Mass spectrometry-based metabolomics for the investigation of antibiotic-bacterial interactions.

With the development of analytical technologies especially mass spectrometry, metabolomics is becoming increasingly hot in the field of studying antibiotic-bacterial interactions. On the one hand, metabolomics can reveal metabolic perturbations in bacteria in the presence of antibiotics and expose metabolic mechanisms. On the other hand, through in-depth analysis of bacterial metabolic profiles, biomarkers and bioactive secondary metabolites with great potential as drug precursors can be discovered. This review focuses on the experimental workflow of bacterial metabolomics and its application to study the interaction between bacteria and antibiotics. Metabolomics improves the understanding of antibiotic lethality, reveals metabolic perturbations in antibiotic-resistant bacteria, guides the diagnosis and antibiotic treatment of infectious diseases, and aids in the exploration of antibacterial metabolites in nature. Furthermore, current limitations and directions for future developments in this area are discussed.

A new approach towards highly sensitive detection of endogenous N-acetylaspartic acid, N-acetylglutamic acid, and N-acetylaspartylglutamic acid in brain tissues based on strong anion exchange monolith microextraction coupled with UHPLC-MS/MS.

A novel in-tube solid-phase microextraction coupled with an ultra-high performance liquid chromatography-mass spectrometry method has been established for simultaneous quantification of three crucial brain biomarkers N-acetylaspartic acid (NAA), N-acetylglutamic acid (NAG), and N-acetylaspartylglutamic acid (NAAG). A polymer monolith with quaternary ammonium as the functional group was designed and exhibited efficient enrichment of target analytes through strong anion exchange interaction. Under the optimized conditions, the proposed method displayed wide linear ranges (0.1-80 nM for NAA and NAG, 0.2-160 nM for NAAG) with good precision (RSDs were lower than 15%) and low limits of detection (0.019-0.052 nM), which is by far the most sensitive approach for NAA, NAG, and NAAG determination. Furthermore, this approach has been applied to measure the target analytes in mouse brain samples, and endogenous NAA, NAG, and NAAG were successfully detected and quantified from only around 5 mg of cerebral cortex, cerebellum, and hippocampus. Compared with existing methods, the newly developed method in the current study provides highest sensitivity and lowest sample consumption for NAA, NAG, and NAAG measurements, which would potentially be utilized in determining and tracking these meaningful brain biomarkers in diseases or treatment processes, benefiting the investigations of pathophysiology and treatment of brain disorders.

Metabolomics as a Critical Tool for Studying Clinical Surgery.

Metabolomics enables the analysis of metabolites within an organism, which offers the closest direct measurement of the physiological activity of the organism, and has advanced efforts to characterize metabolic states, identify biomarkers, and investigate metabolic pathways. A high degree of innovation in analytical techniques has promoted the application of metabolomics, especially in the study of clinical surgery. Metabolomics can be employed as a clinical testing method to maximize therapeutic outcomes, and has been applied in rapid diagnosis of diseases, timely postoperative monitoring, prognostic assessment, and personalized medicine. This review focuses on the use of mass spectrometry and nuclear magnetic resonance-based metabolomics in clinical surgery, including identifying metabolic changes before and after surgery, finding disease-associated biomarkers, and exploring the potential of personalized therapy. Challenges and opportunities of metabolomics in organ transplantation are also discussed, with a particular emphasis on metabolomics in donor organ evaluation and protection, prognostic outcome prediction, as well as postoperative adverse reaction monitoring. In the end, current limitations of metabolomics in clinical surgery and future research directions are presented.

Mass spectrometry-based quantitation combined with time-dependent metabolomics to discover metabolic features in human neurogenesis using neural constructs generated from neural progenitor cells.

Direct studies focusing on the human brain are difficult to plan and conduct due to ethical and practical reasons. The advent of human pluripotent stem cell (hPSC)-derived neurons has revolutionized the research of the human brain and central nervous system, but relevant analytical techniques have been much less explored. Herein, we have designed a novel bioanalytical strategy to discover the characteristics of human neurogenesis using liquid chromatography-mass spectrometry-based quantitation and time-dependent metabolomics in combination with hPSC-derived neural constructs. To examine the growth of neurons in vitro, a quantitative method for the simultaneous measurement of N-acetylaspartic acid (NAA) and N-acetylglutamic acid (NAG) in a culture medium was established. The analysis of endogenous NAA and NAG concentrations over 28 days of neural cell culture not only illustrated the growth and maturation process of neural progenitors, but also confirmed the successful achievement of human neural constructs. Depending on the quantitative results, day 0, 10, 18, and 28 samples representing different growth phases were selected for further investigation of the global metabolic changes in developing human neurons. A versatile non-targeted, time-dependent metabolomics study identified 17 significantly changed metabolites and revealed the altered metabolic pathways including amino acid metabolism (tryptophan, phenylalanine, aspartate and beta-alanine metabolisms), pantothenate and coenzyme A biosynthesis, fatty acid metabolism, and purine and pyrimidine metabolism. The new metabolite profiles and overall metabolic pathways advance our understanding of human neurodevelopment. Additionally, the bioanalytical approach proposed in this study opens an interesting window for the capture and evaluation of the complex metabolic states of human neural cells, which would potentially be utilized in other in vitro models relevant to pathophysiology and treatment of neurological disorders, benefiting biomarker discovery and metabolic mechanism interpretation.