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Enregistrement W3131592236 · doi:10.1093/humrep/deaa372

Mapping the entire functionally active endometrial microbiota

2020· article· en· W3131592236 sur OpenAlex

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Notice bibliographique

RevueHuman Reproduction · 2020
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueReproductive System and Pregnancy
Établissements canadiensChildren's Hospital of Eastern Ontario
Organismes subventionnairesMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaEuropean Regional Development FundUniversidad de GranadaMinisterio de Ciencia, Innovación y Universidades
Mots-clésBiologyEndometriumMenstrual cycleGeneComputational biologyMicroorganismGeneticsPhysiologyBioinformaticsBacteriaEndocrinology

Résumé

récupéré en direct d'OpenAlex

STUDY QUESTION: Does endometrium harbour functionally active microorganisms and whether the microbial composition differs between proliferative and mid-secretory phases? SUMMARY ANSWER: Endometrium harbours functionally alive microorganisms including bacteria, viruses, archaea and fungi whose composition and metabolic functions change along the menstrual cycle. WHAT IS KNOWN ALREADY: Resident microbes in the endometrium have been detected, where microbial dysfunction has been associated with reproductive health and disease. Nevertheless, the core microorganismal composition in healthy endometrium is not determined and whether the identified bacterial DNA sequences refer to alive/functionally active microbes is not clear. Furthermore, whether there are cyclical changes in the microbial composition remains an open issue. STUDY DESIGN, SIZE, DURATION: RNA sequencing (RNAseq) data from 14 endometrial paired samples from healthy women, 7 samples from the mid-secretory phase and 7 samples from the consecutive proliferative phase were analysed for the microbial RNA sequences. PARTICIPANTS/MATERIALS, SETTING, METHODS: The raw RNAseq data were converted into FASTQ format using SRA Toolkit. The unmapped reads to human sequences were aligned to the reference database Kraken2 and visualised with Krona software. Menstrual phase taxonomic differences were performed by R package metagenomeSeq. The functional analysis of endometrial microbiota was obtained with HUMANn2 and the comparison between menstrual phases was conducted by one-way ANOVA. Human RNAseq analysis was performed using miARma-Seq and the functional enrichment analysis was carried out using gene set enrichment analysis (GSEA; HumanCyc). The integration of metabolic pathways between host and microbes was investigated. The developed method of active microbiota mapping was validated in independent sample set. MAIN RESULTS AND THE ROLE OF CHANCE: With the novel metatranscriptomic approach, we mapped the entire alive microbiota composing of >5300 microorganisms within the endometrium of healthy women. Microbes such as bacteria, fungi, viruses and archaea were identified. The validation of three independent endometrial samples from different ethnicity confirmed the findings. Significant differences in the microbial abundances in the mid-secretory vs. proliferative phases were detected with possible metabolic activity in the host-microbiota crosstalk in receptive phase endometrium, specifically in the prostanoid biosynthesis pathway and L-tryptophan metabolism. LARGE SCALE DATA: The raw RNAseq data used in the current study are available at GEO GSE86491 and at BioProject PRJNA379542. LIMITATIONS, REASONS FOR CAUTION: These pioneering results should be confirmed in a bigger sample size. WIDER IMPLICATIONS OF THE FINDINGS: Our study confirms the presence of active microbes, bacteria, fungi, viruses and archaea in the healthy human endometrium with implications in receptive phase endometrial functions, meaning that microbial dysfunction could impair the metabolic pathways important for endometrial receptivity. The results of this study contribute to the better understanding of endometrial microbiota composition in healthy women and its possible role in endometrial functions. In addition, our novel methodological pipeline for analysing alive microbes with transcriptional and metabolic activities could serve to inspire new analysis approaches in reproductive medicine. STUDY FUNDING/COMPETING INTERESTS: This work is supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) and European Regional Development Fund (FEDER): grants RYC-2016-21199 and ENDORE SAF2017-87526-R; FEDER/Junta de Andalucía-Consejería de Economía y Conocimiento: MENDO (B-CTS-500-UGR18) and by the University of Granada Plan Propio de Investigación 2016 - Excellence actions: Unit of Excellence on Exercise and Health (UCEES) (SOMM17/6107/UGR). A.S.-L. and N.M.M. are funded by the Spanish Ministry of Science, Innovation and Universities (PRE2018-0854409 and FPU19/01638). S.A. has received honoraria for lectures from Merck. The funder had no role in this study.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,614
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,065
Tête enseignante GPT0,249
Écart entre enseignants0,184 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle