Unraveling the Cyclization of l-Argininosuccinic Acid in Biological Samples: A Study via Mass Spectrometry and NMR Spectroscopy

CE-MS-Based Clinical Metabolomics of Human Plasma

Capillary electrophoresis coupled to mass spectrometry (CE-MS) has emerged as a powerful analytical technique with significant implications for clinical research and diagnostics. The integration of information from CE and MS strengthens confidence in the identification of compounds present in clinical samples. The ability of CE to separate molecules based on their electrophoretic mobility coupled to MS enables the accurate identification and quantification of analytes, even in complex biological matrices such as human plasma.Here, we present a detailed protocol for an untargeted metabolomics study using CE-MS and its application in a study on human plasma from patients suffering Long COVID syndrome. The protocol ranges from sample preparation to biological interpretation, detailing a workflow enabling the analysis of cationic and anionic compounds, metabolite identification, and data processing.

Metabolomics for enhanced clinical understanding of inflammatory bowel disease

Metabolomics is an emerging field involving the systematic identification and quantification of numerous metabolites in biological samples. Precision medicine applies multiomics systems biology to individual patients for reliable diagnostic classification, disease monitoring, and treatment. Multiomics systems biology encompasses genomics, transcriptomics, proteomics, epigenomics, and metabolomics. Therefore, metabolomic techniques could be highly valuable for future clinical decision-making. This review provides a technical overview of two commonly used techniques for metabolomics measurements: mass spectrometry (MS) and proton nuclear magnetic resonance (1H NMR) spectroscopy. We also discuss recent clinical advances in these techniques. Individuals with inflammatory bowel disease (IBD) exhibit significant variability in prognosis and response to treatment. Since both genetic predisposition and environmental factors contribute to this condition, targeting the metabolome may provide key insights for distinguishing and profiling patients with different clinical needs. Additionally, the considerable overlap in the clinical presentation of various disease subtypes emphasizes the need for enhanced diagnostic methods to improve patient care.

Microwave Radiation Caused Dynamic Metabolic Fluctuations in the Mammalian Hippocampus

To investigate the dynamic changes in hippocampal metabolism after microwave radiation using liquid chromatography in tandem with mass spectrometry/mass spectrometry (LC-MS/MS) and to identify potential biomarkers. Wistar rats were randomly assigned to a sham group and a microwave radiation group. The rats in the microwave radiation group were exposed to 2.856 GHz for 15 min for three times, with 5 min intervals. The rats in the sham group were not exposed. Transmission electron microscope revealed blurring of the synaptic cleft and postsynaptic dense thickening in hippocampal neurons after microwave radiation. Metabolomic analysis revealed 38, 24, and 39 differentially abundant metabolites at 3, 7, and 14 days after radiation, respectively, and the abundance of 9 metabolites, such as argininosuccinic acid, was continuously decreased. After microwave radiation, the abundance of metabolites such as argininosuccinic acid was successively decreased, indicating that these metabolites could be potential biomarkers for hippocampal tissue injury.

Profiling of polar ionogenic metabolites in Polish wines by capillary electrophoresis-mass spectrometry

The composition of wine is determined by a complex interaction between environmental factors, genetic factors (i.e., grape varieties), and winemaking practices (including technology and storage). Metabolomics using NMR spectroscopy, GC-MS, and/or LC-MS has shown to be a useful approach for assessing the origin, authenticity, and quality of various wines. Nonetheless, the use of additional analytical techniques with complementary separation mechanisms may aid in the deeper understanding of wine's metabolic processes. In this study, we demonstrate that CE-MS is a very suitable approach for the efficient profiling of polar ionogenic metabolites in wines. Without using any sample preparation or derivatization, wine was analyzed using a 10-min CE-MS workflow with interday RSD values for 31 polar and charged metabolites below 3.8% and 23% for migration times and peak areas, respectively. The utility of this workflow for the global profiling of polar ionogenic metabolites in wine was evaluated by analyzing different cool-climate Polish wine samples.

Optimization of metabolomic data processing using NOREVA

A typical output of a metabolomic experiment is a peak table corresponding to the intensity of measured signals. Peak table processing, an essential procedure in metabolomics, is characterized by its study dependency and combinatorial diversity. While various methods and tools have been developed to facilitate metabolomic data processing, it is challenging to determine which processing workflow will give good performance for a specific metabolomic study. NOREVA, an out-of-the-box protocol, was therefore developed to meet this challenge. First, the peak table is subjected to many processing workflows that consist of three to five defined calculations in combinatorially determined sequences. Second, the results of each workflow are judged against objective performance criteria. Third, various benchmarks are analyzed to highlight the uniqueness of this newly developed protocol in (1) evaluating the processing performance based on multiple criteria, (2) optimizing data processing by scanning thousands of workflows, and (3) allowing data processing for time-course and multiclass metabolomics. This protocol is implemented in an R package for convenient accessibility and to protect users' data privacy. Preliminary experience in R language would facilitate the usage of this protocol, and the execution time may vary from several minutes to a couple of hours depending on the size of the analyzed data.

Enhancing confidence of metabolite annotation in Capillary Electrophoresis-Mass Spectrometry untargeted metabolomics with relative migration time and in-source fragmentation

Capillary electrophoresis coupled to mass spectrometry is a power tool in untargeted metabolomics studies to analyze charged and polar compounds. However, identification is a challenge due to the variability of migration times and the lack of MS/MS spectra in CE-TOF-MS, the type of instruments most frequently employed. We present here a CE-MS search platform incorporated in CEU Mass Mediator to annotate metabolites with a confidence level L2. For its the development we analyzed 226 compounds using two fragmentor voltages: 100 and 200 V. The information obtained, such as relative migration times (RMT) and in-source fragments, were incorporated into the platform. In addition, we validated the CE-MS search functionality using different types of biological samples such as plasma samples (human, rat, and rabbit), mouse macrophages, and human urine. The RMT tolerance percentage for the search of metabolites has been determined, establishing 5% for all compounds, except for the compounds migrating in the electro-osmotic flow, for which the tolerance should be of 10%. It has also been demonstrated the robustness of the in-source fragmentation, which makes possible the annotation of compounds by means of their fragmentation pattern. As an example, 3-methylhistidine and 1-methilhistidine, whose RMT are very close, have been annotated. Studies of the fragmentation mechanisms of acyl-L-carnitines have shown that in-source fragmentation follows the general fragmentation rules and is a suitable alternative to MS/MS.