The Metabolomic Signature of the Placenta in Spontaneous Preterm Birth

The association of infant urinary adrenal steroids with the risk of childhood asthma development

BACKGROUND

Adrenal steroids play important roles in early-life development. However, our understanding of the effects of perinatal adrenal steroids on the development of childhood asthma is incomplete.

OBJECTIVE

To evaluate the associations between early-life adrenal steroid levels and childhood asthma.

METHODS

Participants included the Infant Susceptibility to Pulmonary Infections and Asthma following Respiratory Syncytial Virus Exposure birth cohort children with untargeted urinary metabolomics data measured during early infancy (n = 264) and nasal immune mediator data measured concurrently at age 2 to 6 months (n = 76). A total of 11 adrenal steroid compounds were identified using untargeted metabolomics and 6 asthma-relevant nasal immune mediators from multiplex assays were a priori selected. Current asthma at ages 5 and 6 years was ascertained using validated questionnaires. Associations were tested using logistic and linear regression with confounders adjustment.

RESULTS

Pregnenetriol disulfate (adjusted odds ratio [aOR] = 0.20, 95% CI = 0.06-0.68) and 3a,21-dihydroxy-5b-pregnane-11,20-dione-21-glucuronide (aOR = 0.34, 95% CI = 0.14-0.75) were inversely associated with childhood asthma at 5 and 6 years after multiple testing adjustment. There was a significant interaction effect of pregnanediol-3-glucuronide by biological sex assigned at birth (aOR = 0.11, 95% CI = 0.02-0.51, for those with female sex) on childhood asthma. Pregnenetriol disulfate was inversely associated with granulocyte-macrophage colony-stimulating factor (β = -0.45, q-value = 0.05). 3a,21-dihydroxy-5b-pregnane-11,20-dione 21-glucuronide was inversely associated with interleukin [IL]-4 (β = -0.29, q-value = 0.02), IL-5 (β = -0.35, q-value = 0.006), IL-13 (β = -0.26, q-value = 0.02), granulocyte-macrophage colony-stimulating factor (β = -0.35, q-value = 0.006), and fibroblast growth factor-β (β = -0.24, q-value = 0.01) after multiple testing adjustment.

CONCLUSION

The inverse association between adrenal steroids downstream of progesterone and 17-hydroxypregnenolone and the odds of childhood asthma and nasopharyngeal type 2 immune biomarkers suggest that increased early-life adrenal steroids may suppress type 2 inflammation and protect against the development of childhood asthma.

2-Hydroxy-5-nitro-3-(trifluoromethyl)pyridine as a Novel Matrix for Enhanced MALDI Imaging of Tissue Metabolites

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which is a label-free imaging technique, determines the spatial distribution and relative abundance of versatile endogenous metabolites in tissues. Meanwhile, matrix selection is generally regarded as a pivotal step in MALDI tissue imaging. This study presents the first report of a novel MALDI matrix, 2-hydroxy-5-nitro-3-(trifluoromethyl)pyridine (HNTP), for the in situ detection and imaging of endogenous metabolites in rat liver and brain tissues by MALDI-MS in positive-ion mode. The HNTP matrix exhibits excellent characteristics, including strong ultraviolet absorption, μm-scale matrix crystals, high chemical stability, low background ion interference, and high metabolite ionization efficiency. Notably, the HNTP matrix also shows superior detection capabilities, successfully showing 185 detectable metabolites in rat liver tissue sections. This outperforms the commonly used matrices of 2,5-dihydroxybenzoic acid and 2-mercaptobenzothiazole, which detect 145 and 120 metabolites from the rat liver, respectively. Furthermore, a total of 152 metabolites are effectively detected and imaged in rat brain tissue using the HNTP matrix, and the spatial distribution of these compounds clearly shows the heterogeneity of the rat brain. The results demonstrate that HNTP is a new and powerful positive-ion mode matrix to enhance the analysis of metabolites in biological tissues by MALDI-MSI.

The role of placental insufficiency in spontaneous preterm birth: A literature review

Preterm Birth (delivery before 37 weeks of gestation) is the leading cause of childhood mortality and is also associated with significant morbidity both in the neonatal period and beyond. The aetiology of spontaneous preterm birth is unclear and likely multifactorial incorporating factors such as infection/inflammation and cervical injury. Placental insufficiency is emerging as an additional contributor to spontaneous preterm delivery; however, the mechanisms by which this occurs are not fully understood. Serum biomarkers and imaging techniques have been investigated as potential predictors of placental insufficiency, however none have yet been found to have a sufficient predictive value. This review examines the evidence for the role of the placenta in preterm birth, preterm prelabour rupture of the membranes and abruption as well as highlighting areas where further research is required.

Phytochemical study of 'tajy' (Handroanthus impetiginosus (Mart.) Mattos) and 'ka'a ovetĩ' (Luehea divaricata Mart.) extracts

This study explores the phytochemical composition of leaf extracts from Handroanthus impetiginosus (Mart.) Mattos and Luehea divaricata Mart., used in a contraceptive decoction by Mbya-Guarani women. The phytocompounds were identified by gas chro-matography-mass spectrometry, while Fourier-transform infrared spectroscopy, multi-elemental, and thermal analyses were used to characterise plant biomass. Notably, no phytoconstituent supporting the efficacy of these extracts as female contraceptives was found, except for a small amount (0.3%) of sitosterol. Conversely, L. divaricata leaves contained compounds like 1,3-dihydroxyacetone dimer, N-methyl-N-nitroso-2-propanamine, 2-methoxy-N-(2-methoxyethyl)-N-methyl-ethanamine, and 1,3,5-triazine-2,4,6-triamine, potentially exerting cytotoxic, genotoxic, and toxicogenomic effects. Due to the absence of scientific support for the claimed contraceptive efficacy and the presence of safety concerns, we propose an alternative valorisation pathway centred on the presence of phytochemicals exhibiting antimicrobial activity. This proposition is substantiated by their considerable in vitro efficacy against Botrytis cinerea.

Associations of the placental metabolome with immune maturation up to one year of age in the Swedish NICE-cohort

INTRODUCTION

Allergies and other immune-mediated diseases are thought to result from incomplete maturation of the immune system early in life. We previously showed that infants' metabolites at birth were associated with immune cell subtypes during infancy. The placenta supplies the fetus with nutrients, but may also provide immune maturation signals.

OBJECTIVES

To examine the relationship between metabolites in placental villous tissue and immune maturation during the first year of life and infant and maternal characteristics (gestational length, birth weight, sex, parity, maternal age, and BMI).

METHODS

Untargeted metabolomics was measured using Liquid Chromatography-Mass Spectrometry. Subpopulations of T and B cells were measured using flow cytometry at birth, 48 h, one, four, and 12 months. Random forest analysis was used to link the metabolomics data with the T and B cell sub populations as well as infant and maternal characteristics.

RESULTS

Modest associations (Q2 = 0.2-0.3) were found between the placental metabolome and kappa-deleting recombination excision circles (KREC) at birth and naïve B cells and memory T cells at 12 months. Weak associations were observed between the placental metabolome and sex and parity. Still, most metabolite features of interest were of low intensity compared to associations previously found in cord blood, suggesting that underlying metabolites were not of placental origin.

CONCLUSION

Our results indicate that metabolomic measurements of the placenta may not effectively recognize metabolites important for immune maturation.

Maternal Acylcarnitine Disruption as a Potential Predictor of Preterm Birth in Primigravida: A Preliminary Investigation

Preterm birth, defined as any birth before 37 weeks of completed gestation, poses adverse health risks to both mothers and infants. Despite preterm birth being associated with several risk factors, its relationship to maternal metabolism remains unclear, especially in first-time mothers. Aims of the present study were to identify maternal metabolic disruptions associated with preterm birth and to evaluate their predictive potentials. Blood was collected, and the serum harvested from the mothers of 24 preterm and 42 term births at 28-32 weeks gestation (onset of the 3rd trimester). Serum samples were assayed by untargeted metabolomic analyses via liquid chromatography/mass spectrometry (QTOF-LC/MS). Metabolites were annotated by inputting the observed mass-to-charge ratio into the Human Metabolome Database (HMDB). Analysis of 181 identified metabolites by PLS-DA modeling using SIMCA (v17) showed reasonable separation between the two groups (CV-ANOVA, p = 0.02). Further statistical analysis revealed lower serum levels of various acyl carnitines and amino acid metabolites in preterm mothers. Butenylcarnitine (C4:1), a short-chain acylcarnitine, was found to be the most predictive of preterm birth (AUROC = 0.73, [CI] 0.60-0.86). These observations, in conjuncture with past literature, reveal disruptions in fatty acid oxidation and energy metabolism in preterm primigravida. While these findings require validation, they reflect altered metabolic pathways that may be predictive of preterm delivery in primigravida.

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.

Maternal serum amino acid levels as predictors of premature rupture of membranes: A comprehensive analysis

INTRODUCTION

The aim of this study is to investigate the association between altered maternal serum amino acids (AAs) levels and premature rupture of membranes (pPROM) in pregnant women.

METHODS

We conducted a case-control study involving 60 pregnant women diagnosed with pPROM and 60 healthy pregnant women as controls. Amino acid levels were quantified using high-performance liquid chromatography. Receiver operating characteristic (ROC) curve analysis was performed to determine the predictive capability of specific AAs for pPROM.

RESULTS

Our findings revealed that lysine, glycine, and glutamic acid levels were significantly elevated in the pPROM group compared with the control group. Lysine, with a threshold value exceeding 137.90 μmol/L, exhibited the highest predictive accuracy, with an area under the curve (AUC) of 0.796 (p < 0.001), sensitivity of 66.7 %, and specificity of 80.0 %. Glycine, with a cut-off value of >242.48 μmol/L, had an AUC of 0.789 (p < 0.001), sensitivity of 83.3 %, and specificity of 65.0 %. Glutamic acid, at a threshold of 111.40 μmol/L, demonstrated an AUC of 0.787 (p < 0.001), sensitivity of 88.3 %, and specificity of 65.0 %. These AAs could effectively predict the occurrence of pPROM.

CONCLUSION

Elevated blood levels of lysine, glycine, and glutamic acid were found to be associated with pPROM. These AAs serve as potential predictive biomarkers for pPROM, with lysine showing the highest AUC and sensitivity. Identifying such biomarkers may contribute to the development of non-invasive diagnostic tools for pPROM risk assessment, enabling timely interventions and improved maternal and fetal outcomes.

Prediction of spontaneous preterm birth using supervised machine learning on metabolomic data: A case-cohort study

OBJECTIVES

To identify and internally validate metabolites predictive of spontaneous preterm birth (sPTB) using multiple machine learning methods and sequential maternal serum samples, and to predict spontaneous early term birth (sETB) using these metabolites.

DESIGN

Case-cohort design within a prospective cohort study.

SETTING

Cambridge, UK.

POPULATION OR SAMPLE

A total of 399 Pregnancy Outcome Prediction study participants, including 98 cases of sPTB.

METHODS

An untargeted metabolomic analysis of maternal serum samples at 12, 20, 28 and 36 weeks of gestation was performed. We applied six supervised machine learning methods and a weighted Cox model to measurements at 28 weeks of gestation and sPTB, followed by feature selection. We used logistic regression with elastic net penalty, followed by best subset selection, to reduce the number of predictive metabolites further. We applied coefficients from the chosen models to measurements from different gestational ages to predict sPTB and sETB.

MAIN OUTCOME MEASURES

sPTB and sETB.

RESULTS

We identified 47 metabolites, mostly lipids, as important predictors of sPTB by two or more methods and 22 were identified by three or more methods. The best 4-predictor model had an optimism-corrected area under the receiver operating characteristics curve (AUC) of 0.703 at 28 weeks of gestation. The model also predicted sPTB in 12-week samples (0.606, 95% CI 0.544-0.667) and 20-week samples (0.657, 95% CI 0.597-0.717) and it predicted sETB in 36-week samples (0.727, 95% CI 0.606-0.849). A lysolipid, 1-palmitoleoyl-GPE (16:1)*, was the strongest predictor of sPTB at 12 weeks of gestation (0.609, 95% CI 0.548-0.670), 20 weeks (0.630, 95% CI 0.569-0.690) and 28 weeks (0.660, 95% CI 0.599-0.722), and of sETB at 36 weeks (0.739, 95% CI 0.618-0.860).

CONCLUSIONS

We identified and internally validated maternal serum metabolites predictive of sPTB. A lysolipid, 1-palmitoleoyl-GPE (16:1)*, is a novel predictor of sPTB and sETB. Further validation in external populations is required.

Identifying placental metabolic biomarkers of preterm birth using nuclear magnetic resonance of intact tissue samples

INTRODUCTION

Our understanding of the etiology of preterm birth (PTB) is incomplete; however, recent evidence has found a strong association between placental dysfunction and PTB. Altered placental metabolism may precede placental dysfunction and therefore the study of placental metabolic profiles could identify early biomarkers of PTB. In this study, we evaluated the placental metabolome in PTB in intact tissue samples using nuclear magnetic resonance (NMR) and spectral editing.

METHODS

Placental tissue samples were collected from nine term pregnancies and nine preterm pregnancies (<37 weeks' gestation). 1H NMR experiments on unprocessed tissue samples were performed using a high field magnet (500 MHz spectrometer) and a comprehensive multiphase NMR probe. The relative concentrations of 23 metabolites were corrected for gestational age and compared between groups.

RESULTS

The relative concentration of valine, glutamate and creatine were significantly decreased while alanine, choline and glucose were elevated in placentas from PTB pregnancies compared to controls (p < 0.05). Multivariate analysis using principal component analysis showed the PTB and control groups were significantly separated (p < 0.0001) and pathway analysis identified perturbations in the glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis and valine, leucine and isoleucine biosynthesis pathways.

CONCLUSION

PTB is associated with significant alterations in placental metabolism. This study helps improve our understanding of the etiology of PTB. It also highlights the potential for small molecule metabolites to serve as placental metabolic biomarkers to aid in the prediction and diagnosis of PTB. The results can be translated to clinical use via in utero magnetic resonance spectroscopy.

A Critical Review on the Opportunity to Use Placenta and Innovative Biomonitoring Methods to Characterize the Prenatal Chemical Exposome

Adverse effects associated with chemical exposures during pregnancy include several developmental and reproductive disorders. However, considering the tens of thousands of chemicals present on the market, the effects of chemical mixtures on the developing fetus is still likely underestimated. In this critical review, we discuss the potential to apply innovative biomonitoring methods using high-resolution mass spectrometry (HRMS) on placenta to improve the monitoring of chemical exposure during pregnancy. The physiology of the placenta and its relevance as a matrix for monitoring chemical exposures and their effects on fetal health is first outlined. We then identify several key parameters that require further investigations before placenta can be used for large-scale monitoring in a robust manner. Most critical is the need for standardization of placental sampling. Placenta is a highly heterogeneous organ, and knowledge of the intraplacenta variability of chemical composition is required to ensure unbiased and robust interindividual comparisons. Other important variables include the time of collection, the sex of the fetus, and mode of delivery. Finally, we discuss the first applications of HRMS methods on the placenta to decipher the chemical exposome and describe how the use of placenta can complement biofluids collected on the mother or the fetus.

Machine learning encodes urine and serum metabolic patterns for autoimmune disease discrimination, classification and metabolic dysregulation analysis

There is a wide variety of autoimmune diseases (ADs) with complex pathogenesis and their accurate diagnosis is difficult to achieve because of their vague symptoms. Metabolomics has been proven to be an efficient tool in the analysis of metabolic disorders to provide clues about the mechanism and diagnosis of diseases. Previous studies of the metabolomics analysis of ADs were not competent in their discrimination. Herein, a liquid chromatography tandem mass spectrometry (LC-MS) strategy combined with machine learning is proposed for the discrimination and classification of ADs. Urine and serum samples were collected from 267 subjects consisting of 127 healthy controls (HC) and 140 AD patients, including those with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), sicca syndrome (SS), ankylosing spondylitis (AS), systemic scleroderma (SSc) and connective tissue disease (CTD). Machine learning algorithms were encoded for the discrimination and classification of ADs with metabolomic patterns obtained by LC-MS, and satisfactory results were achieved. Notably, urine samples exhibited higher accuracy for disease differentiation and triage than serum samples. Apart from that, differential metabolites were selected and metabolite panels were evaluated to demonstrate their representativeness. Metabolic dysregulations were also investigated to gain more knowledge about the pathogenesis of ADs. This research provides a promising method for the application of metabolomics combined with machine learning in precision medicine.

Hypoxia-inducible factor 1 signaling drives placental aging and can provoke preterm labor

Most cases of preterm labor have unknown cause, and the burden of preterm birth is immense. Placental aging has been proposed to promote labor onset, but specific mechanisms remain elusive. We report findings stemming from unbiased transcriptomic analysis of mouse placenta, which revealed that hypoxia-inducible factor 1 (HIF-1) stabilization is a hallmark of advanced gestational timepoints, accompanied by mitochondrial dysregulation and cellular senescence; we detected similar effects in aging human placenta. In parallel in primary mouse trophoblasts and human choriocarcinoma cells, we modeled HIF-1 induction and demonstrated resultant mitochondrial dysfunction and cellular senescence. Transcriptomic analysis revealed that HIF-1 stabilization recapitulated gene signatures observed in aged placenta. Further, conditioned media from trophoblasts following HIF-1 induction promoted contractility in immortalized uterine myocytes, suggesting a mechanism by which the aging placenta may drive the transition from uterine quiescence to contractility at the onset of labor. Finally, pharmacological induction of HIF-1 via intraperitoneal administration of dimethyloxalyl glycine (DMOG) to pregnant mice caused preterm labor. These results provide clear evidence for placental aging in normal pregnancy, and demonstrate how HIF-1 signaling in late gestation may be a causal determinant of the mitochondrial dysfunction and senescence observed within the trophoblast as well as a trigger for uterine contraction.

First Trimester Prediction of Preterm Birth in Patient Plasma with Machine-Learning-Guided Raman Spectroscopy and Metabolomics

Preterm birth (PTB) is the leading cause of infant deaths globally. Current clinical measures often fail to identify women who may deliver preterm. Therefore, accurate screening tools are imperative for early prediction of PTB. Here, we show that Raman spectroscopy is a promising tool for studying biological interfaces, and we examine differences in the maternal metabolome of the first trimester plasma of PTB patients and those that delivered at term (healthy). We identified fifteen statistically significant metabolites that are predictive of the onset of PTB. Mass spectrometry metabolomics validates the Raman findings identifying key metabolic pathways that are enriched in PTB. We also show that patient clinical information alone and protein quantification of standard inflammatory cytokines both fail to identify PTB patients. We show for the first time that synergistic integration of Raman and clinical data guided with machine learning results in an unprecedented 85.1% accuracy of risk stratification of PTB in the first trimester that is currently not possible clinically. Correlations between metabolites and clinical features highlight the body mass index and maternal age as contributors of metabolic rewiring. Our findings show that Raman spectral screening may complement current prenatal care for early prediction of PTB, and our approach can be translated to other patient-specific biological interfaces.

Urine and serum metabolic profiling combined with machine learning for autoimmune disease discrimination and classification

Precision diagnosis and classification of autoimmune diseases (ADs) is challenging due to the obscure symptoms and pathological causes. Biofluid metabolic analysis has the potential for disease screening, in which high throughput, rapid analysis and minimum sample consumption must be addressed. Herein, we performed metabolomic profiling by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) in urine and serum samples. Combined with machine learning (ML), metabolomic patterns from urine achieved the discrimination and classification of ADs with high accuracy. Furthermore, metabolic disturbances among different ADs were also investigated, and provided information of etiology. These results demonstrated that urine metabolic patterns based on MALDI-MS and ML manifest substantial potential in precision medicine.

Combined transcriptome and metabolome analysis reveal key regulatory genes and pathways of feed conversion efficiency of oriental river prawn Macrobrachium nipponense

BACKGROUND

Oriental river prawn Macrobrachium nipponense is an economically important aquaculture species in China, Japan, and Vietnam. In commercial prawn farming, feed cost constitutes about 50 to 65% of the actual variable cost. Improving feed conversion efficiency in prawn culture will not only increase economic benefit, but also save food and protect the environment. The common indicators used for feed conversion efficiency include feed conversion ratio (FCR), feed efficiency ratio (FER), and residual feed intake (RFI). Among these, RFI is much more suitable than FCR and FER during the genetic improvement of feed conversion efficiency for aquaculture species.

RESULTS

In this study, the transcriptome and metabolome of hepatopancreas and muscle of M. nipponense from high RFI low RFI groups, which identified after culture for 75 days, were characterized using combined transcriptomic and metabolomic analysis. A total of 4540 differentially expressed genes (DEGs) in hepatopancreas, and 3894 DEGs in muscle were identified, respectively. The DEGs in hepatopancreas were mainly enriched in KEGG pathways including the metabolism of xenobiotics by cytochrome P450 (down-regulated), fat digestion and absorption (down-regulated) and aminoacyl-tRNA biosynthesis (up-regulated), etc. The DEGs in muscle were mainly enriched in KEGG pathways including the protein digestion and absorption (down-regulated), glycolysis/gluconeogenesis (down-regulated), and glutathione metabolism (up-regulated), etc. At the transcriptome level, the RFI of M. nipponense was mainly controlled in biological pathways such as the high immune expression and the reduction of nutrients absorption capacity. A total of 445 and 247 differently expressed metabolites (DEMs) were identified in the hepatopancreas and muscle, respectively. At the metabolome level, the RFI of M. nipponense was affected considerably by amino acid and lipid metabolism.

CONCLUSIONS

M. nipponense from higher and lower RFI groups have various physiological and metabolic capability processes. The down-regulated genes, such as carboxypeptidase A1, 6-phosphofructokinase, long-chain-acyl-CoA dehydrogenase, et. al., in digestion and absorption of nutrients, and the up-regulated metabolites, such as aspirin, lysine, et. al., in response to immunity could be potential candidate factors contributed to RFI variation for M. nipponense. Overall, these results would provide new insights into the molecular mechanism of feed conversion efficiency and assist in selective breeding to improve feed conversion efficiency in M. nipponense.

Developmental programming: Preconceptional and gestational exposure of sheep to a real-life environmental chemical mixture alters maternal metabolome in a fetal sex-specific manner

BACKGROUND

Everyday, humans are exposed to a mixture of environmental chemicals some of which have endocrine and/or metabolism disrupting actions which may contribute to non-communicable diseases. The adverse health impacts of real-world chemical exposure, characterized by chronic low doses of a mixture of chemicals, are only recently emerging. Biosolids derived from human waste represent the environmental chemical mixtures humans are exposed to in real life. Prior studies in sheep have shown aberrant reproductive and metabolic phenotypes in offspring after maternal biosolids exposure.

OBJECTIVE

To determine if exposure to biosolids perturbs the maternal metabolic milieu of pregnant ewes, in a fetal sex-specific manner.

METHODS

Ewes were grazed on inorganic fertilizer (Control) or biosolids-treated pastures (BTP) from before mating and throughout gestation. Plasma from pregnant ewes (Control n = 15, BTP n = 15) obtained mid-gestation were analyzed by untargeted metabolomics. Metabolites were identified using Agilent MassHunter. Multivariate analyses were done using MetaboAnalyst 5.0 and confirmed using SIMCA.

RESULTS

Univariate and multivariate analysis of 2301 annotated metabolites identified 193 differentially abundant metabolites (DM) between control and BTP sheep. The DM primarily belonged to the super-class of lipids and organic acids. 15-HeTrE, oleamide, methionine, CAR(3:0(OH)) and pyroglutamic acid were the top DM and have been implicated in the regulation of fetal growth and development. Fetal sex further exacerbated differences in metabolite profiles in the BTP group. The organic acids class of metabolites was abundant in animals with male fetuses. Prenol lipid, sphingolipid, glycerolipid, alkaloid, polyketide and benzenoid classes showed fetal sex-specific responses to biosolids.

DISCUSSION

Our study illustrates that exposure to biosolids significantly alters the maternal metabolome in a fetal sex-specific manner. The altered metabolite profile indicates perturbations to fatty acid, arginine, branched chain amino acid and one‑carbon metabolism. These factors are consistent with, and likely contribute to, the adverse phenotypic outcomes reported in the offspring.

A screening test proposal for congenital defects based on maternal serum metabolomics profile

BACKGROUND

Historically, noninvasive techniques are only able to identify chromosomal anomalies that accounted for <50% of all congenital defects; the other congenital defects are diagnosed via ultrasound evaluations in the later stages of pregnancy. Metabolomic analysis may provide an important improvement, potentially addressing the need for novel noninvasive and multicomprehensive early prenatal screening tools. A growing body of evidence outlines notable metabolic alterations in different biofluids derived from pregnant women carrying fetuses with malformations, suggesting that such an approach may allow the discovery of biomarkers common to most fetal malformations. In addition, metabolomic investigations are inexpensive, fast, and risk-free and often generate high performance screening tests that may allow early detection of a given pathology.

OBJECTIVE

This study aimed to evaluate the diagnostic accuracy of an ensemble machine learning model based on maternal serum metabolomic signatures for detecting fetal malformations, including both chromosomal anomalies and structural defects.

STUDY DESIGN

This was a multicenter observational retrospective study that included 2 different arms. In the first arm, a total of 654 Italian pregnant women (334 cases with fetuses with malformations and 320 controls with normal developing fetuses) were enrolled and used to train an ensemble machine learning classification model based on serum metabolomics profiles. In the second arm, serum samples obtained from 1935 participants of the New Zealand Screening for Pregnancy Endpoints study were blindly analyzed and used as a validation cohort. Untargeted metabolomics analysis was performed via gas chromatography-mass spectrometry. Of note, 9 individual machine learning classification models were built and optimized via cross-validation (partial least squares-discriminant analysis, linear discriminant analysis, naïve Bayes, decision tree, random forest, k-nearest neighbor, artificial neural network, support vector machine, and logistic regression). An ensemble of the models was developed according to a voting scheme statistically weighted by the cross-validation accuracy and classification confidence of the individual models. This ensemble machine learning system was used to screen the validation cohort.

RESULTS

Significant metabolic differences were detected in women carrying fetuses with malformations, who exhibited lower amounts of palmitic, myristic, and stearic acids; N-α-acetyllysine; glucose; L-acetylcarnitine; fructose; para-cresol; and xylose and higher levels of serine, alanine, urea, progesterone, and valine (P<.05), compared with controls. When applied to the validation cohort, the screening test showed a 99.4%±0.6% accuracy (specificity of 99.9%±0.1% [1892 of 1894 controls correctly identified] with a sensitivity of 78%±6% [32 of 41 fetal malformations correctly identified]).

CONCLUSION

This study provided clinical validation of a metabolomics-based prenatal screening test to detect the presence of congenital defects. Further investigations are needed to enable the identification of the type of malformation and to confirm these findings on even larger study populations.

Proteomic analysis of amniotic fluid to identify potential targets predicting preterm delivery

Preterm delivery is a common complication of pregnancy which leads to significant neonatal mortality and morbidity. Identifying predictive markers linked to spontaneous preterm delivery (SPTD) is important for effective treatment and prevention of PTD. To explore potential biomarkers related to SPTD, we performed proteomics analysis in amniotic fluid (AF). In total, we enrolled 30 pregnant women with singleton gestation who underwent clinically indicated amniocentesis at 15-24 weeks of gestation. LC-MS analysis was used to analyze the AF samples of 10 women with SPTD < 34 weeks after cervix cerclage (Preterm group), 10 women with term delivery (TD) ≥ 34 weeks after cervix cerclage (Term group), and 10 women who delivered at term (Normal group). ELISA validation was performed for candidate proteins in a second independent cohort. As a result, we identified 44 differentially expressed proteins (DEPs, P < 0.05) via proteomic analysis, and based on that, 9 primary pathways were also determined in SPTD. Results of the ELISA assay confirmed that the increased concentration of Serpin A1, decreased concentrations of Renin and IGFBP4 were significantly associated with SPTD at ≤34 weeks.

Metabolic profiling reveals metabolic features of consolidation therapy in pediatric acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) and its treatment continue to pose substantial risks. To understand ALL more deeply, the metabolome in fasting plasma of 27 ALL patients before and after high-dose methotrexate therapies (consolidation therapy) including methotrexate and 6-mercaptopurine (6-MP) was investigated. Plasma metabolites were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS). Orthogonal projections to latent structures discriminant analysis and significance analysis of microarrays were used to evaluate the metabolic changes. Pathway enrichment and co-expression network analyses were performed to identify clusters of molecules, and 2826 metabolites were identified. Among them, 38 metabolites were identified by univariate analysis, and 7 metabolites that were altered by conditioning therapy were identified by multivariate analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used for pathway enrichment analysis. Among the enriched KEGG pathways, the 3 significantly altered metabolic pathways were pyrimidine metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis; and phenylalanine metabolism. In addition, L-phenylalanine was significantly correlated with blood urea nitrogen (BUN), and palmitoylcarnitine was correlated with aspartate aminotransferase (AST). In summary, consolidation therapy significantly affected pyrimidine- and phenylalanine-associated metabolic pathways in pediatric ALL patients. These findings may provide an insight into the role of metabolic profiling in consolidation treatment and as a potential for pediatric ALL patients.

Placental circadian lincRNAs and spontaneous preterm birth

Long non-coding RNAs (lncRNAs) have a much higher cell- and/or tissue-specificity compared to mRNAs in most cases, making them excellent candidates for therapeutic applications to reduce off-target effects. Placental long non-coding RNAs have been investigated in the pathogenesis of preeclampsia (often causing preterm birth (PTB)), but less is known about their role in preterm birth. Preterm birth occurs in 11% of pregnancies and is the most common cause of death among infants in the world. We recently identified that genes that drive circadian rhythms in cells, termed molecular clock genes, are deregulated in maternal blood of women with spontaneous PTB (sPTB) and in the placenta of women with preeclampsia. Next, we focused on circadian genes-correlated long intergenic non-coding RNAs (lincRNAs, making up most of the long non-coding RNAs), designated as circadian lincRNAs, associated with sPTB. We compared the co-altered circadian transcripts-correlated lincRNAs expressed in placentas of sPTB and term births using two published independent RNAseq datasets (GSE73712 and GSE174415). Nine core clock genes were up- or downregulated in sPTB versus term birth, where the RORA transcript was the only gene downregulated in sPTB across both independent datasets. We found that five circadian lincRNAs (LINC00893, LINC00265, LINC01089, LINC00482, and LINC00649) were decreased in sPTB vs term births across both datasets (p ≤ .0222, FDR≤.1973) and were negatively correlated with the dataset-specific clock genes-based risk scores (correlation coefficient r = -.65 ∼ -.43, p ≤ .0365, FDR≤.0601). Gene set variation analysis revealed that 65 pathways were significantly enriched by these same five differentially expressed lincRNAs, of which over 85% of the pathways could be linked to immune/inflammation/oxidative stress and cell cycle/apoptosis/autophagy/cellular senescence. These findings may improve our understanding of the pathogenesis of spontaneous preterm birth and provide novel insights into the development of potentially more effective and specific therapeutic targets against sPTB.

Placental protein levels in maternal serum are associated with adverse pregnancy outcomes in nulliparous patients

BACKGROUND

The Eunice Kennedy Shriver National Institute of Child Health and Human Development Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be was established to investigate the underlying causes and pathophysiological pathways associated with adverse pregnancy outcomes in nulliparous gravidas.

OBJECTIVE

This study aimed to study placental physiology and identify novel biomarkers concerning adverse pregnancy outcomes, including preterm birth (medically indicated and spontaneous), preeclampsia, small-for-gestational-age neonates, and stillbirth. We measured levels of placental proteins in the maternal circulation in the first 2 trimesters of pregnancy.

STUDY DESIGN

Maternal serum samples were collected at 2 study visits (6-13 weeks and 16-21 weeks), and levels of 9 analytes were measured. The analytes we measured were vascular endothelial growth factor, placental growth factor, endoglin, soluble fms-like tyrosine kinase-1, A disintegrin and metalloproteinase domain-containing protein 12, pregnancy-associated plasma protein A, free beta-human chorionic gonadotropin, inhibin A, and alpha-fetoprotein. The primary outcome was preterm birth between 20 0/7 and 36 6/7 weeks of gestation. The secondary outcomes were spontaneous preterm births, medically indicated preterm births, preeclampsia, small-for-gestational-age neonates, and stillbirth.

RESULTS

A total of 10,038 eligible gravidas were enrolled in the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be cohort, from which a nested case-control study was performed comparing 800 cases with preterm birth (466 spontaneous preterm births, 330 medically indicated preterm births, and 4 unclassified preterm births), 568 with preeclampsia, 406 with small-for-gestational-age birth, and 49 with stillbirth with 911 controls who delivered at term without complications. Although levels of each analyte generally differed between cases and controls at 1 or 2 visits, the odds ratios revealed a <2-fold difference between cases and controls in all comparisons. Receiver operating characteristic curves, generated to determine the relationship between analyte levels and preterm birth and the other adverse pregnancy outcomes, resulted in areas under the receiver operating characteristic curves that were relatively low (range, 0.50-0.64) for each analyte. Logistic regression modeling demonstrated that areas under the receiver operating characteristic curves for predicting adverse pregnancy outcomes were greater using baseline clinical characteristics and combinations of analytes than baseline characteristics alone, but areas under the receiver operating characteristic curves remained relatively low for each outcome (range, 0.65-0.78).

CONCLUSION

We have found significant associations between maternal serum levels of analytes evaluated early in pregnancy and subsequent adverse pregnancy outcomes in nulliparous gravidas. However, the test characteristics for these analytes do not support their use as clinical biomarkers to predict adverse pregnancy outcomes, either alone or in combination with maternal clinical characteristics.

Metabolomics insights into the prenatal exposure effects of polybrominated diphenyl ethers on neonatal birth outcomes

BACKGROUND

Effects of polybrominated diphenyl ethers (PBDEs) on neonatal birth outcomes vary across previous studies, and the related mechanism investigation remains poorly understood, especially at the metabolic level.

OBJECTIVES

To evaluate the associations between prenatal PBDEs exposure and neonatal birth outcomes including gestational age, neonatal weight, birth length, head circumference (HC), Apgar score at 1 min (Apgar1) and 5 min, and further reveal the underlying metabolic disorders in a population-based birth cohort study.

METHODS

Gas chromatography-triple quadrupole tandem mass spectrometry (GC-MS/MS) based targeted method and GC-MS based untargeted method were respectively conducted to obtain PBDE levels and metabolic profiles of 200 placental tissue samples from a typical e-waste recycling area (Guiyu) and reference area (Haojiang) in China. Spearman correlation and regression analyses were applied to assess the associations between the placental PBDE levels and birth outcomes. Metabolome-wide association studies and the meet-in-the-middle approach were employed to explore disruptions linking PBDE exposures and the corresponding adverse birth outcomes.

RESULTS

Eight out of 27 PBDE congeners were detected in placenta with more than 50% frequency in at least one district and significantly higher in Guiyu than those in Haojiang. The lower HC and Apgar1 had significant associations with PBDE exposures after adjustment for potential confounders. A total of 66, 16 and 14 metabolites were significantly correlated with PBDE exposures, HC and Apgar1, respectively. 4 and 12 PBDE-related metabolites were significantly associated with the risks of decreasing neonatal HC and Apgar1. The disrupted metabolites were mainly involved in the pentose phosphate pathway, ascorbate metabolism, threonine metabolism, butanoate metabolism, lipid metabolism, and arginine biosynthesis.

CONCLUSIONS

In this birth cohort, higher placental PBDE levels were significantly associated with the lower HC and Apgar1. The associations might be modified by multiple metabolic disturbances through increasing oxidative stress, mediating neurotoxicity, maternal gut microbiota dysbiosis and vasodilatation regulation.

The landscape of circular RNA in preterm birth

Background

Preterm birth (PTB) is a multifactorial syndrome that seriously threatens the health of pregnant women and babies worldwide. Recently, circular RNAs (circRNAs) have been understood as important regulators of various physiological and pathological processes. However, the expression pattern and potential roles of circRNAs in PTB are largely unclear.

Methods

In this study, we extracted and analyzed the circRNA expression profiles in maternal and fetal samples of preterm and term pregnancies, including maternal plasma, maternal monocytes, myometrium, chorion, placenta, and cord blood. We identified the circRNAs which is associated with PTB in different tissues and explored their relationships from the perspective of the overall maternal-fetal system. Furthermore, co-expression analysis of circRNAs and mRNAs, target microRNAs (miRNAs), and RNA-binding proteins (RBPs), provided new clues about possible mechanisms of circRNA function in PTB. In the end, we investigated the potential special biofunctions of circRNAs in different tissues and their common features and communication in PTB.

Results

Significant differences in circRNA types and expression levels between preterm and term groups have been proved, as well as between tissues. Nevertheless, there were still some PTB-related differentially expressed circRNAs (DECs) shared by these tissues. The functional enrichment analysis showed that the DECs putatively have important tissue-specific biofunctions through their target miRNA and co-expressed mRNAs, which contribute to the signature pathologic changes of each tissue within the maternal-fetal system in PTB (e.g., the contraction of the myometrium). Moreover, DECs in different tissues might have some common biological activities, which are mainly the activation of immune-inflammatory processes (e.g., interleukin1/6/8/17, chemokine, TLRs, and complement).

Conclusions

In summary, our data provide a preliminary blueprint for the expression and possible roles of circRNAs in PTB, which lays the foundation for future research on the mechanisms of circRNAs in PTB.

Prenatal exposure to polycyclic aromatic hydrocarbons and gestational age at birth

BACKGROUND

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous chemicals with mechanisms of toxicity that include endocrine disruption. We examined associations of prenatal urinary PAH with spontaneous preterm birth (PTB) and gestational age (GA) at birth. We also assessed whether infant sex modifies the association of PAH exposure with spontaneous PTB and GA at birth.

METHODS

Participants included 1,677 non-smoking women from three cohorts (CANDLE, TIDES, and GAPPS) in the ECHO PATHWAYS Consortium. Twelve monohydroxylated-PAHs were measured in second trimester maternal urine. Seven metabolites with >60% overall detection were included in analyses: 1-hydroxynaphthalene [1-OH-NAP], 2-hydroxynaphthalene [2-OH-NAP], 2-hydroxyphenanthrene [2-OH-PHEN], 3-hydroxyphenanthrene [3-OH-PHEN], 1/9-hydroxyphenanthrene [1/9-OH-PHEN], 2/3/9-hydroxyfluorene [2/3/9-OH-FLUO], and 1-hydroxypyrene [1-OH-PYR]. Logistic and linear regression models were fit for spontaneous PTB and GA among births ≥34 weeks, respectively, with log₁₀-transformed OH-PAH concentrations as the exposure, adjusted for specific gravity and suspected confounders. Effect modification by infant sex was assessed using interaction terms and marginal estimates.

RESULTS

Percent detection was highest for 2-OH-NAP (99.8%) and lowest for 1-OH-PYR (65.2%). Prevalence of spontaneous PTB was 5.5% (N = 92). Ten-fold higher 2-OH-NAP exposure was associated with 1.60-day (95% CI: -2.92, -0.28) earlier GA at birth. Remaining associations in the pooled population were null. Among females, we observed significant inverse associations between 1-OH-PYR and PTB (OR: 2.65 [95% CI: 1.39, 5.05]); and 2-OH-NAP with GA: -2.46 days [95% CI: -4.15, -0.77]). Among males, we observed an inverse association between 2/3/9-OH-FLUO and PTB (OR = 0.40 [95% CI: 0.17,0.98]). ORs for PTB were higher among females than males for 2-OH-PHEN (p = 0.02) and 1-OH-PYR (p = 0.02).

DISCUSSION

We observed inverse associations of 2-OH-NAP exposure with GA and null associations of remaining OH-PAHs with GA and PTB. Females may be more susceptible to spontaneous PTB or shorter GA following prenatal exposure to some OH-PAHs. This study is the first to assess sex-specific OH-PAH toxicity in relation to spontaneous PTB and GA.

Molecular Gatekeeper Discovery: Workflow for Linking Multiple Exposure Biomarkers to Metabolomics

The exposome reflects multiple exposures across the life-course that can affect health. Metabolomics can reveal the underlying molecular basis linking exposures to health conditions. Here, we explore the concept and general data analysis framework of "molecular gatekeepers"─key metabolites that link single or multiple exposure biomarkers with correlated clusters of endogenous metabolites─to inform health-relevant biological targets. We performed untargeted metabolomics on plasma from 152 adolescent girls participating in the Growing Up Healthy Study in New York City. We then performed network analysis to link metabolites to exposure biomarkers including five trace elements (Cd, Mn, Pb, Se, and Hg) and five perfluorinated chemicals (PFCs; n-PFOS, Sm-PFOS, n-PFOA, PFHxS, and PFNA). We found 144 molecular gatekeepers and annotated 22 of them. Lysophosphatidylcholine (16:0) and taurodeoxycholate were correlated with both n-PFOA and n-PFOS, suggesting a shared dysregulation from multiple xenobiotic exposures. Sphingomyelin (d18:2/14:0) was significantly associated with age at menarche; yet, no direct association was detected between any exposure biomarkers and age at menarche. Thus, molecular gatekeepers can also discover molecular linkages between exposure biomarkers and health outcomes that may otherwise be obscured by complex interactions in direct measurements.

Maternal High-Fat Diet Impairs Placental Fatty Acid β-Oxidation and Metabolic Homeostasis in the Offspring

Maternal overnutrition can affect fetal growth and development, thus increasing susceptibility to obesity and diabetes in later life of the offspring. Placenta is the central organ connecting the developing fetus with the maternal environment. It is indicated placental fatty acid metabolism plays an essential role in affecting the outcome of the pregnancy and fetus. However, the role of placental fatty acid β-oxidation (FAO) in maternal overnutrition affecting glucose metabolism in the offspring remains unclear. In this study, C57BL/6J female mice were fed with normal chow or high-fat diet before and during pregnancy and lactation. The placenta and fetal liver were collected at gestation day 18.5, and the offspring's liver was collected at weaning. FAO-related genes and AMP-activated protein kinase (AMPK) signaling pathway were examined both in the placenta and in the human JEG-3 trophoblast cells. FAO-related genes were further examined in the liver of the fetuses and in the offspring at weaning. We found that dams fed with high-fat diet showed higher fasting blood glucose, impaired glucose tolerance at gestation day 14.5 and higher serum total cholesterol (T-CHO) at gestation day 18.5. The placental weight and lipid deposition were significantly increased in maternal high-fat diet group. At weaning, the offspring mice of high-fat diet group exhibited higher body weight, impaired glucose tolerance, insulin resistance and increased serum T-CHO, compared with control group. We further found that maternal high-fat diet downregulated mRNA and protein expressions of carnitine palmitoyltransferase 2 (CPT2), a key enzyme in FAO, by suppressing the AMPK/Sirt1/PGC1α signaling pathway in the placenta. In JEG-3 cells, protein expressions of CPT2 and CPT1b were both downregulated by suppressing the AMPK/Sirt1/PGC1α signaling pathway under glucolipotoxic condition, but were later restored by the AMPK agonist 5-aminoimidazole-4-carboxyamide ribonucleoside (AICAR). However, there was no difference in CPT2 and CPT1 gene expression in the liver of fetuses and offspring at weaning age. In conclusion, maternal high-fat diet can impair gene expression involved in FAO in the placenta by downregulating the AMPK signaling pathway, and can cause glucose and lipid dysfunction of offspring at weaning, indicating that placental FAO may play a crucial role in regulating maternal overnutrition and metabolic health in the offspring.

Neotropical mustelids: fecal metabolome diversity and its potential for taxonomic discrimination

Chemical profiles of non-invasive biological material, such as feces, have great potential to study elusive animals or those with low population densities. Here, we use a metabolomic approach to evaluate Neotropical mustelids as a biological model to describe the diversity of the metabolites present in fecal samples, as well as to evaluate the potential of chemical profiles for taxonomic discrimination. We collected fecal samples from captive individuals of five species of mustelids occurring in Brazil and analyzed them by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Over 200 compounds have been annotated; "bile acids, alcohols and derivatives" was the most expressive class in the metabolome of all the species. We successfully discriminated three taxonomic groups: 1 - Tayra (Eira barbara); 2 - otters (Lontra longicaudis and Pteronura brasiliensis; 1); and 3 - grisons (Galictis vittata and Galictis cuja). Several compounds seemed to be associated with food intake and the digestive process, while others were found for the first time in Neotropical mustelids. We concluded that mustelids show high metabolome diversity and that species-specific identification through metabolomic profiles is possible, thus contributing to the development and implementation of additional non-invasive approaches in the study of mustelids. This article is protected by copyright. All rights reserved.

Maternal plasma lipids are involved in the pathogenesis of preterm birth

BACKGROUND

Preterm birth is defined by the onset of labor at a gestational age shorter than 37 weeks, and it can lead to premature birth and impose a threat to newborns' health. The Puerto Rico PROTECT cohort is a well-characterized prospective birth cohort that was designed to investigate environmental and social contributors to preterm birth in Puerto Rico, where preterm birth rates have been elevated in recent decades. To elucidate possible relationships between metabolites and preterm birth in this cohort, we conducted a nested case-control study to conduct untargeted metabolomic characterization of maternal plasma of 31 women who experienced preterm birth and 69 controls who underwent full-term labor at 24-28 gestational weeks.

RESULTS

A total of 333 metabolites were identified and annotated with liquid chromatography/mass spectrometry. Subsequent weighted gene correlation network analysis shows that the fatty acid and carene-enriched module has a significant positive association (P = 8e-04, FDR = 0.006) with preterm birth. After controlling for potential clinical confounders, a total of 38 metabolites demonstrated significant changes uniquely associated with preterm birth, where 17 of them were preterm biomarkers. Among 7 machine-learning classifiers, the application of random forest achieved a highly accurate and specific prediction (AUC = 0.92) for preterm birth in testing data, demonstrating their strong potential as biomarkers for preterm births. The 17 preterm biomarkers are involved in cell signaling, lipid metabolism, and lipid peroxidation functions. Additional modeling using only the 19 spontaneous preterm births (sPTB) and controls identifies 16 sPTB markers, with an AUC of 0.89 in testing data. Half of the sPTB overlap with those markers for preterm births. Further causality analysis infers that suberic acid upregulates several fatty acids to promote preterm birth.

CONCLUSIONS

Altogether, this study demonstrates the involvement of lipids, particularly fatty acids, in the pathogenesis of preterm birth.

Cellular Effects of 2',3'-Cyclic Nucleotide Monophosphates in Gram-Negative Bacteria

Organismal adaptations to environmental stimuli are governed by intracellular signaling molecules such as nucleotide second messengers. Recent studies have identified functional roles for the noncanonical 2',3'-cyclic nucleotide monophosphates (2',3'-cNMPs) in both eukaryotes and prokaryotes. In Escherichia coli, 2',3'-cNMPs are produced by RNase I-catalyzed RNA degradation, and these cyclic nucleotides modulate biofilm formation through unknown mechanisms. The present work dissects cellular processes in E. coli and Salmonella enterica serovar Typhimurium that are modulated by 2',3'-cNMPs through the development of cell-permeable 2',3'-cNMP analogs and a 2',3'-cyclic nucleotide phosphodiesterase. Utilization of these chemical and enzymatic tools, in conjunction with phenotypic and transcriptomic investigations, identified pathways regulated by 2',3'-cNMPs, including flagellar motility and biofilm formation, and by oligoribonucleotides with 3'-terminal 2',3'-cyclic phosphates, including responses to cellular stress. Furthermore, interrogation of metabolomic and organismal databases has identified 2',3'-cNMPs in numerous organisms and homologs of the E. coli metabolic proteins that are involved in key eukaryotic pathways. Thus, the present work provides key insights into the roles of these understudied facets of nucleotide metabolism and signaling in prokaryotic physiology and suggest broad roles for 2',3'-cNMPs among bacteria and eukaryotes. IMPORTANCE Bacteria adapt to environmental challenges by producing intracellular signaling molecules that control downstream pathways and alter cellular processes for survival. Nucleotide second messengers serve to transduce extracellular signals and regulate a wide array of intracellular pathways. Recently, 2',3'-cyclic nucleotide monophosphates (2',3'-cNMPs) were identified as contributing to the regulation of cellular pathways in eukaryotes and prokaryotes. In this study, we define previously unknown cell processes that are affected by fluctuating 2',3'-cNMP levels or RNA oligomers with 2',3'-cyclic phosphate termini in E. coli and Salmonella Typhimurium, providing a framework for studying novel signaling networks in prokaryotes. Furthermore, we utilize metabolomics databases to identify additional prokaryotic and eukaryotic species that generate 2',3'-cNMPs as a resource for future studies.

Placental metabolite profiles in late gestation for healthy mice

INTRODUCTION

During pregnancy, appropriate placental metabolism is essential for fetuses to reach their growth potential. However, metabolic mechanisms during pregnancy remain poorly understood. Determination of the levels of placental metabolites in healthy pregnancy and how they change throughout gestation is critical for understanding placental function.

OBJECTIVE

To determine the effects of gestational age on placental metabolites using healthy pregnant mice.

METHODS

In the present study, we collected placental tissue samples from healthy pregnant mice at three timepoints in late gestation (n = 16 placentas per gestational age). Metabolite profiles were determined using ¹H high-resolution magic angle spinning magnetic resonance spectroscopy (HRMAS MRS).

RESULTS

Using HRMAS MRS, we identified 14 metabolites in murine placental tissue samples. The relative concentration of 12 of the 14 metabolites remains unchanged throughout late gestation. Lysine was found to decrease significantly (p = 0.04) and glucose showed an inverted U-shape relationship (p = 0.03) with gestational age.

CONCLUSION

This study demonstrated the feasibility of HRMAS MRS to determine relative metabolite concentrations in murine placental tissue. These findings establish baseline levels of placental tissue metabolite profiles and will serve as reference ranges for future studies using mouse models of fetal distress.

Placental metabolic profiling in gestational diabetes mellitus: An important role of fatty acids

Aim

Gestational diabetes mellitus (GDM) is the most common metabolic disorder during pregnancy. Accumulating studies have reported metabolites that are significantly associated with the development of GDM. However, studies on the metabolism of placenta, the most important organ of maternal‐fetal energy and material transport, are extremely rare. This study aimed to identify and discuss the relationship between differentially expressed metabolites (DEM) and clinical parameters of the mothers and newborns.

Methods

In this study, metabolites from 63 placenta tissues (32 GDM and 31 normal controls) were assayed by ultra‐performance liquid chromatography‐high resolution mass spectrometry (UPLC‐HRMS).

Results

A total of 1297 annotated metabolites were detected, of which 87 significantly different in GDM placenta. Lipids and lipid‐like molecules accounted for 62.1% of DEM as they were significantly enriched via the “biosynthesis of unsaturated fatty acids” and “fatty acid biosynthesis” pathways. Linoleic acid and α‐linolenic acid appeared to be good biomarkers for the prediction and diagnosis of GDM. In addition, the level of PC(14:0/18:0) was negatively correlated with neonatal weight. 14 metabolites significantly different in male and female offspring, with the most increase in female newborns.

Conclusion

Even if maternal blood glucose level is well controlled, there are still metabolic abnormalities in GDM. Lipids and lipid‐like molecules were the main differential metabolites, especially unsaturated fatty acids.

Human Placental Transcriptome Reveals Critical Alterations in Inflammation and Energy Metabolism with Fetal Sex Differences in Spontaneous Preterm Birth

A well-functioning placenta is crucial for normal gestation and regulates the nutrient, gas, and waste exchanges between the maternal and fetal circulations and is an important endocrine organ producing hormones that regulate both the maternal and fetal physiologies during pregnancy. Placental insufficiency is implicated in spontaneous preterm birth (SPTB). We proposed that deficits in the capacity of the placenta to maintain bioenergetic and metabolic stability during pregnancy may ultimately result in SPTB. To explore our hypothesis, we performed a RNA-seq study in male and female placentas from women with SPTB (<36 weeks gestation) compared to normal pregnancies (≥38 weeks gestation) to assess the alterations in the gene expression profiles. We focused exclusively on Black women (cases and controls), who are at the highest risk of SPTB. Six hundred and seventy differentially expressed genes were identified in male SPTB placentas. Among them, 313 and 357 transcripts were increased and decreased, respectively. In contrast, only 61 differentially expressed genes were identified in female SPTB placenta. The ingenuity pathway analysis showed alterations in the genes and canonical pathways critical for regulating inflammation, oxidative stress, detoxification, mitochondrial function, energy metabolism, and the extracellular matrix. Many upstream regulators and master regulators important for nutrient-sensing and metabolism were also altered in SPTB placentas, including the PI3K complex, TGFB1/SMADs, SMARCA4, TP63, CDKN2A, BRCA1, and NFAT. The transcriptome was integrated with published human placental metabolome to assess the interactions of altered genes and metabolites. Collectively, significant and biologically relevant alterations in the transcriptome were identified in SPTB placentas with fetal sex disparities. Altered energy metabolism, mitochondrial function, inflammation, and detoxification may underly the mechanisms of placental dysfunction in SPTB.

Conceptus metabolomic profiling reveals stage-specific phenotypes leading up to pregnancy recognition in cattle†

Reproductive efficiency in livestock is a major driver of sustainable food production. The poorly understood process of ruminant conceptus elongation (a) prerequisites maternal pregnancy recognition, (b) is essential to successful pregnancy establishment, and (c) coincides with a period of significant conceptus mortality. Conceptuses at five key developmental stages between Days 8-16 were recovered and cultured in vitro for 6 h prior to conditioned media analysis by untargeted ultrahigh-performance liquid chromatography tandem mass spectroscopy. This global temporal biochemical interrogation of the ex situ bovine conceptus unearths two antithetical stage-specific metabolic phenotypes during tubular (metabolically retentive) vs. filamentous (secretory) development. Moreover, the retentive conceptus phenotype on Day 14 coincides with an established period of elevated metabolic density in the uterine fluid of heifers with high systemic progesterone-a model of accelerated conceptus elongation. These data, combined, suggest a metabolic mechanism underpinning conceptus elongation, thereby enhancing our understanding of the biochemical reciprocity of maternal-conceptus communication, prior to maternal pregnancy recognition.

Chemical Fingerprint Analysis and Ultra-Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry-Based Metabolomics Study of the Protective Effect of Buxue Yimu Granule in Medical-Induced Incomplete Abortion Rats

Medical abortion is a common method to terminate an early pregnancy and often causes serious complications such as abnormal uterine bleeding and endometritis. Buxue Yimu granule (BYG) is a well-known traditional Chinese medicine prescription composed of five kinds of drugs and is widely used in gynecology and obstetrics. The aim of the present study was to establish the quality standard of BYG and investigate its protective effect on incomplete abortion. The chemical fingerprint of BYG was established by high performance liquid chromatography (HPLC). The major compounds of BYG were determined by ultra-performance liquid chromatography with triple quadrupole mass spectrometry. An incomplete abortion rat model was induced by intragastric administration of mifepristone (8.3 mg·kg^-1) combined with misoprostol (100.0 μg·kg^-1) during early pregnancy. The serum levels of human chorionic gonadotrophin (HCG), estradiol (E₂), and progesterone (PG) were determined. The serum endogenous metabolites were analyzed by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). Multivariate analysis, including partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), was employed to analyze the metabolic profiles, and MetaboAnalyst was used to investigate the metabolic pathways. Furthermore, hematoxylin-eosin staining (HE) was used to evaluate the histopathological changes in uterine tissue. The expression levels of VEGFA and NF-κB were detected by immunohistochemistry. The results indicated that HPLC fingerprint analysis can be successfully used to assess the quality of BYG. The medical-induced incomplete abortion rats were clearly separated from control rats, and the biochemical changes were gradually restored to normal after administration of BYG. Moreover, 19 potential biomarkers, including N-lactoylleucine, 2-piperidinone, isobutyryl-l-carnitine, eicosapentaenoylcholine, LysoPC(14:0), LysoPC(20:5), physagulin C, LysoPC(18:3), leukotriene D5, deoxycholic acid 3-glucuronide, glycine, pregnanediol 3-O-glucuronide, LysoPC(18:2), LysoPC(17:0/0:0), N-acetyl-leukotriene E4, LysoPC(18:0), platelet-activating factor, LysoPA(24:1), and LysoPC(18:1), which were mainly related to the amino acids metabolism, lipids metabolism, and bile acid biosynthesis, were identified. Consequently, BYG exerts a potential protective role in the intervention of incomplete abortion by anti-inflammatory, promote endometrial repair, and regulate the metabolic disorders.

Intrauterine Inflammation Alters the Transcriptome and Metabolome in Placenta

Placental insufficiency is implicated in spontaneous preterm birth (SPTB) associated with intrauterine inflammation. We hypothesized that intrauterine inflammation leads to deficits in the capacity of the placenta to maintain bioenergetic and metabolic stability during pregnancy ultimately resulting in SPTB. Using a mouse model of intrauterine inflammation that leads to preterm delivery, we performed RNA-seq and metabolomics studies to assess how intrauterine inflammation alters gene expression and/or modulates metabolite production and abundance in the placenta. 1871 differentially expressed genes were identified in LPS-exposed placenta. Among them, 1,149 and 722 transcripts were increased and decreased, respectively. Ingenuity pathway analysis showed alterations in genes and canonical pathways critical for regulating oxidative stress, mitochondrial function, metabolisms of glucose and lipids, and vascular reactivity in LPS-exposed placenta. Many upstream regulators and master regulators important for nutrient-sensing and mitochondrial function were also altered in inflammation exposed placentae, including STAT1, HIF1α, mTOR, AMPK, and PPARα. Comprehensive quantification of metabolites demonstrated significant alterations in the glucose utilization, metabolisms of branched-chain amino acids, lipids, purine and pyrimidine, as well as carbon flow in TCA cycle in LPS-exposed placenta compared to control placenta. The transcriptome and metabolome were also integrated to assess the interactions of altered genes and metabolites. Collectively, significant and biologically relevant alterations in the placenta transcriptome and metabolome were identified in placentae exposed to intrauterine inflammation. Altered mitochondrial function and energy metabolism may underline the mechanisms of inflammation-induced placental dysfunction.

Lipidomic profiling of chorionic villi in the placentas of women with chronic venous disease

Background: Chronic venous disease (CVD) is a prevalent lower limb venous pathology that especially affects women, who also show an increased risk of this disease during pregnancy. Studies have shown significant structural changes in the placentas of women with CVD and several markers of tissue damage have been also described. Patients and Methods: To try to understand the different placental pathologies, research efforts have focused on examining metabolomic profiles as indicators of the repercussions of these vascular disorders. This study examines changes produced in the metabolomic profiles of chorionic villi in the placentas of women with CVD. In a study population of 12 pregnant women, 6 with and 6 without CVD, we compared through mass spectroscopy coupled to ultra-high performance liquid chromatography (UHPLC-MS), 240 metabolites in chorionic villus samples. Results: This study is the first to detect in the placental villi of pregnant women with CVD, modifications in lysophosphatidylcholines and amino acids along with diminished levels of other lipids such as triglycerides, sphingomyelins, and non-esterified omega 9 fatty acids, suggesting a role of these abnormalities in the pathogenesis of CVD. Conclusions: Our findings are a starting point for future studies designed to examine the impacts of CVD on maternal and fetal well-being.