Measurement of DNA concentration as a normalization strategy for metabolomic data from adherent cell lines

miR-21/SMAD2 Is Involved in the Decrease in Progesterone Synthesis Caused by Lipopolysaccharide Exposure in Follicular Granulosa Cells of Laying Goose

Lipopolysaccharide (LPS) is one of the important pathogenic substances of E. coli and Salmonella, which causes injury to the reproductive system. Ovarian dysfunction due to Gram-negative bacterial infections is a major cause of reduced reproductive performance in geese. However, the specific molecular mechanisms of LPS-induced impairment of sex steroid hormone synthesis have not been determined. The regulatory mechanism of miRNA has been proposed in many physiological and pathogenic mechanisms. Therefore, the role of miRNA in breeding geese exposed to LPS during the peak laying period was investigated. In this study, twenty Yangzhou geese at peak laying period were injected with LPS for 0 h, 24 h, and 36 h. The follicular granulosa layer was taken for RNA-seq and analyzed for differentially expressed miRNAs. It was observed that LPS changed the appearance of hierarchical follicles. miRNA sequencing analysis was applied, and miR-21 and SMAD2 (SMAD family member 2) were selected from 51 differentially expressed miRNAs through bioinformatics prediction. The results showed that miR-21 down-regulated SMAD2 expression and progesterone (P4) production in LPS-treated goose granulosa cells (GCs). It also determined that overexpression of miR-21 or silence of SMAD2 suppressed the sex steroid biosynthesis pathway by decreasing STAR and CYP11A1 expression. Down-regulation of miR-21 exacerbates the LPS-induced decline in P4 synthesis and vice versa. The findings indicated that miR-21 was involved in LPS regulation of P4 synthesis in goose granulosa cells by down-regulating SMAD2. This study provides theoretical support for the prevention of LPS-induced ovarian dysfunction in geese.

Comparison of Various Extraction Approaches for Optimized Preparation of Intracellular Metabolites from Human Mesenchymal Stem Cells and Fibroblasts for NMR-Based Study

Metabolomics has proven to be a sensitive tool for monitoring biochemical processes in cell culture. It enables multi-analysis, clarifying the correlation between numerous metabolic pathways. Together with other analysis, it thus provides a global view of a cell's physiological state. A comprehensive analysis of molecular changes is also required in the case of mesenchymal stem cells (MSCs), which currently represent an essential portion of cells used in regenerative medicine. Reproducibility and correct measurement are closely connected to careful metabolite extraction, and sample preparation is always a critical point. Our study aimed to compare the efficiencies of four harvesting and six extraction methods. Several organic reagents (methanol, ethanol, acetonitrile, methanol-chloroform, MTBE) and harvesting approaches (trypsinization vs. scraping) were tested. We used untargeted nuclear magnetic resonance spectroscopy (NMR) to determine the most efficient method for the extraction of metabolites from human adherent cells, specifically human dermal fibroblasts adult (HDFa) and dental pulp stem cells (DPSCs). A comprehensive dataset of 29 identified and quantified metabolites were determined to possess statistically significant differences in the abundances of several metabolites when the cells were detached mechanically to organic solvent compared to when applying enzymes mainly in the classes of amino acids and peptides for both types of cells. Direct scraping to organic solvent is a method that yields higher abundances of determined metabolites. Extraction with the use of different polar reagents, 50% and 80% methanol, or acetonitrile, mostly showed the same quality. For both HDFa and DPSC cells, the MTBE method, methanol-chloroform, and 80% ethanol extractions showed higher extraction efficiency for the most identified and quantified metabolites Thus, preparation procedures provided a cell sample processing protocol that focuses on maximizing extraction yield. Our approach may be useful for large-scale comparative metabolomic studies of human mesenchymal stem cell samples.

Polyporus ulleungus mycelia cultured in MEB medium produce metabolites with anticancer property

Cancer cells are characterized by apoptosis evasion and uncontrolled cell cycle progression. To combat these characteristics, efforts have been made to find novel natural-source anticancer compounds. The aim of this work is to find new anticancer compounds in Polyporus ulleungus (P. ulleungus) mycelial culture extracts. P. ulleungus mycelium was cultured on four individual media (DYB, MEB, MYB, and PDB) and four extracts were generated from the mycelium culture media. Extracts of P. ulleungus mycelium cultured in MEB medium (pu-MEB) significantly reduced cancer cell growth by triggering apoptosis and S phase arrest. Furthermore, the anticancer effects of pu-MEB were not confined to one type of cancer. Taken together, our results confirmed that P. ulleungus mycelia cultured in MEB medium produce metabolites that exhibit anticancer properties. Development of an optimal medium for P. ulleungus mycelium through optimization of medium components will enable P. ulleungus mycelium to produce metabolites with more anticancer efficacy.

Protocol for mapping the metabolome and lipidome of medulloblastoma cells using liquid chromatography-mass spectrometry

Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics and lipidomics have recently been used to show that MYC-amplified group 3 medulloblastoma tumors are driven by metabolic reprogramming. Here, we present a protocol to extract metabolites and lipids from human medulloblastoma brain tumor-initiating cells and normal neural stem cells. We describe untargeted LC-MS methods that can be used to achieve extensive coverage of the polar metabolome and lipidome. Finally, we detail strategies for metabolite identification and data analysis. For complete details on the use and execution of this protocol, please refer to Gwynne et al.1.

Chemical screening identifies the anticancer properties of Polyporous tuberaster

Most conventional anticancer drugs cause resistance to chemotherapy, which has emerged as one of the major obstacles to cancer treatment. In order to address this issue, efforts have been made to select new anticancer compounds from natural sources. The aim of this study is to identify novel anticancer compounds from mycelial culture extracts belonging to Polyporus tuberaster (P. tuberaster). Here, we found that mycelial culture extracts of P. tuberaster cultured in PDB medium (pt-PDB) effectively inhibited cancer cell growth. pt-PDB reduced the growth of cancer cells through apoptosis induction and S-phase arrest. The anticancer efficacy of pt-PDB was not to limited to one type of cancer. Furthermore, unlike traditional anticancer medications, pt-PDB did not increase the proportion of side population (SP) cells, which plays a key role in the development of chemoresistance. Taken together, we discovered a novel anticancer drug candidate that has anticancer properties without increasing the proportion of SP cells. This new drug candidate can be used for the treatment of cancer, especially chemoresistant malignancies, and will provide a breakthrough in the treatment of chemoresistant cancer.

Fibroblast phenylalanine concentration as a surrogate biomarker of cellular number

Metabolomics studies in human dermal fibroblasts can elucidate the biological mechanisms associated with some diseases, but several methodological issues that increase variability have been identified. We aimed to quantify the amino acid levels in cultured fibroblasts and to apply different sample-based normalization approaches. Forty-four skin biopsies from control subjects were collected. Amino acids were measured in fibroblasts supernatants by UPLC-MS/MS. Statistical supervised and unsupervised studies were used. Spearman's test showed that phenylalanine displayed the second highest correlation with the remaining amino acids (mean r = 0.8), whereas the total protein concentration from the cell pellet showed a mean of r = 0.67. The lowest percentage of variation was obtained when amino acids were normalized by phenylalanine values, with a mean of 42% vs 57% when normalized by total protein values. When amino acid levels were normalized by phenylalanine, Principal Component Analysis and clustering analyses identified different fibroblasts groups. In conclusion, phenylalanine may be a suitable biomarker to estimate cellular content in cultured fibroblasts.

The assessment of the potential hepatotoxicity of new drugs by in vitro metabolomics

Drug hepatotoxicity assessment is a relevant issue both in the course of drug development as well as in the post marketing phase. The use of human relevant in vitro models in combination with powerful analytical methods (metabolomic analysis) is a promising approach to anticipate, as well as to understand and investigate the effects and mechanisms of drug hepatotoxicity in man. The metabolic profile analysis of biological liver models treated with hepatotoxins, as compared to that of those treated with non-hepatotoxic compounds, provides useful information for identifying disturbed cellular metabolic reactions, pathways, and networks. This can later be used to anticipate, as well to assess, the potential hepatotoxicity of new compounds. However, the applicability of the metabolomic analysis to assess the hepatotoxicity of drugs is complex and requires careful and systematic work, precise controls, wise data preprocessing and appropriate biological interpretation to make meaningful interpretations and/or predictions of drug hepatotoxicity. This review provides an updated look at recent in vitro studies which used principally mass spectrometry-based metabolomics to evaluate the hepatotoxicity of drugs. It also analyzes the principal drawbacks that still limit its general applicability in safety assessment screenings. We discuss the analytical workflow, essential factors that need to be considered and suggestions to overcome these drawbacks, as well as recent advancements made in this rapidly growing field of research.

Functional restoration of lysosomes and mitochondria through modulation of AKT activity ameliorates senescence

Senescence is a phenomenon defined by alterations in cellular organelles and is the primary cause of aging and aging-related diseases. Recent studies have shown that oncogene-induced senescence is driven by activation of serine/threonine protein kinases (AKT1, AKT2 and AKT3). In this study, we evaluated twelve AKT inhibitors and revealed GDC0068 as a potential agent to ameliorate senescence. Senescence-ameliorating effect was evident from the finding that GDC0068 yielded lysosomal functional recovery as observed by reduction in lysosomal mass and induction in autophagic flux. Furthermore, GDC0068-mediated restoration of lysosomal function activated the removal of dysfunctional mitochondria, resulting in restoration of mitochondrial function. Together, our findings revealed a unique mechanism by which senescence is recovered by functional restoration of lysosomes and mitochondria through modulation of AKT activity.

Development of an Untargeted Metabolomics Strategy to Study the Metabolic Rewiring of Dendritic Cells upon Lipopolysaccharide Activation

Dendritic cells (DCs) are essential immune cells for defense against external pathogens. Upon activation, DCs undergo profound metabolic alterations whose precise nature remains poorly studied at a large scale and is thus far from being fully understood. The goal of the present work was to develop a reliable and accurate untargeted metabolomics workflow to get a deeper insight into the metabolism of DCs when exposed to an infectious agent (lipopolysaccharide, LPS, was used to mimic bacterial infection). As DCs transition rapidly from a non-adherent to an adherent state upon LPS exposure, one of the leading analytical challenges was to implement a single protocol suitable for getting comparable metabolomic snapshots of those two cellular states. Thus, a thoroughly optimized and robust sample preparation method consisting of a one-pot solvent-assisted method for the simultaneous cell lysis/metabolism quenching and metabolite extraction was first implemented to measure intracellular DC metabolites in an unbiased manner. We also placed special emphasis on metabolome coverage and annotation by using a combination of hydrophilic interaction liquid chromatography and reverse phase columns coupled to high-resolution mass spectrometry in conjunction with an in-house developed spectral database to identify metabolites at a high confidence level. Overall, we were able to characterize up to 171 unique meaningful metabolites in DCs. We then preliminarily compared the metabolic profiles of DCs derived from monocytes of 12 healthy donors upon in vitro LPS activation in a time-course experiment. Interestingly, the resulting data revealed differential and time-dependent activation of some particular metabolic pathways, the most impacted being nucleotides, nucleotide sugars, polyamines pathways, the TCA cycle, and to a lesser extent, the arginine pathway.

Advances in Microbial NMR Metabolomics

Confidently, nuclear magnetic resonance (NMR) is the most informative technique in analytical chemistry and its use as an analytical platform in metabolomics is well proven. This chapter aims to present NMR as a viable tool for microbial metabolomics discussing its fundamental aspects and applications in metabolomics using some chosen examples.

Chemical screening identifies the anticancer properties of Polyporous parvovarius

One of the biggest obstacles in cancer treatment is the development of chemoresistance. To overcome this, attempts have been made to screen novel anticancer substances derived from natural products. The purpose of this study is to find new anticancer candidates in the mycelium culture extract of mushrooms belonging to Polyporus. Here, we used a high-throughput screening to find agents capable of inhibiting cancer cell proliferation. The culture extract of Polyporus Parvovarius mycelium in DY medium (pp-DY) was effective. pp-DY inhibited cancer cell proliferation by inducing apoptosis and S-phase arrest. The anticancer property of pp-DY was not only effective against one type of cancer, but also against another type of cancer. Compound fractionation was performed, and the active ingredient exhibiting anticancer effects in pp-DY was identified as 3,4-dihydroxybenzaldehyde (Protocatechualdehyde, PCA). PCA, like pp-DY, inhibited the proliferation of cancer cells by inducing apoptosis and S-phase arrest. Furthermore, unlike conventional anticancer drugs, PCA did not increase the proportion of the side population that plays the most important role in the development of chemoresistance. Taken together, our data revealed the novel mycelium culture extract that exhibited anticancer property, and identified active ingredients that did not activate a proportion of the side population. These novel findings may have clinical applications in the treatment of cancer, particularly chemo-resistant cancer.

Optimization of the Sulfo-Phospho-Vanillin Assay for Total Lipid Normalization in Untargeted Quantitative Lipidomic LC-MS/MS Applications

Liquid chromatography (LC)-mass spectrometry (MS)/MS lipidomic normalization is generally performed by equalizing pre-extraction sample materials or via DNA or protein pre-quantitation methods, which have known measurement inaccuracies. We propose the use of the sulfo-phospho-vanillin assay (SPVA), a total lipid colorimetric analysis, as a pre-quantitation method to normalize lipids in lipidomic LC-MS/MS applications. The assay has been applied to a 300 μL well volume in a 96-well plate and tested using Avanti total lipid standards of porcine brain and E. coli. Assay parameters for lipid sample volume, sulfuric acid, vanillin/phosphoric acid, post-reaction incubation time, and wavelength are optimized for robust application to biologically sourced lipid samples. Standard test samples were prepared using three concentrations covering approximately 100 μg/mL range. The optimized assay yielded test sample errors less than 10%, indicating a precise and accurate assay performance. The test samples were then analyzed by LC-MS/MS and normalized using SPVA pre-quantitation and pseudo-mass normalization. The detected lipids showed smaller standard deviations and greater relative concentration differences compared to the pseudo-mass normalized lipids, showing promise as a normalization method.

Restoration of Lysosomal and Mitochondrial Function Through p38 Mitogen-Activated Protein Kinase Inhibition Ameliorates Senescence

Oncogene-induced senescence (OIS), characterized by irreversible cell cycle arrest by oncogene activation, plays an important role in the pathogenesis of aging and age-related diseases. Recent research indicates that OIS is driven by activation of mitogen-activated protein kinase (MAPK). However, it is not apparent whether MAPK inhibition helps to recover senescence. In our previous study, we uncovered p38 MAPK inhibitor, SB203580, as an effective agent to reduce reactive oxygen species and increase proliferation in premature senescent cells. In this study, we evaluated whether SB203580 could ameliorate senescence in normal senescent cells. The senescence-improving effect was observed in the results that SB203580 treatment restored lysosomal function, as evidenced by a decrease in lysosomal mass and an increase in autophagic vacuoles. Then, SB203580-mediated lysosomal function restoration triggered the clearance of damaged mitochondria, leading to metabolic reprogramming necessary for amelioration of senescence. Indeed, p38 MAPK inhibition by SB203580 improved key senescent phenotypes. Our findings suggest a novel mechanism by which modulation of p38 MAPK activity leads to senescence improvement through functional restoration of lysosome and mitochondria.

Linoleic acid metabolism activation in macrophages promotes the clearing of intracellular Staphylococcus aureus

Multidrug-resistant bacterial pathogens pose an increasing threat to human health. Certain bacteria, such as Staphylococcus aureus, are able to survive within professional phagocytes to escape the bactericidal effects of antibiotics and evade killing by immune cells, potentially leading to chronic or persistent infections. By investigating the macrophage response to S. aureus infection, we may devise a strategy to prime the innate immune system to eliminate the infected bacteria. Here we applied untargeted tandem mass spectrometry to characterize the lipidome alteration in S. aureus infected J774A.1 macrophage cells at multiple time points. Linoleic acid (LA) metabolism and sphingolipid metabolism pathways were found to be two major perturbed pathways upon S. aureus infection. The subsequent validation has shown that sphingolipid metabolism suppression impaired macrophage phagocytosis and enhanced intracellular bacteria survival. Meanwhile LA metabolism activation significantly reduced intracellular S. aureus survival without affecting the phagocytic capacity of the macrophage. Furthermore, exogenous LA treatment also exhibited significant bacterial load reduction in multiple organs in a mouse bacteremia model. Two mechanisms are proposed to be involved in this progress: exogenous LA supplement increases downstream metabolites that partially contribute to LA's capacity of intracellular bacteria-killing and LA induces intracellular reactive oxygen species (ROS) generation through an electron transport chain pathway in multiple immune cell lines, which further increases the capacity of killing intracellular bacteria. Collectively, our findings not only have characterized specific lipid pathways associated with the function of macrophages but also demonstrated that exogenous LA addition may activate lipid modulator-mediated innate immunity as a potential therapy for bacterial infections.

Addressing big data challenges in mass spectrometry-based metabolomics

Advancements in computer science and software engineering have greatly facilitated mass spectrometry (MS)-based untargeted metabolomics. Nowadays, gigabytes of metabolomics data are routinely generated from MS platforms, containing condensed structural and quantitative information from thousands of metabolites. Manual data processing is almost impossible due to the large data size. Therefore, in the "omics" era, we are faced with new challenges, the big data challenges of how to accurately and efficiently process the raw data, extract the biological information, and visualize the results from the gigantic amount of collected data. Although important, proposing solutions to address these big data challenges requires broad interdisciplinary knowledge, which can be challenging for many metabolomics practitioners. Our laboratory in the Department of Chemistry at the University of British Columbia is committed to combining analytical chemistry, computer science, and statistics to develop bioinformatics tools that address these big data challenges. In this Feature Article, we elaborate on the major big data challenges in metabolomics, including data acquisition, feature extraction, quantitative measurements, statistical analysis, and metabolite annotation. We also introduce our recently developed bioinformatics solutions for these challenges. Notably, all of the bioinformatics tools and source codes are freely available on GitHub (https://www.github.com/HuanLab), along with revised and regularly updated content.

Phosphatidic acid phosphatase 1 impairs SARS-CoV-2 replication by affecting the glycerophospholipid metabolism pathway

Viruses exploit the host lipid metabolism machinery to achieve efficient replication. We herein characterize the lipids profile reprogramming in vitro and in vivo using liquid chromatography-mass spectrometry-based untargeted lipidomics. The lipidome of SARS-CoV-2-infected Caco-2 cells was markedly different from that of mock-infected samples, with most of the changes involving downregulation of ceramides. In COVID-19 patients' plasma samples, a total of 54 lipids belonging to 12 lipid classes that were significantly perturbed compared to non-infected control subjects' plasma samples were identified. Among these 12 lipid classes, ether-linked phosphatidylcholines, ether-linked phosphatidylethanolamines, phosphatidylcholines, and ceramides were the four most perturbed. Pathway analysis revealed that the glycerophospholipid, sphingolipid, and ether lipid metabolisms pathway were the most significantly perturbed host pathways. Phosphatidic acid phosphatases (PAP) were involved in all three pathways and PAP-1 deficiency significantly suppressed SARS-CoV-2 replication. siRNA knockdown of LPIN2 and LPIN3 resulted in significant reduction of SARS-CoV-2 load. In summary, these findings characterized the host lipidomic changes upon SARS-CoV-2 infection and identified PAP-1 as a potential target for intervention for COVID-19.

MAFFIN: Metabolomics Sample Normalization Using Maximal Density Fold Change with High-Quality Metabolic Features and Corrected Signal Intensities

MOTIVATION

Post-acquisition sample normalization is a critical step in comparative metabolomics to remove the variation introduced by sample amount or concentration difference. Previously reported approaches are either specific to one sample type or built on strong assumptions on data structure, which are limited to certain levels. This encouraged us to develop MAFFIN, an accurate and robust post-acquisition sample normalization workflow that works universally for metabolomics data collected on mass spectrometry (MS) platforms.

RESULTS

MAFFIN calculates normalization factors using maximal density fold change (MDFC) computed by a kernel density-based approach. Using both simulated data and 20 metabolomics data sets, we showcased that MDFC outperforms four commonly used normalization methods in terms of reducing the intragroup variation among samples. Two essential steps, overlooked in conventional methods, were also examined and incorporated into MAFFIN. (1) MAFFIN uses multiple orthogonal criteria to select high-quality features for normalization factor calculation, which minimizes the bias caused by abiotic features or metabolites with poor quantitative performance. (2) MAFFIN corrects the MS signal intensities of high-quality features using serial quality control (QC) samples, which guarantees the accuracy of fold change calculations. MAFFIN was applied to a human saliva metabolomics study and led to better data separation in principal component analysis (PCA) and more confirmed significantly altered metabolites.

AVAILABILITY AND IMPLEMENTATION

The MAFFIN algorithm was implemented in an R package named MAFFIN. Package installation, user instruction, and demo data are available at https://github.com/HuanLab/MAFFIN.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Targeting regulation of ATP synthase 5 alpha/beta dimerization alleviates senescence

Senescence is a distinct set of changes in the senescence-associated secretory phenotype (SASP) and leads to aging and age-related diseases. Here, we screened compounds that could ameliorate senescence and identified an oxazoloquinoline analog (KB1541) designed to inhibit IL-33 signaling pathway. To elucidate the mechanism of action of KB1541, the proteins binding to KB1541 were investigated, and an interaction between KB1541 and 14-3-3ζ protein was found. Specifically, KB1541 interacted with 14-3-3ζ protein and phosphorylated of 14-3-3ζ protein at serine 58 residue. This phosphorylation increased ATP synthase 5 alpha/beta dimerization, which in turn promoted ATP production through increased oxidative phosphorylation (OXPHOS) efficiency. Then, the increased OXPHOS efficiency induced the recovery of mitochondrial function, coupled with senescence alleviation. Taken together, our results demonstrate a mechanism by which senescence is regulated by ATP synthase 5 alpha/beta dimerization upon fine-tuning of KB1541-mediated 14-3-3ζ protein activity.

Cardiotoxicity of cyclophosphamide's metabolites: an in vitro metabolomics approach in AC16 human cardiomyocytes

Cyclophosphamide is a widely used anticancer and immunosuppressive prodrug that unfortunately causes severe adverse effects, including cardiotoxicity. Although the exact cardiotoxic mechanisms are not completely understood, a link between cyclophosphamide's pharmacologically active metabolites, namely 4-hydroxycyclophosphamide and acrolein, and the toxicity observed after the administration of high doses of the prodrug is likely. Therefore, the objective of this study is to shed light on the cardiotoxic mechanisms of cyclophosphamide and its main biotransformation products, through classic and metabolomics studies. Human cardiac proliferative and differentiated AC16 cells were exposed to several concentrations of the three compounds, determining their basic cytotoxic profile and preparing the next study, using subtoxic and toxic concentrations for morphological and biochemical studies. Finally, metabolomics studies were applied to cardiac cells exposed to subtoxic concentrations of the aforementioned compounds to determine early markers of damage. The cytotoxicity, morphological and biochemical assays showed that 4-hydroxycyclophosphamide and acrolein induced marked cardiotoxicity at µM concentrations (lower than 5 µM), being significantly lower than the ones observed for cyclophosphamide (higher than 2500 μM). Acrolein led to increased levels of ATP and total glutathione on proliferative cells at 25 µM, while no meaningful changes were observed in differentiated cells. Higher levels of carbohydrates and decreased levels of fatty acids and monoacylglycerols indicated a metabolic cardiac shift after exposure to cyclophosphamide's metabolites, as well as a compromise of precursor amino acids used in the synthesis of glutathione, seen in proliferative cells' metabolome. Overall, differences in cytotoxic mechanisms were observed for the two different cellular states used and for the three molecules, which should be taken into consideration in the study of cyclophosphamide cardiotoxic mechanisms.

HepG2 as promising cell-based model for biosynthesis of long-term metabolites: Exemplified for metandienone

In order to detect the abuse of substances in sports, the knowledge of their metabolism is of undisputable importance. As in vivo administration of compounds faces ethical problems and might even not be applicable for nonapproved compounds, cell-based models might be a versatile tool for biotransformation studies. We coincubated HepG2 cells with metandienone and D₃ -epitestosterone for 14 days. Phase I and II metabolites were analyzed by high-performance liquid chromatography (HPLC)-tandem mass spectrometry and confirmed by gas chromatography-mass spectrometry (GC-MS). The metandienone metabolites formed by HepG2 cells were comparable with those renally excreted by humans. HepG2 cells also generated the two long-term metabolites 17β-hydroxymethyl-17α-methyl-18-nor-androst-1,4,13-trien-3-one and 17α-hydroxymethyl-17β-methyl-18-nor-androst-1,4,13-trien-3-one used in doping analyses, though in an inverse ratio compared with that observed in human urine. In conclusion, we showed that HepG2 cells are suitable as model for the investigation of biotransformation of androgens, especially for the anabolic androgenic steroid metandienone. They further proved to cover phase I and II metabolic pathways, which combined with a prolonged incubation time with metandienone resulted in the generation of its respective long-term metabolites known from in vivo metabolism. Moreover, we showed the usability of D₃ -epitestosterone as internal standard for the incubation. The method used herein appears to be suitable and advantageous compared with other models for the investigation of doping-relevant compounds, probably enabling the discovery of candidate metabolites for doping analyses.

Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions

Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.

Three-Dimensional Cell Metabolomics Deciphers the Anti-Angiogenic Properties of the Radioprotectant Amifostine

Simple Summary

Cancer and inflammation share aberrant angiogenesis as a hallmark, and, thus, anti-angiogenetic strategies remain of key interest. Amifostine, which is already a drug on the market, may be of further benefit to patients also in the context of drug repurposing. To shed light on the anti-angiogenic properties of amifostine during human adult angiogenesis and grasp the early events of angiogenesis, we employed 3D cell untargeted metabolomics by liquid chromatography–mass spectrometry and nuclear magnetic resonance spectroscopy in the presence of vascular endothelial growth factor-A or deferoxamine (pro-angiogenic factors that exhibit distinct angiogenesis induction profiles). Our findings reveal mechanism-specific inhibitory profiles of amifostine against VEGF-A- and deferoxamine-induced angiogenesis. Amifostine may serve as a dual radioprotective and anti-angiogenic agent in radiotherapy patients.

Abstract

Aberrant angiogenesis is a hallmark for cancer and inflammation, a key notion in drug repurposing efforts. To delineate the anti-angiogenic properties of amifostine in a human adult angiogenesis model via 3D cell metabolomics and upon a stimulant-specific manner, a 3D cellular angiogenesis assay that recapitulates cell physiology and drug action was coupled to untargeted metabolomics by liquid chromatography–mass spectrometry and nuclear magnetic resonance spectroscopy. The early events of angiogenesis upon its most prominent stimulants (vascular endothelial growth factor-A or deferoxamine) were addressed by cell sprouting measurements. Data analyses consisted of a series of supervised and unsupervised methods as well as univariate and multivariate approaches to shed light on mechanism-specific inhibitory profiles. The 3D untargeted cell metabolomes were found to grasp the early events of angiogenesis. Evident of an initial and sharp response, the metabolites identified primarily span amino acids, sphingolipids, and nucleotides. Profiles were pathway or stimulant specific. The amifostine inhibition profile was rather similar to that of sunitinib, yet distinct, considering that the latter is a kinase inhibitor. Amifostine inhibited both. The 3D cell metabolomics shed light on the anti-angiogenic effects of amifostine against VEGF-A- and deferoxamine-induced angiogenesis. Amifostine may serve as a dual radioprotective and anti-angiogenic agent in radiotherapy patients.

DNA-DAPI Interaction-Based Method for Cell Proliferation Rate Evaluation in 3D Structures

Effective cell number monitoring throughout the three-dimensional (3D) scaffold is a key factor in tissue engineering. There are many methods developed to evaluate cell number in 2D environments; however, they often encounter limitations in 3D. Therefore, there is a demand for reliable methods to measure cell proliferation in 3D surroundings. Here, we report a novel technique for the DNA content-based evaluation of cell proliferation using DNA-binding dye DAPI. We demonstrated the method's compatibility with four different cell cultures: cancer lines MCF-7 and MH-22a, embryonic fibroblast cell line Swiss 3T3, and primary mesenchymal stem cell culture isolated from rat's incisors. The DAPI based method was able to successfully evaluate cell proliferation in 2D, 2.5D, and 3D environments. Even though the proposed method does not discriminate between viable and dead cells, it might give a convenient snapshot of the cell number at a given time point. This should help to more reliably evaluate various processes proceeding in 2.5D and 3D cultures.

Differential role of sphingomyelin in influenza virus, rhinovirus and SARS-CoV-2 infection of Calu-3 cells

Host cell lipids play a pivotal role in the pathogenesis of respiratory virus infection. However, a direct comparison of the lipidomic profile of influenza virus and rhinovirus infections is lacking. In this study, we first compared the lipid profile of influenza virus and rhinovirus infection in a bronchial epithelial cell line. Most lipid features were downregulated for both influenza virus and rhinovirus, especially for the sphingomyelin features. Pathway analysis showed that sphingolipid metabolism was the most perturbed pathway. Functional study showed that bacterial sphingomyelinase suppressed influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication, but promoted rhinovirus replication. These findings suggest that sphingomyelin pathway can be a potential target for antiviral therapy, but should be carefully evaluated as it has opposite effects on different respiratory viruses. Furthermore, the differential effect of sphingomyelinase on rhinovirus and influenza virus may explain the interference between rhinovirus and influenza virus infection.

Normalization of metabolic data to total thymine content and its application to determination of 2-hydroxyglutarate

Our first objective was to develop an approach useful for reliable normalization of 2-hydroxyglutarate (2-HG) intracellular levels. The second objective was to use our data normalization strategy to verify previously published report on the higher d-2-HG level in tumors of colorectal cancer (CRC) patients than in normal colon fragments. We examined various methods of 2-HG level normalization in cell/tissue extracts (number of cells, mass of tissue, total protein). In order to solve the problems with reliable normalization of the 2-HG levels in colon fragments, we proposed a strategy based on relating the concentrations of 2-HG isomers to total thymine concentrations measured by ultra-performance liquid chromatography (UPLC) with UV detection in acid hydrolysates of the cell/tissue extracts. We used a common method of derivatization with diacetyl-l-tartaric anhydride (DATAN) to separate l- and d-2-HG enantiomers. DATAN-derivatized 2-HG was quantitated by UPLC with tandem mass spectrometry (MS/MS) in the selected reaction monitoring (SRM) mode. We observed a linear dependence of the total amount of thymine released from lymphocytes, HCT 116, K562, and PC-3 by acid hydrolysis on their number of cells. Our results showed a significantly higher level of l- and d-2-HG in cancer-free colon than in tumor.

Reviewing the metabolome coverage provided by LC-MS: Focus on sample preparation and chromatography-A tutorial

Metabolomics has become an invaluable tool for both studying metabolism and biomarker discovery. The great technical advances in analytical chemistry and bioinformatics have considerably increased the number of measurable metabolites, yet an important part of the human metabolome remains uncovered. Among the various MS hyphenated techniques available, LC-MS stands out as the most used. Here, we aimed to show the capabilities of LC-MS to uncover part of the metabolome and how to best proceed with sample preparation and LC to maximise metabolite detection. The analyses of various open metabolite databases served us to estimate the size of the already detected human metabolome, the expected metabolite composition of most used human biospecimens and which part of the metabolome can be detected when LC-MS is used. Based on an extensive review and on our experience, we have outlined standard procedures for LC-MS analysis of urine, cells, serum/plasma, tissues and faeces, to guide in the selection of the sample preparation method that best matches with one or more LC techniques in order to get the widest metabolome coverage. These standard procedures may be a useful tool to explore, at a glance, the wide spectrum of possibilities available, which can be a good starting point for most of the LC-MS metabolomic studies.

Data normalization strategies in metabolomics: Current challenges, approaches, and tools

Data normalization is a big challenge in quantitative metabolomics approaches, whether targeted or untargeted. Without proper normalization, the mass-spectrometry and spectroscopy data can provide erroneous, sub-optimal data, which can lead to misleading and confusing biological results and thereby result in failed application to human healthcare, clinical, and other research avenues. To address this issue, a number of statistical approaches and software tools have been proposed in the literature and implemented over the years, thereby providing a multitude of approaches to choose from - either sample-based or data-based normalization strategies. In recent years, new dedicated software tools for metabolomics data normalization have surfaced as well. In this account article, I summarize the existing approaches and the new discoveries and research findings in this area of metabolomics data normalization, and I introduce some recent tools that aid in data normalization.

Loss of tumor susceptibility gene 101 (TSG101) perturbs endoplasmic reticulum structure and function

Tumor susceptibility gene 101 (TSG101), an ESCRT-I protein, is implicated in multiple cellular processes and its functional depletion can lead to blocked lysosomal degradation, cell cycle arrest, demyelination and neurodegeneration. Here, we show that loss of TSG101 results in endoplasmic reticulum (ER) stress and this causes ER membrane remodelling (EMR). This correlates with an expansion of ER, increased vacuolation, altered relative distribution of the rough and smooth ER and disruption of three-way junctions. Blocked lysosomal degradation due to TSG101 depletion leads to ER stress and Ca²⁺ leakage from ER stores, causing destabilization of actin cytoskeleton. Inhibiting Ca²⁺ release from the ER by blocking ryanodine receptors (RYRs) with Dantrolene partially rescues the ER stress phenotypes. Hence, in this study we have identified the involvement of TSG101 in modulating ER stress mediated remodelling by engaging the actin cytoskeleton. This is significant because functional depletion of TSG101 effectuates ER-stress, perturbs the structure, mobility and function of the ER, all aspects closely associated with neurodegenerative diseases. SUMMARY STATEMENT: We show that tumor susceptibility gene (TSG) 101 regulates endoplasmic reticulum (ER) stress and its membrane remodelling. Loss of TSG101 perturbs structure, mobility and function of the ER as a consequence of actin destabilization.

Improved workflow for mass spectrometry-based metabolomics analysis of the heart

MS-based metabolomics methods are powerful techniques to map the complex and interconnected metabolic pathways of the heart; however, normalization of metabolite abundance to sample input in heart tissues remains a technical challenge. Herein, we describe an improved GC-MS-based metabolomics workflow that uses insoluble protein-derived glutamate for the normalization of metabolites within each sample and includes normalization to protein-derived amino acids to reduce biological variation and detect small metabolic changes. Moreover, glycogen is measured within the metabolomics workflow. We applied this workflow to study heart metabolism by first comparing two different methods of heart removal: the Langendorff heart method (reverse aortic perfusion) and in situ freezing of mouse heart with a modified tissue freeze-clamp approach. We then used the in situ freezing method to study the effects of acute β-adrenergic receptor stimulation (through isoproterenol (ISO) treatment) on heart metabolism. Using our workflow and within minutes, ISO reduced the levels of metabolites involved in glycogen metabolism, glycolysis, and the Krebs cycle, but the levels of pentose phosphate pathway metabolites and of many free amino acids remained unchanged. This observation was coupled to a 6-fold increase in phosphorylated adenosine nucleotide abundance. These results support the notion that ISO acutely accelerates oxidative metabolism of glucose to meet the ATP demand required to support increased heart rate and cardiac output. In summary, our MS-based metabolomics workflow enables improved quantification of cardiac metabolites and may also be compatible with other methods such as LC or capillary electrophoresis.

Quantification of HER1, HER2 and HER3 by time-resolved Förster resonance energy transfer in FFPE triple-negative breast cancer samples

Background

Triple-negative breast cancer (TNBC) has a worse prognosis compared with other breast cancer subtypes, and biomarkers to identify patients at high risk of recurrence are needed. Here, we investigated the expression of human epidermal receptor (HER) family members in TNBC and evaluated their potential as biomarkers of recurrence.

Methods

We developed Time Resolved-Förster Resonance Energy Transfer (TR-FRET) assays to quantify HER1, HER2 and HER3 in formalin-fixed paraffin-embedded (FFPE) tumour tissues. After assessing the performance and precision of our assays, we quantified HER protein expression in 51 TNBC specimens, and investigated the association of their expression with relapse-free survival.

Results

The assays were quantitative, accurate, and robust. In TNBC specimens, HER1 levels ranged from ≈4000 to more than 2 million receptors per cell, whereas HER2 levels varied from ≈1000 to 60,000 receptors per cell. HER3 expression was very low (less than 5500 receptors per cell in all samples). Moderate HER2 expression was significantly associated with higher risk of recurrence (HR = 3.93; P = 0.003).

Conclusions

Our TR-FRET assays accurately quantify HER1, HER2 and HER3 in FFPE breast tumour specimens. Moderate HER2 expression may represent a novel prognostic marker in patients with TNBC.

Lipidomic Profiling Reveals Significant Perturbations of Intracellular Lipid Homeostasis in Enterovirus-Infected Cells

Enterovirus A71 (EV-A71) and coxsackievirus A16 (CV-A16) are the most common causes of hand, foot, and mouth disease. Severe EV-A71 and CV-A16 infections may be associated with life-threatening complications. However, the pathogenic mechanisms underlying these severe clinical and pathological features remain incompletely understood. Lipids are known to play critical roles in multiple stages of the virus replication cycle. The specific lipid profile induced upon virus infection is required for optimal virus replication. The perturbations in the host cell lipidomic profiles upon enterovirus infection have not been fully characterized. To this end, we performed ultra-high performance liquid chromatography–electrospray ionization–quadrupole–time of flight-mass spectrometry (UPLC-ESI-Q-TOF-MS)-based lipidomics to characterize the change in host lipidome upon EV-A71 and CV-A16 infections. Our results revealed that 47 lipids within 11 lipid classes were significantly perturbed after EV-A71 and CV-A16 infection. Four polyunsaturated fatty acids (PUFAs), namely, arachidonic acid (AA), docosahexaenoic acid (DHA), docosapentaenoic acid (DPA), and eicosapentaenoic acid (EPA), were consistently upregulated upon EV-A71 and CV-A16 infection. Importantly, exogenously supplying three of these four PUFAs, including AA, DHA, and EPA, in cell cultures significantly reduced EV-A71 and CV-A16 replication. Taken together, our results suggested that enteroviruses might specifically modulate the host lipid pathways for optimal virus replication. Excessive exogenous addition of lipids that disrupted this delicate homeostatic state could prevent efficient viral replication. Precise manipulation of the host lipid profile might be a potential host-targeting antiviral strategy for enterovirus infection.

Determination of lipid mediators in breast cancer cells using lyophilization-supercritical fluid extraction online coupled with supercritical fluid chromatography-quadrupole tandem mass spectrometry

A lyophilization-supercritical fluid extraction coupled with supercritical fluid chromatography-quadrupole tandem mass spectrometry online method was developed for the determination of lipid mediators in breast cancer cells. Supercritical fluid extraction was applied to the cell samples for the first time due to the use of lyophilization. The conditions of supercritical fluid extraction and supercritical fluid chromatography-quadrupole tandem mass spectrometry were investigated systematically. Under the optimized conditions, all the calibration curves for the lipid mediators showed good linearity (correlation coefficient > 0.99). The limits of detection and the limits of quantification were in the range of 0.190-5.36 pg and 0.560-16.2 pg, respectively. The recoveries were in the range of 70.3-125%. The relative standard deviations of the precision ranged from 1.49-18.7% and the accuracies were higher than 84%. Compared with liquid-liquid extraction coupled with liquid chromatography and tandem mass spectrometry method, the present approach reduced the manual labor and obtained higher sensitivity as well as higher extraction recoveries for all 15 lipid mediators. Finally, the online method was applied to the quantification of lipid mediators in breast cancer cells and normal mammary epithelial cells. On the basis of the results, this lyophilization-supercritical fluid extraction online coupled with supercritical fluid chromatography-quadrupole tandem mass spectrometry method showed great promise in the analysis of lipid mediators in complex biological samples.

Evaluation and optimization of sample pretreatment for GC/MS-based metabolomics in embryonic zebrafish

Metabolomics tactics have been applied in the research associated with embryonic zebrafish. However, the report regarding the evaluation of impacts of sample pretreatment on metabolomics results from zebrafish embryos is limited. In the present study, different data normalization approaches, extraction solvents, and extraction strategies for off-line derivatization gas chromatography coupled with mass spectrometry-based metabolomics analysis of zebrafish eleutheroembryos were evaluated and optimized. The results showed that, when 4-chlorophenylalanine normalization, sample homogenization and pure methanol combined with ultrasonic extraction were conducted, better repeatabilities, higher signals and broader coverages of detected metabolites can be achieved. The recovery and standard deviation of most standards were in the range of 82%-121% and 6.6%-12%, respectively, while the relative standard deviation of major detected metabolites ranged from 5.4% to 19%, indicating good extraction efficiencies and method precision. Under the developed method, 87 important endogenous metabolites such as citric acid and hypoxanthine were identified by universal databases or standards among 270 extracted metabolites, which consisted of sugars, amines, amino acids, nucleotides, fatty acids, and sterols. Therefore, the results could provide a proper pretreatment protocol for the analysis of wide-coverage metabolome in embryonic zebrafish. In addition, this study highlights the impact of normalization and extraction methods on the data quality of metabolomics analysis.

ROS-Induced GATA4 and GATA6 Downregulation Inhibits StAR Expression in LPS-Treated Porcine Granulosa-Lutein Cells

LPS is a major endotoxin produced by gram-negative bacteria, and exposure to it commonly occurs in animal husbandry. Previous studies have shown that LPS infection disturbs steroidogenesis, including progesterone production, and subsequently decreases animal reproductive performance. However, little information about the underlying mechanisms is available thus far. In the present study, an in vitro-luteinized porcine granulosa cell model was used to study the underlying molecular mechanisms of LPS treatment. We found that LPS significantly inhibits progesterone production and downregulates the expressions of progesterone synthesis-associated genes (StAR, CYP11A1, and 3β-HSD). Furthermore, the levels of ROS were significantly increased in an LPS dose-dependent manner. Moreover, transcriptional factors GATA4 and GATA6, but not NR5A1, were significantly downregulated. Elimination of LPS-stimulated ROS by melatonin or vitamin C could restore the expressions of GATA4, GATA6, and StAR. In parallel, StAR expression was also inhibited by the knockdown of GATA4 and GATA6. Based on these data, we conclude that LPS impairs StAR expression via the ROS-induced downregulation of GATA4 and GATA6. Collectively, these findings provide new insights into the understanding of reproductive losses in animals suffering from bacterial infection and LPS exposure.

Oxidized alginate hydrogels with the GHK peptide enhance cord blood mesenchymal stem cell osteogenesis: A paradigm for metabolomics-based evaluation of biomaterial design

Oxidized alginate hydrogels are appealing alternatives to natural alginate due to their favourable biodegradability profiles and capacity to self-crosslink with amine containing molecules facilitating functionalization with extracellular matrix cues, which enable modulation of stem cell fate, achieve highly viable 3-D cultures, and promote cell growth. Stem cell metabolism is at the core of cellular fate (proliferation, differentiation, death) and metabolomics provides global metabolic signatures representative of cellular status, being able to accurately identify the quality of stem cell differentiation. Herein, umbilical cord blood mesenchymal stem cells (UCB MSCs) were encapsulated in novel oxidized alginate hydrogels functionalized with the glycine-histidine-lysine (GHK) peptide and differentiated towards the osteoblastic lineage. The ADA-GHK hydrogels significantly improved osteogenic differentiation compared to gelatin-containing control hydrogels, as demonstrated by gene expression, alkaline phosphatase activity and bone extracellular matrix deposition. Metabolomics revealed the high degree of metabolic heterogeneity in the gelatin-containing control hydrogels, captured the enhanced osteogenic differentiation in the ADA-GHK hydrogels, confirmed the similar metabolism between differentiated cells and primary osteoblasts, and elucidated the metabolic mechanism responsible for the function of GHK. Our results suggest a novel paradigm for metabolomics-guided biomaterial design and robust stem cell bioprocessing. STATEMENT OF SIGNIFICANCE: Producing high quality engineered bone grafts is important for the treatment of critical sized bone defects. Robust and sensitive techniques are required for quality assessment of tissue-engineered constructs, which result to the selection of optimal biomaterials for bone graft development. Herein, we present a new use of metabolomics signatures in guiding the development of novel oxidised alginate-based hydrogels with umbilical cord blood mesenchymal stem cells and the glycine-histidine-lysine peptide, demonstrating that GHK induces stem cell osteogenic differentiation. Metabolomics signatures captured the enhanced osteogenesis in GHK hydrogels, confirmed the metabolic similarity between differentiated cells and primary osteoblasts, and elucidated the metabolic mechanism responsible for the function of GHK. In conclusion, our results suggest a new paradigm of metabolomics-driven design of biomaterials.

A short-term plastic adherence incubation of the stromal vascular fraction leads to a predictable GMP-compliant cell-product

Introduction:Mesenchymal stromal/stem cells (MSCs) derived from fat tissue are an encouraging tool for regenerative medicine. They share properties similar to the bone marrow-derived MSCs, but the amount of MSCs per gram of fat tissue is 500x higher. The fat tissue can easily be digested by collagenase, releasing a heterogeneous cell fraction called stromal vascular fraction (SVF) which contains a variable amount of stromal/stem cells. In Europe, cell products like the SVF derived from fat tissue are considered advanced therapy medicinal product (ATMPs). As a consequence, the manufacturing process has to be approved via GMP-compliant process validation. The problem of the process validation for SVF is the heterogeneity of this fraction.

Methods: Here, we modified existing purification strategies by adding an additional plastic adherence incubation of maximal 20 hours after SVF isolation. The resulting cell fraction was characterized and compared to SVF as well as cultivated adipose-derived stromal/stem cells (ASCs) with respect to viability and cell yield, the expression of surface markers, differentiation potential and cytokine expression.

Results: Short-term incubation significantly reduced the heterogeneity of the resulting cell fraction compared to SVF. The cells were able to differentiate into adipocytes, chondrocytes, and osteoblasts. More importantly, they expressed trophic proteins which have been previously associated with the beneficial effects of MSCs. Furthermore, GMP compliance of the production process described herein was acknowledged by the national regulatory agencies (DE_BB_01_GMP_2017_1018).

Conclusion: Addition of a short purification-step after the SVF isolation is a cheap and fast strategy to isolate a homogeneous uncultivated GMP-compliant cell fraction of ASCs.

Comparison of human isogeneic Wharton's jelly MSCs and iPSC-derived MSCs reveals differentiation-dependent metabolic responses to IFNG stimulation

Variability among donors, non-standardized methods for isolation, and characterization contribute to mesenchymal stem/stromal cell (MSC) heterogeneity. Induced pluripotent stem cell (iPSCs)-derived MSCs would circumvent many of current issues and enable large-scale production of standardized cellular therapy. To explore differences between native MSCs (nMSCs) and iPSC-derived MSCs (iMSCs), we developed isogeneic lines from Wharton’s jelly (WJ) from the umbilical cords of two donors (#12 and #13) under xeno-free conditions. Next, we reprogrammed them into iPSCs (iPSC12 and iPSC13) and subsequently differentiated them back into iMSCs (iMSC12 and iMSC13) using two different protocols, which we named ARG and TEX. We assessed their differentiation capability, transcriptome, immunomodulatory potential, and interferon-γ (IFNG)-induced changes in metabolome. Our data demonstrated that although both differentiation protocols yield iMSCs similar to their parental nMSCs, there are substantial differences. The ARG protocol resulted in iMSCs with a strong immunomodulatory potential and lower plasticity and proliferation rate, whereas the TEX protocol raised iMSCs with a higher proliferation rate, better differentiation potential, though weak immunomodulatory response. Our data suggest that, following a careful selection and screening of donors, nMSCs from umbilical’s cord WJ can be easily reprogrammed into iPSCs, providing an unlimited source of material for differentiation into iMSCs. However, the differentiation protocol should be chosen depending on their clinical use.

The Chemical Potential of Plasma Membrane Cholesterol: Implications for Cell Biology

Cholesterol is abundant in plasma membranes and exhibits a variety of interactions throughout the membrane. Chemical potential accounts for thermodynamic consequences of molecular interactions, and quantifies the effective concentration (i.e., activity) of any substance participating in a process. We have developed, to our knowledge, the first method to measure cholesterol chemical potential in plasma membranes. This was accomplished by complexing methyl-β-cyclodextrin with cholesterol in an aqueous solution and equilibrating it with an organic solvent containing dissolved cholesterol. The chemical potential of cholesterol was thereby equalized in the two phases. Because cholesterol is dilute in the organic phase, here activity and concentration were equivalent. This equivalence allowed the amount of cholesterol bound to methyl-β-cyclodextrin to be converted to cholesterol chemical potential. Our method was used to determine the chemical potential of cholesterol in erythrocytes and in plasma membranes of nucleated cells in culture. For erythrocytes, the chemical potential did not vary when the concentration was below a critical value. Above this value, the chemical potential progressively increased with concentration. We used standard cancer lines to characterize cholesterol chemical potential in plasma membranes of nucleated cells. This chemical potential was significantly greater for highly metastatic breast cancer cells than for nonmetastatic breast cancer cells. Chemical potential depended on density of the cancer cells. A method to alter and fix the cholesterol chemical potential to any value (i.e., a cholesterol chemical potential clamp) was also developed. Cholesterol content did not change when cells were clamped for 24-48 h. It was found that the level of activation of the transcription factor STAT3 increased with increasing cholesterol chemical potential. The cholesterol chemical potential may regulate signaling pathways.

BETP degradation simultaneously targets acute myelogenous leukemia stem cells and the microenvironment

Anti-leukemic effect of BET/BRD4 (BETP) protein inhibition has been largely attributed to transcriptional downregulation of cellular anabolic/anti-apoptotic processes but its effect on bone marrow microenvironment, a sanctuary favoring persistence of leukemia stem/progenitor cells, is unexplored. Sustained degradation of BETP with small-molecule BET proteolysis-targeting chimera (PROTAC), ARV-825, resulted in marked downregulation of surface CXCR4 and CD44, key proteins in leukemia-microenvironment interaction, in AML cells. Abrogation of surface CXCR4 expression impaired SDF-1α directed migration and was mediated through transcriptional down-regulation of PIM1 kinase that in turn phosphorylates CXCR4 and facilitates its surface localization. Down-regulation of CD44/CD44v8-10 impaired cystine uptake, lowered intracellular reduced glutathione and increased oxidative stress. More importantly, BETP degradation markedly decreased CD34+CD38-CD90-CD45RA+ leukemic stem cell population and alone or in combination with Cytarabine, prolonged survival in mouse model of human leukemia including AML-PDX. Gene expression profiling and single cell proteomics confirmed down regulation of the gene signatures associated with 'stemness' in AML and Wnt/β-catenin, Myc pathways. Hence, BETP degradation by ARV-825 simultaneously targets cell intrinsic signaling, stromal interactions and metabolism in AML.

SREBP-dependent lipidomic reprogramming as a broad-spectrum antiviral target

Viruses are obligate intracellular microbes that exploit the host metabolic machineries to meet their biosynthetic demands, making these host pathways potential therapeutic targets. Here, by exploring a lipid library, we show that AM580, a retinoid derivative and RAR-α agonist, is highly potent in interrupting the life cycle of diverse viruses including Middle East respiratory syndrome coronavirus and influenza A virus. Using click chemistry, the overexpressed sterol regulatory element binding protein (SREBP) is shown to interact with AM580, which accounts for its broad-spectrum antiviral activity. Mechanistic studies pinpoint multiple SREBP proteolytic processes and SREBP-regulated lipid biosynthesis pathways, including the downstream viral protein palmitoylation and double-membrane vesicles formation, that are indispensable for virus replication. Collectively, our study identifies a basic lipogenic transactivation event with broad relevance to human viral infections and represents SREBP as a potential target for the development of broad-spectrum antiviral strategies.

Viruses rely on host cell metabolism for replication, making these pathways potential therapeutic targets. Here, the authors show that AM580, a retinoid derivative and RAR-α agonist, affects replication of several RNA viruses by interfering with the activity of SREBP.

Sample Preparation and Reporting Standards for Metabolomics of Adherent Mammalian Cells

Metabolomics is an analytical technique that investigates the small molecules present within a biological system. Metabolomics of cultured cells allows profiling of the metabolic chemicals involved in a cell type-specific system and the response of that metabolome to external challenges, such as change in environment or exposure to drugs or toxins. The numerous benefits of in vitro metabolomics include a much greater control of external variables and reduced ethical concerns. There is potential for metabolomics of mammalian cells to uncover new information on mechanisms of action for drugs or toxins or to provide a more sensitive, human-specific early risk assessment in drug development or toxicology investigations. One way to achieve stronger biological outcomes from metabolomic data is via the use of these mammalian cultured cell models, particularly in a high-throughput context. With the sensitivity and quantity of data that metabolomics is able to provide, it is important to ensure that the sampling techniques have minimal interference when it comes to interpretation of any observed shifts in the metabolite profile. Here we describe a sampling procedure designed to ensure that the effects seen in metabolomic analyses are explained fully by the experimental factor and not other routine culture-specific activities.

The potential of magnetic hyperthermia for triggering the differentiation of cancer cells

Magnetic hyperthermia is a potential technique for cancer therapy that exploits heat generated by magnetic nanoparticles to kill cancerous cells. Many studies have shown that magnetic hyperthermia is effective at killing cancer cells both in vitro and in vivo, however little attention has been paid to the cellular functioning of the surviving cells. We report here new evidence demonstrating the onset of thermally triggered differentiation in osteosarcoma cancer cells that survive magnetic hyperthermia treatment. This raises the possibility that in addition to causing cell death, magnetic hyperthermia could induce surviving cancer cells to form more mature cell types and thereby inhibit their capacity to self-renew. Such processes could prove to be as important as cell death when considering magnetic hyperthermia for treating cancer.

Multiomics tools for the diagnosis and treatment of rare neurological disease

Conventional workup of rare neurological disease is frequently hampered by diagnostic delay or lack of diagnosis. While biomarkers have been established for many neurometabolic disorders, improved methods are required for diagnosis of previously unidentified or underreported causes of rare neurological disease. This would result in a higher diagnostic yield and increased patient numbers required for interventional studies. Recent studies using next-generation sequencing and metabolomics have led to identification of novel disease-causing genes and biomarkers. This combined approach can assist in overcoming challenges associated with analyzing and interpreting the large amount of data obtained from each technique. In particular, metabolomics can support the pathogenicity of sequence variants in genes encoding enzymes or transporters involved in metabolic pathways. Moreover, metabolomics can show the broader perturbation caused by inborn errors of metabolism and identify a metabolic fingerprint of metabolic disorders. As such, using "omics" has great potential to meet the current needs for improved diagnosis and elucidation of rare neurological disease.