Optimization and Evaluation Strategy of Esophageal Tissue Preparation Protocols for Metabolomics by LC–MS

Mapping the Metabolic Characteristics and Perturbation of Adult Casper Zebrafish by Ambient Mass Spectrometry Imaging

Casper, a type of transparent mutant-line zebrafish, was generated to overcome the opaque trunk of an adult zebrafish for tumor modeling to realize real-time visualization of transplanted cells in vivo. However, the molecular information at the metabolic level has not received much attention. Herein, a spatially resolved metabolomics method based on an airflow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) system for whole-body zebrafish was used to investigate small molecules and the distribution of adult casper (Mitfaw2/w2, roya9/a9) and the differences from wild-type zebrafish. Finally, the spatial distribution information of more than 1500 endogenous ions was obtained in positive and negative detection modes, and 186 metabolites belonging to a variety of structural categories were identified or annotated. Compared with wild-type samples, 85 variables, including 37 known metabolites, were screened out. In addition, the disordered metabolic pathways caused by the genetic mutation were excavated, involving downregulation of purine metabolism and arachidonic acid metabolism, upregulation of glycerophospholipid metabolism, and biosynthesis of unsaturated fatty acids. All these results were observed in the most intuitive way through MSI. This study revealed important metabolic characteristics of and perturbation in adult casper zebrafish, and provides indispensable fundamental knowledge for tumor research based on it.

A Shigella species variant is causally linked to intractable functional constipation

Intractable functional constipation (IFC) is the most severe form of constipation, but its etiology has long been unknown. We hypothesized that IFC is caused by refractory infection by a pathogenic bacterium. Here, we isolated from patients with IFC a Shigella species - peristaltic contraction-inhibiting bacterium (PIB) - that significantly inhibited peristaltic contraction of the colon by production of docosapentenoic acid (DPA). PIB colonized mice for at least 6 months. Oral administration of PIB was sufficient to induce constipation, which was reversed by PIB-specific phages. A mutated PIB with reduced DPA was incapable of inhibiting colonic function and inducing constipation, suggesting that DPA produced by PIB was the key mediator of the genesis of constipation. PIBs were detected in stools of 56% (38 of 68) of the IFC patients, but not in those of non-IFC or healthy individuals (0 of 180). DPA levels in stools were elevated in 44.12% (30 of 68) of the IFC patients but none of the healthy volunteers (0 of 97). Our results suggest that Shigella sp. PIB may be the critical causative pathogen for IFC, and detection of fecal PIB plus DPA may be a reliable method for IFC diagnosis and classification.

Evaluation of liver tissue extraction protocol for untargeted metabolomics analysis by ultra-high-performance liquid chromatography/tandem mass spectrometry

The aim of the untargeted metabolomics study is to obtain a global metabolome coverage from biological samples. Therefore, a comprehensive and systematic protocol for tissue metabolite extraction is highly desirable. In this study, we evaluated a comprehensive liver pretreatment strategy based on ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to obtain more metabolites using four different protocols. These protocols included (A) methanol protein precipitation, (B) two-step extraction of dichloromethane-methanol followed by methanol-water, (C) two-step extraction of methyl tert-butyl ether-methanol followed by methanol-water, and (D) two-step extraction of isopropanol-methanol followed by methanol-water. Our results showed that protocol D was superior to the others due to more extracted features, annotated metabolites, and better reproducibility. And then, the stability and extraction sequence of protocol D were evaluated. The results showed that extraction with isopropanol-methanol followed by methanol-water was the optimum preparation sequence, which offered higher extraction efficiency, satisfactory repeatability, and acceptable stability. Furthermore, the optimal protocol was successfully applied by liver samples of rats after high-fat intervention. In summary, our protocol enabled a comprehensive and systematic evaluation of liver pretreatment to obtain more medium-polar and nonpolar metabolites and was suitable for high-throughput metabolomics analysis.

A Robust Method for Sample Preparation of Gastrointestinal Stromal Tumour for LC/MS Untargeted Metabolomics

Gastrointestinal stromal tumour has already been well explored at the genome level; however, little is known about metabolic processes occurring in the sarcoma. Sample preparation is a crucial step in untargeted metabolomics workflow, highly affecting the metabolome coverage and the quality of the results. In this study, four liquid-liquid extraction methods for the isolation of endogenous compounds from gastrointestinal stromal tumours were compared and evaluated. The protocols covered two-step or stepwise extraction with methyl-tert-butyl ether (MTBE) or dichloromethane. The extracts were subjected to LC-MS analysis by the application of reversed-phase and hydrophilic interaction liquid chromatography to enable the separation and detection of both polar and nonpolar analytes. The extraction methods were compared in terms of efficiency (total number of detected metabolites) and reproducibility. The method was based on the stepwise extraction with MTBE, methanol, and water proved to be the most reproducible, and thus, its robustness to fluctuations in experimental conditions was assessed employing Plackett–Burman design and hierarchical modelling. While most studied factors had no effect on the metabolite abundance, the highest coefficient value was observed for the volume of MTBE added during extraction. Herein, we demonstrate the application and the feasibility of the selected protocol for the analysis of gastrointestinal stromal tumour samples. The method selected could be considered as a reference for the best characterization of underlying molecular changes associated with complex tissue extracts of GIST.

Metabolomic Analysis Identifies Alterations of Amino Acid Metabolome Signatures in the Postmortem Brain of Alzheimer's Disease

Despite significant advances in neuroscience research over the past several decades, the exact cause of AD has not yet fully understood. The metabolic hypothesis as well as the amyloid and tau hypotheses have been proposed to be associated with AD pathogenesis. In order to identify metabolome signatures from the postmortem brains of sporadic AD patients and control subjects, we performed ultra performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometer (UPLC-LTQ-Orbitrap-MS). Not only our study identified new metabolome signatures but also verified previously known metabolome profiles in the brain. Statistical modeling of the analytical data and validation of the structural assignments discovered metabolic biomarkers associated with the AD pathogenesis. Interestingly, hypotaurin, myo-inositol and oxo-proline levels were markedly elevated in AD while lutamate and N-acetyl-aspartate were decreased in the postmortem brain tissue of AD patients. In addition, neurosteroid level such as cortisol was significantly increased in AD. Together, our data indicate that impaired amino acid metabolism is associated with AD pathogenesis and the altered amino acid signatures can be useful diagnostic biomarkers of AD. Thus, modulation of amino acid metabolism may be a possible therapeutic approach to treat AD.

Validated comprehensive metabolomics and lipidomics analysis of colon tissue and cell lines

Current untargeted approaches for metabolic fingerprinting of colon tissue and cell lines lack validation of reproducibility and/or focus on a selection of metabolites as opposed to the entire metabolome. Yet, both are critical to ensure reliable results and pursue a fully holistic analysis. Therefore, we have optimized and validated a platform for analyzing the polar metabolome and lipidome of colon-derived cell and tissue samples based on a consecutive extraction of polar and apolar components. Peak areas of selected targeted analytes and the number of untargeted components were assessed. Analysis was performed using ultra-high performance liquid-chromatography (UHPLC) coupled to hybrid quadrupole-Orbitrap high-resolution mass spectrometry (HRMS). This resulted in an optimized extraction protocol using 50% methanol/ultrapure water to obtain the polar fraction followed by a dichloromethane-based lipid extraction. Using this comprehensive approach, we have detected more than 15,000 components with CV < 30% in internal quality control (IQC) samples and were able to discriminate the non-transformed (NT) and transformed (T) state in human colon tissue and cell lines based on validated OPLS-DA models (R²Y > 0.719 and Q² > 0.674). To conclude, our validated polar metabolomics and lipidomics fingerprinting approach could be of great value to reveal gastrointestinal disease-associated biomarkers and mechanisms.

Balancing metabolome coverage and reproducibility for untargeted NMR-based metabolic profiling in tissue samples through mixture design methods

Untargeted metabolomics attempts to acquire a comprehensive and reproducible set of small-molecule metabolites in biological systems. However, metabolite extraction method significantly affects the quality of metabolomics data. In the present study, we calculated the number of peaks (NP) and coefficient of variation (CV) to reflect metabolome coverage and reproducibility in untargeted NMR-based metabolic profiling of tissue samples in rats under different methanol/chloroform/water (MCW) extraction conditions. Different MCW extractions expectedly generated diverse characteristics of metabolome. Moreover, the classic MCW method revealed tissue-specific differences in the NP and CV values. To obtain high-quality metabolomics data, therefore, we used mixture design methods to optimize the MCW extraction strategy by maximizing the NP value and minimizing the CV value in each tissue sample. Results show that the optimal formulations of MCW extraction were 2:2:8 (ml/mg tissue) for brain sample, 2:4:6 (ml/mg tissue) for heart sample, 1.3:2:8.7 (ml/mg tissue) for liver sample, 4:2:6 (ml/mg tissue) for kidney sample, 2:3:7 (ml/mg tissue) for muscle sample, and 2:4:6 (ml/mg tissue) for pancreas sample. Therefore, these findings demonstrate that different tissue samples need a specific optimal extraction condition for balancing metabolome coverage and reproducibility in the untargeted metabolomics study. Mixture design method is an effective tool to optimize metabolite extraction strategy for tissue samples. Graphical abstract ᅟ.

The Recent Developments in Sample Preparation for Mass Spectrometry-Based Metabolomics

Metabolomics is a critical member in systems biology. Although great progress has been achieved in metabolomics, there are still some problems in sample preparation, data processing and data interpretation. In this review, we intend to explore the roles, challenges and trends in sample preparation for mass spectrometry- (MS-) based metabolomics. The newly emerged sample preparation methods were also critically examined, including laser microdissection, in vivo sampling, dried blood spot, microwave, ultrasound and enzyme-assisted extraction, as well as microextraction techniques. Finally, we provide some conclusions and perspectives for sample preparation in MS-based metabolomics.

Semiautomated Alignment of High-Throughput Metabolite Profiles with Chemometric Tools

The rapid increase in the use of metabolite profiling/fingerprinting techniques to resolve complicated issues in metabolomics has stimulated demand for data processing techniques, such as alignment, to extract detailed information. In this study, a new and automated method was developed to correct the retention time shift of high-dimensional and high-throughput data sets. Information from the target chromatographic profiles was used to determine the standard profile as a reference for alignment. A novel, piecewise data partition strategy was applied for the determination of the target components in the standard profile as markers for alignment. An automated target search (ATS) method was proposed to find the exact retention times of the selected targets in other profiles for alignment. The linear interpolation technique (LIT) was employed to align the profiles prior to pattern recognition, comprehensive comparison analysis, and other data processing steps. In total, 94 metabolite profiles of ginseng were studied, including the most volatile secondary metabolites. The method used in this article could be an essential step in the extraction of information from high-throughput data acquired in the study of systems biology, metabolomics, and biomarker discovery.

New instrumentation for large-scale quantitative analysis of components spanning a wide polarity range by column-switching hydrophilic interaction chromatography-turbulent flow chromatography-reversed phase liquid chromatography-tandem mass spectrometry

New instrumentation, namely column-switching HILIC-TFC-RPLC-MS/MS, was configured for large-scale quantitative analysis of components spanning a wide polarity range in a mimic complicated sample.