Microbial signatures and continuum in endometrial cancer and benign patients.

BACKGROUND: Endometrial cancer is a multifactorial disease with inflammatory, metabolic and potentially microbial cues involved in disease pathogenesis. The endometrial cancer microbiome has been poorly characterised so far and studies have often overestimated bacterial biomass due to lack of integration of appropriate contamination controls. There is also a scarcity of evidence on the functionality of microbial microenvironments in endometrial cancer. This work addresses that knowledge gap by interrogating the genuine, contamination-free microbial signatures in the female genital tract and rectum of women with endometrial cancer and the mechanistic role of microbiome on carcinogenic processes. RESULTS: Here we sampled different regions of the reproductive tract (vagina, cervix, endometrium, fallopian tubes and ovaries) and rectum of 61 patients (37 endometrial cancer; 24 benign controls). We performed 16S rRNA gene sequencing of the V1-V2 hypervariable regions and qPCR of the 16S rRNA gene to qualitatively and quantitatively assess microbial communities and used 3D benign and endometrial cancer organoids to evaluate the effect of microbial products of L. crispatus, which was found depleted in endometrial cancer patients following primary analysis, on endometrial cell proliferation and inflammation. We found that the upper genital tract of a subset of women with and without endometrial cancer harbour microbiota quantitatively and compositionally distinguishable from background contaminants. Endometrial cancer was associated with reduced cervicovaginal and rectal bacterial load together with depletion of Lactobacillus species relative abundance, including L. crispatus, increased bacterial diversity and enrichment of Porphyromonas, Prevotella, Peptoniphilus and Anaerococcus in the lower genital tract and endometrium. Treatment of benign and malignant endometrial organoids with L. crispatus conditioned media exerted an anti-proliferative effect at high concentrations but had minimal impact on cytokine and chemokine profiles. CONCLUSIONS: Our findings provide evidence that the upper female reproductive tract of some women contains detectable levels of bacteria, the composition of which is associated with endometrial cancer. Whether this is a cause or consequence of cancer pathophysiology and what is the functional significance of this finding remain to be elucidated to guide future screening tools and microbiome-based therapeutics. Video Abstract.

The endometrial microbiota and early pregnancy loss.

The human endometrium is a dynamic entity that plays a pivotal role in mediating the complex interplay between the mother and developing embryo. Endometrial disruption can lead to pregnancy loss, impacting both maternal physical and psychological health. Recent research suggests that the endometrial microbiota may play a role in this, although the exact mechanisms are still being explored, aided by recent technological advancements and our growing understanding of host immune responses. Suboptimal or dysbiotic vaginal microbiota, characterized by increased microbial diversity and reduced Lactobacillus dominance, has been associated with various adverse reproductive events, including miscarriage. However, the mechanisms linking the lower reproductive tract microbiota with pregnancy loss remain unclear. Recent observational studies implicate a potential microbial continuum between the vaginal and endometrial niche in patients with pregnancy loss; however, transcervical sampling of the low biomass endometrium is highly prone to cross-contamination, which is often not controlled for. In this review, we explore emerging evidence supporting the theory that a dysbiotic endometrial microbiota may modulate key inflammatory pathways required for successful embryo implantation and pregnancy development. We also highlight that a greater understanding of the endometrial microbiota, its relationship with the local endometrial microenvironment, and potential interventions remain a focus for future research.

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.

Meta-analysis reveals the vaginal microbiome is a better predictor of earlier than later preterm birth.

BACKGROUND: High-throughput sequencing measurements of the vaginal microbiome have yielded intriguing potential relationships between the vaginal microbiome and preterm birth (PTB; live birth prior to 37 weeks of gestation). However, results across studies have been inconsistent. RESULTS: Here, we perform an integrated analysis of previously published datasets from 12 cohorts of pregnant women whose vaginal microbiomes were measured by 16S rRNA gene sequencing. Of 2039 women included in our analysis, 586 went on to deliver prematurely. Substantial variation between these datasets existed in their definition of preterm birth, characteristics of the study populations, and sequencing methodology. Nevertheless, a small group of taxa comprised a vast majority of the measured microbiome in all cohorts. We trained machine learning (ML) models to predict PTB from the composition of the vaginal microbiome, finding low to modest predictive accuracy (0.28-0.79). Predictive accuracy was typically lower when ML models trained in one dataset predicted PTB in another dataset. Earlier preterm birth (< 32 weeks, < 34 weeks) was more predictable from the vaginal microbiome than late preterm birth (34-37 weeks), both within and across datasets. Integrated differential abundance analysis revealed a highly significant negative association between L. crispatus and PTB that was consistent across almost all studies. The presence of the majority (18 out of 25) of genera was associated with a higher risk of PTB, with L. iners, Prevotella, and Gardnerella showing particularly consistent and significant associations. Some example discrepancies between studies could be attributed to specific methodological differences but not most study-to-study variations in the relationship between the vaginal microbiome and preterm birth. CONCLUSIONS: We believe future studies of the vaginal microbiome and PTB will benefit from a focus on earlier preterm births and improved reporting of specific patient metadata shown to influence the vaginal microbiome and/or birth outcomes.

Prostaglandin F2α requires activation of calcium-dependent signalling to trigger inflammation in human myometrium.

Introduction: Preterm birth is one of the major causes of neonatal morbidity and mortality across the world. Both term and preterm labour are preceded by inflammatory activation in uterine tissues. This includes increased leukocyte infiltration, and subsequent increase in chemokine and cytokine levels, activation of pro-inflammatory transcription factors as NF-κB and increased prostaglandin synthesis. Prostaglandin F2α (PGF2α) is one of the myometrial activators and stimulators. Methods: Here we investigated the role of PGF2α in pro-inflammatory signalling pathways in human myometrial cells isolated from term non-labouring uterine tissue. Primary myometrial cells were treated with G protein inhibitors, calcium chelators and/or PGF2α. Nuclear extracts were analysed by TranSignal cAMP/Calcium Protein/DNA Array. Whole cell protein lysates were analysed by Western blotting. mRNA levels of target genes were analysed by RT-PCR. Results: The results show that PGF2α increases inflammation in myometrial cells through increased activation of NF-κB and MAP kinases and increased expression of COX-2. PGF2α was found to activate several calcium/cAMP-dependent transcription factors, such as CREB and C/EBP-ß. mRNA levels of NF-κB-regulated cytokines and chemokines were also elevated with PGF2α stimulation. We have shown that the increase in PGF2α-mediated COX-2 expression in myometrial cells requires coupling of the FP receptor to both Gαq and Gαi proteins. Additionally, PGF2α-induced calcium response was also mediated through Gαq and Gαi coupling. Discussion: In summary, our findings suggest that PGF2α-induced inflammation in myometrial cells involves activation of several transcription factors - NF-κB, MAP kinases, CREB and C/EBP-ß. Our results indicate that the FP receptor signals via Gαq and Gαi coupling in myometrium. This work provides insight into PGF2α pro-inflammatory signalling in term myometrium prior to the onset of labour and suggests that PGF2α signalling pathways could be a potential target for management of preterm labour.

MetChem: a new pipeline to explore structural similarity across metabolite modules.

Summary: Computational analysis and interpretation of metabolomic profiling data remains a major challenge in translational research. Exploring metabolic biomarkers and dysregulated metabolic pathways associated with a patient phenotype could offer new opportunities for targeted therapeutic intervention. Metabolite clustering based on structural similarity has the potential to uncover common underpinnings of biological processes. To address this need, we have developed the MetChem package. MetChem is a quick and simple tool that allows to classify metabolites in structurally related modules, thus revealing their functional information. Availabilityand implementation: MetChem is freely available from the R archive CRAN (http://cran.r-project.org). The software is distributed under the GNU General Public License (version 3 or later).

Comparative analysis of vaginal microbiota sampling using menstrual cups and high vaginal swabs in pregnant women living with HIV-1 infection.

Background: Menstrual cups (MCs) are increasingly used to collect cervicovaginal secretions to characterise vaginal mucosal immunology, in conjunction with high vaginal swabs (HVS) for metataxonomics, particularly in HIV transmission studies. We hypothesised that both methods of collecting bacterial biomass are equivalent for 16S rRNA gene sequencing. Material and Methods: Cervicovaginal fluid (CVF) samples from 16 pregnant women with HIV-1 (PWWH) were included to represent the major vaginal bacterial community state types (CST I-V). Women underwent sampling during the second trimester by liquid amies HVS followed by a MC (Soft disc™) and samples were stored at -80°C. Bacterial cell pellets obtained from swab elution and MC (500 µL, 1 in 10 dilution) were resuspended in 120 µL PBS for DNA extraction. Bacterial 16S rRNA gene sequencing was performed using V1-V2 primers and were analysed using MOTHUR. Paired total DNA, bacterial load, amplicon read counts, diversity matrices and bacterial taxa were compared by sampling method using MicrobiomeAnalyst, SPSS and R. Results: The total DNA eluted from one aliquot of diluted CVF from an MC was similar to that of a HVS (993ng and 609ng, p=0.18); the mean bacterial loads were also comparable for both methods (MC: 8.0 log10 16S rRNA gene copies versus HVS: 7.9 log10 16S rRNA gene copies, p=0.27). The mean number of sequence reads generated from MC samples was lower than from HVS (MC: 12730; HVS:14830, p=0.05). The α-diversity metrices were similar for both techniques; MC Species Observed: 41 (range 12-96) versus HVS: 47 (range 16-96), p=0.15; MC Inverse Simpson Index: 1.98 (range 1.0-4.0) versus HVS: 0.48 (range 1.0-4.4), p=0.22). The three most abundant species observed were: Lactobacillus iners, Lactobacillus crispatus and Gardnerella vaginalis. Hierarchical clustering of relative abundance data showed that samples obtained using different techniques in an individual clustered in the same CST group. Conclusion: These data demonstrate that despite sampling slightly different areas of the lower genital tract, there was no difference in bacterial load or composition between methods. Both are suitable for characterisation of vaginal microbiota in PWWH. The MC offers advantages, including a higher volume of sample available for DNA extraction and complimentary assays.

Microbiome Preterm Birth DREAM Challenge: Crowdsourcing Machine Learning Approaches to Advance Preterm Birth Research.

Globally, every year about 11% of infants are born preterm, defined as a birth prior to 37 weeks of gestation, with significant and lingering health consequences. Multiple studies have related the vaginal microbiome to preterm birth. We present a crowdsourcing approach to predict: (a) preterm or (b) early preterm birth from 9 publicly available vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from raw sequences via an open-source tool, MaLiAmPi. We validated the crowdsourced models on novel datasets representing 331 samples from 148 pregnant individuals. From 318 DREAM challenge participants we received 148 and 121 submissions for our two separate prediction sub-challenges with top-ranking submissions achieving bootstrapped AUROC scores of 0.69 and 0.87, respectively. Alpha diversity, VALENCIA community state types, and composition (via phylotype relative abundance) were important features in the top performing models, most of which were tree based methods. This work serves as the foundation for subsequent efforts to translate predictive tests into clinical practice, and to better understand and prevent preterm birth.

Moving beyond DNA: towards functional analysis of the vaginal microbiome by non-sequencing-based methods.

Over the last two decades, sequencing-based methods have revolutionised our understanding of niche-specific microbial complexity. In the lower female reproductive tract, these approaches have enabled identification of bacterial compositional structures associated with health and disease. Application of metagenomics and metatranscriptomics strategies have provided insight into the putative function of these communities but it is increasingly clear that direct measures of microbial and host cell function are required to understand the contribution of microbe-host interactions to pathophysiology. Here we explore and discuss current methods and approaches, many of which rely upon mass-spectrometry, being used to capture functional insight into the vaginal mucosal interface. In addition to improving mechanistic understanding, these methods offer innovative solutions for the development of diagnostic and therapeutic strategies designed to improve women's health.

VMAP: Vaginal Microbiome Atlas During Pregnancy.

The vaginal microbiome has been shown to be associated with pregnancy outcomes including preterm birth (PTB) risk. Here we present VMAP: Vaginal Microbiome Atlas during Pregnancy (http://vmapapp.org), an application to visualize features of 3,909 vaginal microbiome samples of 1,416 pregnant individuals from 11 studies, aggregated from raw public and newly generated sequences via an open-source tool, MaLiAmPi. Our visualization tool (http://vmapapp.org) includes microbial features such as various measures of diversity, VALENCIA community state types (CST), and composition (via phylotypes and taxonomy). This work serves as a resource for the research community to further analyze and visualize vaginal microbiome data in order to better understand both healthy term pregnancies and those associated with adverse outcomes.

15-Deoxy-Delta-12,14-prostaglandin J2 modulates pro-labour and pro-inflammatory responses in human myocytes, vaginal and amnion epithelial cells.

Background: Prematurity is the leading cause of childhood death under the age of five. The aetiology of preterm birth is multifactorial; however, inflammation and infection are the most common causal factors, supporting a potential role for immunomodulation as a therapeutic strategy. 15-Deoxy-Delta-12,14-prostaglandin J2 (15dPGJ2) is an anti-inflammatory prostaglandin and has been shown to delay lipopolysaccharide (LPS) induced preterm labour in mice and improve pup survival. This study explores the immunomodulatory effect of 15dPGJ2 on the transcription factors NF-κB and AP-1, pro-inflammatory cytokines, and contraction associated proteins in human cultured myocytes, vaginal epithelial cell line (VECs) and primary amnion epithelial cells (AECs). Methods: Cells were pre-incubated with 32µM of 15dPGJ2 and stimulated with 1ng/mL of IL-1ß as an in vitro model of inflammation. Western immunoblotting was used to detect phosphorylated p-65 and phosphorylated c-Jun as markers of NF-κB and AP-1 activation, respectively. mRNA expression of the pro-inflammatory cytokines IL-6, IL-8, and TNF-α was examined, and protein expression of COX-2 and PGE2 were detected by western immunoblotting and ELISA respectively. Myometrial contractility was examined ex-vivo using a myograph. Results: 15dPGJ2 inhibited IL-1ß-induced activation of NF-κB and AP-1, and expression of IL-6, IL-8, TNF-α, COX-2 and PGE2 in myocytes, with no effect on myometrial contractility or cell viability. Despite inhibiting IL-1ß-induced activation of NF-κB, expression of IL-6, TNF-α, and COX-2, 15dPGJ2 led to activation of AP-1, increased production of PGE2 and increased cell death in VECs and AECs. Conclusion: We conclude that 15dPGJ2 has differential effects on inflammatory modulation depending on cell type and is therefore unlikely to be a useful therapeutic agent for the prevention of preterm birth.

N-glycosylation of cervicovaginal fluid reflects microbial community, immune activity, and pregnancy status.

Human cervicovaginal fluid (CVF) is a complex, functionally important and glycan rich biological fluid, fundamental in mediating physiological events associated with reproductive health. Using a comprehensive glycomic strategy we reveal an extremely rich and complex N-glycome in CVF of pregnant and non-pregnant women, abundant in paucimannose and high mannose glycans, complex glycans with 2-4 N-Acetyllactosamine (LacNAc) antennae, and Poly-LacNAc glycans decorated with fucosylation and sialylation. N-glycosylation profiles were observed to differ in relation to pregnancy status, microbial composition, immune activation, and pregnancy outcome. Compared to CVF from women experiencing term birth, CVF from women who subsequently experienced preterm birth showed lower sialylation, which correlated to the presence of a diverse microbiome, and higher fucosylation, which correlated positively to pro-inflammatory cytokine concentration. This study is the first step towards better understanding the role of cervicovaginal glycans in reproductive health, their contribution to the mechanism of microbial driven preterm birth, and their potential for preventative therapy.

Functional rewiring of G protein-coupled receptor signaling in human labor.

Current strategies to manage preterm labor center around inhibition of uterine myometrial contractions, yet do not improve neonatal outcomes as they do not address activation of inflammation. Here, we identify that during human labor, activated oxytocin receptor (OTR) reprograms the prostaglandin E2 receptor, EP2, in the pregnant myometrium to suppress relaxatory/Gαs-cAMP signaling and promote pro-labor/inflammatory responses via altered coupling of EP2 from Gαq/11 to Gαi/o. The ability of EP2 to signal via Gαi/o is recapitulated with in vitro OT and only following OTR activation, suggesting direct EP2-OTR crosstalk. Super-resolution imaging with computational modeling reveals OT-dependent reorganization of EP2-OTR complexes to favor conformations for Gαi over Gαs activation. A selective EP2 ligand, PGN9856i, activates the relaxatory/Gαs-cAMP pathway but not the pro-labor/inflammatory responses in term-pregnant myometrium, even following OT. Our study reveals a mechanism, and provides a potential therapeutic solution, whereby EP2-OTR functional associations could be exploited to delay preterm labor.

Microbial-driven preterm labour involves crosstalk between the innate and adaptive immune response.

There has been a surge in studies implicating a role of vaginal microbiota in spontaneous preterm birth (sPTB), but most are associative without mechanistic insight. Here we show a comprehensive approach to understand the causative factors of preterm birth, based on the integration of longitudinal vaginal microbiota and cervicovaginal fluid (CVF) immunophenotype data collected from 133 women at high-risk of sPTB. We show that vaginal depletion of Lactobacillus species and high bacterial diversity leads to increased mannose binding lectin (MBL), IgM, IgG, C3b, C5, IL-8, IL-6 and IL-1ß and to increased risk of sPTB. Cervical shortening, which often precedes preterm birth, is associated with Lactobacillus iners and elevated levels of IgM, C3b, C5, C5a and IL-6. These data demonstrate a role for the complement system in microbial-driven sPTB and provide a scientific rationale for the development of live biotherapeutics and complement therapeutics to prevent sPTB.

Chromosomally normal miscarriage is associated with vaginal dysbiosis and local inflammation.

BACKGROUND: Emerging evidence supports an association between vaginal microbiota composition and risk of miscarriage; however, the underlying mechanisms are poorly understood. We aim to investigate the vaginal microbial composition and the local immune response in chromosomally normal and abnormal miscarriages and compare this to uncomplicated pregnancies delivering at term. METHODS: We used 16S rRNA gene based metataxonomics to interrogate the vaginal microbiota in a cohort of 167 women, 93 miscarriages (54 euploid and 39 aneuploid using molecular cytogenetics) and 74 women who delivered at term and correlate this with the aneuploidy status of the miscarriages. We also measured the concentrations of IL-2, IL-4, IL-6, IL-8, TNF-α, IFN-γ, IL-1ß, IL-18 and IL-10 in cervical vaginal fluid. RESULTS: We show that euploid miscarriage is associated with a significantly higher prevalence of Lactobacillus spp. deplete vaginal microbial communities compared to aneuploid miscarriage (P = 0.01). Integration of matched cervicovaginal fluid immune-profiles showed that Lactobacillus spp. depleted vaginal microbiota associated with pro-inflammatory cytokine levels most strongly in euploid miscarriage compared to viable term pregnancy (IL-1ß; P < 0.001, IL-8; P = 0.01, IL-6; P < 0.001). CONCLUSIONS: Our data suggest the vaginal microbiota plays an important aetiological role in euploid miscarriage and may represent a target to modify risk of pregnancy loss.

Vaginal Microbiota, Genital Inflammation and Extracellular Matrix Remodelling Collagenase: MMP-9 in Pregnant Women With HIV, a Potential Preterm Birth Mechanism Warranting Further Exploration.

Background: Pregnant women living with HIV infection (PWLWH) have elevated rates of preterm birth (PTB) in which HIV and cART are implicated. PWLWH also have a high prevalence of adverse vaginal microbiota, which associate with genital tract inflammation. The mechanism underlying PTB in PWLWH is unknown. We present the first data in PWLWH on genital-tract matrix-metalloproteinase-9(MMP-9), an important collagenase implicated in labour onset, and tissue inhibitor of metalloproteinases-1(TIMP-1) and explore correlations with local inflammation and vaginal bacteria. Material and Methods: Cervical vaginal fluid (CVF) collected by a soft cup and high vaginal swabs (HVS) were obtained from PWLWH and HIV uninfected pregnant women (HUPW) at three antenatal time points. Maternal characteristics, combination antiretroviral therapy (cART) exposure, and pregnancy outcome were recorded. Concentrations of MMP-9, TIMP-1 and ten cytokines were measured by immunoassays. Vaginal microbiota composition was determined through 16S rRNA amplicon sequencing. MMP-9, TIMP-1 and cytokine concentrations were compared by HIV status, cART, and prematurity and in PWLWH correlations with polymorphonuclear leucocytes, cytokines and bacterial genera were explored. Results: CVF was available for 50 PWLWH (108 samples) and 12 HUPW (20 samples) between gestation weeks 14-38. Thirty-six PWLWH conceived on cART and 14 initiated post-conception. There were five and one PTB outcomes in PWLWH and HUPW respectively. PWLWH had higher mean CVF concentrations of MMP-9 (p<0.001) and TIMP-1 (p=0.035) in the second trimester compared with HUPW with a similar trend in the third trimester. PWLWH also had higher CVF values of cytokines: IL-1ß, IL-8, IL-12 and TNF-α in both trimesters compared to HUPW (p ≤ 0.003). In PWLWH, MMP-9 positively correlated with TIMP-1 (r=0.31, p=0.002) and CVF polymorphonuclear leucocytes (r=0.57, p=0.02). Correlations were observed between MMP-9 and three cytokines: IL-1ß (r=0.61), IL-8 (r=0.57) and TNF-α (r=0.64), p<0.001, similarly for TIMP-1. Abundance of anaerobic pathobionts correlated with MMP-9: Gardnerella (r=0.44, p<0.001), Atopobium (r=0.33, p=0.005), and Prevotella genera (r=0.39, p<0.001). Conversely proportion of Lactobacillus genera negatively correlated with MMP-9 (rho=-0.46, p<0.001). MMP-9/TIMP-1 ratio increased with gestational age at sampling in PWLWH, but this was no longer significant after adjusting for confounders and no difference by prematurity was observed in this sub-study. Conclusions: Here we show strong correlations of MMP-9 to genital tract inflammation and sub-optimal bacterial genera in PWLWH indicating the ascending genital tract infection pathway may be a contributory mechanism to the high risk of PTB.

Large-scale characterisation of the pregnancy vaginal microbiome and sialidase activity in a low-risk Chinese population.

Vaginal microbiota-host interactions are linked to preterm birth (PTB), which continues to be the primary cause of global childhood mortality. Due to population size, the majority of PTB occurs in Asia, yet there have been few studies of the pregnancy vaginal microbiota in Asian populations. Here, we characterized the vaginal microbiome of 2689 pregnant Chinese women using metataxonomics and in a subset (n = 819), the relationship between vaginal microbiota composition, sialidase activity and leukocyte presence and pregnancy outcomes. Vaginal microbiota were most frequently dominated by Lactobacillus crispatus or L. iners, with the latter associated with vaginal leukocyte presence. Women with high sialidase activity were enriched for bacterial vaginosis-associated genera including Gardnerella, Atopobium and Prevotella. Vaginal microbiota composition, high sialidase activity and/or leukocyte presence was not associated with PTB risk suggesting underlying differences in the vaginal microbiota and/or host immune responses of Chinese women, possibly accounting for low PTB rates in this population.

Reporting guidelines for human microbiome research: the STORMS checklist.

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

The vaginal microbiota and innate immunity after local excisional treatment for cervical intraepithelial neoplasia.

BACKGROUND: Vaginal microbiota (VMB) composition is altered in women with cervical intra-epithelial neoplasia (CIN) compared to healthy controls and is associated with disease progression. However, the impact of CIN excision on the VMB and innate immunity is not known. This observational study aims to explore the impact of CIN excision on the VMB, antimicrobial peptides (AMP) and proinflammatory cytokines. METHODS: We sampled 103 non-pregnant, premenopausal women at the time of excisional treatment for CIN and at their 6-month follow-up visit. A further 39 untreated controls with normal cytology were also sampled. We used metataxonomics to group vaginal swab samples into community state types (CSTs) and ELISA to quantify cytokine and AMP levels in matched vaginal secretions. Analyses were performed to compare the bacterial composition and immune analyte levels before and after CIN excision and in healthy controls. RESULTS: Women with CIN had significantly higher rates of Lactobacillus species depletion pre-treatment compared to healthy controls (CST IV 21/103, 20% vs 1/39, 3%, p = 0.0081). Excision did not change the VMB composition, with CST IV remaining significantly more prevalent after excision compared to untreated, healthy controls (CST IV 19/103, 20% vs 1/39, 3%, p = 0.0142). Prevotella bivia and Sneathia amnii were significantly higher in samples before treatment compared to untreated controls, and Prevotella bivia remained significantly higher amongst the treated, with less Lactobacillus crispatus compared to untreated controls. IL-1ß and IL-8 remained significantly elevated pre- (p < 0.0001 and p = 0.0014, respectively) and post-treatment (p < 0.0001 and p = 0.0035, respectively) compared to untreated controls. Levels of human beta-defensin-1 and secretory leukocyte protease inhibitor were both significantly reduced following CIN excision (p < 0.0001); however, their levels remained lower than controls post-treatment. CONCLUSIONS: Women with CIN have an increased prevalence of Lactobacillus sp. depletion, high-diversity VMB composition, and higher levels of proinflammatory cytokines and AMPs compared to normal controls. Surgical excision of the disease reduces levels of vaginal AMPs but does not alter VMB composition or cytokine levels. These findings suggest that women with CIN have an inherent predisposition to a high-diversity proinflammatory environment that is not corrected by disease excision. The failure to re-establish a Lactobacillus-enriched CST may explain why women remain at high risk of pre-invasive and invasive disease recurrence.

Direct on-swab metabolic profiling of vaginal microbiome host interactions during pregnancy and preterm birth.

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.