Comprehensive Lipidomic and Metabolomic Analysis for Studying Metabolic Changes in Lung Tissue Induced by a Vaccine against Respiratory Syncytial Virus

Research on the metabolic regulation mechanism of Yangyin Qingfei decoction plus in severe pneumonia caused by Mycoplasma pneumoniae in mice

Introduction: With amazing clinical efficacy, Yangyin Qingfei Decoction Plus (YQDP), a well-known and age-old Chinese compound made of ten Chinese botanical drugs, is utilized in clinical settings to treat a range of respiratory conditions. This study examines the impact of Yangyin Qingfei Decoction (YQDP) on lung tissue metabolic products in severe Mycoplasma pneumoniae pneumonia (SMPP) model mice and examines the mechanism of YQDP in treating MP infection using UPLC-MS/MS technology. Methods: YQDP's chemical composition was ascertained by the use of Agilent 1260 Ⅱ high-performance liquid chromatography. By using a nasal drip of 1010 CCU/mL MP bacterial solution, an SMPP mouse model was created. The lung index, pathology and ultrastructural observation of lung tissue were utilized to assess the therapeutic effect of YQDP in SMPP mice. Lung tissue metabolites were found in the normal group, model group, and YQDP group using UPLC-MS/MS technology. Using an enzyme-linked immunosorbent test (ELISA), the amount of serum inflammatory factors, such as interleukin-6 (IL-6) and tumor necrosis factor α (TNF-α), was found. Additionally, the protein expression of PI3K, P-PI3K, AKT, P-AKT, NF-κB, and P-NF-κB was found using Western blot. Results: The contents of chlorogenic acid, paeoniflorin, forsythrin A, forsythrin, and paeonol in YQDP were 3.480 ± 0.051, 3.255 ± 0.040, 3.612 ± 0.017, 1.757 ± 0.031, and 1.080 ± 0.007 mg/g respectively. YQDP can considerably lower the SMPP mice's lung index (p < 0.05). In the lung tissue of YQDP groups, there has been a decrease (p < 0.05) in the infiltration of inflammatory cells at varying concentrations in the alveoli compared with the model group. A total of 47 distinct metabolites, including choline phosphate, glutamyl lysine, L-tyrosine, 6-thioinosine, Glu Trp, 5-hydroxydecanoate, etc., were linked to the regulation of YQDP, according to metabolomics study. By controlling the metabolism of porphyrins, pyrimidines, cholines, fatty acids, sphingolipids, glycerophospholipids, ferroptosis, steroid hormone biosynthesis, and unsaturated fatty acid biosynthesis, enrichment analysis suggested that YQDP may be used to treat SMPP. YQDP can lower the amount of TNF-α and IL-6 in model group mice as well as downregulate P-PI3K, P-AKT, and P-NF-κB expression (p < 0.05). Conclusion: A specific intervention effect of YQDP is observed in SMPP model mice. Through the PI3K/Akt/NF-κB signaling pathways, YQDP may have therapeutic benefits by regulating the body's metabolism of α-Linoleic acid, sphingolipids, glycerophospholipids, arachidonic acid, and the production of unsaturated fatty acids.

Analysis of temporal metabolic rewiring for human respiratory syncytial virus infection by integrating metabolomics and proteomics

INTRODUCTION

Human respiratory syncytial virus (HRSV) infection causes significant morbidity, and no effective treatments are currently available. Viral infections induce substantial metabolic changes in the infected cells to optimize viral production. Metabolites that reflect the interactions between host cells and viruses provided an opportunity to identify the pathways underlying severe infections.

OBJECTIVE

To better understand the metabolic changes caused by HRSV infection, we analyzed temporal metabolic profiling to provide novel targets for therapeutic strategies for inhaled HRSV infection.

METHODS

The epithelial cells and BALB/c mice were infected with HRSV. Protein and mRNA levels of inflammation factors were measured by using quantitative reverse transcription polymerase chain reaction and enzyme-linked immunosorbent assay. Untargeted metabolomics, lipidomics and proteomics were performed using liquid chromatography coupled with mass spectrometry to profile the metabolic phenotypic alterations in HRSV infection.

RESULTS

In this study, we evaluated the inflammatory responses in vivo and in vitro and investigated the temporal metabolic rewiring of HRSV infection in epithelial cells. We combined metabolomics and proteomic analyses to demonstrate that the redox imbalance was further provoked by increasing glycolysis and anaplerotic reactions. These responses created an oxidant-rich microenvironment that elevated reactive oxygen species levels and exacerbated glutathione consumption.

CONCLUSION

These observations indicate that adjusting for metabolic events during a viral infection could represent a valuable approach for reshaping the outcome of infections.

Metabolomic Profiling of Lungs from Mice Reveals the Variability of Metabolites in Pneumocystis Infection and the Metabolic Abnormalities in BAFF-R-Deficient Mice

Purpose

The incidence of Pneumocystis pneumonia (PCP) in patients without human immunodeficiency virus (HIV) has been increasing. In this study, we aimed to investigate the metabolic changes in Pneumocystis infection and the metabolic abnormalities in B-cell-activating factor receptor (BAFF-R)-deficient mice with Pneumocystis infection.

Methods

The important function of B cells during Pneumocystis infection is increasingly recognized. In this study, a Pneumocystis-infected mouse model was constructed in BAFF-R^-/- mice and wild-type (WT) mice. Lungs of uninfected WT C57BL/6, WT Pneumocystis-infected, and BAFF-R^-/- Pneumocystis-infected mice were used for metabolomic analyses to compare the metabolomic profiles among the groups, with the aim of exploring the metabolic influence of Pneumocystis infection and the influence of mature B-cell deficiency during infection.

Results

The results indicated that many metabolites, mainly lipids and lipid-like molecules, were dysregulated in Pneumocystis-infected WT mice compared with uninfected WT C57BL/6 mice. The data also demonstrated significant changes in tryptophan metabolism, and the expression levels of key enzymes of tryptophan metabolism, such as indoleamine 2,3-dioxygenase 1 (IDO1), were significantly upregulated. In addition, B-cell development and function might be associated with lipid metabolism. We found a lower level of alitretinoin and the abnormalities of fatty acid metabolism in BAFF-R^-/- Pneumocystis-infected mice. The mRNA levels of enzymes associated with fatty acid metabolism in the lung were upregulated in BAFF-R^-/- Pneumocystis-infected mice and positively correlated with the level of IL17A, thus suggesting that the abnormalities of fatty acid metabolism may be associated with greater inflammatory cell infiltration in the lung tissue of BAFF-R^-/- Pneumocystis-infected mice compared with the WT Pneumocystis-infected mice.

Conclusion

Our data revealed the variability of metabolites in Pneumocystis-infected mice, suggesting that the metabolism plays a vital role in the immune response to Pneumocystis infection.

The metabolic and lipidomic profiling of the effects of tracheal occlusion in a rabbit model of congenital diaphragmatic hernia

PURPOSE

Fetal tracheal occlusion (TO) reverses the pulmonary hypoplasia associated with congenital diaphragmatic hernia (CDH), but its mechanism of action remains poorly understood. 'Omic' readouts capture metabolic and lipid processing function, which aid in understanding CDH and TO metabolic mechanisms.

METHODS

CDH was created in fetal rabbits at 23 days, TO at 28 days and lung collection at 31 days (Term ∼32 days). Lung-body weight ratio (LBWR) and mean terminal bronchiole density (MTBD) were determined. In a cohort, left and right lungs were collected, weighed, and samples homogenized, and extracts collected for non-targeted metabolomic and lipidomic profiling via LC-MS and LC-MS/MS, respectively.

RESULTS

LBWR was significantly lower in CDH while CDH + TO was similar to controls (p = 0.003). MTBD was significantly higher in CDH fetuses and restored to control and sham levels in CDH + TO (p < 0.001). CDH and CDH + TO resulted in significant differences in metabolome and lipidome profiles compared to sham controls. A significant number of altered metabolites and lipids between the controls and CDH groups and the CDH and CDH + TO fetuses were identified. Significant changes in the ubiquinone and other terpenoid-quinone biosynthesis pathway and the tyrosine metabolism pathway were observed in CDH + TO.

CONCLUSION

CDH + TO reverses pulmonary hypoplasia in the CDH rabbit, in association with a specific metabolic and lipid signature. A synergistic untargeted 'omics' approach provides a global signature for CDH and CDH + TO, highlighting cellular mechanisms among lipids and other metabolites, enabling comprehensive network analysis to identify critical metabolic drivers in disease pathology and recovery.

TYPE OF STUDY

Basic Science, Prospective.

LEVEL OF EVIDENCE

II.

Metabolomic Analysis Reveals Potential Biomarkers and the Underlying Pathogenesis Involved in Mycoplasma Pneumoniae Pneumonia

Although previous studies have reported the use of metabolomics for infectious diseases, little is known about the potential function of plasma metabolites in children infected with Mycoplasma pneumoniae (MP). Here, a combination of liquid chromatography-quadrupole time-of-flight mass spectrometry and random forest-based classification model was used to provide a broader range of applications in MP diagnosis. In the training cohort, plasma from 63 MP pneumonia children (MPPs), 37 healthy controls (HC) and 29 infectious disease controls (IDC) was collected. After multivariate analyses, 357 metabolites were identified to be differentially expressed among MPP, HC and IDC groups, and 3 metabolites (568.5661, 459.3493 and 411.3208) had high diagnostic values. In an independent cohort with 57 blinded subjects, samples were successfully classified into different groups, demonstrating the reliability of these biomarkers for distinguishing MPPs from controls. A metabolomic signature analysis identified major classes of glycerophospholipids, sphingolipids and fatty acyls were increased in MPPs. These markedly altered metabolites are mainly involved in glycerophospholipid and sphingolipid metabolism. As the ubiquitous building blocks of eukaryotic cell membranes, dysregulated lipid metabolism indicates damage of the cellular membrane and the activation of immunity in MPPs. Moreover, lipid metabolites, differentially expressed between severe and mild MPPs, were correlated with the markers of extrapulmonary complications, suggesting that they may be involved in MPP disease severity. These findings may offer new insights into biomarker selection and the pathogenesis of MPP in children.

A Distinctive Human Metabolomics Alteration Associated with Osteopenic and Osteoporotic Patients

Osteoporosis is a common progressive metabolic bone disease resulting in decreased bone mineral density (BMD) and a subsequent increase in fracture risk. The known bone markers are not sensitive and specific enough to reflect the balance in the bone metabolism. Finding a metabolomics-based biomarker specific for bone desorption or lack of bone formation is crucial for predicting bone health earlier. This study aimed to investigate patients' metabolomic profiles with low BMD (LBMD), including those with osteopenia (ON) and osteoporosis (OP), compared to healthy controls. An untargeted mass spectrometry (MS)-based metabolomics approach was used to analyze serum samples. Results showed a clear separation between patients with LBMD and control (Q² = 0.986, R² = 0.994), reflecting a significant difference in the dynamic of metabolic processes between the study groups. A total of 116 putatively identified metabolites were significantly associated with LBMD. Ninety-four metabolites were dysregulated, with 52 up- and 42 downregulated in patients with LBMD compared to controls. Histidine metabolism, aminoacyl-tRNA biosynthesis, glyoxylate, dicarboxylate metabolism, and biosynthesis of unsaturated fatty acids were the most common metabolic pathways dysregulated in LBMD. Furthermore, 35 metabolites were significantly dysregulated between ON and OP groups, with 11 up- and 24 downregulated in ON compared to OP. Among the upregulated metabolites were 3-carboxy-4-methyl-5-propyl-2-2furanopropionic acid (CMPF) and carnitine derivatives (i.e., 3-hydroxy-11-octadecenoylcarnitine, and l-acetylcarnitine), whereas phosphatidylcholine (PC), sphingomyelin (SM), and palmitic acid (PA) were among the downregulated metabolites in ON compared to OP. This study would add a layer to understanding the possible metabolic alterations associated with ON and OP. Additionally, this identified metabolic panel would help develop a prediction model for bone health and OP progression.

Comprehensive Serum Lipidomics for Detecting Incipient Dementia in Parkinson's Disease

While a number of methods are available for analyzing lipids, unbiased untargeted lipidomics with high coverage remains a challenge. In this work, we report a study of isotope-standard-assisted liquid chromatography mass spectrometry lipidomics of serum for biomarker discovery. We focus on Parkinson's disease (PD), a neurodegenerative disorder that often progresses to dementia. Currently, the diagnosis of PD is purely clinical and there is limited ability to predict which PD patients will transition to dementia, hampering early interventions. We studied serum samples from healthy controls and PD patients with no clinical signs of dementia. A follow-up 3 years later revealed that a subset of PD patients had transitioned to dementia. Using the baseline samples, we constructed two biomarker panels to differentiate (1) PD patients from healthy controls and (2) PD patients that remained cognitively stable from PD patients with incipient dementia (diagnosed 3 years after sample collection). The proposed biomarker panels displayed excellent performance and may be useful for detecting prodromal PD dementia, allowing early interventions and prevention efforts. The biochemistry of significantly changed lipids is also discussed within the current knowledge of neurological pathologies. Our results are promising and future work using a larger cohort of samples is warranted.

Metabolic Profiling from an Asymptomatic Ferret Model of SARS-CoV-2 Infection

Coronavirus disease (COVID-19) is a contagious respiratory disease that is causing significant global morbidity and mortality. Understanding the impact of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection on the host metabolism is still in its infancy but of great importance. Herein, we investigated the metabolic response during viral shedding and post-shedding in an asymptomatic SARS-CoV-2 ferret model (n = 6) challenged with two SARS-CoV-2 isolates. Virological and metabolic analyses were performed on (minimally invasive) collected oral swabs, rectal swabs, and nasal washes. Fragments of SARS-CoV-2 RNA were only found in the nasal wash samples in four of the six ferrets, and in the samples collected 3 to 9 days post-infection (referred to as viral shedding). Central carbon metabolism metabolites were analyzed during viral shedding and post-shedding periods using a dynamic Multiple Reaction Monitoring (dMRM) database and method. Subsequent untargeted metabolomics and lipidomics of the same samples were performed using a Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry (LC-QToF-MS) methodology, building upon the identified differentiated central carbon metabolism metabolites. Multivariate analysis of the acquired data identified 29 significant metabolites and three lipids that were subjected to pathway enrichment and impact analysis. The presence of viral shedding coincided with the challenge dose administered and significant changes in the citric acid cycle, purine metabolism, and pentose phosphate pathways, amongst others, in the host nasal wash samples. An elevated immune response in the host was also observed between the two isolates studied. These results support other metabolomic-based findings in clinical observational studies and indicate the utility of metabolomics applied to ferrets for further COVID-19 research that advances early diagnosis of asymptomatic and mild clinical COVID-19 infections, in addition to assessing the effectiveness of new or repurposed drug therapies.

High-coverage quantitative liver metabolomics using perfused and non-perfused liver tissues

Comprehensive analysis of the liver metabolome can be very useful for discovering disease biomarkers and studying diseases, especially liver-related diseases. However, the presence of a relatively large amount of blood in liver tissue may have a profound effect on liver tissue metabolome analysis. We designed a study to address this issue in order to develop a liver metabolomics workflow based on high-coverage quantitative metabolome analysis using differential chemical isotope labeling (CIL) LC-MS. In the first set of experiments, we compared the metabolomes of mouse serum, non-perfused liver, and perfused liver without and with varying amounts of blood added. We found that there was a significant metabolome difference between the perfused liver and non-perfused liver. To illustrate the effects of perfusion conditions on tissue metabolome analysis, we analyzed the mouse livers that were subjected to perfusion under two different conditions. We found that ice-cold temperature perfusion led to less change of the liver metabolome, compared to room temperature perfusion; however, there was still a significant metabolome difference between the ice-cold-perfused liver and the non-perfused liver. Finally, we applied the method to a chemical (carbon tetrachloride) exposure liver injury model to examine the effects of blood in liver on the detection of significantly changed metabolites in two comparative groups of mice. Using multivariate and univariate analyses of the serum and liver metabolomes of control and diseased mice, we detected many unique significant metabolites in serum as well as in liver. This work demonstrates that perfusion can alter the liver metabolome significantly. Therefore, we recommend the use of non-perfused liver for high-coverage liver metabolomics.

Tissue Lipidomic Alterations Induced by Prolonged Dexamethasone Treatment

Dexamethasone is a synthetic glucocorticoid medication vastly used to treat abnormal immune responses and inflammation. Although the medication is well-established in the medical community, the prolonged treatment with high dosages of dexamethasone may lead to severe adverse effects through mechanisms that are not yet well-known. Lipids are a large class of hydrophobic molecules involved in energy storage, signaling, modulation of gene expression, and membranes. Hence, untargeted lipidomics may help unravel the biochemical alterations following prolonged treatment with high dosages of dexamethasone. We performed comprehensive lipidomic analyses of brain, heart, kidney, liver, and muscle samples obtained from rats that were treated with intramuscular injections of dexamethasone for 14 weeks compared to healthy controls. The employed methodology and statistical analysis showed that phosphatidic acids, glycerophospholipids, plasmalogens, and fatty acids are deeply affected by prolonged use of the medication. Brain tissue was only mildly affected, but skeletal muscle showed a strong accumulation of lipids that may be correlated with alterations in the energy metabolism, myopathy, and oxidative processes. This work provides new insights into the mechanisms of action and adverse effects for one of the most commonly prescribed class of drugs in the world.

Lipidome Alterations Induced by Cystic Fibrosis, CFTR Mutation, and Lung Function

Cystic fibrosis is a genetic pathology characterized by abnormal accumulation of mucus in the respiratory, gastrointestinal, and reproductive tracts, caused by mutations in the CFTR gene. Although the classical presentation of the condition is well known, there is still a need for a better characterization of metabolic alterations related to cystic fibrosis and different genotypic mutations. We employed untargeted, comprehensive lipidomics of blood serum samples to investigate alterations in the lipid metabolism related to the pathology, mutation classes, and lung function decline. Six unique biomarker candidates were able to independently differentiate diseased individuals from healthy controls with excellent performance. Cystic fibrosis patients showed dyslipidemia for most lipid subclasses, with significantly elevated odd-chain and polyunsaturated fatty acyl lipids. Phosphatidic acids and diacylglycerols were particularly affected by different genotypic mutation classes. We selected a biomarker panel composed of four lipids, including two ceramides, one sphingomyelin, and one fatty acid, which correctly classified all validation samples from classes III and IV. A biomarker panel of five oxidized lipids was further selected to differentiate patients with reduced lung function, measured as predicted FEV1%. Our results indicate that cystic fibrosis is deeply related to lipid metabolism and provide new clues for the investigation of the disease mechanisms and therapeutic targets.