Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome

Neonatal Encephalopathy is a Complex Phenotype Representing Reproductive and Pregnancy Exposome Effects on the Maternal-Placental-Fetal Triad

Reproductive, pregnancy, and placental exposomes influence the fetal neural exposome through toxic stressor interplay, impairing the maternal-placental-fetal (MPF) triad. Neonatal encephalopathy represents different clinical presentations based on complex time-dependent etiopathogenetic mechanisms including hypoxia-ischemia that challenge diagnosis and prognosis. Reproductive, pregnancy, and placental exposomes impair the fetal neural exposome through toxic stressor interplay within the MPF triad. Long intervals often separate disease onset from phenotype. Interdisciplinary fetal-neonatal neurology training, practice, and research closes this knowledge gap. Maintaining reproductive health preserves MPF triad health with life-course benefits.

Untangling Associations of Microbiomes of Pregnancy and Preterm Birth

This review illuminates the complex interplay between various maternal microbiomes and their influence on preterm birth (PTB), a driving and persistent contributor to neonatal morbidity and mortality. Here, we examine the dynamics of oral, gastrointestinal (gut), placental, and vaginal microbiomes, dissecting their roles in the pathogenesis of PTB. Importantly, focusing on the vaginal microbiome and PTB, the review highlights (1) a protective role of Lactobacillus species; (2) an increased risk with select anaerobes; and (3) the influence of social health determinants on the composition of vaginal microbial communities.

Preterm birth, a consequence of immune deviation mediated hyperinflammation

Preterm birth represents a multifaceted syndrome with intricacies still present in our comprehension of its etiology. In the context of a semi-allograft, the prosperity from implantation to pregnancy to delivery hinges on the establishment of a favorable maternal-fetal immune microenvironment and a successful trilogy of immune activation, immune tolerance and then immune activation transitions. The occurrence of spontaneous preterm birth could be related to abnormalities within the immune trilogy, stemming from deviation in maternal and fetal immunity. These immune deviations, characterized by insufficient immune tolerance and early immune activation, ultimately culminated in an unsustainable pregnancy. In this review, we accentuated the role of both innate and adaptive immune reason in promoting spontaneous preterm birth, reviewed the risk of preterm birth from vaginal microbiome mediated by immune changes and the potential of vaginal microbiomes and metabolites as a new predictive marker, and discuss the changes in the role of progesterone and its interaction with immune cells in a preterm birth population. Our objective was to contribute to the growing body of knowledge in the field, shedding light on the immunologic reason of spontaneous preterm birth and effective biomarkers for early prediction, providing a roadmap for forthcoming investigations.

Xenobiotic metabolites modify immune responses of the cervicovaginal epithelium: potential mechanisms underlying barrier disruption

OBJECTIVE

Xenobiotic metabolites are exogenous biochemicals that can adversely impact reproductive health. We previously identified xenobiotics in cervicovaginal fluid during pregnancy in association with short cervix. In other organ systems, xenobiotics can modify epithelial barrier function. We hypothesise that xenobiotics dysregulate epithelial cell and macrophage immune responses as a mechanism to disrupt the cervicovaginal barrier.

DESIGN

In vitro cell culture system.

SETTING

Laboratory within academic institution.

SAMPLE

Vaginal, ectocervical and endocervical epithelial cell lines and primary macrophages.

METHODS

Cells were treated with diethanolamine (2.5 mM), ethyl glucoside (5 mM) or tartrate (2.5 mM) for 24 h.

MAIN OUTCOME MEASURES

Cytokines and matrix metalloproteinases were measured in cell supernatants (n = 3 per condition). One-way analysis of variance (ANOVA) with Dunnett's test for multiple comparisons was performed.

RESULTS

Diethanolamine induces inflammatory cytokines, whereas ethyl glucoside and tartrate generally exert anti-inflammatory effects across all cells. Diethanolamine increases interleukin 6 (IL-6), IL-8, interferon γ-induced protein 10 kDa (IP-10), growth-regulated oncogene (GRO), fractalkine, matrix metalloproteinase 1 (MMP-1), MMP-9 and MMP-10 (p < 0.05 for all), factors involved in acute inflammation and recruitment of monocytes, neutrophils and lymphocytes. Ethyl glucoside and tartrate decrease multiple cytokines, including RANTES and MCP-1 (p < 0.05 for all), which serve as chemotactic factors. Vaginal cells exhibit heightened inflammatory tone compared with cervical cells and macrophages, with a greater number of differentially expressed analytes after xenobiotic exposure.

CONCLUSIONS

Xenobiotic metabolites present in the cervicovaginal space during pregnancy modify immune responses, unveiling potential pathways through which environmental exposures may contribute to the pathogenesis of cervical remodelling preceding preterm birth. Future work identifying xenobiotic sources and routes of exposure offers the potential to modify environmental risks to improve pregnancy outcomes.

Nicotine regulates abnormal macrophage polarization and trophoblast invasion associated with preterm labor via the α7nAChR/SIRT1 axis

INTRODUCTION

Preterm birth (PTB) frequently results from the syndrome of preterm labor (PTL). PTL is linked to an atypical maternal inflammatory response, as well as intrauterine inflammation and/or infection. In this study, we explored the mechanisms involved in nicotine-mediated abnormal macrophage polarization and trophoblast invasion associated with PTL.

METHODS

First, THP-1-M0 macrophages were generated by treating the human monocytic leukemia cell line (THP-1) with phorbol 12-myristate 13-acetate for a duration of 24 h. Afterward, nicotine treatment was administered, followed by coculturing with the HTR-8/SVneo trophoblast cell line (HTR-8) at a ratio of 1:1. Next, we transfected sh-α7nAChR and treated THP-1-M0 macrophages and HTR-8 cells with nicotine. In addition, we transfected THP-1-M0 macrophages with sh-NC or sh-SIRT1 or subjected them to 4 nM nicotinamide adenine dinucleotide (NAD) metabolic inhibitor FK866 treatment. Moreover, HTR-8 cells were treated with nicotine, after which THP-1-M0 macrophages were cocultured with HTR-8 cells. Finally, we constructed an in vivo RU486-induced PTL rat model to verify the effect of nicotine and the mechanisms involved.

RESULTS

We found that nicotine affected polarization and α7nAChR expression in HTR-8 cocultured THP-1-M0 macrophages. Knocking down α7nAChR blocked the effect of nicotine on the proliferation and invasion of HTR-8 cells. Furthermore, nicotine activated the α7nAChR/SIRT1 axis to regulate THP-1-M0 macrophage polarization through the cholinergic anti-inflammatory pathway. Additionally, NAD metabolism mediated the role of the α7nAChR/SIRT1 axis in nicotine-induced polarization of HTR-8 cocultured THP-1-M0 macrophages. In vivo experiments demonstrated that nicotine alleviated inflammation in PTL rats, which involved the α7nAChR/SIRT1 axis.

CONCLUSION

Nicotine regulated abnormal macrophage polarization and trophoblast invasion associated with PTL via the α7nAChR/SIRT1 axis.

Urinary metabolite biomarkers of pregnancy complications associated with maternal exposure to particulate matter

Particulate matter 2.5 (PM2.5) is associated with reproductive health and adverse pregnancy outcomes. However, studies evaluating biological markers of PM2.5 are lacking, and identifying biomarkers for estimating prenatal exposure to prevent pregnancy complications is essential. Therefore, we aimed to explore urine metabolites that are easy to measure as biomarkers of exposure. In this matched case-control study based on the PM2.5 exposure, 30 high PM2.5 group (>15 μg/m3) and 30 low PM2.5 group (<15 μg/m3) were selected from air pollution on pregnancy outcome (APPO) cohort study. We used a time-weighted average model to estimate individual PM exposure, which used indoor PM2.5 and outdoor PM2.5 concentrations by atmospheric measurement network based on residential addresses. Clinical characteristics and urine samples were collected from participants during the second trimester of pregnancy. Urine metabolites were quantitatively measured using gas chromatography-mass spectrometry following multistep chemical derivatization. Statistical analyses were conducted using SPSS version 21 and MetaboAnalyst 5.0. Small for gestational age and gestational diabetes (GDM) were significantly increased in the high PM2.5 group, respectively (P = 0.042, and 0.022). Fifteen metabolites showed significant differences between the two groups (P < 0.05). Subsequent pathway enrichment revealed that four pathways, including pentose and glucuronate interconversion with three pentose sugars (ribose, arabinose, and xylose; P < 0.05). The concentration of ribose increased preterm births (PTB) and GDM (P = 0.044 and 0.049, respectively), and the arabinose concentration showed a tendency to increase in PTB (P = 0.044). Therefore, we identified urinary pentose metabolites as biomarkers of PM2.5 and confirmed the possibility of their relationship with pregnancy complications.

Metabolomic analysis of the human placenta reveals perturbations in amino acids, purine metabolites, and small organic acids in spontaneous preterm birth

Spontaneous preterm delivery presents one of the most complex challenges in obstetrics and is a leading cause of perinatal morbidity and mortality. Although it is a common endpoint for multiple pathological processes, the mechanisms governing the etiological complexity of spontaneous preterm birth and the placental responses are poorly understood. This study examined placental tissues collected between May 2019 and May 2022 from a well-defined cohort of women who experienced spontaneous preterm birth (n = 72) and healthy full-term deliveries (n = 30). Placental metabolomic profiling of polar metabolites was performed using Ultra-High Performance Liquid Chromatography/Mass Spectrometry (UHPLC/MS) analysis. The resulting data were analyzed using multi- and univariate statistical methods followed by unsupervised clustering. A comprehensive metabolomic evaluation of the placenta revealed that spontaneous preterm birth was associated with significant changes in the levels of 34 polar metabolites involved in intracellular energy metabolism and biochemical activity, including amino acids, purine metabolites, and small organic acids. We found that neither the preterm delivery phenotype nor the inflammatory response explain the reported differential placental metabolome. However, unsupervised clustering revealed two molecular subtypes of placentas from spontaneous preterm pregnancies exhibiting differential enrichment of clinical parameters. We also identified differences between early and late preterm samples, suggesting distinct placental functions in early spontaneous preterm delivery. Altogether, we present evidence that spontaneous preterm birth is associated with significant changes in the level of placental polar metabolites. Dysregulation of the placental metabolome may underpin important (patho)physiological mechanisms involved in preterm birth etiology and long-term neonatal outcomes.

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models

Every step in common microbiome profiling protocols has variable efficiency for each microbe. For example, different DNA extraction kits may have different efficiency for Gram-positive and -negative bacteria. These variable efficiencies, combined with technical variation, create strong processing biases, which impede the identification of signals that are reproducible across studies and the development of generalizable and biologically interpretable prediction models. "Batch-correction" methods have been used to alleviate these issues computationally with some success. However, many make strong parametric assumptions which do not necessarily apply to microbiome data or processing biases, or require the use of an outcome variable, which risks overfitting. Lastly and importantly, existing transformations used to correct microbiome data are largely non-interpretable, and could, for example, introduce values to features that were initially mostly zeros. Altogether, processing bias currently compromises our ability to glean robust and generalizable biological insights from microbiome data. Here, we present DEBIAS-M (Domain adaptation with phenotype Estimation and Batch Integration Across Studies of the Microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns bias-correction factors for each microbe in each batch that simultaneously minimize batch effects and maximize cross-study associations with phenotypes. Using benchmarks of HIV and colorectal cancer classification from gut microbiome data, and cervical neoplasia prediction from cervical microbiome data, we demonstrate that DEBIAS-M outperforms batch-correction methods commonly used in the field. Notably, we show that the inferred bias-correction factors are stable, interpretable, and strongly associated with specific experimental protocols. Overall, we show that DEBIAS-M allows for better modeling of microbiome data and identification of interpretable signals that are reproducible across studies.

The human vaginal microbiota: from clinical medicine to models to mechanisms

The composition of the vaginal microbiota is linked to numerous reproductive health problems, including increased susceptibility to infection, pregnancy complications, and impaired vaginal tissue repair; however, the mechanisms contributing to these adverse outcomes are not yet fully defined. In this review, we highlight recent clinical advancements associating vaginal microbiome composition and function with health outcomes. Subsequently, we provide a summary of emerging models employed to identify microbe-microbe interactions contributing to vaginal health, including metagenomic sequencing, multi-omics approaches, and advances in vaginal microbiota cultivation. Last, we review new in vitro, ex vivo, and in vivo models, such as organoids and humanized microbiota murine models, used to define and mechanistically explore host-microbe interactions at the vaginal mucosa.

Interdisciplinary fetal-neonatal neurology training applies neural exposome perspectives to neurology principles and practice

An interdisciplinary fetal-neonatal neurology (FNN) program over the first 1,000 days teaches perspectives of the neural exposome that are applicable across the life span. This curriculum strengthens neonatal neurocritical care, pediatric, and adult neurology training objectives. Teaching at maternal-pediatric hospital centers optimally merges reproductive, pregnancy, and pediatric approaches to healthcare. Phenotype-genotype expressions of health or disease pathways represent a dynamic neural exposome over developmental time. The science of uncertainty applied to FNN training re-enforces the importance of shared clinical decisions that minimize bias and reduce cognitive errors. Trainees select mentoring committee participants that will maximize their learning experiences. Standardized questions and oral presentations monitor educational progress. Master or doctoral defense preparation and competitive research funding can be goals for specific individuals. FNN principles applied to practice offer an understanding of gene-environment interactions that recognizes the effects of reproductive health on the maternal-placental-fetal triad, neonate, child, and adult. Pre-conception and prenatal adversities potentially diminish life-course brain health. Endogenous and exogenous toxic stressor interplay (TSI) alters the neural exposome through maladaptive developmental neuroplasticity. Developmental disorders and epilepsy are primarily expressed during the first 1,000 days. Communicable and noncommunicable illnesses continue to interact with the neural exposome to express diverse neurologic disorders across the lifespan, particularly during the critical/sensitive time periods of adolescence and reproductive senescence. Anomalous or destructive fetal neuropathologic lesions change clinical expressions across this developmental-aging continuum. An integrated understanding of reproductive, pregnancy, placental, neonatal, childhood, and adult exposome effects offers a life-course perspective of the neural exposome. Exosome research promises improved disease monitoring and drug delivery starting during pregnancy. Developmental origins of health and disease principles applied to FNN practice anticipate neurologic diagnoses with interventions that can benefit successive generations. Addressing health care disparities in the Global South and high-income country medical deserts require constructive dialogue among stakeholders to achieve medical equity. Population health policies require a brain capital strategy that reduces the global burden of neurologic diseases by applying FNN principles and practice. This integrative neurologic care approach will prolong survival with an improved quality of life for persons across the lifespan confronted with neurological disorders.

Preterm Birth: Screening and Prediction

Preterm birth (PTB) affects approximately 10% of births globally each year and is the most significant direct cause of neonatal death and of long-term disability worldwide. Early identification of women at high risk of PTB is important, given the availability of evidence-based, effective screening modalities, which facilitate decision-making on preventative strategies, particularly transvaginal sonographic cervical length (CL) measurement. There is growing evidence that combining CL with quantitative fetal fibronectin (qfFN) and maternal risk factors in the extensively peer-reviewed and validated QUanititative Innovation in Predicting Preterm birth (QUiPP) application can aid both the triage of patients who present as emergencies with symptoms of preterm labor and high-risk asymptomatic women attending PTB surveillance clinics. The QUiPP app risk of delivery thus supports shared decision-making with patients on the need for increased outpatient surveillance, in-patient treatment for preterm labor or simply reassurance for those unlikely to deliver preterm. Effective triage of patients at preterm gestations is an obstetric clinical priority as correctly timed administration of antenatal corticosteroids will maximise their neonatal benefits. This review explores the predictive capacity of existing predictive tests for PTB in both singleton and multiple pregnancies, including the QUiPP app v.2. and discusses promising new research areas, which aim to predict PTB through cervical stiffness and elastography measurements, metabolomics, extracellular vesicles and artificial intelligence.

Maternal and infant microbiome: next-generation indicators and targets for intergenerational health and nutrition care

Microbes are commonly sensitive to shifts in the physiological and pathological state of their hosts, including mothers and babies. From this perspective, the microbiome may be a good indicator for diseases during pregnancy and has the potential to be used for perinatal health monitoring. This is embodied in the application of microbiome from multi body sites for auxiliary diagnosis, early prediction, prolonged monitoring, and retrospective diagnosis of pregnancy and infant complications, as well as nutrition management and health products developments of mothers and babies. Here we summarized the progress in these areas and explained that the microbiome of different body sites is sensitive to different diseases and their microbial biomarkers may overlap between each other, thus we need to make a diagnosis prudently for those diseases. Based on the microbiome variances and additional anthropometric and physical data, individualized responses of mothers and neonates to meals and probiotics/prebiotics were predictable, which is of importance for precise nutrition and probiotics/prebiotics managements and developments. Although a great deal of encouraging performance was manifested in previous studies, the efficacy could be further improved by combining multi-aspect data such as multi-omics and time series analysis in the future. This review reconceptualizes maternal and infant health from a microbiome perspective, and the knowledge in it may inspire the development of new options for the prevention and treatment of adverse pregnancy outcomes and bring a leap forward in perinatal health care.

Profiling of vaginal Lactobacillus jensenii isolated from preterm and full-term pregnancies reveals strain-specific factors relating to host interaction

Each year, 15 million infants are born preterm (<37 weeks gestation), representing the leading cause of mortality for children under the age of five. Whilst there is no single cause, factors such as maternal genetics, environmental interactions, and the vaginal microbiome have been associated with an increased risk of preterm birth. Previous studies show that a vaginal microbiota dominated by Lactobacillus is, in contrast to communities containing a mixture of genera, associated with full-term birth. However, this binary principle does not fully consider more nuanced interactions between bacterial strains and the host. Here, through a combination of analyses involving genome-sequenced isolates and strain-resolved metagenomics, we identify that L. jensenii strains from preterm pregnancies are phylogenetically distinct from strains from full-term pregnancies. Detailed analysis reveals several genetic signatures that distinguish preterm birth strains, including genes predicted to be involved in cell wall synthesis, and lactate and acetate metabolism. Notably, we identify a distinct gene cluster involved in cell surface protein synthesis in our preterm strains, and profiling the prevalence of this gene cluster in publicly available genomes revealed it to be predominantly present in the preterm-associated clade. This study contributes to the ongoing search for molecular biomarkers linked to preterm birth and opens up new avenues for exploring strain-level variations and mechanisms that may contribute to preterm birth.

Metabolomic profiling of preterm birth in pregnant women living with HIV

BACKGROUND

Preterm birth is a leading cause of death in children under the age of five. The risk of preterm birth is increased by maternal HIV infection as well as by certain antiretroviral regimens, leading to a disproportionate burden on low- and medium-income settings where HIV is most prevalent. Despite decades of research, the mechanisms underlying spontaneous preterm birth, particularly in resource limited areas with high HIV infection rates, are still poorly understood and accurate prediction and therapeutic intervention remain elusive.

OBJECTIVES

Metabolomics was utilized to identify profiles of preterm birth among pregnant women living with HIV on two different antiretroviral therapy (ART) regimens.

METHODS

This pilot study comprised 100 mother-infant dyads prior to antiretroviral initiation, on zidovudine monotherapy or on protease inhibitor-based antiretroviral therapy. Pregnancies that resulted in preterm births were matched 1:1 with controls by gestational age at time of sample collection. Maternal plasma and blood spots at 23-35 weeks gestation and infant dried blood spots at birth, were assayed using an untargeted metabolomics method. Linear regression and random forests classification models were used to identify shared and treatment-specific markers of preterm birth.

RESULTS

Classification models for preterm birth achieved accuracies of 95.5%, 95.7%, and 80.7% in the untreated, zidovudine monotherapy, and protease inhibitor-based treatment groups, respectively. Urate, methionine sulfone, cortisone, and 17α-hydroxypregnanolone glucuronide were identified as shared markers of preterm birth. Other compounds including hippurate and N-acetyl-1-methylhistidine were found to be significantly altered in a treatment-specific context.

CONCLUSION

This study identified previously known as well as novel metabolomic features of preterm birth in pregnant women living with HIV. Validation of these models in a larger, independent cohort is necessary to ascertain whether they can be utilized to predict preterm birth during a stage of gestation that allows for therapeutic intervention or more effective resource allocation.

Structural Racism and Adverse Pregnancy Outcomes Through the Lens of the Maternal Microbiome

Microbiome science offers a glimpse into personalized medicine by characterizing health and disease states according to an individual's microbial signatures. Without a critical examination of the use of race as a variable, microbiome studies may be susceptible to the same pitfalls as other areas of science grounded in racist biology. We will examine the use of race as a biological variable in pregnancy-related microbiome research. Emerging data from studies that investigate the intestinal microbiome in pregnancy suggest strong influence of a poor diet on adverse pregnancy outcomes. Differences in the vaginal microbiome implicated in adverse pregnancy outcomes are frequently attributed to race. We review evidence that links systemic racism to pregnancy health outcome differences with a focus on the vaginal and intestinal microbiomes as well as diet. We also review how structural racism ultimately contributes to inequitable access to healthy food and higher risk environmental exposures among pregnant people of lower socioeconomic status and exacerbates common pregnancy comorbidities.

Exploring the Microbiome in Human Reproductive Tract: High-Throughput Methods for the Taxonomic Characterization of Microorganisms

Microorganisms are important due to their widespread presence and multifaceted roles across various domains of life, ecology, and industries. In humans, they underlie the proper functioning of multiple systems crucial to well-being, including immunological and metabolic functions. Emerging research addressing the presence and roles of microorganisms within human reproduction is increasingly relevant. Studies implementing new methodologies (e.g., to investigate vaginal, uterine, and semen microenvironments) can now provide relevant insights into fertility, reproductive health, or pregnancy outcomes. In that sense, cutting-edge sequencing techniques, as well as others such as meta-metabolomics, culturomics, and meta-proteomics, are becoming more popular and accessible worldwide, allowing the characterization of microbiomes at unprecedented resolution. However, they frequently involve rather complex laboratory protocols and bioinformatics analyses, for which researchers may lack the required expertise. A suitable pipeline would successfully enable both taxonomic classification and functional profiling of the microbiome, providing easy-to-understand biological interpretations. However, the selection of an appropriate methodology would be crucial, as it directly impacts the reproducibility, accuracy, and quality of the results and observations. This review focuses on the different current microbiome-related techniques in the context of human reproduction, encompassing niches like vagina, endometrium, and seminal fluid. The most standard and reliable methods are 16S rRNA gene sequencing, metagenomics, and meta-transcriptomics, together with complementary approaches including meta-proteomics, meta-metabolomics, and culturomics. Finally, we also offer case examples and general recommendations about the most appropriate methods and workflows and discuss strengths and shortcomings for each technique.

The Urinary Metabolomic Fingerprint in Extremely Preterm Infants on Total Parenteral Nutrition vs. Enteral Feeds

Total Parenteral Nutrition (TPN), which uses intravenous administration of nutrients, minerals and vitamins, is essential for sustaining premature infants until they transition to enteral feeds, but there is limited information on metabolomic differences between infants on TPN and enteral feeds. We performed untargeted global metabolomics on urine samples collected between 23-30 days of life from 314 infants born <29 weeks gestational age from the TOLSURF and PROP cohorts. Principal component analysis across all metabolites showed a separation of infants solely on TPN compared to infants who had transitioned to enteral feeds, indicating global metabolomic differences between infants based on feeding status. Among 913 metabolites that passed quality control filters, 609 varied in abundance between infants on TPN vs. enteral feeds at p < 0.05. Of these, 88% were in the direction of higher abundance in the urine of infants on enteral feeds. In a subset of infants in a longitudinal analysis, both concurrent and delayed changes in metabolite levels were observed with the initiation of enteral feeds. These infants had higher concentrations of essential amino acids, lipids, and vitamins, which are necessary for growth and development, suggesting the nutritional benefit of an enteral feeding regimen.

Microdiversity of the vaginal microbiome is associated with preterm birth

Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this association are not fully understood. Understanding microbial genetic adaptations to selective pressures, especially those related to the host, may yield insights into these associations. Here, we analyze metagenomic data from 705 vaginal samples collected during pregnancy from 40 women who delivered preterm spontaneously and 135 term controls from the Multi-Omic Microbiome Study-Pregnancy Initiative. We find that the vaginal microbiome of pregnancies that ended preterm exhibited unique genetic profiles. It was more genetically diverse at the species level, a result which we validate in an additional cohort, and harbored a higher richness and diversity of antimicrobial resistance genes, likely promoted by transduction. Interestingly, we find that Gardnerella species drove this higher genetic diversity, particularly during the first half of the pregnancy. We further present evidence that Gardnerella spp. underwent more frequent recombination and stronger purifying selection in genes involved in lipid metabolism. Overall, our population genetics analyses reveal associations between the vaginal microbiome and PTB and suggest that evolutionary processes acting on vaginal microbes may play a role in adverse pregnancy outcomes such as PTB.

Advances in mass spectrometry technologies to characterize cervicovaginal microbiome functions that impact spontaneous preterm birth

Preterm birth (PTB) is a leading cause of morbidity and mortality in young children. Infection is a major cause of this adverse outcome, particularly in PTBs characterised by spontaneous rupture of membranes, referred to as spontaneous (s)PTB. However, the aetiology of sPTB is not well defined and specific bacteria associated with sPTB differ between studies and at the individual level. This may be due to many factors including a lack of understanding of strain-level differences in bacteria that influence how they function and interact with each other and the host. Metaproteomics and metabolomics are mass spectrometry-based methods that enable the collection of detailed microbial and host functional information. Technological advances in this field have dramatically increased the resolution of these approaches, enabling the simultaneous detection of thousands of proteins or metabolites. These data can be used for taxonomic analysis of vaginal bacteria and other microbes, to understand microbiome-host interactions, and identify diagnostic biomarkers or therapeutic targets. Although these methods have been used to assess host proteins and metabolites, few have characterized the microbial compartment in the context of pregnancy. The utilisation of metaproteomic and metabolomic-based approaches has the potential to vastly improve our understanding of the mechanisms leading to sPTB.

Microdiversity of the Vaginal Microbiome is Associated with Preterm Birth

Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this association are not fully understood. Understanding microbial genetic adaptations to selective pressures, especially those related to the host, may yield new insights into these associations. To this end, we analyzed metagenomic data from 705 vaginal samples collected longitudinally during pregnancy from 40 women who delivered preterm spontaneously and 135 term controls from the Multi-Omic Microbiome Study-Pregnancy Initiative (MOMS-PI). We find that the vaginal microbiome of pregnancies that ended preterm exhibits unique genetic profiles. It is more genetically diverse at the species level, a result which we validate in an additional cohort, and harbors a higher richness and diversity of antimicrobial resistance genes, likely promoted by transduction. Interestingly, we find that Gardnerella species, a group of central vaginal pathobionts, are driving this higher genetic diversity, particularly during the first half of the pregnancy. We further present evidence that Gardnerella spp. undergoes more frequent recombination and stronger purifying selection in genes involved in lipid metabolism. Overall, our results reveal novel associations between the vaginal microbiome and PTB using population genetics analyses, and suggest that evolutionary processes acting on the vaginal microbiome may play a vital role in adverse pregnancy outcomes such as preterm birth.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.