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PloS one2025; 20(4); e0321389; doi: 10.1371/journal.pone.0321389

Metagenomic and proteomic analyses reveal similar reproductive microbial profiles and shared functional pathways in uterine immune regulation in mares and jennies.

Abstract: This study aims to unveil potential differences in the vaginal and uterine microbiomes in mares and jennies, and to identify possible mechanisms involved in uterine immune homeostasis. The microbiota was characterized using 16S rRNA sequencing, and the uterine proteome was analyzed using UHPLC/MS/MS in 18 samples from healthy mares and 14 from jennies. While taxonomic analysis revealed high interspecies similarities, β-diversity analysis showed distinct clustering, with only two vaginal taxa and five uterine taxa differing between species. Despite compositional differences, PICRUSt analysis suggested minimal variations in predicted functional pathways across species. Comparing vaginal and uterine microbiota within the same species revealed overlapping bacterial taxa, but significant differences in α- and β-diversity and functional pathways. The uterine microbiota of both species was dominated by Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria, with abundant taxa like Streptococcus, Pseudomonas, Bacillus, Corynebacterium, and Staphylococcus, many of which are frequently associated with endometritis. The presence of Lactobacillus in the equine reproductive tract was minimal or non-existent. KEGG functional pathway analysis predicted that uterine microbiota of both species utilize metabolic pathways with potential immunomodulatory effects. Proteomic enrichment analysis showed that numerous overexpressed uterine proteins in both species are linked to adaptive and innate immune regulation and defense mechanisms against symbionts. Gene enrichment analysis identified several enriched Gene Ontology terms, including response to bacterial stimuli, humoral immune regulation, and TGF-beta receptor signaling, underscoring microbial-host interactions. The uterine microbiota may play a vital role in maintaining immune balance. Further research is required to confirm its interaction with the uterine immune system and clarify the mechanisms involved.
Copyright: © 2025 da Silva-Álvarez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Publication Date: 2025-04-16 PubMed ID: 40238748PubMed Central: PMC12002498DOI: 10.1371/journal.pone.0321389Google Scholar: Lookup
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  • 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.

The study explores the potential differences and similarities in the vaginal and uterine microbiomes of mares and jennies, with a focus on the possible mechanisms that help maintain uterine immune balance.

Methodology

  • The research incorporated metagenomic and proteomic analyses of 18 samples from healthy mares and 14 from jennies.
  • Microbiota was characterized using 16S rRNA sequencing, a technique that enables the identification and study of microorganisms within the tested samples.
  • UHPLC/MS/MS technique (ultra high-performance liquid chromatography coupled with tandem mass spectrometry) was employed to analyze the uterine proteome or the set of expressed proteins in a cell, tissue, or organism.

Findings

  • The taxonomic analysis showed high interspecies microbiota similarities between mares and jennies.
  • A beta diversity analysis indicated a distinct clustering in both species, signifying different species abundance and distribution.
  • Although there were compositional differences, the PICRUSt analysis indicated minimal variations in the predicted functional pathways across both species.
  • When comparing the vaginal and uterine microbiota within the same species, there were overlapping bacterial taxa but noticeable differences in alpha and beta diversity and functional pathways.
  • The uterine microbiota of both species was dominated by Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria. Common taxa, such as Streptococcus, Pseudomonas, Bacillus, Corynebacterium, and Staphylococcus, were abundant.

Implications of the Study

  • Many of the microbes are frequently found in conditions such as endometritis, suggesting a link between certain bacteria and uterine health.
  • The researchers found surprisingly little or non-existent traces of Lactobacillus, a type of bacteria known to be beneficial for human reproductive health, in the equine reproductive tract.
  • The data interpreted from the KEGG (Kyoto Encyclopedia of Genes and Genomes) functional pathway analysis suggested that the uterine microbiota of both species utilize metabolic pathways that may have immunomodulatory effects, implicating that the uterine microbiota may play a role in the immune regulation of the uterus.
  • Proteomic enrichment analysis found that several overexpressed uterine proteins in both species are linked to adaptive and innate immune regulation, suggesting microbial-symbiont defensive interactions.
  • The gene enrichment analysis identified several enriched Gene Ontology terms, emphasizing a mutual interaction between the host and microbes.
  • However, despite these promising results, further research is needed to confirm the interplay between uterine microbiota and the immune system and clarify the mechanisms involved in maintaining immune balance within the uterus.

Cite This Article

APA
da Silva-Álvarez E, Gómez-Arrones V, Correa-Fiz F, Martín-Cano FE, Gaitskell-Phillips G, Carrasco JJ, Rey J, Aparicio IM, Peña FJ, Alonso JM, Ortega-Ferrusola C. (2025). Metagenomic and proteomic analyses reveal similar reproductive microbial profiles and shared functional pathways in uterine immune regulation in mares and jennies. PLoS One, 20(4), e0321389. https://doi.org/10.1371/journal.pone.0321389

Publication

PloS one
ISSN: 1932-6203
NlmUniqueID: 101285081
Country: United States
Language: English
Volume: 20
Issue: 4
Pages: e0321389

Researcher Affiliations

da Silva-Álvarez, Eva
  • Department of Animal Medicine, Laboratory of Equine Reproduction and Equine Spermatology, Faculty of Veterinary Medicine, University of Extremadura, Cáceres, Spain.
Gómez-Arrones, Vanessa
  • Centro de Selección y Reproducción animal de Extremadura. Junta de Extremadura, Badajoz, Spain.
Correa-Fiz, Florencia
  • Centre de Recerca en Sanitat Animal (CReSA), Unitat Mixta d'Investigació IRTA-UAB en Sanitat Animal, Campus de la Universitat Autònoma de Barcelona (UAB), Barcelona, Spain.
  • IRTA, Programa de Sanitat Animal, Centre de Recerca en Sanitat Animal (CReSA), Campus de la Universitat Autònoma de Barcelona (UAB), Barcelona, Spain.
  • WOAH Collaborating Centre for the Research and Control of Emerging and Re-Emerging Swine Diseases in Europe (IRTA-CReSA), Barcelona, Spain.
Martín-Cano, Francisco Eduardo
  • Department of Animal Medicine, Laboratory of Equine Reproduction and Equine Spermatology, Faculty of Veterinary Medicine, University of Extremadura, Cáceres, Spain.
Gaitskell-Phillips, Gemma
  • Department of Animal Medicine, Laboratory of Equine Reproduction and Equine Spermatology, Faculty of Veterinary Medicine, University of Extremadura, Cáceres, Spain.
Carrasco, Juan Jesús
  • Centro de Selección y Reproducción animal de Extremadura. Junta de Extremadura, Badajoz, Spain.
Rey, Joaquín
  • Department of Animal Health, Unit of Infectious Diseases, University of Extremadura, Caceres, Spain.
Aparicio, Inés María
  • Department of Anatomy, Cell Biology and Zoology, Faculty of Nursery and Occupational Therapy, University of Extremadura, Caceres, Spain.
Peña, Fernando Juan
  • Department of Animal Medicine, Laboratory of Equine Reproduction and Equine Spermatology, Faculty of Veterinary Medicine, University of Extremadura, Cáceres, Spain.
Alonso, Juan Manuel
  • Department of Animal Health, Unit of Infectious Diseases, University of Extremadura, Caceres, Spain.
Ortega-Ferrusola, Cristina
  • Department of Animal Medicine, Laboratory of Equine Reproduction and Equine Spermatology, Faculty of Veterinary Medicine, University of Extremadura, Cáceres, Spain.

MeSH Terms

  • Animals
  • Female
  • Horses / microbiology
  • Horses / immunology
  • Uterus / microbiology
  • Uterus / immunology
  • Uterus / metabolism
  • Proteomics / methods
  • Microbiota / genetics
  • RNA, Ribosomal, 16S / genetics
  • Metagenomics
  • Vagina / microbiology
  • Vagina / immunology
  • Bacteria / genetics
  • Bacteria / classification
  • Proteome

Conflict of Interest Statement

The authors have declared that no competing interests exist.

References

This article includes 78 references
  1. Li J, Zhu Y, Mi J, Zhao Y, Holyoak GR, Yi Z. Endometrial and vaginal microbiome in donkeys with and without clinical endometritis. Front Microbiol 2022;13:884574.
    doi: 10.3389/fmicb.2022.884574pmc: PMC9376452pubmed: 35979491google scholar: lookup
  2. Virendra A, Gulavane SU, Ahmed ZA, Reddy R, Chaudhari RJ, Gaikwad SM. Metagenomic analysis unravels novel taxonomic differences in the uterine microbiome between healthy mares and mares with endometritis. Vet Med Sci 2024;10(2):e1369.
    doi: 10.1002/vms3.1369pmc: PMC10867593pubmed: 38357732google scholar: lookup
  3. Da Silva E, Martín-Cano FE, Gómez-Arrones V, Gaitskell-Phillips G, Alonso JM, Rey J. Bacterial endometritis-induced changes in the endometrial proteome in mares: Potential uterine biomarker for bacterial endometritis. Theriogenology 2024;226:202–12.
    doi: 10.1016/j.theriogenology.2024.06.009pubmed: 38909435google scholar: lookup
  4. LeBlanc MM, Causey RC. Clinical and subclinical endometritis in the mare: Both threats to fertility. Reprod Domest Anim 2009;44(Suppl 3):10–22.
    doi: 10.1111/j.1439-0531.2009.01485.xpubmed: 19660076google scholar: lookup
  5. Diel de Amorim M, Gartley CJ, Foster RA, Hill A, Scholtz EL, Hayes A. Comparison of clinical signs, endometrial culture, endometrial cytology, uterine low-volume lavage, and uterine biopsy and combinations in the diagnosis of equine endometritis. J Equine Vet Sci 2016;44:54–61.
    doi: 10.1016/j.jevs.2015.10.012google scholar: lookup
  6. Garcia-Grau I, Simon C, Moreno I. Uterine microbiome-low biomass and high expectations. Biol Reprod 2019;101(6):1102–14.
    doi: 10.1093/biolre/ioy257pubmed: 30544156google scholar: lookup
  7. Chen C, Song X, Wei W, Zhong H, Dai J, Lan Z. The microbiota continuum along the female reproductive tract and its relation to uterine-related diseases. Nat Commun 2017;8(1):875.
    doi: 10.1038/s41467-017-00901-0pmc: PMC5645390pubmed: 29042534google scholar: lookup
  8. Heil BA, Paccamonti DL, Sones JL. Role for the mammalian female reproductive tract microbiome in pregnancy outcomes. Physiol Genomics 2019;51(8):390–9.
    doi: 10.1152/physiolgenomics.00045.2019pubmed: 31251700google scholar: lookup
  9. Moreno I, Codoñer FM, Vilella F, Valbuena D, Martinez-Blanch JF, Jimenez-Almazán J. Evidence that the endometrial microbiota has an effect on implantation success or failure. Am J Obstet Gynecol 2016;215(6):684–703.
    doi: 10.1016/j.ajog.2016.09.075pubmed: 27717732google scholar: lookup
  10. Keburiya LK, Smolnikova VY, Priputnevich TV, Muravieva VV, Gordeev AB, Trofimov DY. Does the uterine microbiota affect the reproductive outcomes in women with recurrent implantation failures?. BMC Womens Health 2022;22(1):168.
    doi: 10.1186/s12905-022-01750-wpmc: PMC9107114pubmed: 35568852google scholar: lookup
  11. Romero R, Hassan SS, Gajer P, Tarca AL, Fadrosh DW, Nikita L. The composition and stability of the vaginal microbiota of normal pregnant women is different from that of non-pregnant women. Microbiome 2014;2(1):4.
    doi: 10.1186/2049-2618-2-4pmc: PMC3916806pubmed: 24484853google scholar: lookup
  12. Haahr T, Jensen JS, Thomsen L, Duus L, Rygaard K, Humaidan P. Abnormal vaginal microbiota may be associated with poor reproductive outcomes: A prospective study in IVF patients. Hum Reprod 2016;31(4):795–803.
    doi: 10.1093/humrep/dew026pubmed: 26911864google scholar: lookup
  13. Lykke MR, Becher N, Haahr T, Boedtkjer E, Jensen JS, Uldbjerg N. Vaginal, cervical and uterine ph in women with normal and abnormal vaginal microbiota. Pathogens 2021;10(2):90.
    doi: 10.3390/pathogens10020090pmc: PMC7909242pubmed: 33498288google scholar: lookup
  14. Mändar R, Sõerunurk G, Štšepetova J, Smidt I, Rööp T, Kõljalg S. Impact of Lactobacillus crispatus-containing oral and vaginal probiotics on vaginal health: A randomised double-blind placebo controlled clinical trial. Benef Microbes 2023;14(2):143–52.
    doi: 10.3920/BM2022.0091pubmed: 36856121google scholar: lookup
  15. López-Moreno A, Aguilera M. Vaginal probiotics for reproductive health and related dysbiosis: Systematic review and meta-analysis. J Clin Med 2021;10(7):1461.
    doi: 10.3390/jcm10071461pmc: PMC8037567pubmed: 33918150google scholar: lookup
  16. Koester LR, Petry AL, Youngs CR, Schmitz-Esser S. Ewe vaginal microbiota: Associations with pregnancy outcome and changes during gestation. Front Microbiol 2021;12:745884.
    doi: 10.3389/fmicb.2021.745884pmc: PMC8570082pubmed: 34745049google scholar: lookup
  17. Quereda JJ, Barba M, Mocé ML, Gomis J, Jiménez-Trigos E, García-Muñoz Á. Vaginal microbiota changes during estrous cycle in dairy heifers. Front Vet Sci 2020;7:371.
    doi: 10.3389/fvets.2020.00371pmc: PMC7350931pubmed: 32719814google scholar: lookup
  18. Barba M, Martínez-Boví R, Quereda JJ, Mocé ML, Plaza-Dávila M, Jiménez-Trigos E. Vaginal microbiota is stable throughout the estrous cycle in arabian maress. Animals (Basel) 2020;10(11):2020.
    doi: 10.3390/ani10112020pmc: PMC7692283pubmed: 33153053google scholar: lookup
  19. Yang X, Cheng G, Li C, Yang J, Li J, Chen D. The normal vaginal and uterine bacterial microbiome in giant pandas (Ailuropoda melanoleuca). Microbiol Res 2017;199:1–9.
    doi: 10.1016/j.micres.2017.01.003pubmed: 28454704google scholar: lookup
  20. Lyman CC, Holyoak GR, Meinkoth K, Wieneke X, Chillemi KA, DeSilva U. Canine endometrial and vaginal microbiomes reveal distinct and complex ecosystems. PLoS One 2019;14(1):e0210157.
    doi: 10.1371/journal.pone.0210157pmc: PMC6322750pubmed: 30615657google scholar: lookup
  21. Malaluang P, Åkerholm T, Nyman G, Lindahl J, Hansson I, Morrell JM. Bacteria in the healthy equine vagina during the estrous cycle. Theriogenology 2024;213:11–8.
    doi: 10.1016/j.theriogenology.2023.09.011pubmed: 37793220google scholar: lookup
  22. Stumpf RM, Wilson BA, Rivera A, Yildirim S, Yeoman CJ, Polk JD. The primate vaginal microbiome: Comparative context and implications for human health and disease. Am J Phys Anthropol 2013;152:119–34.
    doi: 10.1002/ajpa.22395pubmed: 24166771google scholar: lookup
  23. Yildirim S, Yeoman CJ, Janga SC, Thomas SM, Ho M, Leigh SR. Primate vaginal microbiomes exhibit species specificity without universal lactobacillus dominance. ISME J 2014;8(12):2431–44.
    doi: 10.1038/ismej.2014.90pmc: PMC4260710pubmed: 25036926google scholar: lookup
  24. Holyoak GR, Premathilake HU, Lyman CC, Sones JL, Gunn A, Wieneke X. The healthy equine uterus harbors a distinct core microbiome plus a rich and diverse microbiome that varies with geographical location. Sci Rep 2022;12(1):14790.
    doi: 10.1038/s41598-022-18971-6pmc: PMC9427864pubmed: 36042332google scholar: lookup
  25. Maloney SE, Khan FA, Chenier TS, Diel de Amorim M, Anthony Hayes M, Scholtz EL. A comparison of the uterine proteome of mares in oestrus and dioestrus. Reprod Domest Anim 2019;54(3):473–9.
    doi: 10.1111/rda.13375pubmed: 30428136google scholar: lookup
  26. Lawson EF, Gibb Z, de Ruijter-Villani M, Smith ND, Stout TA, Clutton-Brock A. Proteomic analysis of pregnant mare uterine fluid. J Equine Vet Sci 2018;66:171–2.
    doi: 10.1016/j.jevs.2018.05.064google scholar: lookup
  27. Diel de Amorim M, Khan FA, Chenier TS, Scholtz EL, Hayes MA. Analysis of the uterine flush fluid proteome of healthy mares and mares with endometritis or fibrotic endometrial degeneration. Reprod Fertil Dev 2020;32(6):572–81.
    doi: 10.1071/RD19085pubmed: 31987068google scholar: lookup
  28. Wolf CA, Maslchitzky E, Gregory RM, Jobim MIM, Mattos RC. Effect of corticotherapy on proteomics of endometrial fluid from mares susceptible to persistent postbreeding endometritis. Theriogenology 2012;77(7):1351–9.
    doi: 10.1016/j.theriogenology.2011.10.042pubmed: 22225686google scholar: lookup
  29. Bohn AA, Ferris RA, McCue PM. Comparison of equine endometrial cytology samples collected with uterine swab, uterine brush, and low-volume lavage from healthy mares. Vet Clin Pathol 2014;43(4):594–600.
    doi: 10.1111/vcp.12194pubmed: 25208767google scholar: lookup
  30. Riddle WT, LeBlanc MM, Stromberg AJ. Relationships between uterine culture, cytology and pregnancy rates in a thoroughbred practice. Theriogenology 2007;68(3):395–402.
    doi: 10.1016/j.theriogenology.2007.05.050pubmed: 17583785google scholar: lookup
  31. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 2019;37(8):852–7.
    doi: 10.1038/s41587-019-0209-9pmc: PMC7015180pubmed: 31341288google scholar: lookup
  32. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 2016;13(7):581–3.
    doi: 10.1038/nmeth.3869pmc: PMC4927377pubmed: 27214047google scholar: lookup
  33. McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A. An improved greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J 2012;6(3):610–8.
    doi: 10.1038/ismej.2011.139pmc: PMC3280142pubmed: 22134646google scholar: lookup
  34. Rognes T, Flouri T, Nichols B, Quince C, Mahé F. VSEARCH: A versatile open source tool for metagenomics. PeerJ 2016;4:e2584.
    doi: 10.7717/peerj.2584pmc: PMC5075697pubmed: 27781170google scholar: lookup
  35. Janssen S, McDonald D, Gonzalez A, Navas-Molina JA, Jiang L, Xu ZZ. Phylogenetic placement of exact amplicon sequences improves associations with clinical information. mSystems 2018;3(3):e00021-18.
    doi: 10.1128/mSystems.00021-18pmc: PMC5904434pubmed: 29719869google scholar: lookup
  36. Lane D. 16S/23S rRNA sequencing. Nucleic Acids Technol Bact Syst 1991;36.
  37. Price MN, Dehal PS, Arkin AP. FastTree 2-Approximately maximum-likelihood trees for large alignments. PLoS One 2010;5(3):e9490.
    doi: 10.1371/journal.pone.0009490pmc: PMC2835736pubmed: 20224823google scholar: lookup
  38. Faith DP. Conservation evaluation and phylogenetic diversity. Biol Conserv 1992;61(1):1–10.
    doi: 10.1016/0006-3207(92)91201-3google scholar: lookup
  39. Eren MI, Chao A, Hwang WH, Colwell RK. Estimating the richness of a population when the maximum number of classes is fixed: A nonparametric solution to an archaeological problem. PLoS One 2012;7(5):e34179.
    doi: 10.1371/journal.pone.0034179pmc: PMC3362599pubmed: 22666316google scholar: lookup
  40. Kruskal WH, Wallis WA. Use of ranks in one-criterion variance analysis. J Am Stat Assoc 1952;47(260):583–621.
    doi: 10.1080/01621459.1952.10483441google scholar: lookup
  41. Lozupone C, Knight R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 2005;71(12):8228–35.
    doi: 10.1128/AEM.71.12.8228-8235.2005pmc: PMC1317376pubmed: 16332807google scholar: lookup
  42. Anderson MJ. A new method for non-parametric multivariate analysis of variance. Austral Ecol 2001;26(1):32–46.
    doi: 10.1046/j.1442-9993.2001.01070.xgoogle scholar: lookup
  43. Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci 2003;14(6):927–30.
    doi: 10.1111/j.1654-1103.2003.tb02228.xgoogle scholar: lookup
  44. Lin H, Das PS. Analysis of compositions of microbiomes with bias correction. Nat Commun 2020;11(1):3514.
    doi: 10.1038/s41467-020-17041-7pmc: PMC7360769pubmed: 32665548google scholar: lookup
  45. Barbera P, Kozlov AM, Czech L, Morel B, Darriba D, Flouri T. EPA-ng: Massively parallel evolutionary placement of genetic sequences. Syst Biol 2019;68(2):365–9.
    doi: 10.1093/sysbio/syy054pmc: PMC6368480pubmed: 30165689google scholar: lookup
  46. Parks DH, Beiko RG. Identifying biologically relevant differences between metagenomic communities. Bioinformatics 2010;26(6):715–21.
    doi: 10.1093/bioinformatics/btq041pubmed: 20130030google scholar: lookup
  47. R Core Team R. RStudio: Integrated development for R. PBC, Boston, MA: RStudio; 2023.
  48. Hadley W. ggplot2: Elegant graphics for data analysis. J Stat Softw 2009;28(1):1–25.
    doi: 10.18637/jss.v028.i01google scholar: lookup
  49. Tamhane AC, Hochberg Y, Dunnett CW. Multiple test procedures for dose finding. Biometrics 1996;52(1):21.
    doi: 10.2307/2533141pubmed: 8934584google scholar: lookup
  50. Raudvere U, Kolberg L, Kuzmin I, Arak T, Adler P, Peterson H. g:Profiler: A web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res 2019;47:W191–8.
    doi: 10.1093/nar/gkz369pmc: PMC6602461pubmed: 31066453google scholar: lookup
  51. Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523.
    doi: 10.1038/s41467-019-09234-6pmc: PMC6447622pubmed: 30944313google scholar: lookup
  52. Renner-Martin TFP, Forstenpointner G, Weissengruber GE, Eberhardt L. Gross anatomy of the female genital organs of the domestic donkey (Equus asinus Linné, 1758). Anat Histol Embryol 2009;38(2):133–8.
    doi: 10.1111/j.1439-0264.2008.00911.xpubmed: 19007353google scholar: lookup
  53. Fraga M, Perelmuter K, Delucchi L, Cidade E, Zunino P. Vaginal lactic acid bacteria in the mare: evaluation of the probiotic potential of native Lactobacillus spp. and Enterococcus spp. strains. Antonie Van Leeuwenhoek J 2008;93(1–2):71–8.
    doi: 10.1007/s10482-007-9180-4pubmed: 17588124google scholar: lookup
  54. Liu P, Lu Y, Li R, Chen X. Use of probiotic lactobacilli in the treatment of vaginal infections: In vitro and in vivo investigations. Front Cell Infect Microbiol 2023;13:1153894.
    doi: 10.3389/fcimb.2023.1153894pmc: PMC10106725pubmed: 37077531google scholar: lookup
  55. Albihn A, Båverud V, Magnusson U. Uterine microbiology and antimicrobial susceptibility in isolated bacteria from mares with fertility problems. Acta Vet Scand 2003;44(3–4):121–9.
    doi: 10.1186/1751-0147-44-121pmc: PMC1831563pubmed: 15074625google scholar: lookup
  56. Christoffersen M, Söderlind M, Rí»ùlk SR, Pedersen HG, Allen J, Krekeler N. Risk factors associated with uterine fluid after breeding caused by Streptococcus zooepidemicus. Theriogenology 2015;84(8):1283–90.
    doi: 10.1016/j.theriogenology.2015.07.007pubmed: 26300275google scholar: lookup
  57. Rasmussen CD, Haugaard MM, Petersen MR, Nielsen JM, Pedersen HG, Bojesen AM. Streptococcus equi subsp. zooepidemicus isolates from equine infectious endometritis belong to a distinct genetic group. Vet Res 2013;44(1):26.
    doi: 10.1186/1297-9716-44-26pmc: PMC3640914pubmed: 23597033google scholar: lookup
  58. Petersen MR, Skive B, Christoffersen M, Lu K, Nielsen JM, Troedsson MHT. Activation of persistent Streptococcus equi subspecies zooepidemicus in mares with subclinical endometritis. Vet Microbiol 2015;179(1–2):119–25.
    doi: 10.1016/j.vetmic.2015.06.006pubmed: 26123371google scholar: lookup
  59. Skive B, Rohde M, Molinari G, Braunstein TH, Bojesen AM. Streptococcus equi subsp. zooepidemicus invades and survives in epithelial cells. Front Cell Infect Microbiol 2017;7:465.
    doi: 10.3389/fcimb.2017.00465pmc: PMC5681531pubmed: 29164073google scholar: lookup
  60. H A Morris L, M McCue P, Aurich C. Equine endometritis: A review of challenges and new approaches. Reproduction 2020;160(5):R95–110.
    doi: 10.1530/REP-19-0478pubmed: 32805710google scholar: lookup
  61. Troedsson MHT, Woodward EM. Our current understanding of the pathophysiology of equine endometritis with an emphasis on breeding-induced endometritis. Reprod Biol 2016;16(1):8–12.
    doi: 10.1016/j.repbio.2016.01.003pubmed: 26952748google scholar: lookup
  62. Bain AM. The rôle of infection in infertility in the thoroughbred mare. Vet Rec 1966;78(5):168–73.
    doi: 10.1136/vr.78.5.168pubmed: 5948366google scholar: lookup
  63. Díaz-Bertrana ML, Deleuze S, Pitti Rios L, Yeste M, Morales Fariña I, Rivera Del Alamo MM. Microbial prevalence and antimicrobial sensitivity in equine endometritis in field conditions. Animals (Basel) 2021;11(5):1476.
    doi: 10.3390/ani11051476pmc: PMC8160901pubmed: 34065566google scholar: lookup
  64. Ravaioli V, Raffini E, Tamburini M, Galletti G, Frasnelli M. Infectious endometritis in mares: Microbiological findings in field samples. J Equine Vet Sci 2022;112:103913.
    doi: 10.1016/j.jevs.2022.103913pubmed: 35196546google scholar: lookup
  65. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome the human microbiome project consortium HHS public access. Nature 2012;486.
    pmc: PMC3564958pubmed: 22699609
  66. Lee WJ, Hase K. Gut microbiota-generated metabolites in animal health and disease. Nat Chem Biol 2014;10(6):416–24.
    doi: 10.1038/nchembio.1535pubmed: 24838170google scholar: lookup
  67. Chang PV, Hao L, Offermanns S, Medzhitov R. The microbial metabolite butyrate regulates intestinal macrophage function via histone deacetylase inhibition. Proc Natl Acad Sci U S A 2014;111(6):2247–52.
    doi: 10.1073/pnas.1322269111pmc: PMC3926023pubmed: 24390544google scholar: lookup
  68. Singh N, Thangaraju M, Prasad PD, Martin PM, Lambert NA, Boettger T. Blockade of dendritic cell development by bacterial fermentation products butyrate and propionate through a transporter (Slc5a8)-dependent inhibition of histone deacetylases. J Biol Chem 2010;285(36):27601–8.
    doi: 10.1074/jbc.M110.102947pmc: PMC2934627pubmed: 20601425google scholar: lookup
  69. Vinolo MAR, Rodrigues HG, Hatanaka E, Sato FT, Sampaio SC, Curi R. Suppressive effect of short-chain fatty acids on production of proinflammatory mediators by neutrophils. J Nutr Biochem 2011;22(9):849–55.
    doi: 10.1016/j.jnutbio.2010.07.009pubmed: 21167700google scholar: lookup
  70. Arpaia N, Campbell C, Fan X, Dikiy S, van der Veeken J, deRoos P. Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature 2013;504(7480):451–5.
    doi: 10.1038/nature12726pmc: PMC3869884pubmed: 24226773google scholar: lookup
  71. Furusawa Y, Obata Y, Fukuda S, Endo TA, Nakato G, Takahashi D. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature 2013;504(7480):446–50.
    doi: 10.1038/nature12721pubmed: 24226770google scholar: lookup
  72. Klaassen MAY, Imhann F, Collij V, Fu J, Wijmenga C, Zhernakova A. Anti-inflammatory gut microbial pathways are decreased during crohn’s disease exacerbations. J Crohns Colitis 2019;13(11):1439–49.
    doi: 10.1093/ecco-jcc/jjz077pmc: PMC7142399pubmed: 31066440google scholar: lookup
  73. Jarchum I, Pamer EG. Regulation of innate and adaptive immunity by the commensal microbiota. Curr Opin Immunol 2011;23(3):353–60.
    doi: 10.1016/j.coi.2011.03.001pmc: PMC3109238pubmed: 21466955google scholar: lookup
  74. Fernández-Montero A, Ding Y, Mani A, Casadei E, Shibasaki Y, Takizawa F. Secretory IgM (sIgM) is an ancient master regulator of microbiota homeostasis and metabolism. Dev Comp Immunol 2023;148:104948.
    doi: 10.1016/j.dci.2023.104948google scholar: lookup
  75. Johnston CJC, Smyth DJ, Dresser DW, Maizels RM. TGF-β in tolerance, development and regulation of immunity. Cell Immunol 2016;299:14–22.
    doi: 10.1016/j.cellimm.2015.10.006pmc: PMC4711336pubmed: 26617281google scholar: lookup
  76. Batlle E, Massagué J. Transforming growth factor-β signaling in immunity and cancer. Immunity 2019;50(4):924–40.
    doi: 10.1016/j.immuni.2019.03.024pmc: PMC7507121pubmed: 30995507google scholar: lookup
  77. Li C, Hancock MA, Sehgal P, Zhou S, Reinhardt DP, Philip A. Soluble CD109 binds TGF-β and antagonizes TGF-β signalling and responses. Biochem J 2016;473(5):537–47.
    doi: 10.1042/BJ20141488pubmed: 26621871google scholar: lookup
  78. Khan FA, Chenier TS, Foster RA, Hewson J, Scholtz EL. Endometrial nitric oxide synthase activity in mares susceptible or resistant to persistent breeding-induced endometritis and the effect of a specific iNOS inhibitor in vitro. Reprod Domest Anim 2018;53(3):718–24.
    doi: 10.1111/rda.13162pubmed: 29537110google scholar: lookup

Citations

This article has been cited 1 times.
  1. Zhao Y, Liu Y, Tao J, Cao J, Lin Y, He Q, Fang X, Yun S, Du M, Su S, Bao T, Bai D, Zhang X, Dugarjaviin M. Isolation, identification and comparative genomic analysis of Lactobacillus salivarius from Mongolian horse vagina. Front Microbiol 2025;16:1635639.
    doi: 10.3389/fmicb.2025.1635639pubmed: 40822386google scholar: lookup
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