Mapping the entire functionally active endometrial microbiota
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".