Untargeted Lipidomic Approach for Studying Different Nervous System Tissues of the Murine Model of Krabbe Disease.

Krabbe disease is a rare neurodegenerative disease with an autosomal recessive character caused by a mutation in the GALC gene. The mutation leads to an accumulation of psychosine and a subsequent degeneration of oligodendrocytes and Schwann cells. Psychosine is the main biomarker of the disease. The Twitcher mouse is the most commonly used animal model to study Krabbe disease. Although there are many references to this model in the literature, the lipidomic study of nervous system tissues in the Twitcher model has received little attention. This study focuses on the comparison of the lipid profiles of four nervous system tissues (brain, cerebellum, spinal cord, and sciatic nerve) in the Twitcher mouse compared to the wild-type mouse. Altogether, approximately 230 molecular species belonging to 19 lipid classes were annotated and quantified. A comparison at the levels of class, molecular species, and lipid building blocks showed significant differences between the two groups, particularly in the sciatic nerve. The in-depth study of the lipid phenotype made it possible to hypothesize the genes and enzymes involved in the changes. The integration of metabolic data with genetic data may be useful from a systems biology perspective to gain a better understanding of the molecular basis of the disease.

Combining Feature-Based Molecular Networking and Contextual Mass Spectral Libraries to Decipher Nutrimetabolomics Profiles.

Untargeted metabolomics approaches deal with complex data hindering structural information for the comprehensive analysis of unknown metabolite features. We investigated the metabolite discovery capacity and the possible extension of the annotation coverage of the Feature-Based Molecular Networking (FBMN) approach by adding two novel nutritionally-relevant (contextual) mass spectral libraries to the existing public ones, as compared to widely-used open-source annotation protocols. Two contextual mass spectral libraries in positive and negative ionization mode of ~300 reference molecules relevant for plant-based nutrikinetic studies were created and made publicly available through the GNPS platform. The postprandial urinary metabolome analysis within the intervention of Vaccinium supplements was selected as a case study. Following the FBMN approach in combination with the added contextual mass spectral libraries, 67 berry-related and human endogenous metabolites were annotated, achieving a structural annotation coverage comparable to or higher than existing non-commercial annotation workflows. To further exploit the quantitative data obtained within the FBMN environment, the postprandial behavior of the annotated metabolites was analyzed with Pearson product-moment correlation. This simple chemometric tool linked several molecular families with phase II and phase I metabolism. The proposed approach is a powerful strategy to employ in longitudinal studies since it reduces the unknown chemical space by boosting the annotation power to characterize biochemically relevant metabolites in human biofluids.

Evaluation of polarity switching for untargeted lipidomics using liquid chromatography coupled to high resolution mass spectrometry.

Untargeted lipidomics using liquid chromatography high-resolution mass spectrometry (LC-HRMS) was performed using polarity switching, and in positive and negative polarity separately on the same set of serum samples, and the performances of the methods were evaluated. Polarity switching causes an increase in the cycle time of the HRMS measurements (1.18 s/cycle vs 0.27 s/cycle), resulting in fewer data points across chromatographic peaks. The coefficient of variation (CV) was on average lower for the added isotopically labelled standards in pooled samples (QC) and patient samples using separate polarities (QC = 5.6%, samples = 12.5%) compared to polarity switching (QC = 8.5%, samples = 13.4%), but the difference was not statistically significant. For the endogenous features measured in the QCs polarity switching resulted in on average significantly higher CVs (3.80 (p = 4.25e-30) and 3.3 percentage points (p = 6.84e-40), for positive and negative modes, respectively) however still acceptable for an untargeted method (mean CVs of 17.9% and 12.2% in positive and negative modes respectively). A slightly larger number of endogenous features were detected using the separate polarities, but the large majority of features (>95%) were detected with both methodologies. The overlap of features detected in both positive and negative polarities was low (4.1%) demonstrating the importance of using both polarities for untargeted lipidomics. When investigating the effects of a treatment on multiple sclerosis patients it was found that both methodologies gave highly similar biological results, further confirming the applicability of polarity switching.

Molecular signature of soil organic matter under different land uses in the Lake Chaohu Basin.

The concentration and molecular composition of soil organic matter (SOM) are important factors in mitigation against climate change as well as providing other ecosystem services. Our quantitative understanding of how land use influences SOM molecular composition and associated turnover dynamics is limited, which underscores the need for high-throughput analytical approaches and molecular marker signatures to clarify this etiology. Combining a high-throughput untargeted mass spectrometry screening and molecular markers, we show that forest, farmland and urban land uses result in distinct molecular signatures of SOM in the Lake Chaohu Basin. Molecular markers indicate that forest SOM has abundant carbon contents from vegetation and condensed organic carbon, leading to high soil organic carbon (SOC) concentration. Farmland SOM has moderate carbon contents from vegetation, and limited content of condensed organic carbon, with SOC significantly lower than that of forest soils. Urban SOM has high abundance of condensed organic carbon markers due to anthropogenic activities but relatively low in markers from vegetation. Consistently, urban soils have the highest black carbon/SOC ratio among these land uses. Overall, our results suggested that the molecular signature of SOM varies significantly with land use in the Lake Chaohu Basin, influencing carbon dynamics. Our strategy of molecular fingerprinting and marker discovery is expected to enlighten further research on SOM molecular signatures and cycling dynamics.

Using Porcine Jejunum Ex Vivo to Study Absorption and Biotransformation of Natural Products in Plant Extracts: Pueraria lobata as a Case Study.

Herbal preparations (HPs) used in folk medicine are complex mixtures of natural products (NPs). Their efficacy in vivo after ingestion depends on the uptake of the active ingredient, and, in some cases, their metabolites, in the gastrointestinal tract. Thus, correlating bioactivities measured in vitro and efficacy in vivo is a challenge. An extract of Pueraria lobata rich in different types of isoflavones was used to evaluate the capacity of viable porcine small intestine ex vivo to elucidate the absorption of HP constituents, and, in some cases, their metabolites. The identification and transport of permeants across the jejunum was monitored by liquid chromatography-mass spectrometry (LC-MS), combining targeted and untargeted metabolite profiling approaches. It was observed that the C-glycoside isoflavones were stable and crossed the intestinal membrane, while various O-glycoside isoflavones were metabolized into their corresponding aglycones, which were then absorbed. These results are consistent with human data, highlighting the potential of using this approach. A thorough investigation of the impact of absorption and biotransformation was obtained without in vivo studies. The combination of qualitative untargeted and quantitative targeted LC-MS methods effectively monitored a large number of NPs and their metabolites, which is essential for research on HPs.

Breaking Through the Barrier: Regulatory Considerations Relevant to Ambient Mass Spectrometry at the Bedside.

Rapid characterization of tissue disorder using ambient mass spectrometry (MS) techniques, requiring little to no preanalytical preparations of sampled tissues, has been shown using a variety of ion sources and with many disease classes. A brief overview of ambient MS in clinical applications, the state of the art in regulatory affairs, and recommendations to facilitate adoption for use at the bedside are presented. Unique challenges in the validation of untargeted MS methods and additional safety and compliance requirements for deployment within a clinical setting are further discussed. Development of a harmonized validation strategy for ambient MS methods is emphasized.

Untargeted mass spectrometry-based metabolomics approach unveils molecular changes in raw and processed foods and beverages.

In our daily lives, we consume foods that have been transported, stored, prepared, cooked, or otherwise processed by ourselves or others. Food storage and preparation have drastic effects on the chemical composition of foods. Untargeted mass spectrometry analysis of food samples has the potential to increase our chemical understanding of these processes by detecting a broad spectrum of chemicals. We performed a time-based analysis of the chemical changes in foods during common preparations, such as fermentation, brewing, and ripening, using untargeted mass spectrometry and molecular networking. The data analysis workflow presented implements an approach to study changes in food chemistry that can reveal global alterations in chemical profiles, identify changes in abundance, as well as identify specific chemicals and their transformation products. The data generated in this study are publicly available, enabling the replication and re-analysis of these data in isolation, and serve as a baseline dataset for future investigations.

Direct analysis real-time-high-resolution mass spectrometry for Triticum species authentication.

Due to favourable climate condition, Italy is a prominent producer of different wheat varieties. Several wheat baked goods are produced, but the most typical Italian foods, like pasta, pizza and bread, are made of durum and common wheat flour. Because of the great importance of wheat in the Italian food market, authenticity represents an essential quality parameter not only for the producers and regulatory bodies but also for consumers. The aim of our study was to test the effectiveness of an unconventional non-targeted method for the discrimination of Triticum species using direct analysis real time-high-resolution mass spectrometry (DART-HRMS). For this purpose, 60 wheat samples including durum, common and hulled wheat varieties were collected over two consecutive harvest years. Chemometric evaluation revealed an optimal sample clustering according to the wheat species and the presence of 18 significant markers able to discriminate the groups. The discrimination power obtained is promising since the use of DART-HRMS can significantly reduce the analysis time compared to chromatographic techniques. A plausible future commercial and industrial scenario could see the application of this analytical approach especially to evaluate the risk of substitution of higher value wheat species with lower value flours.