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Sola-Leyva A, Andrés-León E, Terrón-Camero L, Pérez-Prieto I, Clavero A, Gonzalvo M, Morales-Rincón N, Castilla-Alcalá J, Fontes J, Salas E, Ruiz-Duran S, Velthut-Meikas A, Salumets A, Altmäe S. P-431 Functionally active microbiota in the receptive-phase endometria in women with recurrent implantation failure. Hum Reprod 2022. [DOI: 10.1093/humrep/deac105.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Study question
Does the functionally active microbial composition at the receptive phase endometria differ between women with recurrent implantation failure (RIF) and healthy controls?
Summary answer
Women with RIF have different functionally active microbiota in the receptive-phase endometria that are involved in distinct metabolical pathways when compared to healthy women.
What is known already
Recurrent implantation failure (RIF) is a common and burdening diagnosis in infertility treatment. Despite scientific advances in the field, the cause of RIF remains unclear and the treatment options ambiguous. Microorganisms have important role in human physiology and pathophysiology, and their potential involvement in endometrial functions and health are gaining support. Our previous work of microbiota mapping of healthy endometrium identified over 5000 functionally active microorganisms (bacteria, viruses, fungi, archaea) that participate in key metabolic pathways for embryo implantation. In the present work we focus on microbiota mapping in RIF patients, where endometrial dysfunction is suspected.
Study design, size, duration
A case-control age-match study of 20 RIF and 20 healthy controls was performed. Endometrial samples were obtained at the mid-secretory phase (LH + 7/8) using Pipelle curette.
Participants/materials, setting, methods
Total RNA sequencing (RNA-seq) was performed. R package MetagenomeSeq was used for metataxonomic microorganismal analyses and HUMAnN2 algorithm was used for functional metagenome assessment. The microbial maps were created using Kraken metagenomic sequence classification. With this approach we were able to identify and map the ‘active’ microorganisms in samples.
Main results and the role of chance
We identified a total of 4175 microorganisms in the human endometrial samples including different bacteria, fungi, viruses, and archaea. At the taxonomic level, RIF patients demonstrated a total of 180 microorganism with differential abundance when compared to controls (FDR<0.05), where the biggest difference was in Streptomyces, Xanthomonas, Fusarium and Burkholderia that were significantly less detected in RIF. The metabolical functions analysis of the microbes differed significantly between the two groups, with a total of 150 different pathways, where fatty acid biosynthesis, mucin glycosylation, folate pathway and serotonin pathways were influenced in RIF.
Limitations, reasons for caution
Poly A enrichment could avoid the detection of some microorganism. However, the resolution power in microbial identification was comparable to previous metatranscriptomics published studies.
Wider implications of the findings
Our study findings are first to demonstrate that alive microbes are involved in the uterine pathology as is RIF, where different metabolic pathways could be dysregulated. This knowledge could help to develop pre-/probiotic strategies to modulate uterine environment for improving endometrial functions in RIF.
Trial registration number
not applicable
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Affiliation(s)
- A Sola-Leyva
- University of Granada- Faculty of Sciences, Biochemistry and Molecular Bology I , Granada, Spain
- Instituto Investigación Biosanitaria Ibs.GRANADA, Tec-14 , Granada, Spain
| | - E Andrés-León
- Instituto de Parasitología y Biomedicina “López-Neyra”- CSIC IPBLN-CSIC-, Bioinformatic Unit , Granada, Spain
| | - L Terrón-Camero
- Instituto de Parasitología y Biomedicina “López-Neyra”- CSIC IPBLN-CSIC-, Bioinformatic Unit , Granada, Spain
| | - I Pérez-Prieto
- University of Granada- Faculty of Sciences, Biochemistry and Molecular Bology I , Granada, Spain
- Instituto Investigación Biosanitaria Ibs.GRANADA, Tec-14 , Granada, Spain
| | - A Clavero
- Instituto Investigación Biosanitaria Ibs.GRANADA, Tec-14 , Granada, Spain
- University Hospital Virgen de las Nieves, Reproduction Unit , Granada, Spain
| | - M.C Gonzalvo
- Instituto Investigación Biosanitaria Ibs.GRANADA, Tec-14 , Granada, Spain
- University Hospital Virgen de las Nieves, Reproduction Unit , Granada, Spain
| | - N Morales-Rincón
- Instituto Investigación Biosanitaria Ibs.GRANADA, Tec-14 , Granada, Spain
- University Hospital Virgen de las Nieves, Reproduction Unit , Granada, Spain
| | - J.A Castilla-Alcalá
- Instituto Investigación Biosanitaria Ibs.GRANADA, Tec-14 , Granada, Spain
- University Hospital Virgen de las Nieves, Reproduction Unit , Granada, Spain
| | - J Fontes
- Instituto Investigación Biosanitaria Ibs.GRANADA, Tec-14 , Granada, Spain
- University Hospital Virgen de las Nieves, Reproduction Unit , Granada, Spain
| | - E Salas
- University of Granada- Faculty of Sciences, Biochemistry and Molecular Bology I , Granada, Spain
| | - S Ruiz-Duran
- University Hospital Virgen de las Nieves, Reproduction Unit , Granada, Spain
| | - A Velthut-Meikas
- Tallinn University of Technology, Department of Chemistry and Biotechnology , Tallinn, Estonia
| | - A Salumets
- Karolinska Institutet, Division of Obstetrics and Gynaecology- CLINTEC , Stockholm, Sweden
- Competence Centre on Health Technologies, ccth , Tartu, Estonia
| | - S Altmäe
- University of Granada- Faculty of Sciences, Biochemistry and Molecular Bology I , Granada, Spain
- Karolinska Institutet, Division of Obstetrics and Gynaecology- CLINTEC , Stockholm, Sweden
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