Evaluating protocols for reproducible targeted metabolomics by NMR.

Metabolomics aims to study the downstream effects of variables like diet, environment, or disease on a given biological system. However, inconsistencies in sample preparation, data acquisition/processing protocols lead to reproducibility and accuracy concerns. A systematic study was conducted to assess how sample preparation methods and data analysis platforms affect metabolite susceptibility. A targeted panel of 25 metabolites was evaluated in 69 clinical metabolomics samples prepared following three different protocols: intact, ultrafiltration, and protein precipitation. The resulting metabolic profiles were characterized by 1D 1H nuclear magnetic resonance (NMR) spectroscopy and analyzed with Chenomx v8.3 and SMolESY software packages. Greater than 90% of the metabolites were extracted more efficiently using protein precipitation than filtration, which aligns with previously reported results. Additionally, analysis of data processing software suggests that metabolite concentrations were overestimated by Chenomx batch-fitting, which only appears reliable for determining relative fold changes rather than absolute quantification. However, an assisted-fit method provided sufficient guidance to achieve accurate results while avoiding a time-consuming fully manual-fitting approach. By combining our results with previous studies, we can now provide a list of 5 common metabolites [2-hydroxybutyrate (2-HB), choline, dimethylamine (DMA), glutamate, lactate] with a high degree of variability in reported fold changes and standard deviations that need careful consideration before being annotated as potential biomarkers. Our results show that sample preparation and data processing package critically impact clinical metabolomics study success. There is a clear need for an increased degree of standardization and harmonization of methods across the metabolomics community to ensure reliable outcomes.

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Applications for Metabolomics.

Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (105-106) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (<1 ppm mass error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the routine adoption of FT-ICR-MS by metabolomics researchers. This review examines recent applications of FT-ICR-MS metabolomics in the search for clinical and non-human biomarkers; for the analysis of food, beverage, and environmental samples; and for the high-resolution imaging of tissues and other biological samples. We provide recent examples of metabolomics studies that highlight the advantages of FT-ICR-MS for the detailed and reliable characterization of the metabolome. Additionally, we offer some practical considerations for implementing FT-ICR-MS into a research program by providing a list of FT-ICR-MS facilities and by identifying different high-throughput interfaces, varieties of sample types, analysis methods (e.g., van Krevelen diagrams, Kendrick mass defect plot, etc.), and sample preparation and handling protocols used in FT-ICR-MS experiments. Overall, FT-ICR-MS holds great promise as a vital research tool for advancing metabolomics investigations.

Modeling normal mouse uterine contraction and placental perfusion with non-invasive longitudinal dynamic contrast enhancement MRI.

BACKGROUND: The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual's entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities. OBJECTIVE: Our goal is to create a non-invasive preclinical imaging pipeline that can longitudinally probe murine placental health in vivo. We use advanced imaging processing schemes to establish functional biomarkers for non-invasive longitudinal evaluation of placental development. METHODOLOGY: We implement dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and analysis pipeline to quantify uterine contraction and placental perfusion dynamics. We use optic flow and time-frequency analysis to quantify and characterize contraction-related placental motion. Our novel imaging and analysis pipeline uses subcutaneous administration of gadolinium for steepest slope-based perfusion evaluation, enabling non-invasive longitudinal monitoring. RESULTS: We demonstrate that the placenta exhibits spatially asymmetric contractile motion that develops from E14.5 to E17.5. Additionally, we see that placental perfusion, perfusion delivery rate, and substrate delivery all increase from E14.5 to E17.5, with the High Perfusion Chamber (HPC) leading the placental changes that occur from E14.5 to E17.5. DISCUSSION: We advance the placental perfusion chamber paradigm with a novel, physiologically based threshold model for chamber localization and demonstrate spatially varying placental chambers using multiple functional metrics that assess mouse placental development and remodeling throughout gestation. CONCLUSION: Our pipeline enables the non-invasive, longitudinal assessment of multiple placenta functions from a single imaging session. Our pipeline serves as a key toolbox for advancing research in mouse models of placental disease and disorder.

In Vitro Fermentation of Animal and Plant Protein Isolates by the Human Gut Microbiota Under High and Low Carbohydrate Conditions.

SCOPE: There is a lack of research comparing how different protein isolates influence the microbiome, especially when carbohydrate (CHO) availability is varied. The objective is to determine changes in gut microbiota composition and function during fermentation of digested protein isolates under high and low CHO conditions. METHODS AND RESULTS: Protein isolates from beef, egg white, milk, pea, and soy are subjected to in vitro digestion and fermentation with human fecal microbiota. Under low CHO conditions, the microbiota is primarily proteolytic with decreased concentrations of peptides and increased variance among microbial taxa and production of ammonia and branched chain fatty acids by the microbiota. Milk protein not only results in the highest production of butyrate and p-hydroxyphenylacetate but also has high concentrations of deleterious fermentation metabolites. Amino acid composition of the protein isolates is significantly correlated with abundances of many microbial taxa and metabolites, but the correlations are stronger in the low CHO medium. CONCLUSION: This study shows that low CHO conditions increase proteolytic fermentation and result in increased differences in microbiota response to protein isolates. It also showed that amino acid composition is highly associated with microbiota composition and function especially under low CHO conditions.

Simulated LC-MS Data Set for Assessing the Metabolomics Data Processing Pipeline Implemented into MVAPACK.

Metabolomics commonly relies on using one-dimensional (1D) 1H NMR spectroscopy or liquid chromatography-mass spectrometry (LC-MS) to derive scientific insights from large collections of biological samples. NMR and MS approaches to metabolomics require, among other issues, a data processing pipeline. Quantitative assessment of the performance of these software platforms is challenged by a lack of standardized data sets with "known" outcomes. To resolve this issue, we created a novel simulated LC-MS data set with known peak locations and intensities, defined metabolite differences between groups (i.e., fold change > 2, coefficient of variation ≤ 25%), and different amounts of added Gaussian noise (0, 5, or 10%) and missing features (0, 10, or 20%). This data set was developed to improve benchmarking of existing LC-MS metabolomics software and to validate the updated version of our MVAPACK software, which added gas chromatography-MS and LC-MS functionality to its existing 1D and two-dimensional NMR data processing capabilities. We also included two experimental LC-MS data sets acquired from a standard mixture andMycobacterium smegmatiscell lysates since a simulated data set alone may not capture all the unique characteristics and variability of real spectra needed to assess software performance properly. Our simulated and experimental LC-MS data sets were processed with the MS-DIAL and XCMSOnline software packages and our MVAPACK toolkit to showcase the utility of our data sets to benchmark MVAPACK against community standards. Our results demonstrate the enhanced objectivity and clarity of software assessment that can be achieved when both simulated and experimental data are employed since distinctly different software performances were observed with the simulated and experimental LC-MS data sets. We also demonstrate that the performance of MVAPACK is equivalent to or exceeds existing LC-MS software programs while providing a single platform for processing and analyzing both NMR and MS data sets.

Applications of chromatographic methods in metabolomics: A review.

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

Cancer-associated fibroblast-derived acetate promotes pancreatic cancer development by altering polyamine metabolism via the ACSS2-SP1-SAT1 axis.

The ability of tumour cells to thrive in harsh microenvironments depends on the utilization of nutrients available in the milieu. Here we show that pancreatic cancer-associated fibroblasts (CAFs) regulate tumour cell metabolism through the secretion of acetate, which can be blocked by silencing ATP citrate lyase (ACLY) in CAFs. We further show that acetyl-CoA synthetase short-chain family member 2 (ACSS2) channels the exogenous acetate to regulate the dynamic cancer epigenome and transcriptome, thereby facilitating cancer cell survival in an acidic microenvironment. Comparative H3K27ac ChIP-seq and RNA-seq analyses revealed alterations in polyamine homeostasis through regulation of SAT1 gene expression and enrichment of the SP1-responsive signature. We identified acetate/ACSS2-mediated acetylation of SP1 at the lysine 19 residue that increased SP1 protein stability and transcriptional activity. Genetic or pharmacologic inhibition of the ACSS2-SP1-SAT1 axis diminished the tumour burden in mouse models. These results reveal that the metabolic flexibility imparted by the stroma-derived acetate enabled cancer cell survival under acidosis via the ACSS2-SP1-SAT1 axis.

Perspective: use and reuse of NMR-based metabolomics data: what works and what remains challenging.

BACKGROUND: The National Cancer Institute issued a Request for Information (RFI; NOT-CA-23-007) in October 2022, soliciting input on using and reusing metabolomics data. This RFI aimed to gather input on best practices for metabolomics data storage, management, and use/reuse. AIM OF REVIEW: The nuclear magnetic resonance (NMR) Interest Group within the Metabolomics Association of North America (MANA) prepared a set of recommendations regarding the deposition, archiving, use, and reuse of NMR-based and, to a lesser extent, mass spectrometry (MS)-based metabolomics datasets. These recommendations were built on the collective experiences of metabolomics researchers within MANA who are generating, handling, and analyzing diverse metabolomics datasets spanning experimental (sample handling and preparation, NMR/MS metabolomics data acquisition, processing, and spectral analyses) to computational (automation of spectral processing, univariate and multivariate statistical analysis, metabolite prediction and identification, multi-omics data integration, etc.) studies. KEY SCIENTIFIC CONCEPTS OF REVIEW: We provide a synopsis of our collective view regarding the use and reuse of metabolomics data and articulate several recommendations regarding best practices, which are aimed at encouraging researchers to strengthen efforts toward maximizing the utility of metabolomics data, multi-omics data integration, and enhancing the overall scientific impact of metabolomics studies.

At-Risk Median Motor Branch to the Thenar Musculature Crossing Under the Flexor Carpi Radialis in the Forearm: A Case Report.

CASE: A 77-year-old woman who sustained a distal radius and ulna fracture underwent open reduction internal fixation through a standard flexor carpi radialis (FCR) approach. On dissection, a proximal division of the median nerve was identified, with an aberrant motor branch crossing radial to ulnar deep to FCR and superficial to flexor pollicis longus. CONCLUSION: Although many anatomic variants of the median nerve have been described, the current case demonstrates a particularly important median motor branch variant, imposing a substantial risk of iatrogenic injury during a standard FCR approach.

Potential Metabolite Biomarkers of Multiple Sclerosis from Multiple Biofluids.

Multiple sclerosis (MS) is a chronic and progressive neurological disorder without a cure, but early intervention can slow disease progression and improve the quality of life for MS patients. Obtaining an accurate diagnosis for MS is an arduous and error-prone task that requires a combination of a detailed medical history, a comprehensive neurological exam, clinical tests such as magnetic resonance imaging, and the exclusion of other possible diseases. A simple and definitive biofluid test for MS does not exist, but is highly desirable. To address this need, we employed NMR-based metabolomics to identify potentially unique metabolite biomarkers of MS from a cohort of age and sex-matched samples of cerebrospinal fluid (CSF), serum, and urine from 206 progressive MS (PMS) patients, 46 relapsing-remitting MS (RRMS) patients, and 99 healthy volunteers without a MS diagnosis. We identified 32 metabolites in CSF that varied between the control and PMS patients. Utilizing patient-matched serum samples, we were able to further identify 31 serum metabolites that may serve as biomarkers for PMS patients. Lastly, we identified 14 urine metabolites associated with PMS. All potential biomarkers are associated with metabolic processes linked to the pathology of MS, such as demyelination and neuronal damage. Four metabolites with identical profiles across all three biofluids were discovered, which demonstrate their potential value as cross-biofluid markers of PMS. We further present a case for using metabolic profiles from PMS patients to delineate biomarkers of RRMS. Specifically, three metabolites exhibited a variation from healthy volunteers without MS through RRMS and PMS patients. The consistency of metabolite changes across multiple biofluids, combined with the reliability of a receiver operating characteristic classification, may provide a rapid diagnostic test for MS.

Modeling Normal Mouse Uterine Contraction and Placental Perfusion with Non-invasive Longitudinal Dynamic Contrast Enhancement MRI.

The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual's entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities. Non-invasive imaging that can longitudinally probe murine placental health in vivo are critical to understanding placental development throughout pregnancy. We developed advanced imaging processing schemes to establish functional biomarkers for non-invasive longitudinal evaluation of placental development. We developed a dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) pipeline combined with advanced image process methods to model uterine contraction and placental perfusion dynamics. Our novel imaging pipeline uses subcutaneous administration of gadolinium for steepest-slope based perfusion evaluation. This enables non-invasive longitudinal monitoring. Additionally, we advance the placental perfusion chamber paradigm with a novel physiologically-based threshold model for chamber localization and demonstrate spatially varying placental chambers using multiple functional metrics that assess mouse placental development and continuing remodeling throughout gestation. Lastly, using optic flow to quantify placental motions arisen from uterine contractions in conjunction with time-frequency analysis, we demonstrated that the placenta exhibited asymmetric contractile motion.

Central Role for Glycolysis and Fatty Acids in LH-responsive Progesterone Synthesis.

Progesterone production by the corpus luteum is fundamental for establishing and maintaining pregnancy. The pituitary gonadotropin luteinizing hormone (LH) is recognized as the primary stimulus for luteal formation and progesterone synthesis, regardless of species. Previous studies demonstrated an elevation in abundance of genes related to glucose and lipid metabolism during the follicular to luteal transition. However, the metabolic phenotype of these highly steroidogenic cells has not been studied. Herein, we determined acute metabolic changes induced by LH in primary luteal cells and defined pathways required for progesterone synthesis. Untargeted metabolomics analysis revealed that LH induces rapid changes in vital metabolic pathways, including glycolysis, tricarboxylic acid (TCA) cycle, pentose phosphate pathway, de novo lipogenesis, and hydrolysis of phospholipids. LH stimulated glucose uptake, enhanced glycolysis, and flux of [U- 13 C 6 ]-labeled glucose-derived carbons into metabolic branches associated with adenosine 5'-triphosphate (ATP) and NADH/NADPH production, synthesis of nucleotides, proteins, and lipids, glycosylation of proteins or lipids, and redox homeostasis. Selective use of small molecule inhibitors targeting the most significantly changed pathways, such as glycolysis, TCA cycle, and lipogenesis, uncovered cellular metabolic routes required for LH-stimulated steroidogenesis. Furthermore, LH via the protein kinase A (PKA) pathway triggered post- translational modification of acetyl-CoA carboxylase alpha (ACACA) and ATP citrate lyase (ACLY), enzymes involved in de novo synthesis of fatty acids. Inhibition of ACLY and fatty acid transport into mitochondria reduced LH-stimulated ATP, cAMP production, PKA activation, and progesterone synthesis. Taken together, these findings reveal novel hormone-sensitive metabolic pathways essential for maintaining LHCGR/PKA signaling and steroidogenesis in ovarian luteal cells. Significance: The establishment and maintenance of pregnancy require a well-developed corpus luteum, an endocrine gland within the ovary that produces progesterone. Although there is increased awareness of intracellular signaling events initiating the massive production of progesterone during the reproductive cycle and pregnancy, there are critical gaps in our knowledge of the metabolic and lipidomic pathways required for initiating and maintaining luteal progesterone synthesis. Here, we describe rapid, hormonally triggered metabolic pathways, and define metabolic targets crucial for progesterone synthesis by ovarian steroidogenic cells. Understanding hormonal control of metabolic pathways may help elucidate approaches for improving ovarian function and successful reproduction or identifying metabolic targets for developing nonhormonal contraceptives.

The reversible low-temperature instability of human DJ-1 oxidative states.

DJ-1 is a homodimeric protein that is centrally involved in various human diseases including Parkinson disease (PD). DJ-1 protects against oxidative damage and mitochondrial dysfunction through a homeostatic control of reactive oxygen species (ROS). DJ-1 pathology results from a loss of function, where ROS readily oxidizes a highly conserved and functionally essential cysteine (C106). The over-oxidation of DJ-1 C106 leads to a dynamically destabilized and biologically inactivated protein. An analysis of the structural stability of DJ-1 as a function of oxidative state and temperature may provide further insights into the role the protein plays in PD progression. NMR spectroscopy, circular dichroism, analytical ultracentrifugation sedimentation equilibrium, and molecular dynamics simulations were utilized to investigate the structure and dynamics of the reduced, oxidized (C106-SO2 - ), and over-oxidized (C106-SO3 - ) forms of DJ-1 for temperatures ranging from 5°C to 37°C. The three oxidative states of DJ-1 exhibited distinct temperature-dependent structural changes. A cold-induced aggregation occurred for the three DJ-1 oxidative states by 5°C, where the over-oxidized state aggregated at significantly higher temperatures than both the oxidized and reduced forms. Only the oxidized and over-oxidized forms of DJ-1 exhibited a mix state containing both folded and partially denatured protein that likely preserved secondary structure content. The relative amount of this denatured form of DJ-1 increased as the temperature was lowered, consistent with a cold-denaturation. Notably, the cold-induced aggregation and denaturation for the DJ-1 oxidative states were completely reversible. The dramatic changes in the structural stability of DJ-1 as a function of oxidative state and temperature are relevant to its role in PD and its functional response to oxidative stress.

Reduced Brain Cortex Angiogenesis in the Offspring of the Preeclampsia-Like Syndrome.

BACKGROUND: Children from pregnancies affected by preeclampsia have an increased risk of cognitive and behavioral alterations via unknown pathophysiology. We tested the hypothesis that preeclampsia generated reduced brain cortex angiogenesis in the offspring. METHODS: The preeclampsia-like syndrome (PELS) mouse model was generated by administering the nitric oxide inhibitor NG-nitroarginine methyl ester hydrochloride. Confirmatory experiments were done using 2 additional PELS models. While in vitro analysis used mice and human brain endothelial cells exposed to serum of postnatal day 5 pups or umbilical plasma from preeclamptic pregnancies, respectively. RESULTS: We report significant reduction in the area occupied by blood vessels in the motor and somatosensory brain cortex of offspring (postnatal day 5) from PELS compared with uncomplicated control offspring. These data were confirmed using 2 additional PELS models. Furthermore, circulating levels of critical proangiogenic factors, VEGF (vascular endothelial growth factor), and PlGF (placental growth factor) were lower in postnatal day 5 PELS. Also we found lower VEGF receptor 2 (KDR [kinase insert domain-containing receptor]) levels in mice and human endothelial cells exposed to the serum of postnatal day 5 PELS or fetal plasma of preeclamptic pregnancies, respectively. These changes were associated with lower in vitro angiogenic capacity, diminished cell migration, larger F-actin filaments, lower number of filopodia, and lower protein levels of F-actin polymerization regulators in brain endothelial cells exposed to serum or fetal plasma of offspring from preeclampsia. CONCLUSIONS: Offspring from preeclampsia exhibited diminished brain cortex angiogenesis, associated with lower circulating VEGF/PlGF/KDR protein levels, impaired brain endothelial migration, and dysfunctional assembly of F-actin filaments. These alterations may predispose to structural and functional alterations in long-term brain development.

Histidine Enhances the Anticancer Effect of Gemcitabine against Pancreatic Cancer via Disruption of Amino Acid Homeostasis and Oxidant-Antioxidant Balance.

Due to the severe toxicity posed by chemotherapeutic drugs, adjuvant nutritional intervention has gained increased attention in the treatment of pancreatic cancer (PC). Amino acid (AA) metabolism is aberrantly regulated in PC and circulating histidine (His) levels are low in PC patients. We hypothesized that His uptake and/or metabolism is dysregulated in PC and that combining His with gemcitabine (Gem), a drug used in the treatment of PC, will enhance the anti-cancer effects of Gem. We performed in vitro and in vivo studies to determine the anticancer effect of the combination of His and Gem against lethal PC. We demonstrate that circulating His levels are low in both human subjects and genetically engineered mice exhibiting pancreatic tumors. Interestingly, the expression of histidine ammonia lyase, an enzyme involved in His catabolism, is higher in PC compared to normal subjects. His + Gem exerts a more potent cytotoxic effect in PC cells compared to individual treatments. His treatment results in a profound increase in His accumulation, accompanied by a depletion of a number of AAs, promoting cancer cell survival and/or glutathione (GSH) synthesis. His but not Gem increases hydrogen peroxide and depletes cellular GSH. Supplementation with GSH protects cells against His + Gem-induced cytotoxicity. Further, our in vivo studies demonstrate that His + Gem potently reduced tumor mass and improved mouse survival. Taken together, our data suggest that PC cells exhibit an aberrant His uptake/accumulation which, in turn, leads to oxidative stress and depletion of AA pool, thereby enhancing the anticancer effect of Gem.

Pre-pregnancy stress induces maternal vascular dysfunction during pregnancy and postpartum.

An estimated 20% of women suffer from a stress-related mood disorder including depression and anxiety during and after pregnancy, making these disorders among the most common complications of pregnancy. These stress-related disorders are associated with adverse pregnancy outcomes including gestational hypertension and preeclampsia, which are associated with poor cardiometabolic health postpartum. Despite these associations, the direct impact of stress and related disorders on maternal vascular health, and contributing mechanisms, remain understudied. The aim of this study was to investigate the effect of pre-pregnancy stress on maternal vascular outcomes in a BALB/c mouse model of chronic unpredictable stress. Maternal blood pressure and ex-vivo vascular function were investigated during pregnancy and postpartum. Offspring characteristics were assessed at the end of pregnancy and postpartum. Main findings show that pre-pregnancy stress exposure increased blood pressure during mid and late pregnancy and impaired ex vivo vascular function at the end of pregnancy. These effects persisted into the postpartum period, suggesting a long-term effect of stress on maternal vascular health, which appear to be partially attributable to disruptions in nitric oxide (NO) pathway signaling. These data suggest exposure to stress and related disorders, even prior to pregnancy, can contribute to vascular complications during pregnancy and postpartum.

Multiplatform untargeted metabolomics.

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Redox Regulation and Metabolic Dependency of Zika Virus Replication: Inhibition by Nrf2-Antioxidant Response and NAD(H) Antimetabolites.

Viral infections alter host cell metabolism and homeostasis; however, the mechanisms that regulate these processes have only begun to be elucidated. We report here that Zika virus (ZIKV) infection activates the antioxidant nuclear factor erythroid 2-related factor 2 (Nrf2), which precedes oxidative stress. Downregulation of Nrf2 or inhibition of glutathione (GSH) synthesis resulted in significantly increased viral replication. Interestingly, 6-amino-nicotinamide (6-AN), a nicotinamide analog commonly used as an inhibitor of the pentose phosphate pathway (PPP), decreased viral replication by over 1,000-fold. This inhibition was neither recapitulated by the knockdown of PPP enzymes, glucose 6-phosphate dehydrogenase (G6PD), or 6-phosphogluconate dehydrogenase (6PGD), nor prevented by supplementation with ribose 5-phosphate. Instead, our metabolomics and metabolic phenotype studies support a mechanism in which 6-AN depletes cells of NAD(H) and impairs NAD(H)-dependent glycolytic steps resulting in inhibition of viral replication. The inhibitory effect of 6-AN was rescued with precursors of the salvage pathway but not with those of other NAD+ biosynthesis pathways. Inhibition of glycolysis reduced viral protein levels, which were recovered transiently. This transient recovery in viral protein synthesis was prevented when oxidative metabolism was inhibited by blockage of the mitochondrial pyruvate carrier, fatty acid oxidation, or glutaminolysis, demonstrating a compensatory role of mitochondrial metabolism in ZIKV replication. These results establish an antagonistic role for the host cell Nrf2/GSH/NADPH-dependent antioxidant response against ZIKV and demonstrate the dependency of ZIKV replication on NAD(H). Importantly, our work suggests the potential use of NAD(H) antimetabolite therapy against the viral infection. IMPORTANCE Zika virus (ZIKV) is a major public health concern of international proportions. While the incidence of ZIKV infections has declined substantially in recent years, the potential for the reemergence or reintroduction remains high. Although viral infection alters host cell metabolism and homeostasis to promote its replication, deciphering the mechanism(s) involved in these processes is important for identifying therapeutic targets. The present work reveals the complexities of host cell redox regulation and metabolic dependency of ZIKV replication. An antagonistic effect of the Nrf2/GSH/NADP(H)-dependent antioxidant response against ZIKV infection and an essential role of NAD(H) metabolism and glycolysis for viral replication are established for the first time. These findings highlight the potential use of NAD(H) antimetabolites to counter ZIKV infection and pathogenesis.