Analyze Diet
Microorganisms2026; 14(2); 484; doi: 10.3390/microorganisms14020484

Multi-Kingdom Fecal Microbiota Alterations in Horses with Severe Equine Asthma.

Abstract: Severe equine asthma (SEA) is a chronic inflammation of airways affecting ~14-20% of adult horses in the Northern Hemisphere. SEA is characterized by a mixed phenotype of T helper cell responses with marked neutrophilia in the bronchoalveolar lavage fluid (BALF) of affected horses. Human studies have demonstrated the impact of gut microbiota in many diseases, including asthma susceptibility and severity. However, the potential role of the gut-lung axis in the development and persistence of SEA remains to be determined. This study aimed to identify key bacterial, archaeal, and fungal microbiota alterations in the feces of horses with severe neutrophilic asthma (n = 4) compared to healthy horses (n = 8). Archaea alpha diversity was lower in the feces of SEA-affected horses, but with high abundance of archaea genus , which impacts hydrogen metabolism in horses with SEA. Other key bacterial and fungi species differences lower in SEA included and , respectively. is associated with positive metabolic health due to its fibrolytic capabilities. Overall, our findings indicate that horses experiencing severe neutrophilic asthma have an imbalance in the intestinal microbiota that may exacerbate systemic inflammatory responses through the gut-lung axis.
Publication Date: 2026-02-17 PubMed ID: 41753770PubMed Central: PMC12943238DOI: 10.3390/microorganisms14020484Google 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 gut microbiota—including bacteria, archaea, and fungi—differs in horses with severe equine asthma (SEA) compared to healthy horses, suggesting that intestinal microbial imbalances may contribute to the disease’s inflammatory nature via the gut-lung axis.

Background

  • Severe equine asthma (SEA) is a chronic airway inflammation affecting 14-20% of adult horses in the Northern Hemisphere.
  • SEA is characterized by mixed T helper cell immune responses and a high presence of neutrophils in bronchoalveolar lavage fluid (BALF).
  • In humans, the gut microbiota has been linked to susceptibility and severity of asthma, indicating a possible gut-lung axis in respiratory diseases.
  • The role of the gut microbiome in SEA pathogenesis remains unclear, motivating this study to explore multi-kingdom microbial changes related to the disease.

Objectives

  • To identify alterations in bacterial, archaeal, and fungal fecal microbiota between horses with severe neutrophilic asthma (SEA) and healthy controls.

Methods

  • Fecal samples were collected from two groups: horses with SEA (n=4) and healthy horses (n=8).
  • Microbial diversity and abundance across three domains—bacteria, archaea, and fungi—were analyzed to detect differences.

Key Findings

  • Archaeal alpha diversity, which measures species richness and evenness, was lower in SEA horses, indicating less archaeal diversity.
  • Despite reduced diversity, the abundance of a particular archaeal genus associated with hydrogen metabolism was higher in SEA cases. This suggests these archaea may influence metabolic conditions related to SEA.
  • Certain beneficial bacterial species, such as those linked to positive metabolic health due to fibrolytic activity, were found in lower levels in horses with SEA.
  • Fungal species presence also differed, with some species reduced in SEA, implicating fungi as part of the microbial changes in disease.

Interpretation

  • The imbalance observed across multiple microbial kingdoms suggests dysbiosis in the gut flora of SEA-affected horses.
  • Alterations in microbes involved in fiber digestion and hydrogen metabolism could affect systemic inflammation via metabolic pathways.
  • This supports the concept of a gut-lung axis in horses, where intestinal microbes influence respiratory health and disease severity.
  • These microbial changes may exacerbate or perpetuate neutrophilic inflammation in the airways characteristic of SEA.

Significance and Future Directions

  • Understanding specific gut microbiota changes in SEA can open avenues for novel therapeutic strategies targeting the gut-lung axis.
  • Future research could investigate mechanistic links between altered microbial metabolites and airway inflammation.
  • Interventions such as probiotics, prebiotics, or dietary modulation may help restore a healthy microbial balance to mitigate asthma symptoms in horses.
  • Broader studies with larger sample sizes and longitudinal designs are needed to confirm these findings and further elucidate causality.

Cite This Article

APA
Santos R, Hunyadi L, Sundman E, Morales Luna L, Hyde SC, Cain M, Migl K, Ancira J, Tipton C, Rosa F. (2026). Multi-Kingdom Fecal Microbiota Alterations in Horses with Severe Equine Asthma. Microorganisms, 14(2), 484. https://doi.org/10.3390/microorganisms14020484

Publication

ISSN: 2076-2607
NlmUniqueID: 101625893
Country: Switzerland
Language: English
Volume: 14
Issue: 2
PII: 484

Researcher Affiliations

Santos, Rafaela
  • School of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Hunyadi, Laszlo
  • School of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Sundman, Emily
  • School of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Morales Luna, Luis
  • School of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Hyde, Sarah Cate
  • School of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Cain, Makala
  • School of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Migl, Kagan
  • School of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.
Ancira, Jacob
  • Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA.
  • RTL Genomics, MicroGenDX, Lubbock, TX 79413, USA.
Tipton, Craig
  • RTL Genomics, MicroGenDX, Lubbock, TX 79413, USA.
Rosa, Fernanda
  • School of Veterinary Medicine, Texas Tech University, Amarillo, TX 79106, USA.

Grant Funding

  • 2024-0000000551 / American Quarter Horse Association

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Authors Craig Tipton and Jacob Ancira are employed by RTL Genomics (Lubbock, TX, USA) and were compensated for their contributions to sequencing data analysis. However, these authors did not participate in the study design, data collection, or data interpretation. The authors have no other conflicts of interest to declare.

References

This article includes 100 references
  1. White SJ, Moore-Colyer M, Marti E, Hannant D, Gerber V, Coüetil L, Richard EA, Alcocer M. Antigen array for serological diagnosis and novel allergen identification in severe equine asthma.. Sci. Rep. 2019;9:15170.
    doi: 10.1038/s41598-019-51820-7pmc: PMC6811683pubmed: 31645629google scholar: lookup
  2. Gerber V, Tessier C, Marti E. Genetics of upper and lower airway diseases in the horse.. Equine Vet. J. 2015;47:390–397.
    doi: 10.1111/evj.12289pubmed: 24773614google scholar: lookup
  3. Tessier L, Côté O, Clark ME, Viel L, Diaz-Méndez A, Anders S, Bienzle D. Impaired response of the bronchial epithelium to inflammation characterizes severe equine asthma.. BMC Genom. 2017;18:708.
    doi: 10.1186/s12864-017-4107-6pmc: PMC5591550pubmed: 28886691google scholar: lookup
  4. Meiseberg LK, Delarocque J, de Buhr N, Ohnesorge B. Clinical variability of equine asthma phenotypes and analysis of diagnostic steps in phenotype differentiation.. Acta Vet. Scand. 2024;66:51.
    doi: 10.1186/s13028-024-00773-7pmc: PMC11409572pubmed: 39294710google scholar: lookup
  5. Couetil LL, Cardwell JM, Gerber V, Lavoie JP, Leguillette R, Richard EA. Inflammatory Airway Disease of Horses–Revised Consensus Statement.. J. Vet. Intern. Med. 2016;30:503–515.
    doi: 10.1111/jvim.13824pmc: PMC4913592pubmed: 26806374google scholar: lookup
  6. Bond S, Leguillette R, Richard EA, Couetil L, Lavoie JP, Martin JG, Pirie RS. Equine asthma: Integrative biologic relevance of a recently proposed nomenclature.. J. Vet. Intern. Med. 2018;32:2088–2098.
    doi: 10.1111/jvim.15302pmc: PMC6271326pubmed: 30294851google scholar: lookup
  7. Begley L, Madapoosi S, Opron K, Ndum O, Baptist A, Rysso K, Erb-Downward JR, Huang YJ. Gut microbiota relationships to lung function and adult asthma phenotype: A pilot study.. BMJ Open Respir. Res. 2018;5:e000324.
    doi: 10.1136/bmjresp-2018-000324pmc: PMC6157510pubmed: 30271607google scholar: lookup
  8. McGorum BC, Dixon PM, Halliwell RE. Phenotypic analysis of peripheral blood and bronchoalveolar lavage fluid lymphocytes in control and chronic obstructive pulmonary disease affected horses, before and after ‘natural (hay and straw) challenges’.. Vet. Immunol. Immunopathol. 1993;36:207–222.
    doi: 10.1016/0165-2427(93)90020-5pubmed: 7685131google scholar: lookup
  9. Lavoie JP, Maghni K, Desnoyers M, Taha R, Martin JG, Hamid QA. Neutrophilic airway inflammation in horses with heaves is characterized by a Th2-type cytokine profile.. Am. J. Respir. Crit. Care Med. 2001;164:1410–1413.
    doi: 10.1164/ajrccm.164.8.2012091pubmed: 11704587google scholar: lookup
  10. Moran G, Folch H, Henriquez C, Ortloff A, Barria M. Reaginic antibodies from horses with recurrent airway obstruction produce mast cell stimulation.. Vet. Res. Commun. 2012;36:251–258.
    doi: 10.1007/s11259-012-9534-xpubmed: 23011757google scholar: lookup
  11. Kleiber C, McGorum BC, Horohov DW, Pirie RS, Zurbriggen A, Straub R. Cytokine profiles of peripheral blood and airway CD4 and CD8 T lymphocytes in horses with recurrent airway obstruction.. Vet. Immunol. Immunopathol. 2005;104:91–97.
    doi: 10.1016/j.vetimm.2004.10.002pubmed: 15661334google scholar: lookup
  12. Biesbroek G, Tsivtsivadze E, Sanders EA, Montijn R, Veenhoven RH, Keijser BJ, Bogaert D. Early respiratory microbiota composition determines bacterial succession patterns and respiratory health in children.. Am. J. Respir. Crit. Care Med. 2014;190:1283–1292.
    doi: 10.1164/rccm.201407-1240OCpubmed: 25329446google scholar: lookup
  13. Martinez FD, Guerra S. Early Origins of Asthma. Role of Microbial Dysbiosis and Metabolic Dysfunction.. Am. J. Respir. Crit. Care Med. 2018;197:573–579.
    doi: 10.1164/rccm.201706-1091PPpmc: PMC6005239pubmed: 29048927google scholar: lookup
  14. Schwarzer M, Srutkova D, Schabussova I, Hudcovic T, Akgün J, Wiedermann U, Kozakova H. Neonatal colonization of germ-free mice with Bifidobacterium longum prevents allergic sensitization to major birch pollen allergen Bet v 1.. Vaccine. 2013;31:5405–5412.
    doi: 10.1016/j.vaccine.2013.09.014pubmed: 24055352google scholar: lookup
  15. Morin S, Fischer R, Przybylski-Nicaise L, Bernard H, Corthier G, Rabot S, Wal JM, Hazebrouck S. Delayed bacterial colonization of the gut alters the host immune response to oral sensitization against cow’s milk proteins.. Mol. Nutr. Food Res. 2012;56:1838–1847.
    doi: 10.1002/mnfr.201200412pubmed: 23065810google scholar: lookup
  16. Gensollen T, Blumberg RS. Correlation between early-life regulation of the immune system by microbiota and allergy development.. J. Allergy Clin. Immunol. 2017;139:1084–1091.
    doi: 10.1016/j.jaci.2017.02.011pmc: PMC5402752pubmed: 28390575google scholar: lookup
  17. Schank N, Cottone A, Wulf M, Seiter K, Thomas B, Miller LMJ, Anderson SL, Sahyoun A, Abidi AH, Kassan M. The Role of Short-Chain Fatty Acids (SCFAs) in Colic and Anti-Inflammatory Pathways in Horses.. Animals 2025;15:3482.
    doi: 10.3390/ani15233482pmc: PMC12691112pubmed: 41375540google scholar: lookup
  18. Vargas A, Robinson BL, Houston K, Vilela Sangay AR, Saadeh M, D’Souza S, Johnson DA. Gut microbiota-derived metabolites and chronic inflammatory diseases.. Explor. Med. 2025;6:1001275.
  19. Marsland BJ, Trompette A, Gollwitzer ES. The Gut–Lung Axis in Respiratory Disease.. Ann. Am. Thorac. Soc. 2015;12:S150–S156.
  20. Enaud R, Prevel R, Ciarlo E, Beaufils F, Wieërs G, Guery B, Delhaes L. The Gut–Lung Axis in Health and Respiratory Diseases: A Place for Inter-Organ and Inter-Kingdom Crosstalks.. Front. Cell. Infect. Microbiol. 2020;10:9.
    doi: 10.3389/fcimb.2020.00009pmc: PMC7042389pubmed: 32140452google scholar: lookup
  21. Frati F, Salvatori C, Incorvaia C, Bellucci A, Di Cara G, Marcucci F, Esposito S. The Role of the Microbiome in Asthma: The Gut–Lung Axis.. Int. J. Mol. Sci. 2018;20:123.
    doi: 10.3390/ijms20010123pmc: PMC6337651pubmed: 30598019google scholar: lookup
  22. Sun M, Lu F, Yu D, Wang Y, Chen P, Liu S. Respiratory diseases and gut microbiota: Relevance, pathogenesis, and treatment.. Front. Microbiol. 2024;15:1358597.
    doi: 10.3389/fmicb.2024.1358597pmc: PMC11286581pubmed: 39081882google scholar: lookup
  23. Leduc L, Costa M, Leclère M. The Microbiota and Equine Asthma: An Integrative View of the Gut–Lung Axis.. Animals 2024;14:253.
    doi: 10.3390/ani14020253pmc: PMC10812655pubmed: 38254421google scholar: lookup
  24. Kaiser-Thom S, Hilty M, Gerber V. Effects of hypersensitivity disorders and environmental factors on the equine intestinal microbiota.. Vet. Q. 2020;40:97–107.
  25. Leclere M, Costa MC. Fecal microbiota in horses with asthma.. J. Vet. Intern. Med. 2020;34:996–1006.
    doi: 10.1111/jvim.15748pmc: PMC7096608pubmed: 32128892google scholar: lookup
  26. Costa MC, Silva G, Ramos RV, Staempfli HR, Arroyo LG, Kim P, Weese JS. Characterization and comparison of the bacterial microbiota in different gastrointestinal tract compartments in horses.. Vet. J. 2015;205:74–80.
    doi: 10.1016/j.tvjl.2015.03.018pubmed: 25975855google scholar: lookup
  27. Mazan MR, Hoffman AM. Clinical techniques for diagnosis of inflammatory airway disease in the horse.. Clin. Tech. Equine Pract. 2003;2:238–257.
  28. Pickles K, Pirie RS, Rhind S, Dixon PM, McGorum BC. Cytological analysis of equine bronchoalveolar lavage fluid. Part 2: Comparison of smear and cytocentrifuged preparations.. Equine Vet. J. 2002;34:292–296.
    doi: 10.2746/042516402776186155pubmed: 12108750google scholar: lookup
  29. Davis KU, Sheats MK. Bronchoalveolar Lavage Cytology Characteristics and Seasonal Changes in a Herd of Pastured Teaching Horses.. Front. Vet. Sci. 2019;6:74.
    doi: 10.3389/fvets.2019.00074pmc: PMC6426765pubmed: 30923711google scholar: lookup
  30. Li M, Mao J, Diaz I, Kopylova E, Melnik AV, Aksenov AA, Tipton CD, Soliman N, Morgan AM, Boyd T. Multi-omic approach to decipher the impact of skincare products with pre/postbiotics on skin microbiome and metabolome.. Front. Med. 2023;10:1165980.
    doi: 10.3389/fmed.2023.1165980pmc: PMC10392128pubmed: 37534320google scholar: lookup
  31. Hoffman C, Siddiqui NY, Fields I, Gregory WT, Simon HM, Mooney MA, Wolfe AJ, Karstens L. Species-Level Resolution of Female Bladder Microbiota from 16S rRNA Amplicon Sequencing. mSystems 2021;6:e0051821.
    doi: 10.1128/msystems.00518-21pmc: PMC8547459pubmed: 34519534google scholar: lookup
  32. Allen HK, Bayles DO, Looft T, Trachsel J, Bass BE, Alt DP, Bearson SM, Nicholson T, Casey TA. Pipeline for amplifying and analyzing amplicons of the V1–V3 region of the 16S rRNA gene. BMC Res. Notes 2016;9:380.
    doi: 10.1186/s13104-016-2172-6pmc: PMC4970291pubmed: 27485508google scholar: lookup
  33. Wimmer-Scherr C, Taminiau B, Renaud B, van Loon G, Palmers K, Votion D, Amory H, Daube G, Cesarini C. Comparison of Fecal Microbiota of Horses Suffering from Atypical Myopathy and Healthy Co-Grazers. Animals 2021;11:506.
    doi: 10.3390/ani11020506pmc: PMC7919468pubmed: 33672034google scholar: lookup
  34. Loublier C, Taminiau B, Heinen J, Lecoq L, Amory H, Daube G, Cesarini C. Evaluation of Bacterial Composition and Viability of Equine Feces after Processing for Transplantation. Microorganisms 2023;11:231.
  35. Tipton CD, Sanford NE, Everett JA, Gabrilska RA, Wolcott RD, Rumbaugh KP, Phillips CD. Chronic wound microbiome colonization on mouse model following cryogenic preservation. PLoS ONE 2019;14:e0221565.
  36. Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010;26:2460–2461.
    doi: 10.1093/bioinformatics/btq461pubmed: 20709691google scholar: lookup
  37. Zhang J, Kobert K, Flouri T, Stamatakis A. PEAR: A fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 2014;30:614–620.
  38. Edgar RC. UNOISE2: Improved error-correction for Illumina 16S and ITS amplicon sequencing. bioRxiv 2016:081257.
    doi: 10.1101/081257google scholar: lookup
  39. Edgar RC. SINTAX: A simple non-Bayesian taxonomy classifier for 16S and ITS sequences. bioRxiv 2016:074161.
    doi: 10.1101/074161google scholar: lookup
  40. Edgar RC. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004;32:1792–1797.
    doi: 10.1093/nar/gkh340pmc: PMC390337pubmed: 15034147google scholar: lookup
  41. Nawrocki EP, Kolbe DL, Eddy SR. Infernal 1.0: Inference of RNA alignments. Bioinformatics 2009;25:1335–1337.
  42. Price MN, Dehal PS, Arkin AP. FastTree 2—Approximately Maximum-Likelihood Trees for Large Alignments. PLoS ONE 2010;5:e9490.
  43. Dixon P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 2003;14:927–930.
  44. McMurdie PJ, Holmes S. phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE 2013;8:e61217.
  45. Chao A, Chiu C-H, Jost L. Unifying Species Diversity, Phylogenetic Diversity, Functional Diversity, and Related Similarity and Differentiation Measures Through Hill Numbers. Annu. Rev. Ecol. Evol. Syst. 2014;45:297–324.
  46. Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R. UniFrac: An effective distance metric for microbial community comparison. Isme J. 2011;5:169–172.
    doi: 10.1038/ismej.2010.133pmc: PMC3105689pubmed: 20827291google scholar: lookup
  47. Wang Z, Yu J, Liu Y, Gong J, Hu Z, Liu Z. Role of the microbiota-gut-lung axis in the pathogenesis of pulmonary disease in children and novel therapeutic strategies. Front. Immunol. 2025;16:1636876.
    doi: 10.3389/fimmu.2025.1636876pmc: PMC12507888pubmed: 41080577google scholar: lookup
  48. Edwards JE, Shetty SA, van den Berg P, Burden F, van Doorn DA, Pellikaan WF, Dijkstra J, Smidt H. Multi-kingdom characterization of the core equine fecal microbiota based on multiple equine (sub)species. Anim. Microbiome 2020;2:6.
    doi: 10.1186/s42523-020-0023-1pmc: PMC7807809pubmed: 33499982google scholar: lookup
  49. Dougal K, de la Fuente G, Harris PA, Girdwood SE, Pinloche E, Geor RJ, Nielsen BD, Schott HC 2nd, Elzinga S, Newbold CJ. Characterisation of the faecal bacterial community in adult and elderly horses fed a high fibre, high oil or high starch diet using 454 pyrosequencing. PLoS ONE 2014;9:e87424.
  50. Rios-Covian D, Salazar N, Gueimonde M, de Los Reyes-Gavilan CG. Shaping the Metabolism of Intestinal Bacteroides Population through Diet to Improve Human Health. Front. Microbiol. 2017;8:376.
    doi: 10.3389/fmicb.2017.00376pmc: PMC5339271pubmed: 28326076google scholar: lookup
  51. Ericsson AC, Johnson PJ, Lopes MA, Perry SC, Lanter HR. A Microbiological Map of the Healthy Equine Gastrointestinal Tract. PLoS ONE 2016;11:e0166523.
  52. Julliand V, de Vaux A, Millet L, Fonty G. Identification of Ruminococcus flavefaciens as the predominant cellulolytic bacterial species of the equine cecum. Appl. Environ. Microbiol. 1999;65:3738–3741.
  53. Steelman SM, Chowdhary BP, Dowd S, Suchodolski J, Janečka JE. Pyrosequencing of 16S rRNA genes in fecal samples reveals high diversity of hindgut microflora in horses and potential links to chronic laminitis. BMC Vet. Res. 2012;8:231.
    doi: 10.1186/1746-6148-8-231pmc: PMC3538718pubmed: 23186268google scholar: lookup
  54. Dougal K, Harris PA, Edwards A, Pachebat JA, Blackmore TM, Worgan HJ, Newbold CJ. A comparison of the microbiome and the metabolome of different regions of the equine hindgut. FEMS Microbiol. Ecol. 2012;82:642–652.
  55. Shepherd ML, Swecker WS Jr, Jensen RV, Ponder MA. Characterization of the fecal bacteria communities of forage-fed horses by pyrosequencing of 16S rRNA V4 gene amplicons. FEMS Microbiol. Lett. 2012;326:62–68.
  56. Everard A, Belzer C, Geurts L, Ouwerkerk JP, Druart C, Bindels LB, Guiot Y, Derrien M, Muccioli GG, Delzenne NM. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc. Natl. Acad. Sci. USA 2013;110:9066–9071.
    doi: 10.1073/pnas.1219451110pmc: PMC3670398pubmed: 23671105google scholar: lookup
  57. O’Donnell MM, Harris HMB, Ross RP, O’Toole PW. Core fecal microbiota of domesticated herbivorous ruminant, hindgut fermenters, and monogastric animals. Microbiologyopen 2017;6:e00509.
    doi: 10.1002/mbo3.509pmc: PMC5635170pubmed: 28834331google scholar: lookup
  58. O’Donnell MM, Harris HM, Jeffery IB, Claesson MJ, Younge B, O’Toole PW, Ross RP. The core faecal bacterial microbiome of Irish Thoroughbred racehorses. Lett. Appl. Microbiol. 2013;57:492–501.
    doi: 10.1111/lam.12137pubmed: 23889584google scholar: lookup
  59. Park T, Cheong H, Yoon J, Kim A, Yun Y, Unno T. Comparison of the Fecal Microbiota of Horses with Intestinal Disease and Their Healthy Counterparts. Vet. Sci. 2021;8:113.
    doi: 10.3390/vetsci8060113pmc: PMC8234941pubmed: 34204317google scholar: lookup
  60. Lara F, Castro R, Thomson P. Changes in the gut microbiome and colic in horses: Are they causes or consequences?. Open Vet. J. 2022;12:242–249.
    doi: 10.5455/OVJ.2022.v12.i2.12pmc: PMC9109837pubmed: 35603065google scholar: lookup
  61. Durack J, Boushey HA, Lynch SV. Airway Microbiota and the Implications of Dysbiosis in Asthma. Curr. Allergy Asthma Rep. 2016;16:52.
    doi: 10.1007/s11882-016-0631-8pubmed: 27393699google scholar: lookup
  62. Hufnagl K, Pali-Schöll I, Roth-Walter F, Jensen-Jarolim E. Dysbiosis of the gut and lung microbiome has a role in asthma. Semin. Immunopathol. 2020;42:75–93.
    doi: 10.1007/s00281-019-00775-ypmc: PMC7066092pubmed: 32072252google scholar: lookup
  63. Liang W, Yang Y, Gong S, Wei M, Ma Y, Feng R, Gao J, Liu X, Tu F, Ma W. Airway dysbiosis accelerates lung function decline in chronic obstructive pulmonary disease. Cell Host Microbe 2023;31:1054–1070.e9.
    doi: 10.1016/j.chom.2023.04.018pubmed: 37207649google scholar: lookup
  64. Pu Q, Lin P, Gao P, Wang Z, Guo K, Qin S, Zhou C, Wang B, Wu E, Khan N. Gut Microbiota Regulate Gut–Lung Axis Inflammatory Responses by Mediating ILC2 Compartmental Migration. J. Immunol. 2021;207:257–267.
    doi: 10.4049/jimmunol.2001304pmc: PMC8674377pubmed: 34135060google scholar: lookup
  65. Fillion-Bertrand G, Dickson RP, Boivin R, Lavoie JP, Huffnagle GB, Leclere M. Lung Microbiome Is Influenced by the Environment and Asthmatic Status in an Equine Model of Asthma. Am. J. Respir. Cell Mol. Biol. 2019;60:189–197.
    doi: 10.1165/rcmb.2017-0228OCpubmed: 30183323google scholar: lookup
  66. McKinney CA, Oliveira BCM, Bedenice D, Paradis MR, Mazan M, Sage S, Sanchez A, Widmer G. The fecal microbiota of healthy donor horses and geriatric recipients undergoing fecal microbial transplantation for the treatment of diarrhea. PLoS ONE 2020;15:e0230148.
  67. Costa MC, Weese JS. The equine intestinal microbiome. Anim. Health Res. Rev. 2012;13:121–128.
    doi: 10.1017/S1466252312000035pubmed: 22626511google scholar: lookup
  68. Radcliffe RM. Equine Clinical Immunology. John Wiley & Sons, Ltd.; Hoboken, NJ, USA: 2016. Anaphylaxis; pp. 31–38.
  69. Liu J, Hong W, Sun Z, Zhang S, Xue C, Dong N. The gut–lung axis: Effects and mechanisms of gut microbiota on pulmonary diseases. Front. Immunol. 2025;16:1693964.
    doi: 10.3389/fimmu.2025.1693964pmc: PMC12812986pubmed: 41562083google scholar: lookup
  70. Liu Y, Dai J, Zhou G, Chen R, Bai C, Shi F. Innovative Therapeutic Strategies for Asthma: The Role of Gut Microbiome in Airway Immunity. J. Asthma Allergy 2025;18:257–267.
    doi: 10.2147/JAA.S504571pmc: PMC11849427pubmed: 39996012google scholar: lookup
  71. Tang D, Wang C, Liu H, Wu J, Tan L, Liu S, Lv H, Wang C, Wang F, Liu J. Integrated Multi-Omics Analysis Reveals Mountain-Cultivated Ginseng Ameliorates Cold-Stimulated Steroid-Resistant Asthma by Regulating Interactions among Microbiota, Genes, and Metabolites. Int. J. Mol. Sci. 2024;25:9110.
    doi: 10.3390/ijms25169110pmc: PMC11354367pubmed: 39201796google scholar: lookup
  72. Ray A, Kolls JK. Neutrophilic Inflammation in Asthma and Association with Disease Severity. Trends Immunol. 2017;38:942–954.
    doi: 10.1016/j.it.2017.07.003pmc: PMC5711587pubmed: 28784414google scholar: lookup
  73. Ouyang W, Kolls JK, Zheng Y. The Biological Functions of T Helper 17 Cell Effector Cytokines in Inflammation. Immunity 2008;28:454–467.
  74. Kao CY, Chen Y, Thai P, Wachi S, Huang F, Kim C, Harper RW, Wu R. IL-17 markedly up-regulates beta-defensin-2 expression in human airway epithelium via JAK and NF-kappaB signaling pathways. J. Immunol. 2004;173:3482–3491.
    doi: 10.4049/jimmunol.173.5.3482pubmed: 15322213google scholar: lookup
  75. Sorbello V, Ciprandi G, Di Stefano A, Massaglia GM, Favatà G, Conticello S, Malerba M, Folkerts G, Profita M, Rolla G. Nasal IL-17F is related to bronchial IL-17F/neutrophilia and exacerbations in stable atopic severe asthma. Allergy 2015;70:236–240.
    doi: 10.1111/all.12547pubmed: 25394579google scholar: lookup
  76. Ricciardolo FLM, Sorbello V, Folino A, Gallo F, Massaglia GM, Favatà G, Conticello S, Vallese D, Gani F, Malerba M. Identification of IL-17F/frequent exacerbator endotype in asthma. J. Allergy Clin. Immunol. 2017;140:395–406.
    doi: 10.1016/j.jaci.2016.10.034pubmed: 27931975google scholar: lookup
  77. Chambers ES, Nanzer AM, Pfeffer PE, Richards DF, Timms PM, Martineau AR, Griffiths CJ, Corrigan CJ, Hawrylowicz CM. Distinct endotypes of steroid-resistant asthma characterized by IL-17A(high) and IFN-γ(high) immunophenotypes: Potential benefits of calcitriol. J. Allergy Clin. Immunol. 2015;136:628–637.e4.
    doi: 10.1016/j.jaci.2015.01.026pmc: PMC4559139pubmed: 25772594google scholar: lookup
  78. Zhang M, Qin Z, Huang C, Liang B, Zhang X, Sun W. The gut microbiota modulates airway inflammation in allergic asthma through the gut–lung axis related immune modulation: A review. Biomol. Biomed. 2025;25:727–738.
    doi: 10.17305/bb.2024.11280pmc: PMC11959394pubmed: 39465678google scholar: lookup
  79. Wilson NG, Hernandez-Leyva A, Schwartz DJ, Bacharier LB, Kau AL. The gut metagenome harbors metabolic and antibiotic resistance signatures of moderate-to-severe asthma. FEMS Microbes 2024;5:xtae010.
    doi: 10.1093/femsmc/xtae010pmc: PMC10981462pubmed: 38560624google scholar: lookup
  80. Wang Q, Ji J, Xiao S, Wang J, Yan X, Fang L. Explore Alteration of Lung and Gut Microbiota in a Murine Model of OVA-Induced Asthma Treated by CpG Oligodeoxynucleotides. J. Inflamm. Res. 2025;18:445–461.
    doi: 10.2147/JIR.S487916pmc: PMC11734504pubmed: 39816955google scholar: lookup
  81. Lv J, Zhang Y, Liu S, Wang R, Zhao J. Gut–lung axis in allergic asthma: Microbiota-driven immune dysregulation and therapeutic strategies.. Front. Pharmacol. 2025;16:1617546.
    doi: 10.3389/fphar.2025.1617546pmc: PMC12350297pubmed: 40822476google scholar: lookup
  82. Deng X, Wu X, Wang R, Qiao X, Cao T, Xu Y, Jin Q, Jia L, Liang W. Gut microbiota-based biomarkers for precision subtype classification and mechanistic understanding of biliary and hyperlipidemic acute pancreatitis.. Front. Microbiol. 2025;16:1695811.
    doi: 10.3389/fmicb.2025.1695811pmc: PMC12669208pubmed: 41341501google scholar: lookup
  83. Muralitharan RR, Zheng T, Dinakis E, Xie L, Barbaro-Wahl A, Jama HA, Nakai M, Paterson M, Leung KC, McArdle Z. Gut Microbiota Metabolites Sensed by Host GPR41/43 Protect Against Hypertension.. Circ. Res. 2025;136:e20–e33.
    doi: 10.1161/CIRCRESAHA.124.325770pubmed: 39840468google scholar: lookup
  84. Liu XF, Shao JH, Liao YT, Wang LN, Jia Y, Dong PJ, Liu ZZ, He DD, Li C, Zhang X. Regulation of short-chain fatty acids in the immune system.. Front. Immunol. 2023;14:1186892.
    doi: 10.3389/fimmu.2023.1186892pmc: PMC10196242pubmed: 37215145google scholar: lookup
  85. Zhang J, Zou Y, Chen L, Xu Q, Wang Y, Xie M, Liu X, Zhao J, Wang CY. Regulatory T Cells, a Viable Target Against Airway Allergic Inflammatory Responses in Asthma.. Front. Immunol. 2022;13:902318.
    doi: 10.3389/fimmu.2022.902318pmc: PMC9226301pubmed: 35757774google scholar: lookup
  86. Kang H, Chen Z, Wang B, Chen Z. The AhR/IL-22 axis in chronic gut inflammation: Unraveling mechanisms and therapeutic prospects.. Front. Immunol. 2025;16:1668173.
    doi: 10.3389/fimmu.2025.1668173pmc: PMC12463905pubmed: 41019044google scholar: lookup
  87. Kim YC, Sohn KH, Kang HR. Gut microbiota dysbiosis and its impact on asthma and other lung diseases: Potential therapeutic approaches.. Korean J. Intern. Med. 2024;39:746–758.
    doi: 10.3904/kjim.2023.451pmc: PMC11384250pubmed: 39252487google scholar: lookup
  88. Lwin KO, Matsui H. Comparative analysis of the methanogen diversity in horse and pony by using mcrA gene and archaeal 16s rRNA gene clone libraries.. Archaea 2014;2014:483574.
    doi: 10.1155/2014/483574pmc: PMC3941164pubmed: 24678264google scholar: lookup
  89. Hu D, Yang J, Qi Y, Li B, Li K, Mok KM. Metagenomic Analysis of Fecal Archaea, Bacteria, Eukaryota, and Virus in Przewalski’s Horses Following Anthelmintic Treatment.. Front. Vet. Sci. 2021;8:708512.
    doi: 10.3389/fvets.2021.708512pmc: PMC8416479pubmed: 34490397google scholar: lookup
  90. Li Y, Meng Z, Xu Y, Shi Q, Ma Y, Aung M, Cheng Y, Zhu W. Interactions between Anaerobic Fungi and Methanogens in the Rumen and Their Biotechnological Potential in Biogas Production from Lignocellulosic Materials.. Microorganisms 2021;9:190.
  91. Murru F, Fliegerova K, Mura E, Mrázek J, Kopečný J, Moniello G. A comparison of methanogens of different regions of the equine hindgut.. Anaerobe 2018;54:104–110.
  92. Han S, Kim S, Sedlacek CJ, Farooq A, Song C, Lee S, Liu S, Brüggemann N, Rohe L, Kwon M. Adaptive traits of Nitrosocosmicus clade ammonia-oxidizing archaea.. mBio 2024;15:e0216924.
    doi: 10.1128/mbio.02169-24pmc: PMC11559005pubmed: 39360821google scholar: lookup
  93. Volmer JG, McRae H, Morrison M. The evolving role of methanogenic archaea in mammalian microbiomes.. Front. Microbiol. 2023;14:1268451.
    doi: 10.3389/fmicb.2023.1268451pmc: PMC10506414pubmed: 37727289google scholar: lookup
  94. Thomas CM, Desmond-Le Quéméner E, Gribaldo S, Borrel G. Factors shaping the abundance and diversity of the gut archaeome across the animal kingdom.. Nat. Commun. 2022;13:3358.
    doi: 10.1038/s41467-022-31038-4pmc: PMC9187648pubmed: 35688919google scholar: lookup
  95. Hess M, Paul SS, Puniya AK, van der Giezen M, Shaw C, Edwards JE, Fliegerová K. Anaerobic Fungi: Past, Present, and Future.. Front. Microbiol. 2020;11:584893.
    doi: 10.3389/fmicb.2020.584893pmc: PMC7609409pubmed: 33193229google scholar: lookup
  96. Edwards JE, Schennink A, Burden F, Long S, van Doorn DA, Pellikaan WF, Dijkstra J, Saccenti E, Smidt H. Domesticated equine species and their derived hybrids differ in their fecal microbiota.. Anim. Microbiome 2020;2:8.
    doi: 10.1186/s42523-020-00027-7pmc: PMC7807894pubmed: 33499942google scholar: lookup
  97. Hallen-Adams HE, Suhr MJ. Fungi in the healthy human gastrointestinal tract.. Virulence 2017;8:352–358.
  98. Zheng T, Huang Y, Yao H. Advances in the Gut–Lung Axis and Bronchial Asthma: From Mechanisms to Therapeutic Potential.. Clin. Transl. Allergy 2025;15:e70128.
    doi: 10.1002/clt2.70128pmc: PMC12660059pubmed: 41310922google scholar: lookup
  99. Zhao Ma, Chu J, Feng S, Guo C, Xue B, He K, Li L. Immunological mechanisms of inflammatory diseases caused by gut microbiota dysbiosis: A review.. Biomed. Pharmacother. 2023;164:114985.
    doi: 10.1016/j.biopha.2023.114985pubmed: 37311282google scholar: lookup
  100. Di Vincenzo F, Del Gaudio A, Petito V, Lopetuso LR, Scaldaferri F. Gut microbiota, intestinal permeability, and systemic inflammation: A narrative review.. Intern. Emerg. Med. 2024;19:275–293.
    doi: 10.1007/s11739-023-03374-wpmc: PMC10954893pubmed: 37505311google scholar: lookup

Citations

This article has been cited 0 times.