitude Extreme Environments Drive Convergent Evolution of Skin Microbiota in Humans and Horses. Microorganisms, 14(1), 57. https://doi.org/10.3390/microorganisms14010057

Publication

ISSN: 2076-2607
NlmUniqueID: 101625893
Country: Switzerland
Language: English
Volume: 14
Issue: 1
PII: 57

Researcher Affiliations

Zhang, Yuwei
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Zhang, Manyu
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Zhao, Zhengge
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Peng, Yunjuan
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Deng, Feilong
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Jiang, Hui
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Zhang, Meimei
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Song, Bo
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Kim, Jae Kyeom
  • Department of Food and Biotechnology, Korea University, Sejong 339770, Republic of Korea.
Pan, Jeong Hoon
  • Department of Food and Nutrition, Chosun University, Gwangju 61452, Republic of Korea.
Chai, Jianmin
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.
Li, Ying
  • Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Animal Science and Technology, Foshan University, Foshan 528000, China.

Grant Funding

  • 32170430 / the National Natural Science Foundation of China

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 62 references
  1. Zhao S, Zhong H, He Y, Li X, Zhu L, Xiong Z, Zhang X, Zheng N, Morgavi DP, Wang J. Leveraging core enzyme structures for microbiota targeted functional regulation: Urease as an example.. Imeta 2025;4:e70032.
    doi: 10.1002/imt2.70032pmc: PMC12130578pubmed: 40469508google scholar: lookup
  2. Yoshio H, Lagercrantz H, Gudmundsson GH, Agerberth B. First line of defense in early human life.. Semin. Perinatol. 2004;28:304–311.
    doi: 10.1053/j.semperi.2004.08.008pubmed: 15565791google scholar: lookup
  3. Ross AA, Doxey AC, Neufeld JD. The Skin Microbiome of Cohabiting Couples.. mSystems 2017;2:e00043-17.
    doi: 10.1128/mSystems.00043-17pmc: PMC5527301pubmed: 28761935google scholar: lookup
  4. Smythe P, Wilkinson HN. The Skin Microbiome: Current Landscape and Future Opportunities.. Int. J. Mol. Sci. 2023;24:3950.
    doi: 10.3390/ijms24043950pmc: PMC9963692pubmed: 36835363google scholar: lookup
  5. Moissl-Eichinger C, Probst AJ, Birarda G, Auerbach A, Koskinen K, Wolf P, Holman HN. Human age and skin physiology shape diversity and abundance of Archaea on skin.. Sci. Rep. 2017;7:4039.
    doi: 10.1038/s41598-017-04197-4pmc: PMC5481324pubmed: 28642547google scholar: lookup
  6. Oh J, Byrd AL, Park M, Kong HH, Segre JA. Temporal Stability of the Human Skin Microbiome.. Cell 2016;165:854–866.
    doi: 10.1016/j.cell.2016.04.008pmc: PMC4860256pubmed: 27153496google scholar: lookup
  7. Grice EA, Segre JA. The skin microbiome.. Nat. Rev. Microbiol. 2011;9:244–253.
    doi: 10.1038/nrmicro2537pmc: PMC3535073pubmed: 21407241google scholar: lookup
  8. Kortekaas Krohn I, Callewaert C, Belasri H, De Pessemier B, Diez Lopez C, Mortz CG, O’Mahony L, Pérez-Gordo M, Sokolowska M, Unger Z. The influence of lifestyle and environmental factors on host resilience through a homeostatic skin microbiota: An EAACI Task Force Report.. Allergy 2024;79:3269–3284.
    doi: 10.1111/all.16378pmc: PMC11657040pubmed: 39485000google scholar: lookup
  9. Cha J, Kim TG, Ryu JH. Conversation between skin microbiota and the host: From early life to adulthood.. Exp. Mol. Med. 2025;57:703–713.
    doi: 10.1038/s12276-025-01427-ypmc: PMC12045987pubmed: 40164684google scholar: lookup
  10. Lunjani N, Ahearn-Ford S, Dube FS, Hlela C, O’Mahony L. Mechanisms of microbe-immune system dialogue within the skin.. Genes Immun. 2021;22:276–288.
    doi: 10.1038/s41435-021-00133-9pmc: PMC8497273pubmed: 33993202google scholar: lookup
  11. Lefèvre-Utile A, Braun C, Haftek M, Aubin F. Five Functional Aspects of the Epidermal Barrier.. Int. J. Mol. Sci. 2021;22:11676.
    doi: 10.3390/ijms222111676pmc: PMC8583944pubmed: 34769105google scholar: lookup
  12. Mead MN. Nutrigenomics: The genome–food interface.. Environ. Health Perspect. 2007;115:A582–A589.
    doi: 10.1289/ehp.115-a582pmc: PMC2137135pubmed: 18087577google scholar: lookup
  13. Gao Z, Tseng CH, Strober BE, Pei Z, Blaser MJ. Substantial alterations of the cutaneous bacterial biota in psoriatic lesions.. PLoS ONE 2008;3:e2719.
  14. Grice EA, Kong HH, Renaud G, Young AC, Bouffard GG, Blakesley RW, Wolfsberg TG, Turner ML, Segre JA. A diversity profile of the human skin microbiota.. Genome Res. 2008;18:1043–1050.
    doi: 10.1101/gr.075549.107pmc: PMC2493393pubmed: 18502944google scholar: lookup
  15. Roszkowski W, Roszkowski K, Ko HL, Beuth J, Jeljaszewicz J. Immunomodulation by propionibacteria.. Zentralbl Bakteriol. 1990;274:289–298.
    doi: 10.1016/S0934-8840(11)80686-9pubmed: 2090145google scholar: lookup
  16. Tang YW, Stratton CW. Staphylococcus aureus: An old pathogen with new weapons.. Clin. Lab. Med. 2010;30:179–208.
    doi: 10.1016/j.cll.2010.01.005pubmed: 20513547google scholar: lookup
  17. Deng F, Han Y, Li M, Peng Y, Chai J, Yang G, Li Y, Zhao J. HiFi based metagenomic assembly strategy provides accuracy near isolated genome resolution in MAG assembly.. iMetaOmics 2025;2:e70041.
    doi: 10.1002/imo2.70041google scholar: lookup
  18. Shu M, Wang Y, Yu J, Kuo S, Coda A, Jiang Y, Gallo RL, Huang CM. Fermentation of Propionibacterium acnes, a commensal bacterium in the human skin microbiome, as skin probiotics against methicillin-resistant Staphylococcus aureus.. PLoS ONE 2013;8:e55380.
  19. Wang Y, Kuo S, Shu M, Yu J, Huang S, Dai A, Two A, Gallo RL, Huang CM. Staphylococcus epidermidis in the human skin microbiome mediates fermentation to inhibit the growth of Propionibacterium acnes: Implications of probiotics in acne vulgaris.. Appl. Microbiol. Biotechnol. 2014;98:411–424.
    doi: 10.1007/s00253-013-5394-8pmc: PMC3888247pubmed: 24265031google scholar: lookup
  20. Knackstedt R, Knackstedt T, Gatherwright J. The role of topical probiotics in skin conditions: A systematic review of animal and human studies and implications for future therapies.. Exp. Dermatol. 2020;29:15–21.
    doi: 10.1111/exd.14032pubmed: 31494971google scholar: lookup
  21. Beall CM. Andean, Tibetan, and Ethiopian patterns of adaptation to high-altitude hypoxia.. Integr. Comp. Biol. 2006;46:18–24.
    doi: 10.1093/icb/icj004pubmed: 21672719google scholar: lookup
  22. Jablonski NG, Chaplin G. Colloquium paper: Human skin pigmentation as an adaptation to UV radiation.. Proc. Natl. Acad. Sci. USA 2010;107:8962–8968.
    doi: 10.1073/pnas.0914628107pmc: PMC3024016pubmed: 20445093google scholar: lookup
  23. Olsen CM, Wilson LF, Green AC, Bain CJ, Fritschi L, Neale RE, Whiteman DC. Cancers in Australia attributable to exposure to solar ultraviolet radiation and prevented by regular sunscreen use.. Aust. N. Z. J. Public Health 2015;39:471–476.
    doi: 10.1111/1753-6405.12470pmc: PMC4606762pubmed: 26437734google scholar: lookup
  24. Li H, Wang Y, Yu Q, Feng T, Zhou R, Shao L, Qu J, Li N, Bo T, Zhou H. Elevation is Associated with Human Skin Microbiomes.. Microorganisms 2019;7:611.
  25. Zeng B, Zhao J, Guo W, Zhang S, Hua Y, Tang J, Kong F, Yang X, Fu L, Liao K. High-Altitude Living Shapes the Skin Microbiome in Humans and Pigs.. Front. Microbiol. 2017;8:1929.
    doi: 10.3389/fmicb.2017.01929pmc: PMC5635199pubmed: 29056930google scholar: lookup
  26. Zhang Z, Ran H, Hua Y, Deng F, Zeng B, Chai J, Li Y. Screening and evaluation of skin potential probiotic from high-altitude Tibetans to repair ultraviolet radiation damage.. Front. Microbiol. 2023;14:1273902.
    doi: 10.3389/fmicb.2023.1273902pmc: PMC10620709pubmed: 37928688google scholar: lookup
  27. Yang S, Zheng J, Mao H, Vinitchaikul P, Wu D, Chai J. Multiomics of yaks reveals significant contribution of microbiome into host metabolism.. npj Biofilms Microbiomes 2024;10:133.
    doi: 10.1038/s41522-024-00609-2pmc: PMC11582361pubmed: 39572587google scholar: lookup
  28. Deng F, Wang C, Li D, Peng Y, Deng L, Zhao Y, Zhang Z, Wei M, Wu K, Zhao J. The unique gut microbiome of giant pandas involved in protein metabolism contributes to the host’s dietary adaption to bamboo.. Microbiome 2023;11:180.
    doi: 10.1186/s40168-023-01603-0pmc: PMC10424351pubmed: 37580828google scholar: lookup
  29. Bizley SC, Dudhia J, Smith RKW, Williams AC. Transdermal drug delivery in horses: An in vitro comparison of skin structure and permeation of two model drugs at various anatomical sites.. Vet. Dermatol. 2023;34:235–245.
    doi: 10.1111/vde.13162pubmed: 37185892google scholar: lookup
  30. Johnson JS, Spakowicz DJ, Hong BY, Petersen LM, Demkowicz P, Chen L, Leopold SR, Hanson BM, Agresta HO, Gerstein M. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis.. Nat. Commun. 2019;10:5029.
    doi: 10.1038/s41467-019-13036-1pmc: PMC6834636pubmed: 31695033google scholar: lookup
  31. Estaki M, Jiang L, Bokulich NA, McDonald D, González A, Kosciolek T, Martino C, Zhu Q, Birmingham A, Vázquez-Baeza Y. QIIME 2 Enables Comprehensive End-to-End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data.. Curr. Protoc. Bioinform. 2020;70:e100.
    doi: 10.1002/cpbi.100pmc: PMC9285460pubmed: 32343490google scholar: lookup
  32. Ramirez M, Duncan C, Schaffer PA, Wobeser B, Magzamen S. Environmental risk factors for UV-induced cutaneous neoplasia in horses: A GIS approach.. Can. Vet. J. 2023;64:971–975.
    pmc: PMC10506358pubmed: 37780476
  33. Hodgson DR, McCutcheon LJ, Byrd SK, Brown WS, Bayly WM, Brengelmann GL, Gollnick PD. Dissipation of metabolic heat in the horse during exercise.. J. Appl. Physiol. 1993;74:1161–1170.
    doi: 10.1152/jappl.1993.74.3.1161pubmed: 8482654google scholar: lookup
  34. Wang Y, Yu Q, Zhou R, Feng T, Hilal MG, Li H. Nationality and body location alter human skin microbiome.. Appl. Microbiol. Biotechnol. 2021;105:5241–5256.
    doi: 10.1007/s00253-021-11387-8pubmed: 34125277google scholar: lookup
  35. Grice EA, Kong HH, Conlan S, Deming CB, Davis J, Young AC, Bouffard GG, Blakesley RW, Murray PR, Green ED. Topographical and temporal diversity of the human skin microbiome.. Science 2009;324:1190–1192.
    doi: 10.1126/science.1171700pmc: PMC2805064pubmed: 19478181google scholar: lookup
  36. Park H, Arellano K, Lee Y, Yeo S, Ji Y, Ko J, Holzapfel W. Pilot Study on the Forehead Skin Microbiome and Short Chain Fatty Acids Depending on the SC Functional Index in Korean Cohorts.. Microorganisms 2021;9:2216.
  37. Fung C, Rusling M, Lampeter T, Love C, Karim A, Bongiorno C, Yuan LL. Automation of QIIME2 Metagenomic Analysis Platform.. Curr. Protoc. 2021;1:e254.
    doi: 10.1002/cpz1.254pubmed: 34554657google scholar: lookup
  38. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection.. Bioinformatics 2011;27:2194–2200.
  39. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.. Appl. Environ. Microbiol. 2007;73:5261–5267.
    doi: 10.1128/AEM.00062-07pmc: PMC1950982pubmed: 17586664google scholar: lookup
  40. Legendre P, De Cáceres M. Beta diversity as the variance of community data: Dissimilarity coefficients and partitioning.. Ecol. Lett. 2013;16:951–963.
    doi: 10.1111/ele.12141pubmed: 23809147google scholar: lookup
  41. Bray JR, Curtis JT. An Ordination of the Upland Forest Communities of Southern Wisconsin.. Ecol. Monogr. 1957;27:325–349.
    doi: 10.2307/1942268google scholar: lookup
  42. Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation.. Genome Biol. 2011;12:R60.
    doi: 10.1186/gb-2011-12-6-r60pmc: PMC3218848pubmed: 21702898google scholar: lookup
  43. R Core Team. R: A Language and Environment for Statistical Computing.. R Foundation for Statistical Computing; Vienna, Austria: 2021.
  44. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: A software environment for integrated models of biomolecular interaction networks.. Genome Res. 2003;13:2498–2504.
    doi: 10.1101/gr.1239303pmc: PMC403769pubmed: 14597658google scholar: lookup
  45. Seifert H, Dijkshoorn L, Gerner-Smidt P, Pelzer N, Tjernberg I, Vaneechoutte M. Distribution of Acinetobacter species on human skin: Comparison of phenotypic and genotypic identification methods.. J. Clin. Microbiol. 1997;35:2819–2825.
  46. Veloo ACM, de Vries ED, Jean-Pierre H, van Winkelhoff AJ. Anaerococcus nagyae sp. nov., isolated from human clinical specimens.. Anaerobe 2016;38:111–115.
  47. Fujii T, Shinozaki J, Kajiura T, Iwasaki K, Fudou R. A newly discovered Anaerococcus strain responsible for axillary odor and a new axillary odor inhibitor, pentagalloyl glucose.. FEMS Microbiol. Ecol. 2014;89:198–207.
    doi: 10.1111/1574-6941.12347pubmed: 24784923google scholar: lookup
  48. Sladecek V, Senk D, Stolar P, Bzdil J, Holy O. Predominance of Acinetobacter pseudolwoffii among Acinetobacter species in domestic animals in the Czech Republic.. Vet. Med. 2023;68:419–427.
    doi: 10.17221/65/2023-VETMEDpmc: PMC10755813pubmed: 38163045google scholar: lookup
  49. Tamaki H, Tanaka Y, Matsuzawa H, Muramatsu M, Meng XY, Hanada S, Mori K, Kamagata Y. Armatimonas rosea gen. nov., sp. nov., of a novel bacterial phylum, Armatimonadetes phyl. nov., formally called the candidate phylum OP10.. Int. J. Syst. Evol. Microbiol. 2011;61:1442–1447.
    doi: 10.1099/ijs.0.025643-0pubmed: 20622056google scholar: lookup
  50. Xu N, Yang X, Yang Q, Guo M. Comparative Genomic and Transcriptomic Analysis of Phenol Degradation and Tolerance in Acinetobacter lwoffii through Adaptive Evolution.. Int. J. Mol. Sci. 2023;24:16529.
    doi: 10.3390/ijms242216529pmc: PMC10671910pubmed: 38003719google scholar: lookup
  51. Di Capua C, Bortolotti A, Farías ME, Cortez N. UV-resistant Acinetobacter sp. isolates from Andean wetlands display high catalase activity.. FEMS Microbiol. Lett. 2011;317:181–189.
  52. Asker D, Beppu T, Ueda K. Sphingomonas astaxanthinifaciens sp. nov., a novel astaxanthin-producing bacterium of the family Sphingomonadaceae isolated from Misasa, Tottori, Japan.. FEMS Microbiol. Lett. 2007;273:140–148.
  53. Nishida Y, Adachi K, Kasai H, Shizuri Y, Shindo K, Sawabe A, Komemushi S, Miki W, Misawa N. Elucidation of a carotenoid biosynthesis gene cluster encoding a novel enzyme, 2,2′-beta-hydroxylase, from Brevundimonas sp. strain SD212 and combinatorial biosynthesis of new or rare xanthophylls.. Appl. Environ. Microbiol. 2005;71:4286–4296.
  54. Rezaeeyan Z, Safarpour A, Amoozegar MA, Babavalian H, Tebyanian H, Shakeri F. High carotenoid production by a halotolerant bacterium, Kocuria sp. strain QWT-12 and anticancer activity of its carotenoid.. EXCLI J. 2017;16:840–851.
    doi: 10.17179/excli2017-218pmc: PMC5547384pubmed: 28827999google scholar: lookup
  55. Paredes Contreras BV, Vermelho AB, Casanova L, de Alencar Santos Lage C, Spindola Vilela CL, da Silva Cardoso V, Pacheco Arge LW, Cardoso-Rurr JS, Correa SS, Passos De Mansoldo FR. Enhanced UV-B photoprotection activity of carotenoids from the novel Arthrobacter sp. strain LAPM80 isolated from King George Island, Antarctica.. Heliyon 2025;11:e41400.
  56. Seel W, Baust D, Sons D, Albers M, Etzbach L, Fuss J, Lipski A. Carotenoids are used as regulators for membrane fluidity by Staphylococcus xylosus.. Sci. Rep. 2020;10:330.
    doi: 10.1038/s41598-019-57006-5pmc: PMC6962212pubmed: 31941915google scholar: lookup
  57. Giani M, Martínez-Espinosa RM. Carotenoids as a Protection Mechanism against Oxidative Stress in Haloferax mediterranei.. Antioxidants 2020;9:1060.
    doi: 10.3390/antiox9111060pmc: PMC7694103pubmed: 33137984google scholar: lookup
  58. Liu Y, Chen T, Cui X, Xu Y, Hu S, Zhao Y, Zhang W, Liu G, Zhang G. Sphingomonas radiodurans sp. nov., a novel radiation-resistant bacterium isolated from the north slope of Mount Everest.. Int. J. Syst. Evol. Microbiol. 2022;72:005312.
    doi: 10.1099/ijsem.0.005312pubmed: 35412454google scholar: lookup
  59. Thiele JJ, Ekanayake-Mudiyanselage S. Vitamin E in human skin: Organ-specific physiology and considerations for its use in dermatology.. Mol. Aspects Med. 2007;28:646–667.
    doi: 10.1016/j.mam.2007.06.001pubmed: 17719081google scholar: lookup
  60. Uchida Y. Ceramide signaling in mammalian epidermis.. Biochim. Biophys. Acta 2014;1841:453–462.
  61. Albarracín VH, Pathak GP, Douki T, Cadet J, Borsarelli CD, Gärtner W, Farias ME. Extremophilic Acinetobacter strains from high-altitude lakes in Argentinean Puna: Remarkable UV-B resistance and efficient DNA damage repair.. Orig. Life Evol. Biosph. 2012;42:201–221.
    doi: 10.1007/s11084-012-9276-3pubmed: 22644565google scholar: lookup
  62. Muletz Wolz CR, Yarwood SA, Campbell Grant EH, Fleischer RC, Lips KR. Effects of host species and environment on the skin microbiome of Plethodontid salamanders.. J. Anim. Ecol. 2018;87:341–353.
    doi: 10.1111/1365-2656.12726pubmed: 28682480google scholar: lookup

Citations

This article has been cited 0 times.