An Optimized Dual Extraction Method for the Simultaneous and Accurate Analysis of Polar Metabolites and Lipids Carried out on Single Biological Samples

Integrative processing of untargeted metabolomic and lipidomic data using MultiABLER

Mass spectrometry (MS)-based untargeted metabolomic and lipidomic approaches are being used increasingly in biomedical research. The adoption and integration of these data are critical to the overall multi-omic toolkit. Recently, a sample extraction method called Multi-ABLE has been developed, which enables concurrent generation of proteomic and untargeted metabolomic and lipidomic data from a small amount of tissue. The proteomics field has a well-established set of software for processing of acquired data; however, there is a lack of a unified, off-the-shelf, ready-to-use bioinformatics pipeline that can take advantage of and prepare concurrently generated metabolomic and lipidomic data for joint downstream analyses. Here we present an R pipeline called MultiABLER as a unified and simple upstream processing and analysis pipeline for both metabolomics and lipidomics datasets acquired using liquid chromatography-tandem mass spectrometry. The code is available via an open-source license at https://github.com/holab-hku/MultiABLER.

Optimized protocol to isolate primary mouse peritoneal macrophage metabolites

Peritoneal macrophages (PMs) have been shown to have higher stability compared to other macrophage subtypes. However, obtaining enough PMs from a single mouse is often a limitation for metabolomics analysis. Here, we describe a protocol to isolate metabolites from a small number of mouse primary PMs for 13C-stable glucose tracing and metabolomics. Our protocol uses X for metabolite extraction instead of methanol. Our protocol can consistently extract metabolites from low cell number samples with fewer steps than methanol-based approaches. For complete details on the use and execution of this protocol, please refer to De Jesus et al., (2022).

Endo- and Exometabolome Crosstalk in Mesenchymal Stem Cells Undergoing Osteogenic Differentiation

This paper describes, for the first time to our knowledge, a lipidome and exometabolome characterization of osteogenic differentiation for human adipose tissue stem cells (hAMSCs) using nuclear magnetic resonance (NMR) spectroscopy. The holistic nature of NMR enabled the time-course evolution of cholesterol, mono- and polyunsaturated fatty acids (including ω-6 and ω-3 fatty acids), several phospholipids (phosphatidylcholine, phosphatidylethanolamine, sphingomyelins, and plasmalogens), and mono- and triglycerides to be followed. Lipid changes occurred almost exclusively between days 1 and 7, followed by a tendency for lipidome stabilization after day 7. On average, phospholipids and longer and more unsaturated fatty acids increased up to day 7, probably related to plasma membrane fluidity. Articulation of lipidome changes with previously reported polar endometabolome profiling and with exometabolome changes reported here in the same cells, enabled important correlations to be established during hAMSC osteogenic differentiation. Our results supported hypotheses related to the dynamics of membrane remodelling, anti-oxidative mechanisms, protein synthesis, and energy metabolism. Importantly, the observation of specific up-taken or excreted metabolites paves the way for the identification of potential osteoinductive metabolites useful for optimized osteogenic protocols.

Metabolomic Profiling of Dongxiang Wild Rice Under Salinity Demonstrates the Significant Role of Amino Acids in Rice Salt Stress

Dongxiang common wild rice is a precious rice germplasm resource for the study and improvement of salt tolerance in rice.The metabolism profile of Dongxiang wild rice (DXWR) under salinity was determined by high performance liquid chromatography-mass spectrometry (HPLC-MS) to find differential metabolites and screen potential biomarkers for salt-tolerant rice varieties. A global untargeted metabolism analysis showed 4,878 metabolites accumulated in seedlings of Dongxiang wild rice. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) results provided a clear metabolism discrimination between DXWR under control and DXWR under salinity. A total of 90 metabolites were significantly changed (49 upregulated and 41 downregulated) under salinity, of which the largest increase was in DL-2-Aminoadipic acid (27.08-fold) and the largest decrease was in L-Carnitine (0.014-fold). Amino acids and nuclear glycosides were mainly upregulated, while carbohydrates and organic acids were mainly downregulated in the salt-treated group. Among the top 10 upregulated metabolites, five kinds of differential metabolites were amino acids. According to the survival rates of the seedlings under salinity, we selected three backcross inbred lines of DXWR with survival rates above 80% as salt-tolerant progenies (pro-DS) and three backcross inbred lines with survival rates below 10% as non-salt-tolerant progenies (pro-NDS) for an amino acid change analysis. This analysis found that the change in L-Asparagine (2.59-fold) was the biggest between pro-DS and pro-NDS under salinity, revealing that the contents of L-Asparagine may be one of the indices we can use to evaluate the salt tolerance of rice varieties.

Unraveling the Extracellular Metabolism of Immortalized Hippocampal Neurons Under Normal Growth Conditions

Metabolomic profiling of cell lines has shown many potential applications and advantages compared to animal models and human subjects, and an accurate cellular metabolite analysis is critical to understanding both the intracellular and extracellular environments in cell culture. This study provides a fast protocol to investigate in vitro metabolites of immortalized hippocampal neurons HN9.10e with minimal perturbation of the cell system using a targeted approach. HN9.10e neurons represent a reliable model of one of the most vulnerable regions of the central nervous system. Here, the assessment of their extracellular metabolic profile was performed by studying the cell culture medium before and after cell growth under standard conditions. The targeted analysis was performed by a direct, easy, high-throughput reversed-phase liquid chromatography with diode array detector (RP-HPLC-DAD) method and by headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) for the study of volatile organic compounds (VOCs). The analysis of six different batches of cells has allowed to investigate the metabolic reproducibility of neuronal cells and to describe the metabolic "starting" conditions that are mandatory for a well-grounded interpretation of the results of any following cellular treatment. An accurate study of the metabolic profile of the HN9.10e cell line has never been performed before, and it could represent a quality parameter before any other targeting assay or further exploration.

Metabolic Drug Response Phenotyping in Colorectal Cancer Organoids by LC-QTOF-MS

As metabolic rewiring is crucial for cancer cell proliferation, metabolic phenotyping of patient-derived organoids is desirable to identify drug-induced changes and trace metabolic vulnerabilities of tumor subtypes. We established a novel protocol for metabolomic and lipidomic profiling of colorectal cancer organoids by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) facing the challenge of capturing metabolic information from a minimal sample amount (<500 cells/injection) in the presence of an extracellular matrix (ECM). The best procedure of the tested protocols included ultrasonic metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v/v) without ECM removal. To eliminate ECM-derived background signals, we implemented a data filtering procedure based on the p-value and fold change cut-offs, which retained features with signal intensities >120% compared to matrix-derived signals present in blank samples. As a proof-of-concept, the method was applied to examine the early metabolic response of colorectal cancer organoids to 5-fluorouracil treatment. Statistical analysis revealed dose-dependent changes in the metabolic profiles of treated organoids including elevated levels of 2′-deoxyuridine, 2′-O-methylcytidine, inosine and 1-methyladenosine and depletion of 2′-deoxyadenosine and specific phospholipids. In accordance with the mechanism of action of 5-fluorouracil, changed metabolites are mainly involved in purine and pyrimidine metabolism. The novel protocol provides a first basis for the assessment of metabolic drug response phenotypes in 3D organoid models.

Addendum: An Optimised Dual Extraction Method for the Simultaneous and Accurate Analysis of Polar Metabolites and Lipids Carried out on Single Biological Samples. Metabolites 2020, 10, 338

The authors wish to make the following comment to the paper [...]