Globally Optimized Targeted Mass Spectrometry: Reliable Metabolomics Analysis with Broad Coverage

Joint exome and metabolome analysis in individuals with dyslexia: Evidence for associated dysregulations of olfactory perception and autoimmune functions

Dyslexia is a learning disability that negatively affects reading, writing, and spelling development at the word level in 5%-9% of children. The phenotype is variable and complex, involving several potential cognitive and physical concomitants such as sensory dysregulation and immunodeficiencies. The biological pathogenesis is not well-understood. Toward a better understanding of the biological drivers of dyslexia, we conducted the first joint exome and metabolome investigation in a pilot sample of 30 participants with dyslexia and 13 controls. In this analysis, eight metabolites of interest emerged (pyridoxine, kynurenic acid, citraconic acid, phosphocreatine, hippuric acid, xylitol, 2-deoxyuridine, and acetylcysteine). A metabolite-metabolite interaction analysis identified Krebs cycle intermediates that may be implicated in the development of dyslexia. Gene ontology analysis based on exome variants resulted in several pathways of interest, including the sensory perception of smell (olfactory) and immune system-related responses. In the joint exome and metabolite analysis, the olfactory transduction pathway emerged as the primary pathway of interest. Although the olfactory transduction and Krebs cycle pathways have not previously been described in dyslexia literature, these pathways have been implicated in other neurodevelopmental disorders including autism spectrum disorder and obsessive-compulsive disorder, suggesting the possibility of these pathways playing a role in dyslexia as well. Immune system response pathways, on the other hand, have been implicated in both dyslexia and other neurodevelopmental disorders.

Baseline gut microbiome and metabolites are correlated with alcohol consumption in a zonisamide clinical trial of heavy drinking alcoholic civilians

Development and severity of alcohol use disorder (AUD) has been linked to variations in gut microbiota and their associated metabolites in both animal and human studies. However, the involvement of the gut microbiome in alcohol consumption of individuals with AUD undergoing treatment remains unclear. To address this, stool samples (n=48) were collected at screening (baseline) and trial completion from a single site of a multi-site double-blind, placebo-controlled trial of Zonisamide in individuals with AUD. Alcohol consumption, gamma-glutamyl transferase (GGT), and phosphatidylethanol (PEth)levels were measured both at baseline and endpoint of 16-week trial period. Fecal microbiome was analyzed via 16S rRNA sequencing and metabolome via untargeted LC-MS. Both sex (p = 0.003) and psychotropic medication usage (p = 0.025) are associated with baseline microbiome composition. The relative abundance of 12 genera at baseline was correlated with percent drinking reduction, baseline and endpoint alcohol consumption, and changes in GGT and PeTH over the course of treatment (p.adj < 0.05). Overall microbiome community structure at baseline differed between high and low responders (67-100% and 0-33% drinking reduction, respectively; p = 0.03). A positive relationship between baseline fecal GABA levels and percent drinking reduction (R=0.43, p < 0.05) was identified by microbiome function prediction and confirmed by ELISA and metabolomics. Predicted microbiome function and metabolomics analysis have found that tryptophan metabolic pathways are over-represented in low responders. These findings highlight importance of baseline microbiome and metabolites in alcohol consumption in AUD patients undergoing zonisamide treatment.

Inverse-Vaccines for Rheumatoid Arthritis Re-establish Metabolic and Immunological Homeostasis in Joint Tissues

Rheumatoid arthritis (RA) causes immunological and metabolic imbalances in tissue, exacerbating inflammation in affected joints. Changes in immunological and metabolic tissue homeostasis at different stages of RA are not well understood. Herein, the changes in the immunological and metabolic profiles in different stages in collagen induced arthritis (CIA), namely, early, intermediate, and late stage is examined. Moreover, the efficacy of the inverse-vaccine, paKG(PFK15+bc2) microparticle, to restore tissue homeostasis at different stages is also investigated. Immunological analyses of inverse-vaccine-treated group revealed a significant decrease in the activation of pro-inflammatory immune cells and remarkable increase in regulatory T-cell populations in the intermediate and late stages compared to no treatment. Also, glycolysis in the spleen is normalized in the late stages of CIA in inverse-vaccine-treated mice, which is similar to no-disease tissues. Metabolomics analyses revealed that metabolites UDP-glucuronic acid and L-Glutathione oxidized are significantly altered between treatment groups, and thus might provide new druggable targets for RA treatment. Flux metabolic modeling identified amino acid and carnitine pathways as the central pathways affected in arthritic tissue with CIA progression. Overall, this study shows that the inverse-vaccines initiate early re-establishment of homeostasis, which persists through the disease span.

Metabolomics-driven investigation of plant defense response against pest and pathogen attack

The advancement of metabolomics has assisted in the identification of various bewildering characteristics of the biological system. Metabolomics is a standard approach, facilitating crucial aspects of system biology with absolute quantification of metabolites using minimum samples, based on liquid/gas chromatography, mass spectrometry and nuclear magnetic resonance. The metabolome profiling has narrowed the wide gaps of missing information and has enhanced the understanding of a wide spectrum of plant-environment interactions by highlighting the complex pathways regulating biochemical reactions and cellular physiology under a particular set of conditions. This high throughput technique also plays a prominent role in combined analyses of plant metabolomics and other omics datasets. Plant metabolomics has opened a wide paradigm of opportunities for developing stress-tolerant plants, ensuring better food quality and quantity. However, despite advantageous methods and databases, the technique has a few limitations, such as ineffective 3D capturing of metabolites, low comprehensiveness, and lack of cell-based sampling. In the future, an expansion of plant-pathogen and plant-pest response towards the metabolite architecture is necessary to understand the intricacies of plant defence against invaders, elucidation of metabolic pathway operational during defence and developing a direct correlation between metabolites and biotic stresses. Our aim is to provide an overview of metabolomics and its utilities for the identification of biomarkers or key metabolites associated with biotic stress, devising improved diagnostic methods to efficiently assess pest and pathogen attack and generating improved crop varieties with the help of combined application of analytical and molecular tools.

Targeted metabolomics reveals plasma biomarkers and metabolic alterations of the aging process in healthy young and older adults

With the exponential growth in the older population in the coming years, many studies have aimed to further investigate potential biomarkers associated with the aging process and its incumbent morbidities. Age is the largest risk factor for chronic disease, likely due to younger individuals possessing more competent adaptive metabolic networks that result in overall health and homeostasis. With aging, physiological alterations occur throughout the metabolic system that contribute to functional decline. In this cross-sectional analysis, a targeted metabolomic approach was applied to investigate the plasma metabolome of young (21-40y; n = 75) and older adults (65y + ; n = 76). A corrected general linear model (GLM) was generated, with covariates of gender, BMI, and chronic condition score (CCS), to compare the metabolome of the two populations. Among the 109 targeted metabolites, those associated with impaired fatty acid metabolism in the older population were found to be most significant: palmitic acid (p < 0.001), 3-hexenedioic acid (p < 0.001), stearic acid (p = 0.005), and decanoylcarnitine (p = 0.036). Derivatives of amino acid metabolism, 1-methlyhistidine (p = 0.035) and methylhistamine (p = 0.027), were found to be increased in the younger population and several novel metabolites were identified, such as cadaverine (p = 0.034) and 4-ethylbenzoic acid (p = 0.029). Principal component analysis was conducted and highlighted a shift in the metabolome for both groups. Receiver operating characteristic analyses of partial least squares-discriminant analysis models showed the candidate markers to be more powerful indicators of age than chronic disease. Pathway and enrichment analyses uncovered several pathways and enzymes predicted to underlie the aging process, and an integrated hypothesis describing functional characteristics of the aging process was synthesized. Compared to older participants, the young group displayed greater abundance of metabolites related to lipid and nucleotide synthesis; older participants displayed decreased fatty acid oxidation and reduced tryptophan metabolism, relative to the young group. As a result, we offer a better understanding of the aging metabolome and potentially reveal new biomarkers and predicted mechanisms for future study.

Database-assisted, globally optimized targeted secondary electrospray ionization high resolution mass spectrometry (dGOT-SESI-HRMS) and spectral stitching enhanced volatilomics analysis of bacterial metabolites

Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an innovative analytical technique for the rapid and non-invasive analysis of volatile organic compounds (VOCs). However, compound annotation and ion suppression in the SESI source has hindered feature detection, stability and reproducibility of SESI-HRMS in untargeted volatilomics. To address this, we have developed and optimized a novel pseudo-targeted approach, database-assisted globally optimized targeted (dGOT)-SESI-HRMS using the microbial-VOC (mVOC) database, and spectral stitching methods to enhance metabolite detection in headspace of anaerobic bacterial cultures. Headspace volatiles from representative bacteria strains were assessed using full scan with data dependent acquisition (DDA), conventional globally optimized targeted (GOT) method, and spectral stitching supported dGOT experiments based on a MS peaks list derived from mVOC. Our results indicate that spectral stitching supported dGOT-SESI-HRMS can proportionally fragment peaks with respect to different analysis windows, with a total of 109 VOCs fragmented from 306 targeted compounds. Of the collected spectra, 88 features were confirmed as culture derived volatiles with respect to media blanks. Annotation was also achieved with a total of 25 unique volatiles referenced to standard databases allowing for biological interpretation. Principal component analysis (PCA) summarizing the headspace volatile demonstrated improved separation of clusters when data was acquired using the dGOT method. Collectively, our dGOT-SESI-HRMS method afforded robust capability of capturing unique VOC profiles from different bacterial strains and culture conditions when compared to conventional GOT and DDA modes, suggesting the newly developed approach can serve as a more reliable analytical method for the sensitive monitoring of gut microbial metabolism.

Recent advances in LC-MS-based metabolomics for clinical biomarker discovery

The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.

NEUROMETABOLOMIC IMPACTS OF MODELED WILDFIRE SMOKE AND PROTECTIVE BENEFITS OF ANTI-AGING THERAPEUTICS IN AGED FEMALE C57BL/6J MICE

Wildland fires have become progressively more extensive over the past 30 years in the US, and now routinely generate smoke that deteriorates air quality for most of the country. We explored the neurometabolomic impact that smoke derived from biomass has on older (18 months) female C57BL/6J mice, both acutely and after 10 weeks of recovery from exposures. Mice (N=6/group) were exposed to wood smoke (WS) 4 hours/day, every other day, for 2 weeks (7 exposures total) to an average concentration of 0.448mg/m 3 per exposure. One group was euthanized 24 hours after the last exposure. Other groups were then placed on 1 of 4 treatment regimens for 10 weeks after wood smoke exposures: vehicle; resveratrol in chow plus nicotinamide mononucleotide in water (RNMN); senolytics via gavage (dasatanib+quercetin; DQ); or both RNMN with DQ (RNDQ). Among the findings, the aging from 18 months to 21 months was associated with the greatest metabolic shift, including changes in nicotinamide metabolism, with WS exposure effects that were relatively modest. WS caused a reduction in NAD+ within the prefrontal cortex immediately after exposure and a long-term reduction in serotonin that persisted for 10 weeks. The serotonin reductions were corroborated by forced swim tests, which revealed an increased immobility (reduction in motivation) immediately post-exposure and persisted for 10 weeks. RNMN had the most beneficial effects after WS exposure, while RNDQ caused markers of brain aging to be upregulated within WS-exposed mice. Findings highlight the persistent neurometabolomic and behavioral effects of woodsmoke exposure in an aged mouse model.

Significance Statement

Neurological impacts of wildfire smoke are largely underexplored but include neuroinflammation and metabolic changes. The present study highlights modulation of major metabolites in the prefrontal cortex and behavioral consequences in aged (18 month) female mice that persists 10 weeks after wood smoke exposure ended. Supplements derived from the anti-aging field were able to mitigate much of the woodsmoke effect, especially a combination of resveratrol and nicotinamide mononucleotide.

Recent Review on Selected Xenobiotics and Their Impacts on Gut Microbiome and Metabolome

As it is well known, the gut is one of the primary sites in any host for xenobiotics, and the many microbial metabolites responsible for the interactions between the gut microbiome and the host. However, there is a growing concern about the negative impacts on human health induced by toxic xenobiotics. Metabolomics, broadly including lipidomics, is an emerging approach to studying thousands of metabolites in parallel. In this review, we summarized recent advancements in mass spectrometry (MS) technologies in metabolomics. In addition, we reviewed recent applications of MS-based metabolomics for the investigation of toxic effects of xenobiotics on microbial and host metabolism. It was demonstrated that metabolomics, gut microbiome profiling, and their combination have a high potential to identify metabolic and microbial markers of xenobiotic exposure and determine its mechanism. Further, there is increasing evidence supporting that reprogramming the gut microbiome could be a promising approach to the intervention of xenobiotic toxicity.

Biomass smoke inhalation promotes neuroinflammatory and metabolomic temporal changes in the hippocampus of female mice

Smoke from wildland fires has been shown to produce neuroinflammation in preclinical models, characterized by neural infiltrations of neutrophils and monocytes, as well as altered neurovascular endothelial phenotypes. To address the longevity of such outcomes, the present study examined the temporal dynamics of neuroinflammation and metabolomics after inhalation exposures from biomass-derived smoke. 2-month-old female C57BL/6 J mice were exposed to wood smoke every other day for 2 weeks at an average exposure concentration of 0.5 mg/m3. Subsequent serial euthanasia occurred at 1-, 3-, 7-, 14-, and 28-day post-exposure. Flow cytometry of right hemispheres revealed two endothelial populations of CD31Hi and CD31Med expressors, with wood smoke inhalation causing an increased proportion of CD31Hi. These populations of CD31Hi and CD31Med were associated with an anti-inflammatory and pro-inflammatory response, respectively, and their inflammatory profiles were largely resolved by the 28-day mark. However, activated microglial populations (CD11b+/CD45low) remained higher in wood smoke-exposed mice than controls at day 28. Infiltrating neutrophil populations decreased to levels below controls by day 28. However, the MHC-II expression of the peripheral immune infiltrate remained high, and the population of neutrophils retained an increased expression of CD45, Ly6C, and MHC-II. Utilizing an unbiased approach examining the metabolomic alterations, we observed notable hippocampal perturbations in neurotransmitter and signaling molecules, such as glutamate, quinolinic acid, and 5-α-dihydroprogesterone. Utilizing a targeted panel designed to explore the aging-associated NAD+ metabolic pathway, wood smoke exposure drove fluctuations and compensations across the 28-day time course, ending with decreased hippocampal NAD+ abundance on day 28. Summarily, these results indicate a highly dynamic neuroinflammatory environment, with potential resolution extending past 28 days, the implications of which may include long-term behavioral changes, systemic and neurological sequalae directly associated with wildfire smoke exposure.

Dysregulated lipid metabolism in TMZ-resistant glioblastoma: pathways, proteins, metabolites and therapeutic opportunities

Glioblastoma (GBM) is a highly aggressive and lethal brain tumor with limited treatment options, such as the chemotherapeutic agent, temozolomide (TMZ). However, many GBM tumors develop resistance to TMZ, which is a major obstacle to effective therapy. Recently, dysregulated lipid metabolism has emerged as an important factor contributing to TMZ resistance in GBM. The dysregulation of lipid metabolism is a hallmark of cancer and alterations in lipid metabolism have been linked to multiple aspects of tumor biology, including proliferation, migration, and resistance to therapy. In this review, we aimed to summarize current knowledge on lipid metabolism in TMZ-resistant GBM, including key metabolites and proteins involved in lipid synthesis, uptake, and utilization, and recent advances in the application of metabolomics to study lipid metabolism in GBM. We also discussed the potential of lipid metabolism as a target for novel therapeutic interventions. Finally, we highlighted the challenges and opportunities associated with developing these interventions for clinical use, and the need for further research to fully understand the role of lipid metabolism in TMZ resistance in GBM. Our review suggests that targeting dysregulated lipid metabolism may be a promising approach to overcome TMZ resistance and improve outcomes in patients with GBM.

Maternal PBDE exposure disrupts gut microbiome and promotes hepatic proinflammatory signaling in humanized PXR-transgenic mouse offspring over time

Developmental exposure to the persistent environmental pollutant, polybrominated diphenyl ethers (PBDEs), is associated with increased diabetes prevalence. The microbial tryptophan metabolite, indole-3-propionic acid (IPA), is associated with reduced risk of type 2 diabetes and lower-grade inflammation and is a pregnane X receptor (PXR) activator. To explore the role of IPA in modifying the PBDE developmental toxicity, we orally exposed humanized PXR-transgenic (hPXR-TG) mouse dams to vehicle, 0.1 mg/kg/day DE-71 (an industrial PBDE mixture), DE-71+IPA (20 mg/kg/day), or IPA, from 4 weeks preconception to the end of lactation. Pups were weaned at 21 days of age and IPA supplementation continued in the corresponding treatment groups. Tissues were collected at various ages until 6 months of age (n = 5 per group). In general, the effect of maternal DE-71 exposure on the gut microbiome of pups was amplified over time. The regulation of hepatic cytokines and prototypical xenobiotic-sensing transcription factor target genes by DE-71 and IPA was age- and sex-dependent, where DE-71-mediated mRNA increased selected cytokines (Il10, Il12p40, Il1β [both sexes], and [males]). The hepatic mRNA of the aryl hydrocarbon receptor (AhR) target gene Cyp1a2 was increased by maternal DE-71 and DE-71+IPA exposure at postnatal day 21 but intestinal Cyp1a1 was not altered by any of the exposures and ages. Maternal DE-71 exposure persistently increased serum indole, a known AhR ligand, in age- and sex-dependent manner. In conclusion, maternal DE-71 exposure produced a proinflammatory signature along the gut-liver axis, including gut dysbiosis, dysregulated tryptophan microbial metabolism, attenuated PXR signaling, and elevated AhR signaling in postweaned hPXR-TG pups over time, which was partially corrected by IPA supplementation.

Increased cardiac PFK-2 protects against high-fat diet-induced cardiomyopathy and mediates beneficial systemic metabolic effects

A healthy heart adapts to changes in nutrient availability and energy demands. In metabolic diseases like type 2 diabetes (T2D), increased reliance on fatty acids for energy production contributes to mitochondrial dysfunction and cardiomyopathy. A principal regulator of cardiac metabolism is 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFK-2), which is a central driver of glycolysis. We hypothesized that increasing PFK-2 activity could mitigate cardiac dysfunction induced by high-fat diet (HFD). Wild type (WT) and cardiac-specific transgenic mice expressing PFK-2 (GlycoHi) were fed a low fat or HFD for 16 weeks to induce metabolic dysfunction. Metabolic phenotypes were determined by measuring mitochondrial bioenergetics and performing targeted quantitative proteomic and metabolomic analysis. Increasing cardiac PFK-2 had beneficial effects on cardiac and mitochondrial function. Unexpectedly, GlycoHi mice also exhibited sex-dependent systemic protection from HFD, including increased glucose homeostasis. These findings support improving glycolysis via PFK-2 activity can mitigate mitochondrial and functional changes that occur with metabolic syndrome.

Neuroinflammatory and Metabolomic Temporal Dynamics Following Wood Smoke Inhalation

Smoke from wildland fires has been shown to produce neuroinflammation in preclinical models, characterized by neural infiltrations of neutrophils and monocytes, as well as altered neurovascular endothelial phenotypes. To address the longevity of such outcomes, the present study examined the neuroinflammatory and metabolomic temporal dynamics after inhalation exposures from biomass-derived smoke. 2-month-old female C57BL/6J mice were exposed to wood smoke every other day for two weeks at an average exposure concentration of 0.5mg/m 3 . Subsequent serial euthanasia occurred at 1-, 3-, 7-, 14-, and 28-days post-exposure. Flow cytometry of right hemispheres revealed two endothelial populations of PECAM (CD31), high and medium expressors, with wood smoke inhalation causing an increased proportion of PECAM Hi . These populations of PECAM Hi and PECAM Med were associated with an anti-inflammatory and pro-inflammatory response, respectively, and their inflammatory profiles were largely resolved by the 28-day mark. However, activated microglial populations (CD11b + /CD45 low ) remained higher in wood smoke-exposed mice than controls at day 28. Infiltrating neutrophil populations decreased to levels below controls by day 28. However, the MHC-II expression of the peripheral immune infiltrate remained high, and the population of neutrophils retained an increased expression of CD45, Ly6C, and MHC-II. Utilizing an unbiased approach examining the metabolomic alterations, we observed notable hippocampal perturbations in neurotransmitter and signaling molecules like glutamate, quinolinic acid, and 5-α-dihydroprogesterone. Utilizing a targeted panel designed to explore the aging-associated NAD + metabolic pathway, wood smoke exposure drove fluctuations and compensations across the 28-day time course, ending with decreased hippocampal NAD + abundance at day 28. Summarily, these results indicate a highly dynamic neuroinflammatory environment, with potential resolution extending past 28 days, the implications of which may include long-term behavioral changes, systemic and neurological sequalae directly associated wtith wildfire smoke exposure.

Multi-omic assessment shows dysregulation of pulmonary and systemic immunity to e-cigarette exposure

Electronic cigarette (Ecig) use has become more common, gaining increasing acceptance as a safer alternative to tobacco smoking. However, the 2019 outbreak of Ecig and Vaping-Associated Lung Injury (EVALI) alerted the community to the potential for incorporation of deleterious ingredients such as vitamin E acetate into products without adequate safety testing. Understanding Ecig induced molecular changes in the lung and systemically can provide a path to safety assessment and protect consumers from unsafe formulations. While vitamin E acetate has been largely removed from commercial and illicit products, many Ecig products contain additives that remain largely uncharacterized. In this study, we determined the lung-specific effects as well as systemic immune effects in response to exposure to a common Ecig base, propylene glycol and vegetable glycerin (PGVG), with and without a 1% addition of phytol, a diterpene alcohol that has been found in commercial products. We exposed animals to PGVG with and without phytol and assessed metabolite, lipid, and transcriptional markers in the lung. We found both lung-specific as well as systemic effects in immune parameters, metabolites, and lipids. Phytol drove modest changes in lung function and increased splenic CD4 T cell populations. We also conducted multi-omic data integration to better understand early complex pulmonary responses, highlighting a central enhancement of acetylcholine responses and downregulation of palmitic acid connected with conventional flow cytometric assessments of lung, systemic inflammation, and pulmonary function. Our results demonstrate that Ecig exposure not only leads to changes in pulmonary function but also affects systemic immune and metabolic parameters.

Identification of Metabolite Interference Is Necessary for Accurate LC-MS Targeted Metabolomics Analysis

Targeted metabolomics has been broadly used for metabolite measurement due to its good quantitative linearity and simple metabolite annotation workflow. However, metabolite interference, the phenomenon where one metabolite generates a peak in another metabolite's MRM setting (Q1/Q3) with a close retention time (RT), may lead to inaccurate metabolite annotation and quantification. Besides isomeric metabolites having the same precursor and product ions that may interfere with each other, we found other metabolite interferences as the result of inadequate mass resolution of triple-quadruple mass spectrometry and in-source fragmentation of metabolite ions. Characterizing the targeted metabolomics data using 334 metabolite standards revealed that about 75% of the metabolites generated measurable signals in at least one other metabolite's MRM setting. Different chromatography techniques can resolve 65-85% of these interfering signals among standards. Metabolite interference analysis combined with the manual inspection of cell lysate and serum data suggested that about 10% out of ∼180 annotated metabolites were mis-annotated or mis-quantified. These results highlight that a thorough investigation of metabolite interference is necessary for accurate metabolite measurement in targeted metabolomics.

Metabolomic Profiling in Mouse Model of Menopause-Associated Asthma

Menopause-associated asthma impacts a subset of women, tends to be more severe, and is less responsive to current treatments. We recently developed a model of menopause-associated asthma using 4-Vinylcyclohexene Diepoxide (VCD) and house dust mites (HDM). The goal of this study was to uncover potential biomarkers and drivers of menopause-onset asthma by assessing serum and bronchoalveolar lavage fluid (BALF) samples from mice with and without menopause and HDM challenge by large-scale targeted metabolomics. Female mice were treated with VCD/HDM to model menopause-associated asthma, and serum and BALF samples were processed for large-scale targeted metabolomic assessment. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine metabolites of potential biological significance. We identified over 50 individual metabolites, impacting 46 metabolic pathways, in the serum and BALF that were significantly different across the four study groups. In particular, glutamate, GABA, phosphocreatine, and pyroglutamic acid, which are involved in glutamate/glutamine, glutathione, and arginine and proline metabolisms, were significantly impacted in the menopausal HDM-challenged mice. Additionally, several metabolites had significant correlations with total airway resistance including glutamic acid, histamine, uridine, cytosine, cytidine, and acetamide. Using metabolic profiling, we identified metabolites and metabolic pathways that may aid in discriminating potential biomarkers for and drivers of menopause-associated asthma.

Aging influence on pulmonary and systemic inflammation and neural metabolomics arising from pulmonary multi-walled carbon nanotube exposure in apolipoprotein E-deficient and C57BL/6 female mice

OBJECTIVE

Environmental exposures exacerbate age-related pathologies, such as cardiovascular and neurodegenerative diseases. Nanoparticulates, and specifically carbon nanomaterials, are a fast-growing contributor to the category of inhalable pollutants, whose risks to health are only now being unraveled. The current study assessed the exacerbating effect of age on multiwalled-carbon nanotube (MWCNT) exposure in young and old C57BL/6 and ApoE-/- mice.

MATERIALS AND METHODS

Female C57BL/6 and apolipoprotein E-deficient (ApoE-/-) mice, aged 8 weeks and 15 months, were exposed to 0 or 40 µg MWCNT via oropharyngeal aspiration. Pulmonary inflammation, inflammatory bioactivity of serum, and neurometabolic changes were assessed at 24 h post-exposure.

RESULTS

Pulmonary neutrophil infiltration was induced by MWCNT in bronchoalveolar lavage fluid in both C57BL/6 and ApoE-/-. Macrophage counts decreased with MWCNT exposure in ApoE-/- mice but were unaffected by exposure in C57BL/6 mice. Older mice appeared to have greater MWCNT-induced total protein in lavage fluid. BALF cytokines and chemokines were elevated with MWCNT exposure, but CCL2, CXCL1, and CXCL10 showed reduced responses to MWCNT in older mice. However, no significant serum inflammatory bioactivity was detected. Cerebellar metabolic changes in response to MWCNT were modest, but age and strain significantly influenced metabolite profiles assessed. ApoE-/- mice and older mice exhibited less robust metabolite changes in response to exposure, suggesting a reduced health reserve.

CONCLUSIONS

Age influences the pulmonary and neurological responses to short-term MWCNT exposure. However, with only the model of moderate aging (15 months) in this study, the responses appeared modest compared to inhaled toxicant impacts in more advanced aging models.

Hyperkalemic or Low Potassium Cardioplegia Protects against Reduction of Energy Metabolism by Oxidative Stress

Open-heart surgery is often an unavoidable option for the treatment of cardiovascular disease and prevention of cardiomyopathy. Cardiopulmonary bypass surgery requires manipulating cardiac contractile function via the perfusion of a cardioplegic solution. Procedure-associated ischemia and reperfusion (I/R) injury, a major source of oxidative stress, affects postoperative cardiac performance and long-term outcomes. Using large-scale liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics, we addressed whether cardioplegic solutions affect the baseline cellular metabolism and prevent metabolic reprogramming by oxidative stress. AC16 cardiomyocytes in culture were treated with commonly used cardioplegic solutions, High K+ (HK), Low K+ (LK), Del Nido (DN), histidine-tryptophan-ketoglutarate (HTK), or Celsior (CS). The overall metabolic profile shown by the principal component analysis (PCA) and heatmap revealed that HK or LK had a minimal impact on the baseline 78 metabolites, whereas HTK or CS significantly repressed the levels of multiple amino acids and sugars. H2O2-induced sublethal mild oxidative stress causes decreases in NAD, nicotinamide, or acetylcarnitine, but increases in glucose derivatives, including glucose 6-P, glucose 1-P, fructose, mannose, and mannose 6-P. Additional increases include metabolites of the pentose phosphate pathway, D-ribose-5-P, L-arabitol, adonitol, and xylitol. Pretreatment with HK or LK cardioplegic solution prevented most metabolic changes and increases of reactive oxygen species (ROS) elicited by H2O2. Our data indicate that HK and LK cardioplegic solutions preserve baseline metabolism and protect against metabolic reprogramming by oxidative stress.

Creation of a Plant Metabolite Spectral Library for Untargeted and Targeted Metabolomics

Large-scale high throughput metabolomic technologies are indispensable components of systems biology in terms of discovering and defining the metabolite parts of the system. However, the lack of a plant metabolite spectral library limits the metabolite identification of plant metabolomic studies. Here, we have created a plant metabolite spectral library using 544 authentic standards, which increased the efficiency of identification for untargeted metabolomic studies. The process of creating the spectral library was described, and the mzVault library was deposited in the public repository for free download. Furthermore, based on the spectral library, we describe a process of creating a pseudo-targeted method, which was applied to a proof-of-concept study of Arabidopsis leaf extracts. As authentic standards become available, more metabolite spectra can be easily incorporated into the spectral library to improve the mzVault package.

An integrative cellular metabolomic study reveals downregulated tricarboxylic acid cycle and potential biomarkers induced by tetrabromobisphenol A in human lung A549 cells

Tetrabromobisphenol A (TBBPA) is extensively utilized as a brominated flame retardant in numerous chemical products. As an environmental contaminant, the potential human toxicity of TBBPA has been attracting increasing attention. Nonetheless, the exact underlying mechanisms of toxicological effects caused by TBBPA remain uncertain. In this study, we investigated the potential mechanisms of TBBPA toxicity in vitro in the A549 cell line, one of the widely used type II pulmonary epithelial cell models in toxicology research. Cell viability was determined after treatment with varying concentrations of TBBPA. Liquid chromatography-mass spectrometry (LC-MS) metabolomics and metabolic flux approaches were utilized to evaluate metabolite and tricarboxylic acid (TCA) cycle oxidative flux changes. Our findings demonstrated that TBBPA significantly reduced the viability of cells and attenuated mitochondrial respiration in A549 cells. Additionally, LC-MS data showed significant reductions in TCA cycle metabolites including citrate, malate, fumarate, and alpha-ketoglutarate in 50 μM TBBPA-treated A549 cells. Metabolic flux analysis indicated reduced oxidative capacity in mitochondrial metabolism following TBBPA exposure. Moreover, diverse metabolic pathways, particularly alanine, aspartate, and glutamate metabolism and the TCA cycle, were found to be dysregulated. In total, 12 metabolites were significantly changed (p < .05) in response to 50 μM TBBPA exposure. Our results provide potential biomarkers of TBBPA toxicity in A549 cells and help elucidate the molecular mechanisms of pulmonary toxicity induced by TBBPA exposure.

Metabolomic Signatures of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is associated with many variations in metabolism, but the ex-act correlates of these metabolic disturbances with behavior and development and their links to other core metabolic disruptions are understudied. In this study, large-scale targeted LC-MS/MS metabolomic analysis was conducted on fasting morning plasma samples from 57 children with ASD (29 with neurodevelopmental regression, NDR) and 37 healthy controls of similar age and gender. Linear model determined the metabolic signatures of ASD with and without NDR, measures of behavior and neurodevelopment, as well as markers of oxidative stress, inflammation, redox, methylation, and mitochondrial metabolism. MetaboAnalyst ver 5.0 (the Wishart Research Group at the University of Alberta, Edmonton, Canada) identified the pathways associated with altered metabolic signatures. Differences in histidine and glutathione metabolism as well as aromatic amino acid (AAA) biosynthesis differentiated ASD from controls. NDR was associated with disruption in nicotinamide and energy metabolism. Sleep and neurodevelopment were associated with energy metabolism while neurodevelopment was also associated with purine metabolism and aminoacyl-tRNA biosynthesis. While behavior was as-sociated with some of the same pathways as neurodevelopment, it was also associated with alternations in neurotransmitter metabolism. Alterations in methylation was associated with aminoacyl-tRNA biosynthesis and branched chain amino acid (BCAA) and nicotinamide metabolism. Alterations in glutathione metabolism was associated with changes in glycine, serine and threonine, BCAA and AAA metabolism. Markers of oxidative stress and inflammation were as-sociated with energy metabolism and aminoacyl-tRNA biosynthesis. Alterations in mitochondrial metabolism was associated with alterations in energy metabolism and L-glutamine. Using behavioral and biochemical markers, this study finds convergent disturbances in specific metabolic pathways with ASD, particularly changes in energy, nicotinamide, neurotransmitters, and BCAA, as well as aminoacyl-tRNA biosynthesis.

Central Nervous System Metabolism in Autism, Epilepsy and Developmental Delays: A Cerebrospinal Fluid Analysis

Neurodevelopmental disorders are associated with metabolic pathway imbalances; however, most metabolic measurements are made peripherally, leaving central metabolic disturbances under-investigated. Cerebrospinal fluid obtained intraoperatively from children with autism spectrum disorder (ASD, n = 34), developmental delays (DD, n = 20), and those without known DD/ASD (n = 34) was analyzed using large-scale targeted mass spectrometry. Eighteen also had epilepsy (EPI). Metabolites significantly related to ASD, DD and EPI were identified by linear models and entered into metabolite–metabolite network pathway analysis. Common disrupted pathways were analyzed for each group of interest. Central metabolites most involved in metabolic pathways were L-cysteine, adenine, and dodecanoic acid for ASD; nicotinamide adenine dinucleotide phosphate, L-aspartic acid, and glycine for EPI; and adenosine triphosphate, L-glutamine, ornithine, L-arginine, L-lysine, citrulline, and L-homoserine for DD. Amino acid and energy metabolism pathways were most disrupted in all disorders, but the source of the disruption was different for each disorder. Disruption in vitamin and one-carbon metabolism was associated with DD and EPI, lipid pathway disruption was associated with EPI and redox metabolism disruption was related to ASD. Two microbiome metabolites were also detected in the CSF: shikimic and cis-cis-muconic acid. Overall, this study provides increased insight into unique metabolic disruptions in distinct but overlapping neurodevelopmental disorders.

Metabolic Footprinting of Microbial Systems Based on Comprehensive In Silico Predictions of MS/MS Relevant Data

Metabolic footprinting represents a holistic approach to gathering large-scale metabolomic information of a given biological system and is, therefore, a driving force for systems biology and bioprocess development. The ongoing development of automated cultivation platforms increases the need for a comprehensive and rapid profiling tool to cope with the cultivation throughput. In this study, we implemented a workflow to provide and select relevant metabolite information from a genome-scale model to automatically build an organism-specific comprehensive metabolome analysis method. Based on in-house literature and predicted metabolite information, the deduced metabolite set was distributed in stackable methods for a chromatography-free dilute and shoot flow-injection analysis multiple-reaction monitoring profiling approach. The workflow was used to create a method specific for Saccharomyces cerevisiae, covering 252 metabolites with 7 min/sample. The method was validated with a commercially available yeast metabolome standard, identifying up to 74.2% of the listed metabolites. As a first case study, three commercially available yeast extracts were screened with 118 metabolites passing quality control thresholds for statistical analysis, allowing to identify discriminating metabolites. The presented methodology provides metabolite screening in a time-optimised way by scaling analysis time to metabolite coverage and is open to other microbial systems simply starting from genome-scale model information.

Neuroinflammatory and Neurometabolomic Consequences From Inhaled Wildfire Smoke-Derived Particulate Matter in the Western United States

Utilizing a mobile laboratory located >300 km away from wildfire smoke (WFS) sources, this study examined the systemic immune response profile, with a focus on neuroinflammatory and neurometabolomic consequences, resulting from inhalation exposure to naturally occurring wildfires in California, Arizona, and Washington in 2020. After a 20-day (4 h/day) exposure period in a mobile laboratory stationed in New Mexico, WFS-derived particulate matter (WFPM) inhalation resulted in significant neuroinflammation while immune activity in the peripheral (lung, bone marrow) appeared to be resolved in C57BL/6 mice. Importantly, WFPM exposure increased cerebrovascular endothelial cell activation and expression of adhesion molecules (VCAM-1 and ICAM-1) in addition to increased glial activation and peripheral immune cell infiltration into the brain. Flow cytometry analysis revealed proinflammatory phenotypes of microglia and peripheral immune subsets in the brain of WFPM-exposed mice. Interestingly, endothelial cell neuroimmune activity was differentially associated with levels of PECAM-1 expression, suggesting that subsets of cerebrovascular endothelial cells were transitioning to resolution of inflammation following the 20-day exposure. Neurometabolites related to protection against aging, such as NAD+ and taurine, were decreased by WFPM exposure. Additionally, increased pathological amyloid-beta protein accumulation, a hallmark of neurodegeneration, was observed. Neuroinflammation, together with decreased levels of key neurometabolites, reflect a cluster of outcomes with important implications in priming inflammaging and aging-related neurodegenerative phenotypes.

Metabolomics of oxidative stress: Nrf2 independent depletion of NAD or increases of sugar alcohols

Nrf2 encodes a transcription factor best known for regulating the expression of antioxidant and detoxification genes. Recent evidence suggested that Nrf2 mediates metabolic reprogramming in cancer cells. However, the role of Nrf2 in the biochemical metabolism of cardiac cells has not been studied. Using LC-MS/MS-based metabolomics, we addressed whether knocking out the Nrf2 gene in AC16 human cardiomyocytes affects metabolic reprogramming by oxidative stress. Profiling the basal level metabolites showed an elevated pentose phosphate pathway and increased levels of sugar alcohols, sorbitol, L-arabitol, xylitol and xylonic acid, in Nrf2 KO cells. With sublethal levels of oxidative stress, depletion of NAD, an increase of GDP and elevation of sugar alcohols, sorbitol and dulcitol, were detected in parent wild type (WT) cells. Knocking out Nrf2 did not affect these changes. Biochemical assays confirmed depletion of NAD in WT and Nrf2 KO cells due to H₂O₂ treatment. These data support that although Nrf2 deficiency caused baseline activation of the pentose phosphate pathway and sugar alcohol synthesis, a brief exposure to none-lethal doses of H₂O₂ caused NAD depletion in an Nrf2 independent manner. Loss of NAD may contribute to oxidative stress associated cell degeneration as observed with aging, diabetes and heart failure.

LC-MS Based Metabolomics Study of the Effects of EGCG on A549 Cells

(−)-Epigallocatechin-3-gallate (EGCG) is the main bioactive catechin in green tea. The antitumor activity of EGCG has been confirmed in various types of cancer, including lung cancer. However, the precise underlying mechanisms are still largely unclear. In the present study, we investigated the metabolite changes in A549 cells induced by EGCG in vitro utilizing liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. The result revealed 33 differentially expressed metabolites between untreated and 80 μM EGCG-treated A549 cells. The altered metabolites were involved in the metabolism of glucose, amino acid, nucleotide, glutathione, and vitamin. Two markedly altered pathways, including glycine, serine and threonine metabolism and alanine, aspartate and glutamate metabolism, were identified by MetaboAnalyst 5.0 metabolic pathway analysis. These results may provide potential clues for the intramolecular mechanisms of EGCG’s effect on A549 cells. Our study may contribute to future molecular mechanistic studies of EGCG and the therapeutic application of EGCG in cancer management.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

A guide to interrogating immunometabolism

The metabolic charts memorized in early biochemistry courses, and then later forgotten, have come back to haunt many immunologists with new recognition of the importance of these pathways. Metabolites and the activity of metabolic pathways drive energy production, macromolecule synthesis, intracellular signalling, post-translational modifications and cell survival. Immunologists who identify a metabolic phenotype in their system are often left wondering where to begin and what does it mean? Here, we provide a framework for navigating and selecting the appropriate biochemical techniques to explore immunometabolism. We offer recommendations for initial approaches to develop and test metabolic hypotheses and how to avoid common mistakes. We then discuss how to take things to the next level with metabolomic approaches, such as isotope tracing and genetic approaches. By proposing strategies and evaluating the strengths and weaknesses of different methodologies, we aim to provide insight, note important considerations and discuss ways to avoid common misconceptions. Furthermore, we highlight recent studies demonstrating the power of these metabolic approaches to uncover the role of metabolism in immunology. By following the framework in this Review, neophytes and seasoned investigators alike can venture into the emerging realm of cellular metabolism and immunity with confidence and rigour.

Metabolic Profiling of Neocortical Tissue Discriminates Alzheimer's Disease from Mild Cognitive Impairment, High Pathology Controls, and Normal Controls

Alzheimer's disease (AD) is the most common cause of dementia, accounting for an estimated 60-80% of cases, and is the sixth-leading cause of death in the United States. While considerable advancements have been made in the clinical care of AD, it remains a complicated disorder that can be difficult to identify definitively in its earliest stages. Recently, mass spectrometry (MS)-based metabolomics has shown significant potential for elucidation of disease mechanisms and identification of therapeutic targets as well diagnostic and prognostic markers that may be useful in resolving some of the difficulties affecting clinical AD studies, such as effective stratification. In this study, complementary gas chromatography- and liquid chromatography-MS platforms were used to detect and monitor 2080 metabolites and features in 48 postmortem tissue samples harvested from the superior frontal gyrus of male and female subjects. Samples were taken from four groups: 12 normal control (NC) patients, 12 cognitively normal subjects characterized as high pathology controls (HPC), 12 subjects with nonspecific mild cognitive impairment (MCI), and 12 subjects with AD. Multivariate statistics informed the construction and cross-validation (p < 0.01) of partial least squares-discriminant analysis (PLS-DA) models defined by a nine-metabolite panel of disease markers (lauric acid, stearic acid, myristic acid, palmitic acid, palmitoleic acid, and four unidentified mass spectral features). Receiver operating characteristic analysis showed high predictive accuracy of the resulting PLS-DA models for discrimination of NC (97%), HPC (92%), MCI (∼96%), and AD (∼96%) groups. Pathway analysis revealed significant disturbances in lysine degradation, fatty acid metabolism, and the degradation of branched-chain amino acids. Network analysis showed significant enrichment of 11 enzymes, predominantly within the mitochondria. The results expand basic knowledge of the metabolome related to AD and reveal pathways that can be targeted therapeutically. This study also provides a promising basis for the development of larger multisite projects to validate these candidate markers in readily available biospecimens such as blood to enable the effective screening, rapid diagnosis, accurate surveillance, and therapeutic monitoring of AD. All raw mass spectrometry data have been deposited to MassIVE (data set identifier MSV000087165).

A Metabolomic Analysis of the Sex-Dependent Hispanic Paradox

In Mexican Americans, metabolic conditions, such as obesity and type 2 diabetes (T2DM), are not necessarily associated with an increase in mortality; this is the so-called Hispanic paradox. In this cross-sectional analysis, we used a metabolomic analysis to look at the mechanisms behind the Hispanic paradox. To do this, we examined dietary intake and body mass index (BMI; kg/m²) in men and women and their effects on serum metabolomic fingerprints in 70 Mexican Americans (26 men, 44 women). Although having different BMI values, the participants had many similar anthropometric and biochemical parameters, such as systolic and diastolic blood pressure, total cholesterol, and LDL cholesterol, which supported the paradox in these subjects. Plasma metabolomic phenotypes were measured using liquid chromatography tandem mass spectrometry (LC-MS/MS). A two-way ANOVA assessing sex, BMI, and the metabolome revealed 23 significant metabolites, such as 2-pyrrolidinone (p = 0.007), TMAO (p = 0.014), 2-aminoadipic acid (p = 0.019), and kynurenine (p = 0.032). Pathway and enrichment analyses discovered several significant metabolic pathways between men and women, including lysine degradation, tyrosine metabolism, and branch-chained amino acid (BCAA) degradation and biosynthesis. A log-transformed OPLS-DA model was employed and demonstrated a difference due to BMI in the metabolomes of both sexes. When stratified for caloric intake (<2200 kcal/d vs. >2200 kcal/d), a separate OPLS-DA model showed clear separation in men, while females remained relatively unchanged. After accounting for caloric intake and BMI status, the female metabolome showed substantial resistance to alteration. Therefore, we provide a better understanding of the Mexican-American metabolome, which may help demonstrate how this population—particularly women—possesses a longer life expectancy despite several comorbidities, and reveal the underlying mechanisms of the Hispanic paradox.

A Metabolomic Aging Clock Using Human Cerebrospinal Fluid

Quantifying the physiology of aging is essential for improving our understanding of age-related disease and the heterogeneity of healthy aging. Recent studies have shown that, in regression models using "-omic" platforms to predict chronological age, residual variation in predicted age is correlated with health outcomes, and suggest that these "omic clocks" provide measures of biological age. This paper presents predictive models for age using metabolomic profiles of cerebrospinal fluid (CSF) from healthy human subjects and finds that metabolite and lipid data are generally able to predict chronological age within 10 years. We use these models to predict the age of a cohort of subjects with Alzheimer's and Parkinson's disease and find an increase in prediction error, potentially indicating that the relationship between the metabolome and chronological age differs with these diseases. However, evidence is not found to support the hypothesis that our models will consistently overpredict the age of these subjects. In our analysis of control subjects, we find the carnitine shuttle, sucrose, biopterin, vitamin E metabolism, tryptophan, and tyrosine to be the most associated with age. We showcase the potential usefulness of age prediction models in a small data set (n = 85) and discuss techniques for drift correction, missing data imputation, and regularized regression, which can be used to help mitigate the statistical challenges that commonly arise in this setting. To our knowledge, this work presents the first multivariate predictive metabolomic and lipidomic models for age using mass spectrometry analysis of CSF.

NAD+ Redox Imbalance in the Heart Exacerbates Diabetic Cardiomyopathy

BACKGROUND

Diabetes is a risk factor for heart failure and promotes cardiac dysfunction. Diabetic tissues are associated with nicotinamide adenine dinucleotide (NAD⁺) redox imbalance; however, the hypothesis that NAD⁺ redox imbalance causes diabetic cardiomyopathy has not been tested. This investigation used mouse models with altered NAD⁺ redox balance to test this hypothesis.

METHODS

Diabetic stress was induced in mice by streptozotocin. Cardiac function was measured by echocardiography. Heart and plasma samples were collected for biochemical, histological, and molecular analyses. Two mouse models with altered NAD⁺ redox states (1, Ndufs4 [NADH:ubiquinone oxidoreductase subunit S4] knockout, cKO, and 2, NAMPT [nicotinamide phosphoribosyltranferase] transgenic mice, NMAPT) were used.

RESULTS

Diabetic stress caused cardiac dysfunction and lowered NAD⁺/NADH ratio (oxidized/reduced ratio of nicotinamide adenine dinucleotide) in wild-type mice. Mice with lowered cardiac NAD⁺/NADH ratio without baseline dysfunction, cKO mice, were challenged with chronic diabetic stress. NAD⁺ redox imbalance in cKO hearts exacerbated systolic (fractional shortening: 27.6% versus 36.9% at 4 weeks, male cohort P<0.05), and diastolic dysfunction (early-to-late ratio of peak diastolic velocity: 0.99 versus 1.20, P<0.05) of diabetic mice in both sexes. Collagen levels and transcripts of fibrosis and extracellular matrix-dependent pathways did not show changes in diabetic cKO hearts, suggesting that the exacerbated cardiac dysfunction was due to cardiomyocyte dysfunction. NAD⁺ redox imbalance promoted superoxide dismutase 2 acetylation, protein oxidation, troponin I S150 phosphorylation, and impaired energetics in diabetic cKO hearts. Importantly, elevation of cardiac NAD⁺ levels by NAMPT normalized NAD⁺ redox balance, alleviated cardiac dysfunction (fractional shortening: 40.2% versus 24.8% in cKO:NAMPT versus cKO, P<0.05; early-to-late ratio of peak diastolic velocity: 1.32 versus 1.04, P<0.05), and reversed pathogenic mechanisms in diabetic mice.

CONCLUSIONS

Our results show that NAD⁺ redox imbalance to regulate acetylation and phosphorylation is a critical mediator of the progression of diabetic cardiomyopathy and suggest the therapeutic potential for diabetic cardiomyopathy by harnessing NAD⁺ metabolism.

Toxoplasma gondii induces metabolic disturbances in the hippocampus of BALB/c mice

Toxoplasma gondii can cross the blood-brain barrier and infect different regions of the brain including the hippocampus. In the present study, we examined the impact of Toxoplasma gondii infection on the metabolism of the hippocampus of female BALB/c mice compared to control mice using ultra-high-performance liquid chromatography-tandem mass spectrometry. Multivariate analysis revealed significant differences between infected and control hippocampi and identified 25, 82, and 105 differential metabolites (DMs) in the infected hippocampi at 7, 14, and 21 days post-infection (dpi), respectively. One DM (sphingosyl-phosphocholine in the sphingolipid metabolism pathway) and 11 dysregulated pathways were detected at all time points post-infection, suggesting their important roles in the neuropathogenesis of T. gondii infection. These pathways were related to neural activity, such as inflammatory mediator regulation of TRP channels, retrograde endocannabinoid signaling, and arachidonic acid metabolism. Weighted correlation network analysis and receiver operating characteristic analysis identified 33 metabolites significantly associated with T. gondii infection in the hippocampus, and 30 of these were deemed as potential biomarkers for T. gondii infection. This study provides, for the first time, a global view of the metabolic perturbations that occur in the mouse hippocampus during T. gondii infection. The potential relevance of the identified metabolites and pathways to the pathogenesis of cognitive impairment and psychiatric disorders are discussed.

Enhanced Detection of Short-Chain Fatty Acids Using Gas Chromatography Mass Spectrometry

Short-chain fatty acids (SCFAs) are produced mainly by intestinal microbiota and play an important role in many host biological processes such as immune system development, glucose and energy homeostasis, and regulation of immune response and inflammation. In addition, they participate in the regulation of anorectic hormones, which have a role in appetite control, tumor suppression, and regulating the central and peripheral nervous systems. As such, there is great interest in monitoring levels of SCFAs in various biological samples. Due to the highly hydrophilic and volatile characteristics of SCFAs, optimizing extraction and sample preparation procedures is often a central component to further improve SCFA quantification. Here, we describe a rapid and highly sensitive analytical method for measuring SCFAs in human serum and feces. Briefly, SCFAs are protected by adding sodium hydroxide, followed by a one-step extraction (pH > 7). Then, SCFAs are quantified by gas chromatography coupled to mass spectrometry (GC-MS) after derivatization with N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide (MTBSTFA). This method demonstrates excellent sensitivity, linearity, and derivatization efficiency for simultaneous determination of 14 different SCFAs. Further, this validated method can be successfully applied to quantify SCFAs in micro-scale biological samples. In summary, we describe efficient and advanced sample preparation and detection procedures that are critically needed for monitoring SCFA concentrations in human biological samples. © 2021 Wiley Periodicals LLC. Basic Protocol: SCFA extraction and detection from fecal and serum samples with gas chromatography-mass spectrometry.

Early Breast Cancer Detection Using Untargeted and Targeted Metabolomics

Breast cancer (BC) is a common cause of morbidity and mortality, particularly in women. Moreover, the discovery of diagnostic biomarkers for early BC remains a challenging task. Previously, we [Jasbi et al. J. Chromatogr. B. 2019, 1105, 26-37] demonstrated a targeted metabolic profiling approach capable of identifying metabolite marker candidates that could enable highly sensitive and specific detection of BC. However, the coverage of this targeted method was limited and exhibited suboptimal classification of early BC (EBC). To expand the metabolome coverage and articulate a better panel of metabolites or mass spectral features for classification of EBC, we evaluated untargeted liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) data, both individually as well as in conjunction with previously published targeted LC-triple quadruple (QQQ)-MS data. Variable importance in projection scores were used to refine the biomarker panel, whereas orthogonal partial least squares-discriminant analysis was used to operationalize the enhanced biomarker panel for early diagnosis. In this approach, 33 altered metabolites/features were detected by LC-QTOF-MS from 124 BC patients and 86 healthy controls. For EBC diagnosis, significance testing and analysis of the area under receiver operating characteristic (AUROC) curve identified six metabolites/features [ethyl (R)-3-hydroxyhexanoate; caprylic acid; hypoxanthine; and m/z 358.0018, 354.0053, and 356.0037] with p < 0.05 and AUROC > 0.7. These metabolites informed the construction of EBC diagnostic models; evaluation of model performance for the prediction of EBC showed an AUROC = 0.938 (95% CI: 0.895-0.975), with sensitivity = 0.90 when specificity = 0.90. Using the combined untargeted and targeted data set, eight metabolic pathways of potential biological relevance were indicated to be significantly altered as a result of EBC. Metabolic pathway analysis showed fatty acid and aminoacyl-tRNA biosynthesis as well as inositol phosphate metabolism to be most impacted in response to the disease. The combination of untargeted and targeted metabolomics platforms has provided a highly predictive and accurate method for BC and EBC diagnosis from plasma samples. Furthermore, such a complementary approach yielded critical information regarding potential pathogenic mechanisms underlying EBC that, although critical to improved prognosis and enhanced survival, are understudied in the current literature. All mass spectrometry data and deidentified subject metadata analyzed in this study have been deposited to Mendeley Data and are publicly available (DOI: 10.17632/kcjg8ybk45.1).

Metabolomics Analysis of Viral Therapeutics

Virotherapy, enabled by recent advances in the transdisciplinary field of biotechnology, has emerged as a powerful tool for use in anticancer treatment, gene therapy, immunotherapy, etc. Examining the effects of viruses and virus-derived immune-modulating therapeutics is of great fundamental and clinical interest. Here we describe a sample preparation protocol for metabolite extraction from virus-infected tissue, in addition to liquid chromatography-mass spectrometry conditions essential for subsequent analysis. This metabolomics approach delivers highly sensitive and specific metabolite information on various biospecimens. Such an approach may be adopted to monitor biological changes in over 30 relevant metabolic pathways in response to viral infection and also viral therapeutics.

Hypoxia promotes erythroid differentiation through the development of progenitors and proerythroblasts

Oxygen is a critical noncellular component of the bone marrow microenvironment that plays an important role in the development of hematopoietic cell lineages. In this study, we investigated the impact of low oxygen (hypoxia) on ex vivo myeloerythroid differentiation of human cord blood-derived CD34⁺ hematopoietic stem and progenitor cells. We characterized the culture conditions to demonstrate that low oxygen inhibits cell proliferation and causes a metabolic shift in the stem and progenitor populations. We found that hypoxia promotes erythroid differentiation by supporting the development of progenitor populations. Hypoxia also increases the megakaryoerythroid potential of the common myeloid progenitors and the erythroid potential of megakaryoerythroid progenitors and significantly accelerates maturation of erythroid cells. Specifically, we determined that hypoxia promotes the loss of CD71 and the appearance of the erythroid markers CD235a and CD239. Further, evaluation of erythroid populations revealed a hypoxia-induced increase in proerythroblasts and in enucleation of CD235a⁺ cells. These results reveal the extensive role of hypoxia at multiple steps during erythroid development. Overall, our work establishes a valuable model for further investigations into the relationship between erythroid progenitors and/or erythroblast populations and their hypoxic microenvironment.

"Force iteration molecular designing" strategy for the systematic characterization and discovery of new protostane triterpenoids from Alisma Rhizoma by UHPLC/LTQ-Orbitrap-MS

Comprehensive analysis and identification of chemical components are of great significance for evaluating the efficacy and safety of herbal medicines, as well as for drug exploitation and development. Here we developed a "force iteration molecular designing" strategy, by combing a database-based in-house software for a precursor ion list (PIL) and PIL-triggered collision-induced dissociation-MS² and high-energy C-trap dissociation-MS² (PIL-CID/MS²-HCD/MS²) on an LTQ-Orbitrap mass spectrometer, aiming for the systematic characterization and discovery of new protostane triterpenoids (PTs) from Alisma Rhizoma (AR). AR was a well-known herbal remedy widely used for diarrhea, but its systematic characterization and comparison between two botanical origins have not been reported. Firstly, in-house software was developed based on force iteration, to generate a PIL that contains 483 accurate precursor ions. Secondly, to facilitate the acquisition of rich fragments and diagnostic ions sufficient for the structural elucidation of different types of PTs, a hybrid data acquisition method, namely PIL-CID/MS²-HCD/MS², was generated. Thirdly, a total of 473 PTs were rapidly characterized from two botanical origins of AR according to an established four-step interpretation method, and the common constituents were 277 with ratio 70% (277/395) and 78% (277/355) in the rhizome of Alisma plantago-aquatica and A. orientale, respectively. Finally, two new PTs were isolated and unambiguously identified by NMR verifying the feasibility of this combined data acquisition strategy. This integrated strategy could improve the efficiency in the detection of new compounds in a single run and is practical to comprehensively characterize the complex components in herbal medicines.

ApoE4 Impairs Neuron-Astrocyte Coupling of Fatty Acid Metabolism

Alzheimer’s disease (AD) risk gene ApoE4 perturbs brain lipid homeostasis and energy transduction. However, the cell-type-specific mechanism of ApoE4 in modulating brain lipid metabolism is unclear. Here, we describe a detrimental role of ApoE4 in regulating fatty acid (FA) metabolism across neuron and astrocyte in tandem with their distinctive mitochondrial phenotypes. ApoE4 disrupts neuronal function by decreasing FA sequestering in lipid droplets (LDs). FAs in neuronal LDs are exported and internalized by astrocytes, with ApoE4 diminishing the transport efficiency. Further, ApoE4 lowers FA oxidation and leads to lipid accumulation in both astrocyte and the hippocampus. Importantly, diminished capacity of ApoE4 astrocytes in eliminating neuronal lipids and degrading FAs accounts for their compromised metabolic and synaptic support to neurons. Collectively, our findings reveal a mechanism of ApoE4 disruption to brain FA and bioenergetic homeostasis that could underlie the accelerated lipid dysregulation and energy deficits and increased AD risk for ApoE4 carriers.

Qi et al. reveal a role of Alzheimer’s disease risk gene ApoE4 in disrupting fatty acid metabolism coupled between neuron and astrocyte. A systematic impairment in neuronal sequestering, neuron-to-astrocyte transport, and astrocytic degradation of fatty acids could contribute to lipid dysregulation, bioenergetic deficits, and increased Alzheimer’s risk in ApoE4 carriers.

Investigating biological effects of multidimensional carboxylated carbon-based nanomaterials on human lung A549 cells revealed via non-targeted metabolomics approach

The biological responses of multidimensional carboxylated carbon-based nanomaterials (c-CBNs), including carboxylated graphene, carbon nanotube, and fullerene, on human lung A549 cells were investigated by using metabolomics technology. The structure and components of c-CBNs were characterized, and their biological effects were evaluated through cell apoptosis and viability analysis. Additionally, the metabolomics analysis of the nanomaterial-cell interaction system was performed using the established platform combining liquid chromatography-mass spectrometry (LC-MS) with the bioinformatics system. Results revealed that all tested c-CBNs demonstrated some biological effects in our cell model. However, significant metabolomic alterations induced by c-CBNs were also observed mainly in amino acids, organic acids, glycerophospholipids, and glycerolipids. Further, under the tested concentrations, the multiple dimensions of c-CBNs played a major role in determining the metabolic process in various interaction modes. This study provides an advanced alternative for evaluating metabolic effects of multidimensional nanomaterials through metabolomics technology considering the association between dimension and metabolic characteristics.

Phosphorylation of PDHA by AMPK Drives TCA Cycle to Promote Cancer Metastasis

Cancer metastasis accounts for the major cause of cancer-related deaths. How disseminated cancer cells cope with hostile microenvironments in secondary site for full-blown metastasis is largely unknown. Here, we show that AMPK (AMP-activated protein kinase), activated in mouse metastasis models, drives pyruvate dehydrogenase complex (PDHc) activation to maintain TCA cycle (tricarboxylic acid cycle) and promotes cancer metastasis by adapting cancer cells to metabolic and oxidative stresses. This AMPK-PDHc axis is activated in advanced breast cancer and predicts poor metastasis-free survival. Mechanistically, AMPK localizes in the mitochondrial matrix and phosphorylates the catalytic alpha subunit of PDHc (PDHA) on two residues S295 and S314, which activates the enzymatic activity of PDHc and alleviates an inhibitory phosphorylation by PDHKs, respectively. Importantly, these phosphorylation events mediate PDHc function in cancer metastasis. Our study reveals that AMPK-mediated PDHA phosphorylation drives PDHc activation and TCA cycle to empower cancer cells adaptation to metastatic microenvironments for metastasis.

Five Easy Metrics of Data Quality for LC-MS-Based Global Metabolomics

Data quality in global metabolomics is of great importance for biomarker discovery and system biology studies. However, comprehensive metrics and methods to evaluate and compare the data quality of global metabolomics data sets are lacking. In this work, we combine newly developed metrics, along with well-known measures, to comprehensively and quantitatively characterize the data quality across two similar liquid chromatography coupled with mass spectrometry (LC-MS) platforms, with the goal of providing an efficient and improved ability to evaluate the data quality in global metabolite profiling experiments. A pooled human serum sample was run 50 times on two high-resolution LC-QTOF-MS platforms to provide profile and centroid MS data. These data were processed using Progenesis QI software and then analyzed using five important data quality measures, including retention time drift, the number of compounds detected, missing values, and MS reproducibility (2 measures). The detected compounds were fit to a γ distribution versus compound abundance, which was normalized to allow comparison of different platforms. To evaluate missing values, characteristic curves were obtained by plotting the compound detection percentage versus extraction frequency. To characterize reproducibility, the accumulative coefficient of variation (CV) versus the percentage of total compounds detected and intraclass correlation coefficient (ICC) versus compound abundance were investigated. Key findings include significantly better performance using profile mode data compared to centroid mode as well quantitatively better performance from the newer, higher resolution instrument. A summary table of results gives a snapshot of the experimental results and provides a template to evaluate the global metabolite profiling workflow. In total, these measures give a good overall view of data quality in global profiling and allow comparisons of data acquisition strategies and platforms as well as optimization of parameters.

2,2',4,4'-tetrabromodiphenyl ether (BDE-47) induces wide metabolic changes including attenuated mitochondrial function and enhanced glycolysis in PC12 cells

Polybrominated diphenyl ethers (PBDEs) are extensively used as brominated flame retardants in various factory products. As environmental pollutants, the adverse effects of PBDEs on human health have been receiving considerable attention. However, the precise fundamental mechanisms of toxicity induced by PBDEs are still not fully understood. In this study, the mechanism of cytotoxicity induced by 2,2',4,4'-tetrabromodiphenyl ether (BDE-47) was investigated by combining Seahorse XFp analysis and mass spectrometry-based metabolomics and flux approaches in PC12 cells, one of the most widely used neuron-like cell lines for investigating cytotoxic effects. The Seahorse results suggest that BDE-47 significantly attenuated mitochondrial respiration and enhanced glycolysis in PC12 cells. Additionally, metabolomics results revealed the reduction of TCA metabolites such as citrate, succinate, aconitate, malate, fumarate, and glutamate after BDE-47 exposure. Metabolic flux analysis showed that BDE-47 exposure reduced the oxidative metabolic capacity of mitochondria in PC12 cells. Furthermore, various altered metabolites were found in multiple metabolic pathways, especially in glycine-serine-threonine metabolism and glutathione metabolism. A total of 17 metabolic features were determined in order to distinguish potentially disturbed metabolite markers of BDE-47 exposure. Our findings provide possible biomarkers of cytotoxic effects induced by BDE-47 exposure, and elicit a deeper understanding of the intramolecular mechanisms that could be used in further studies to validate the potential neurotoxicity of PBDEs in vivo. Based on our results, therapeutic approaches targeting mitochondrial function and the glycolysis pathway may be a promising direction against PBDE exposure.

FUNCTIONAL METABOLOMICS DECIPHER BIOCHEMICAL FUNCTIONS AND ASSOCIATED MECHANISMS UNDERLIE SMALL-MOLECULE METABOLISM

Metabolism is the collection of biochemical reactions enabled by chemically diverse metabolites, which facilitate different physiological processes to exchange substances and synthesize energy in diverse living organisms. Metabolomics has emerged as a cutting-edge method to qualify and quantify the metabolites in different biological matrixes, and it has the extraordinary capacity to interrogate the biological significance that underlies metabolic modification and modulation. Liquid chromatography combined with mass spectrometry (LC/MS), as a robust platform for metabolomics analysis, has increased in popularity over the past 10 years due to its excellent sensitivity, throughput, and versatility. However, metabolomics investigation currently provides us with only phenotype data without revealing the biochemical functions and associated mechanisms. This limitation indeed weakens the core value of metabolomics data in a broad spectrum of the life sciences. In recent years, the scientific community has actively explored the functional features of metabolomics and translated this cutting-edge approach to be used to solve key multifaceted questions, such as disease pathogenesis, the therapeutic discovery of drugs, nutritional issues, agricultural problems, environmental toxicology, and microbial evolution. Here, we are the first to briefly review the history and applicable progression of LC/MS-based metabolomics, with an emphasis on the applications of metabolic phenotyping. Furthermore, we specifically highlight the next era of LC/MS-based metabolomics to target functional metabolomes, through which we can answer phenotype-related questions to elucidate biochemical functions and associated mechanisms implicated in dysregulated metabolism. Finally, we propose many strategies to enhance the research capacity of functional metabolomics by enabling the combination of contemporary omics technologies and cutting-edge biochemical techniques. The main purpose of this review is to improve the understanding of LC/MS-based metabolomics, extending beyond the conventional metabolic phenotype toward biochemical functions and associated mechanisms, to enhance research capability and to enlarge the applicable scope of functional metabolomics in small-molecule metabolism in different living organisms.

Comprehensive Isotopic Targeted Mass Spectrometry: Reliable Metabolic Flux Analysis with Broad Coverage

Metabolic flux analysis (MFA) is highly relevant to understanding metabolic mechanisms of various biological processes. While the pace of methodology development in MFA has been rapid, a major challenge the field continues to witness is limited metabolite coverage, often restricted to a small to moderate number of well-known compounds. In addition, isotopic peaks from an enriched metabolite tend to have low abundances, which makes liquid chromatography tandem mass spectrometry (LC-MS/MS) highly useful in MFA due to its high sensitivity and specificity. Previously we have built large-scale LC-MS/MS approaches that can be routinely used for measurement of up to ∼1,900 metabolite/feature levels [Gu et al. Anal. Chem. 2015, 87, 12355-12362. Shi et al. Anal. Chem. 2019, 91, 13737-13745.]. In this study, we aim to expand our previous studies focused on metabolite level measurements to flux analysis and establish a novel comprehensive isotopic targeted mass spectrometry (CIT-MS) method for reliable MFA analysis with broad coverage. As a proof-of-principle, we have applied CIT-MS to compare the steady-state enrichment of metabolites between Myc(oncogene)-On and Myc-Off Tet21N human neuroblastoma cells cultured with U-13C6-glucose medium. CIT-MS is operationalized using multiple reaction monitoring (MRM) mode and is able to perform MFA of 310 identified metabolites (142 reliably detected, 46 kinetically profiled) selected from >35 metabolic pathways of strong biological significance. Further, we developed a novel concept of relative flux, which eliminates the requirement of absolute quantitation in traditional MFA and thus enables comparative MFA under the pseudosteady state. As a result, CIT-MS was shown to possess the advantages of broad coverage, easy implementation, fast throughput, and more importantly, high fidelity and accuracy in MFA. In principle, CIT-MS can be easily adapted to track the flux of other labeled tracers (such as 15N-tracers) in any metabolite detectable by LC-MS/MS and in various biological models (such as mice). Therefore, CIT-MS has great potential to bring new insights to both basic and clinical metabolism research.

Bridging Targeted and Untargeted Mass Spectrometry-Based Metabolomics via Hybrid Approaches

This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.

Antibiotic-induced gut metabolome and microbiome alterations increase the susceptibility to Candida albicans colonization in the gastrointestinal tract

Antibiotic-induced alterations in the gut ecosystem increases the susceptibility to Candida albicans, yet the mechanisms involved remains poorly understood. Here we show that mice treated with the broad-spectrum antibiotic cefoperazone promoted the growth, morphogenesis and gastrointestinal (GI) colonization of C. albicans. Using metabolomics, we revealed that the cecal metabolic environment of the mice treated with cefoperazone showed a significant alteration in intestinal metabolites. Levels of carbohydrates, sugar alcohols and primary bile acids increased, whereas carboxylic acids and secondary bile acids decreased in antibiotic treated mice susceptible to C. albicans. Furthermore, using in-vitro assays, we confirmed that carbohydrates, sugar alcohols and primary bile acids promote, whereas carboxylic acids and secondary bile acids inhibit the growth and morphogenesis of C. albicans. In addition, in this study we report changes in the levels of gut metabolites correlated with shifts in the gut microbiota. Taken together, our in-vivo and in-vitro results indicate that cefoperazone-induced metabolome and microbiome alterations favor the growth and morphogenesis of C. albicans, and potentially play an important role in the GI colonization of C. albicans.