Ontology highlight
ABSTRACT:
PROVIDER: PRJNA845012 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19534800_1.fastq.gz | Fastqsanger.gz | |||
| SRR19534800_2.fastq.gz | Fastqsanger.gz | |||
| SRR19534900_1.fastq.gz | Fastqsanger.gz | |||
| SRR19534900_2.fastq.gz | Fastqsanger.gz | |||
| SRR19534801_1.fastq.gz | Fastqsanger.gz |
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Project description:Predicting preterm birth using machine learning techniques in oral microbiome
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Project description:Spontaneous preterm birth (sPTB) is a leading cause of maternal and neonatal morbidity and mortality, yet its prevention and early risk stratification are limited. Previous investigations have suggested that vaginal microbes and metabolites may be implicated in sPTB. Here we performed untargeted metabolomics on 232 second-trimester vaginal samples, 80 from pregnancies ending preterm. We find multiple associations between vaginal metabolites and subsequent preterm birth, and propose that several of these metabolites, including diethanolamine and ethyl glucoside, are exogenous. We observe associations between the metabolome and microbiome profiles previously obtained using 16S ribosomal RNA amplicon sequencing, including correlations between bacteria considered suboptimal, such as Gardnerella vaginalis, and metabolites enriched in term pregnancies, such as tyramine. We investigate these associations using metabolic models. We use machine learning models to predict sPTB risk from metabolite levels, weeks to months before birth, with good accuracy (area under receiver operating characteristic curve of 0.78). These models, which we validate using two external cohorts, are more accurate than microbiome-based and maternal covariates-based models (area under receiver operating characteristic curve of 0.55-0.59). Our results demonstrate the potential of vaginal metabolites as early biomarkers of sPTB and highlight exogenous exposures as potential risk factors for prematurity.
2022-11-21 | MTBLS702 | MetaboLights
Project description:<p>The pregnancy vaginal microbiome contributes to risk of preterm birth, the primary cause of death in children under 5 years of age. Here we describe direct on-swab metabolic profiling by Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) for sample preparation-free characterisation of the cervicovaginal metabolome in two independent pregnancy cohorts (VMET, n = 160; 455 swabs; VMET II, n = 205; 573 swabs). By integrating metataxonomics and immune profiling data from matched samples, we show that specific metabolome signatures can be used to robustly predict simultaneously both the composition of the vaginal microbiome and host inflammatory status. In these patients, vaginal microbiota instability and innate immune activation, as predicted using DESI-MS, associated with preterm birth, including in women receiving cervical cerclage for preterm birth prevention. These findings highlight direct on-swab metabolic profiling by DESI-MS as an innovative approach for preterm birth risk stratification through rapid assessment of vaginal microbiota-host dynamics.</p><p><br></p><p><strong>Linked cross omic data sets:</strong></p><p>Meta-taxonomics data associated with this study are available in the European Nucleotide Archive (ENA): accession number <a href='https://www.ebi.ac.uk/ena/browser/view/PRJEB11895' rel='noopener noreferrer' target='_blank'>PRJEB11895</a>, <a href='https://www.ebi.ac.uk/ena/browser/view/PRJEB12577' rel='noopener noreferrer' target='_blank'>PRJEB12577</a> and <a href='https://www.ebi.ac.uk/ena/browser/view/PRJEB41427' rel='noopener noreferrer' target='_blank'>PRJEB41427</a>.</p>
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Project description:This study aims to investigate the alterations in cervical remodeling and the underlying molecular mechanisms in a lipopolysaccharide (LPS)-induced rat model of preterm birth through RNA sequencing. The results demonstrate that LPS triggers preterm birth by activating inflammatory and bradykinin pathways, disrupting extracellular matrix stability, and promoting cervical insufficiency.
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Project description:The interaction between the vaginal microbiome, cervical length and vaginal progesterone treatment for preterm birth risk
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Project description:Cervical dysfunction, a major contributor to preterm labor and neonatal mortality, remains poorly understood due to the absence of physiologically relevant human models. Here, we show that a microfluidic human Endocervix Chip lined by primary endocervical epithelial interfaced with stromal cells and cultured under pregnancy-like hormonal conditions recapitulates key aspects of the biology of the endocervix, including formation of a mucus plug-like structure with antimicrobial properties. Culturing a dysbiotic cervico-vaginal microbiome on-chip increased secretion of pro-inflammatory cytokines observed in patients with preterm labor and enhanced production of matrix metalloproteinases (MMPs) that degrade stromal extracellular matrix (ECM). Perfusion with inflammatory cytokines at clinically relevant concentrations altered cervical mucus composition, upregulated prostaglandin-endoperoxide synthase 2 expression, increased MMP secretion, and reduced collagen production, which together drive dissolution of the stromal ECM and promote cervical ripening. Addition of circulating peripheral blood mononuclear cells (PBMCs) amplified these effects. Administration of a clinically approved drug for prevention of preterm labor that the FDA recently deemed ineffective was also found to be inactive in the chip, while an approved therapeutic antagonist of the IL-1 receptor successfully protected against cervical dysfunction in this model. These findings demonstrate that IL-1 acts directly on human cervical tissues to promote changes associated with initiation of labor and that primary human endocervix chips may represent a useful preclinical model for studies on cervical dysfunction associated with preterm birth.
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