A High-Throughput Targeted Metabolomics Workflow for the Detection of 200 Polar Metabolites in Central Carbon Metabolism

Arginase 1 and L-arginine coordinate fetal lung development and the initiation of labor in mice

Fetal development and parturition are precisely regulated processes that involve continuous crosstalk between the mother and the fetus. Our previous discovery that wild-type mice carrying steroid receptor coactivator (Src)-1 and Src-2 double-deficient fetuses exhibit impaired lung development and delayed labor, which indicates that the signals for parturition emanate from the fetus. In this study, we perform RNA sequencing and targeted metabolomics analyses of the lungs from fetal Src-1/-2 double-knockout mice and find that expression of arginase 1 (Arg1) is significantly decreased, accompanied by increased levels of the Arg1 substrate L-arginine. Knockdown of Arg1 in the lungs of fetal mice induces apoptosis of epithelial cells and dramatically delays initiation of labor. Moreover, treatment of human myometrial smooth muscle cells with L-arginine significantly inhibits spontaneous contractions by attenuating activation of NF-κB and downregulating expression of contraction-associated protein genes. Transcription factors GR and C/EBPβ increase transcription of Arg1 in an Src-1/Src-2-dependent manner. These findings provide new evidence that fetus-derived factors may play dual roles in coordinating fetal lung development and the initiation of labor.

Cancer metabolites: promising biomarkers for cancer liquid biopsy

Cancer exerts a multitude of effects on metabolism, including the reprogramming of cellular metabolic pathways and alterations in metabolites that facilitate inappropriate proliferation of cancer cells and adaptation to the tumor microenvironment. There is a growing body of evidence suggesting that aberrant metabolites play pivotal roles in tumorigenesis and metastasis, and have the potential to serve as biomarkers for personalized cancer therapy. Importantly, high-throughput metabolomics detection techniques and machine learning approaches offer tremendous potential for clinical oncology by enabling the identification of cancer-specific metabolites. Emerging research indicates that circulating metabolites have great promise as noninvasive biomarkers for cancer detection. Therefore, this review summarizes reported abnormal cancer-related metabolites in the last decade and highlights the application of metabolomics in liquid biopsy, including detection specimens, technologies, methods, and challenges. The review provides insights into cancer metabolites as a promising tool for clinical applications.

Comparison of Widely Targeted Metabolomics and Untargeted Metabolomics of Wild Ophiocordyceps Sinensis

The authors of this paper conducted a comparative metabolomic analysis of Ophiocordyceps sinensis (OS), providing the metabolic profiles of the stroma (OSBSz) and sclerotia (OSBSh) of OS by widely targeted metabolomics and untargeted metabolomics. The results showed that 778 and 1449 metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. The metabolites in OSBSz and OSBSh are significantly differentiated; 71 and 96 differentially expressed metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. This suggests that these 71 metabolites (riboflavine, tripdiolide, bromocriptine, lumichrome, tetrahymanol, citrostadienol, etc.) and 96 metabolites (sancycline, vignatic acid B, pirbuterol, rubrophen, epalrestat, etc.) are potential biomarkers. 4-Hydroxybenzaldehyde, arginine, and lumichrome were common differentially expressed metabolites. Using the widely targeted metabolomics approach, the key pathways identified that are involved in creating the differentiation between OSBSz and OSBSh may be nicotinate and nicotinamide metabolism, thiamine metabolism, riboflavin metabolism, glycine, serine, and threonine metabolism, and arginine biosynthesis. The differentially expressed metabolites identified using the untargeted metabolomics approach were mainly involved in arginine biosynthesis, terpenoid backbone biosynthesis, porphyrin and chlorophyll metabolism, and cysteine and methionine metabolism. The purpose of this research was to provide support for the assessment of the differences between the stroma and sclerotia, to furnish a material basis for the evaluation of the physical effects of OS, and to provide a reference for the selection of detection methods for the metabolomics of OS.

Longitudinal metabolomics profiling of serum amino acids in rotenone-induced Parkinson's mouse model

Recently, the detailed etiology and pathogenesis of Parkinson's disease (PD) have not been fully clarified yet. Increasing evidences suggested that the disturbance of peripheral branched-chain amino acids (BCAAs) metabolism can promote the occurrence and progression of neurodegenerative diseases through neuroinflammatory signaling. Although there are several studies on the metabolomics of PD, longitudinal study of metabolic pathways is still lacking. Therefore, the purpose of the present study was to determine the longitudinal alterations in serum amino acid profiles in PD mouse model. Gas chromatography-mass spectrometry (GC-MS) was applied to detect serum amino acid concentrations in C57BL/6 mice after 0, 3 and 4 weeks of oral administration with rotenone. Then the data were analysed by principal component analysis (PCA) and orthogonal projection to latent structures (OPLS) analysis. Finally, the correlations between different kinds of serum amino acids and behaviors in rotenone-treated mice were also explored. Compared with 0-week mice, the levels of L-isoleucine and L-leucine were down-regulated in 3-week and 4-week mice, especially in 4-week mice. Moreover, the comprehensive analysis showed that L-isoleucine and L-leucine were negatively correlated with pole-climbing time and positively correlated with fecal weight and water content of PD mice. These results not only suggested that L-isoleucine and L-leucine may be potential biomarkers, but also pointed out the possibility of treating PD by intervening in the circulating amino acids metabolism.

Gut Microbiota Dysbiosis Aggravates Mycoplasma gallisepticum Colonization in the Chicken Lung

Mycoplasma gallisepticum (MG) is the pathogen that causes chronic respiratory diseases in chickens. Gut microbiota plays an important role in maintaining body health and resisting respiratory infection, but the correlation between gut microbiota and MG infection is poorly defined. Therefore, in this study, the correlation between gut microbiota and MG infection was explored by disturbing gut microbiota in chickens with antibiotic cocktail. The results showed that the gut microbiota dysbiosis impairs pulmonary immune response against MG infection. It has been noted that MG colonization in the lung was significantly increased following gut microbiota dysbiosis, and this could be reversed by intranasally administrated toll-like receptor 2 (TLR2) ligand, recombinant chicken IL-17 protein or recombinant chicken granulocyte-macrophage colony-stimulating factor (GM-CSF) protein. In addition, the levels of short-chain fatty acids (SCFAs) and vitamin A were significantly reduced in gut microbiota dysbiosis group, however, butyric acid or vitamin A as feed additives promoted MG clearance in the lung of gut microbiota dysbiosis group via increasing TLR2/IL17/GM-CSF and host defense peptides genes expression. The present study revealed an important role of gut microbiota in the defense against MG colonization in the lung of chicken.

RIPK1 regulates starvation resistance by modulating aspartate catabolism

RIPK1 is a crucial regulator of cell death and survival. Ripk1 deficiency promotes mouse survival in the prenatal period while inhibits survival in the early postnatal period without a clear mechanism. Metabolism regulation and autophagy are critical to neonatal survival from severe starvation at birth. However, the mechanism by which RIPK1 regulates starvation resistance and survival remains unclear. Here, we address this question by discovering the metabolic regulatory role of RIPK1. First, metabolomics analysis reveals that Ripk1 deficiency specifically increases aspartate levels in both mouse neonates and mammalian cells under starvation conditions. Increased aspartate in Ripk1^−/− cells enhances the TCA  flux and ATP production. The energy imbalance causes defective autophagy induction by inhibiting the AMPK/ULK1 pathway. Transcriptional analyses demonstrate that Ripk1^−/− deficiency downregulates gene expression in aspartate catabolism by inactivating SP1. To summarize, this study reveals that RIPK1 serves as a metabolic regulator responsible for starvation resistance.

RIPK1 is critical for normal development and cell death. Here, the authors identify a metabolic role for RIPK1 in aspartate homeostasis, as increased aspartate levels in RIPK1-deficient cells inhibits starvation-induced autophagy by ULK1.

Metabolomics meets lipidomics: Assessing the small molecule component of metabolism

Metabolomics, including lipidomics, is emerging as a quantitative biology approach for the assessment of energy flow through metabolism and information flow through metabolic signaling; thus, providing novel insights into metabolism and its regulation, in health, healthy ageing and disease. In this forward-looking review we provide an overview on the origins of metabolomics, on its role in this postgenomic era of biochemistry and its application to investigate metabolite role and (bio)activity, from model systems to human population studies. We present the challenges inherent to this analytical science, and approaches and modes of analysis that are used to resolve, characterize and measure the infinite chemical diversity contained in the metabolome (including lipidome) of complex biological matrices. In the current outbreak of metabolic diseases such as cardiometabolic disorders, cancer and neurodegenerative diseases, metabolomics appears to be ideally situated for the investigation of disease pathophysiology from a metabolite perspective.

Targeted metabolomics study of early pathological features in hippocampus of triple transgenic Alzheimer's disease male mice

Alzheimer's disease (AD) is a serious neurodegenerative disease in people of age 65 or above. The detailed etiology and pathogenesis of AD have not been elucidated yet. In this study, the hippocampi of 2- and 6-month-old triple transgenic Alzheimer's disease male mice and age-sex-matched wild-type (WT) mice were analyzed by using targeted metabolomics approach. Compared with WT mice, 24 and 60 metabolites were found with significant differences in 2- and 6-month-old AD mice. Among these, 14 metabolites were found common while 10 metabolites showed consistent variable trends in both groups. These differential metabolites are found associated with amino acid, lipid, vitamin, nucleotide-related base, neurotransmitter and energy metabolisms, and oxidative stress. The results suggest that these differential metabolites might play a critical role in AD pathophysiology, and may serve as potential biomarkers for AD. Moreover, the results highlight the involvement of abnormal purine, pyrimidine, arginine, and proline metabolism, along with glycerophospholipid metabolism in early pathology of AD. For the first time, several differential metabolites are found to be associated with AD in this study. Targeted metabolomics can be used for rapid and accurate quantitative analysis of specific target metabolites associated with AD.

Comparative Metabolomics Study Revealed Difference in Central Carbon Metabolism between Sika Deer and Red Deer Antler

The antler regeneration has been well studied for the past two decades and adopted in the regenerative medicine model for studying on developmental biology. Despite our growing knowledge of functional molecules regulating antler regeneration, we still do not know whether antler from different deer species possess the exact same mechanism or not. Our previous comparative study between sika deer and red deer suggests that the metabolic pathways between them are profoundly different based on protein level. Therefore, the metabolomic technology is used to identify and quantify the metabolites in antler samples, providing interesting insights into differential metabolite profile of antlers between sika deer and red deer. The distinct metabolic characteristics of sika deer compared to red deer provide an opportunity to explain why the red deer antler with a larger size. The enrichment analysis of differential metabolites showed that three pathways including glycine and serine metabolism, methionine metabolism, and pterine biosynthesis had a significant difference between two antler groups.

Recent advances in the application of metabolomics for food safety control and food quality analyses

As one of the omics fields, metabolomics has unique advantages in facilitating the understanding of physiological and pathological activities in biology, physiology, pathology, and food science. In this review, based on developments in analytical chemistry tools, cheminformatics, and bioinformatics methods, we highlight the current applications of metabolomics in food safety, food authenticity and quality, and food traceability. Additionally, the combined use of metabolomics with other omics techniques for "foodomics" is comprehensively described. Finally, the latest developments and advances, practical challenges and limitations, and requirements related to the application of metabolomics are critically discussed, providing new insight into the application of metabolomics in food analysis.

Implementation of liquid chromatography-high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: A tutorial

Untargeted metabolomics is now widely recognized as a useful tool for exploring metabolic changes taking place in biological systems under different conditions. By its nature, this is a highly interdisciplinary field of research, and mastering all of the steps comprised in the pipeline can be a challenging task, especially for those researchers new to the topic. In this tutorial, we aim to provide an overview of the most widely adopted methods of performing LC-HRMS-based untargeted metabolomics of biological samples. A detailed protocol is provided in the Supplementary Information for rapidly implementing a basic screening workflow in a laboratory setting. This tutorial covers experimental design, sample preparation and analysis, signal processing and data treatment, and, finally, data analysis and its biological interpretation. Each section is accompanied by up-to-date literature to guide readers through the preparation and optimization of such a workflow, as well as practical information for avoiding or fixing some of the most frequently encountered pitfalls.