Lipidomic profiling of amniotic fluid and its application in fetal lung maturity prediction

Lipidomic profiling of amniotic fluid reveals aberrant fetal lung development and fetal growth disrupted by lipid disorders during gestational asthma

This study aimed to investigate how maternal asthma during pregnancy disrupts fetal lung development by altering lipid metabolism in the amniotic fluid, which is crucial for fetal development. A pregnancy-induced asthma model was established in female rats using house dust mite (HDM) as a common allergen. The fetuses were divided into four groups based on whether the mother and fetus were exposed to the allergen: PBS+PBS, PBS+HDM, HDM+PBS, and HDM+HDM. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was employed to analyze changes in the lipid profile of the amniotic fluid and bronchoalveolar lavage fluid (BALF). Principal component analysis (PCA) and ChemRICH methods were used to explore the potential relationship between lipid metabolism abnormalities and impaired fetal lung development. The results indicate that maternal asthma exacerbates asthma-related inflammatory markers in fetuses, leading to pathological changes in the lungs and elevated levels of cytokines IL-5, IL-13, and IgE. Additionally, 18 differential lipids, primarily oxygenated lipids, were identified in the amniotic fluid after modeling, suggesting an enhanced oxidative stress environment for the fetus. This environment causes metabolic disturbances in various lipid groups in fetal lungs, with the HDM+HDM group showing significant abnormalities in lipids critical for lung development, including phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and fatty acids (FA). In conclusion, gestational asthma can reshape the lipid profile in the amniotic fluid and BALF, significantly disrupting fetal growth and lung development. Restoring normal lipid metabolism in the amniotic fluid and fetal lungs may offer a potential therapeutic approach to managing aberrant fetal lung development in asthmatic mothers.

Temporal metabolomics state in pregnant rat: Analysis of amniotic fluid, placenta, and maternal plasma at embryonic and fetal time points

INTRODUCTION

During pregnancy, the dynamic metabolic demands for fetal growth require a continuous supply of essential metabolites. Understanding maternal metabolome changes during gestation is crucial for predicting disease risks in neonates.

METHODS

The study aimed to characterize the placental and amniotic fluid (AF) metabolomes during gestation in rats at gestational days GD-13 and 19 reflecting the end of the embryonic and fetal periods, respectively, and the maternal plasma, using metabolomics (LC-MS) and chemometrics. The objective was to highlight, through univariate and multivariate analyses, the complementarity of the data obtained from these different biological matrices.

RESULTS

The biological matrix had more impact on the metabolome composition than the gestational stage. The placental and AF metabolomes showed specific metabolome evolving over the two gestational stages. Analyzing the three targeted metabolomes revealed evolving pathways in arginine and proline metabolism/glutathione metabolism and phenylalanine metabolism; purine metabolism; and carbohydrate metabolism. Significantly, lipid metabolism in the placenta exhibited substantial changes with higher levels of certain phosphatidylethanolamine and sphingomyelins at GD19 while some cholesteryl esters and some glycosphingolipids levels being in higher levels at GD13.

DISCUSSION

These data highlight the metabolic gradients (mainly in placenta, also in AF, but only a few in plasma) observed through embryonic patterning and organ development during mid-to late gestation.

Network pharmacology combined with metabolomics to explore the mechanism for Lonicerae Japonicae flos against respiratory syncytial virus

BACKGROUND

Respiratory Syncytial Virus (RSV) stands out as a primary contributor to lower respiratory tract infections and hospitalizations, particularly in infants. Lonicerae japonicae flos (LJF), a traditional Chinese medicine renowned for its efficacy against various viral infections, including RSV, has been widely employed. Despite its common use, the precise therapeutic mechanism of LJF against RSV remains elusive. This study aimed to investigate the underlying mechanism of LJF against RSV through network pharmacology and metabolomics.

METHODS

In this study, based on network pharmacology, potential targets related to LJF and RSV were obtained from PubChem and Swiss Target Prediction. The core targets and pathways were established and verified by enrichment analysis and molecular docking. The anti-RSV efficacy of LJF was determined by in vitro experiments. Additionally, metabolomics analysis was integrated, allowing for the identification of differential metabolites and their correlation with targets following LJF treatment in the context of RSV infection.

RESULTS

A total of 23 active ingredients and 780 targets were obtained, of which 102 targets were associated with LJF anti-RSV. The construction of the corresponding Protein-Protein Interaction (PPI) network unveiled potential core targets, including STAT3, TNF, and AKT1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that LJF's anti-RSV effects primarily involve key pathways such as the PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, and FoxO signaling pathway. Molecular docking showed that ZINC03978781, 4,5'-Retro-.beta.,.beta.-Carotene -3,3'-dione, 4',5'-didehydro and 7-epi-Vogeloside had better binding ability. The cellular assay showed that the therapeutic index of LJF against RSV was 4.79. Furthermore, 18 metabolites were screened as potential biomarkers of LJF against RSV, and these metabolites were mainly involved in the pathways of purine metabolism, linoleic acid metabolism, alpha-linolenic acid metabolism, and other related pathways.

CONCLUSIONS

The intergration of network pharmacology and metabolomics can clarify the active targets and related pathways of LJF against RSV, which could provide a valuable reference for further research and clinical application of LJF.

Qushi Huayu decoction ameliorates non-alcoholic fatty liver disease in rats by modulating gut microbiota and serum lipids

Introduction

Non-alcoholic fatty liver disease (NAFLD) is a multifactorial disease. As a clinical empirical prescription of traditional Chinese medicine, Qushi Huayu decoction (QHD) has attracted considerable attention for its advantages in multi-target treatment of NAFLD. However, the intervention mechanism of QHD on abnormal lipid levels and gut microbiota in NAFLD has not been reported.

Methods

Therefore, we verified the therapeutic effect of QHD on high-fat diet (HFD)-induced NAFLD in rats by physiological parameters and histopathological examination. In addition, studies on gut microbiota and serum lipidomics based on 16S rRNA sequencing and ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) were conducted to elucidate the therapeutic mechanism of NAFLD in QHD.

Results

The changes in gut microbiota in NAFLD rats are mainly reflected in their diversity and composition, while QHD treated rats restored these changes. The genera Blautia, Lactobacillus, Allobaculum, Lachnoclostridium and Bacteroides were predominant in the NAFLD group, whereas, Turicibacter, Blautia, Sporosarcina, Romboutsia, Clostridium_sensu_stricto_1, Allobaculum, and Psychrobacter were predominant in the NAFLD+QHD group. Lipid subclasses, including diacylglycerol (DG), triglycerides (TG), phosphatidylethanolamine (PE), phosphatidylcholine (PC), phosphatidic acid (PA), phosphatidylserine (PS), lysophosphatidylinositol (LPI), and phosphatidylglycerol (PG), were significantly different between the NAFLD and the control groups, while QHD treatment significantly altered the levels of DG, TG, PA, lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), and platelet activating factor (PAF). Finally, Spearman's correlation analysis showed that NAFLD related differential lipid molecules were mainly associated with the genera of Bacteroides, Blautia, Lachnoclostridium, Clostridium_sensu_stricto_1, and Turicibacter, which were also significantly correlated with the biological parameters of NAFLD.

Discussion

Taken together, QHD may exert beneficial effects by regulating the gut microbiota and thus intervening in serum lipids.

Metabolomics coupled with network pharmacology study on the protective effect of Keguan-1 granules in LPS-induced acute lung injury

CONTEXT

Keguan-1 (KG-1) plays a vital role in enhancing the curative effects, improving quality of life, and reducing the development of acute lung injury (ALI).

OBJECTIVE

To unravel the protective effect and underlying mechanism of KG-1 against ALI.

MATERIALS AND METHODS

C57BL/6J mice were intratracheally instilled with lipopolysaccharide to establish the ALI model. Then, mice in the KG-1 group received a dose of 5.04 g/kg for 12 h. The levels of proinflammatory cytokines, chemokines, and pathological characteristics were determined to explore the effects of KG-1. Next, untargeted metabolomics was used to identify the differential metabolites and involved pathways for KG-1 anti-ALI. Network pharmacology was carried out to predict the putative active components and drug targets of KG-1 anti-ALI.

RESULTS

KG-1 significantly improved the levels of TNF-α (from 2295.92 ± 529.87 pg/mL to 1167.64 ± 318.91 pg/mL), IL-6 (from 4688.80 ± 481.68 pg/mL to 3604.43 ± 382.00 pg/mL), CXCL1 (from 4361.76 ± 505.73 pg/mL to 2981.04 ± 526.18 pg/mL), CXCL2 (from 5034.09 ± 809.28 pg/mL to 2980.30 ± 747.63 pg/mL), and impaired lung histological damage. Untargeted metabolomics revealed that KG-1 significantly regulated 12 different metabolites, which mainly related to lipid, amino acid, and vitamin metabolism. Network pharmacology showed that KG-1 exhibited anti-ALI effects through 17 potentially active components acting on seven putative drug targets to regulate four metabolites.

DISCUSSION AND CONCLUSIONS

This work elucidated the therapeutic effect and underlying mechanism by which KG-1 protects against ALI from the view of the metabolome, thus providing a scientific basis for the usage of KG-1.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research.

OBJECTIVES

This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data.

RESULTS

The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities.

CONCLUSIONS

The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

Candidate Circulating Biomarkers of Spontaneous Miscarriage After IVF-ET Identified via Coupling Machine Learning and Serum Lipidomics Profiling

Spontaneous miscarriage is a common pregnancy complication. Multiple etiologies have been proposed such as genetic aberrations, endocrinology disorder, and immunologic derangement; however, the relevance of circulating lipidomes to the specific condition remains unclear. In the present study, lipidomics profiling was examined on serum of women with spontaneous miscarriage after in vitro fertilization and embryo transfer (IVF-ET). Screening and analysis of differential lipid levels were conducted using a machine learning approach to verify the stability and validity of potential serum biomarkers. Seven lipid species presented significant differences between the abortion and term birth patients, including three types of sphingomyelins (SMs), two types of diglycerides (DGs), one phosphatidylcholine (PC), and one lysophosphatidylethanolamine (LPE). All the SMs presented with a fold change of > 1, while both the PC and LPE had a fold change of < 1. The DG containing two saturated fatty acyl chains was decreased, but that containing two unsaturated fatty acyl chains was increased in the miscarriage group compared to the control group. This study reveals the relevance of lipid profiles to spontaneous abortion after IVF-ET, providing potential biomarkers and therapeutic targets for the specific clinical scenario.

Induced sputum metabolomic profiles and oxidative stress are associated with chronic obstructive pulmonary disease (COPD) severity: potential use for predictive, preventive, and personalized medicine

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease, and metabolomics plays a hub role in predictive, preventive, and personalized medicine (PPPM) related to COPD. This study thus aimed to reveal the role of induced sputum metabolomics in predicting COPD severity. In this pilot study, a total of 20 COPD patients were included. The induced sputum metabolites were assayed using a liquid chromatography-mass spectrometry (LC-MS/MS) system. Five oxidative stress products (myeloperoxidase (MPO), superoxide dismutase (SOD), glutathione (GSH), neutrophil elastase (NE), and 8-iso-PGF2α) in induced sputum were measured by ELISA, and the metabolomic profiles were distinguished by principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA). The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for pathway enrichment analysis, and a significant difference in induced sputum metabolomics was observed between moderate and severe COPD. The KEGG analysis revealed that the glycerophospholipid metabolism pathway was downregulated in severe COPD. Due to the critical role of glycerophospholipid metabolism in oxidative stress, significant negative correlations were discovered between glycerophospholipid metabolites and three oxidative stress products (SOD, MPO, and 8-iso-PGF2α). The diagnostic values of SOD, MPO, and 8-iso-PGF2α in induced sputum were found to exhibit high sensitivities and specificities in the prediction of COPD severity. Collectively, this study provides the first identification of the association between induced sputum metabolomic profiles and COPD severity, indicating the potential value of metabolomics in PPPM for COPD management. The study also reveals the correlation between glycerophospholipid metabolites and oxidative stress products and their value for predicting COPD severity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-020-00227-w.

Lipidomic profiling of amniotic fluid and its application in fetal lung maturity prediction

Background

The pulmonary surfactant especially lipids in amniotic fluid can reflect the development stage of fetal lung maturity (FLM). However, the conventional lecithin/sphingomyelin (L/S) ratio method by thin layer chromatography (TLC) is insufficient and inconvenient for FLM prediction in clinical practice.

Methods

The amniotic fluid samples were collected from the pregnant women in labor or undergoing amniocentesis and analyzed for its lipid contents with the liquid chromatography coupled with high‐resolution mass spectrometry (LC‐HRMS) method and the lamellar body count (LBC) method. To reveal the lipidomic profiling of different FLM stages, three groups of amniotic fluid samples including 8 from premature group (gestational week (GW) < 37), 10 from mature group (GW < 37), and 10 from mature group (GW > 38) were compared with the control group (n = 6) of 18 GWs separately.

Results

In the FLM prediction study, the sensitivity of the LC‐HRMS method and LBC method was 91% and 73%, respectively; the specificity was 100% and 95%, respectively. The most significant metabolic pathway was linoleic acid metabolism between the premature group and the control group. Both glycerophospholipid metabolism and glycosylphosphatidylinositol‐anchor biosynthesis were enriched in the mature groups. In search of potential FLM prediction markers in amniotic fluid, 8 phosphatidylcholines, 1 sphingomyelin, and 1 phosphatidylethanolamine were significantly increased in the mature groups compared with the premature group.

Conclusion

An efficient LC‐HRMS method for L/S ratio in predicting FLM was established. The linoleic acid metabolism may play an important role in the fetal lung development.