Infant microbes and metabolites point to childhood neurodevelopmental disorders.

This study has followed a birth cohort for over 20 years to find factors associated with neurodevelopmental disorder (ND) diagnosis. Detailed, early-life longitudinal questionnaires captured infection and antibiotic events, stress, prenatal factors, family history, and more. Biomarkers including cord serum metabolome and lipidome, human leukocyte antigen (HLA) genotype, infant microbiota, and stool metabolome were assessed. Among the 16,440 Swedish children followed across time, 1,197 developed an ND. Significant associations emerged for future ND diagnosis in general and for specific ND subtypes, spanning intellectual disability, speech disorder, attention-deficit/hyperactivity disorder, and autism. This investigation revealed microbiome connections to future diagnosis as well as early emerging mood and gastrointestinal problems. The findings suggest links to immunodysregulation and metabolism, compounded by stress, early-life infection, and antibiotics. The convergence of infant biomarkers and risk factors in this prospective, longitudinal study on a large-scale population establishes a foundation for early-life prediction and intervention in neurodevelopment.

The lipidomics reporting checklist a framework for transparency of lipidomic experiments and repurposing resource data.

The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic easy-to-use checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.

Divergent Metabolic Fates of Aromatic Amino Acid-Derived Isomers: Insights from Ex Vivo Metabolomics and HDX-HRMS/MS-Based Resolution of Tautomers.

Tautomers are one of the many types of isomers, and differences in tautomeric structures confer altered chemical and biological properties. Using ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) ex vivo metabolomics, we investigate, in whole blood, the divergent metabolism of enol and keto forms of indole-3-pyruvate (IPyA), a tautomeric product of aromatic amino acid metabolism. Two new compounds resulting from IPyA metabolism were discovered, 3-(1H-indol-3-yl)-2,3-dioxopropanoic acid or "indole-3-oxopyruvic acid" and glutathionyl-indole pyruvate (GSHIPyA), which were characterized via ultraviolet photodissociation (UVPD) and higher-energy collisional dissociation (HCD). Computational calculations support the hypothesis that GSHIPyA forms specifically through the enol form of IPyA. GSHIPyA is also hypothesized to be tautomeric, and a hydrogen-deuterium exchange-high-resolution tandem mass spectrometry (HDX-HRMS/MS) approach is developed to prove the presence of an enol and keto tautomer. HDX of GSHIPyA labels the keto form with an additional deuterium, relative to the enol form. HRMS/MS of the labeled isomers is employed to leverage the relationship of resolving power scaling inversely with the square root of m/z, for Orbitrap mass analyzers. HRMS/MS yields a smaller-molecular-weight deuterated tautomeric product ion, reducing the analyte ion m/z and thus lowering the resolving power necessary to separate the deuterated keto tautomer product ion from the [13]C product ion.

Indole-3-pyruvate: Analysis and Control of Tautomerism and Reactivity.

It is well-known in biochemistry that structure confers function, meaning that chemical structural elucidation is critical to truly understanding the function of a given metabolite. Indole-3-pyruvate (IPyA) exists in an equilibrium between the keto and enol tautomeric forms. IPyA is suggested to play a role in immune function; however, determining whether the tautomeric forms function differently can only be studied if an analytical method is capable of distinguishing between the two forms. Herein, we describe the use of UHPLC-HRMS to gain insight into the physical variables that govern IPyA tautomer equilibrium, reactivity, and detection limit. We use hydrogen-deuterium exchange (HDX) to identify enol and keto peaks, and we show that tautomers exhibit a valley of fronting followed by a tailing peak shape (though separation is still attainable) and identical MS/MS spectra. We observed drastically different ratios of keto and enol forms in different solvents, which is an important consideration for in vitro studies. IPyA was found to be highly unstable with accelerated reactivity in peroxides. Through in vitro reactivity studies, IPyA produced a myriad of known and unknown metabolites via nonenzymatic processes, many of which were mapped in vivo via the analysis of human plasma. Finally, we show that vitamin C (ascorbic acid) can slow this reactivity and enable sensitive detection in whole blood.

Severe anemia in preterm infants associated with increased bacterial virulence potential and metabolic disequilibrium.

BACKGROUND: Anemia in preterm infants is associated with gut dysbiosis and necrotizing enterocolitis. Our study aimed to identify the bacterial functions and metabolites that can explain the underlying mechanisms of anemia associated disease conditions. METHODS: We conducted a case control study in preterm infants with cases having a hematocrit ≤ 25%. The control infants were matched by birth gestational age and weight. Fecal samples were collected before, at the onset, and after the onset of anemia in cases and with matched postnatal age in controls for metagenomics and metabolomics analyzes. RESULTS: 18 anemic and 20 control infants with fecal samples collected at 17 days, 5 weeks, and 7 weeks postnatal age were included. Virulence factor potential, decrease in beta diversity evolution, and larger changes in metabolome were associated with severe anemia. Metabolite abundances of N-acetylneuraminate and butyrobetaine were associated with virulence factor potential. Anemic group had decreased prostaglandin and lactic acid levels. CONCLUSION: Fecal omics data showed that severe anemia is associated with a pro-inflammatory gut microbiota with more virulent and less commensal anaerobic bacterial activities. Future studies can examine the link between anemia-associated dysbiosis and clinical outcomes and predict an infant-specific hematocrit threshold that negatively affects clinical outcomes. IMPACT: Severe anemia in preterm infants contributes to a pro-inflammatory gut with greater bacterial virulence and less commensal bacterial activities. The multiomics approach using non-invasive fecal biospecimens identified functional and metabolic changes in the gut microbiota and these mechanistic changes are plausible explanations for anemia-associated disease conditions in preterm infants. Our findings identified biological changes of the gut environment in severely anemic preterm infants that can offer guidance for clinical management.

MetaWise: Combined Feature Selection and Weighting Method to Link the Serum Metabolome to Treatment Response and Survival in Glioblastoma.

Glioblastoma (GBM) is a highly malignant and devastating brain cancer characterized by its ability to rapidly and aggressively grow, infiltrating brain tissue, with nearly universal recurrence after the standard of care (SOC), which comprises maximal safe resection followed by chemoirradiation (CRT). The metabolic triggers leading to the reprogramming of tumor behavior and resistance are an area increasingly studied in relation to the tumor molecular features associated with outcome. There are currently no metabolomic biomarkers for GBM. Studying the metabolomic alterations in GBM patients undergoing CRT could uncover the biochemical pathways involved in tumor response and resistance, leading to the identification of novel biomarkers and the optimization of the treatment response. The feature selection process identifies key factors to improve the model's accuracy and interpretability. This study utilizes a combined feature selection approach, incorporating both Least Absolute Shrinkage and Selection Operator (LASSO) and Minimum Redundancy-Maximum Relevance (mRMR), alongside a rank-based weighting method (i.e., MetaWise) to link metabolomic biomarkers to CRT and the 12-month and 20-month overall survival (OS) status in patients with GBM. Our method shows promising results, reducing feature dimensionality when employed on serum-based large-scale metabolomic datasets (University of Florida) for all our analyses. The proposed method successfully identified a set of eleven serum biomarkers shared among three datasets. The computational results show that the utilized method achieves 96.711%, 92.093%, and 86.910% accuracy rates with 48, 46, and 33 selected features for the CRT, 12-month, and 20-month OS-based metabolomic datasets, respectively. This discovery has implications for developing personalized treatment plans and improving patient outcomes.

Segmented Flow Strategies for Integrating Liquid Chromatography-Mass Spectrometry with Nuclear Magnetic Resonance for Lipidomics.

Building an accurate lipid inventory relies on coordinated information from orthogonal analytical capabilities. Integrating the familiar workflow of liquid chromatography (LC), high-resolution mass spectrometry (HRMS), and tandem mass spectrometry (MS/MS) with proton nuclear magnetic resonance spectroscopy (1H NMR) would be ideal for building that inventory. For absolute lipid structural elucidation, LC-HRMS/MS can provide lower-level structural information with superior sensitivity, while 1H NMR can provide invaluable higher-order structural information for the disambiguation of isomers with absolute chemical specificity. Digitization of the LC eluent followed by splitting the microfractions into two flow paths in a defined ratio for HRMS/MS and NMR would be the ideal strategy to permit correlation of the MS and NMR data as a function of chromatographic retention time. Here, we report an active segmentation platform to transform analytical flow rate LC eluent into parallel microliter segmented flow queues for high confidence correlation of the MS, MS/MS, and NMR data. The practical details in implementing this strategy to achieve an integrated LC-MS-NMR platform are presented, including the development of an active segmentation technology using a four-port two-way valve to transform the LC eluent into parallel segmented flows for online MS analysis followed by offline segment-specific 1H NMR and optimization of the detector response toward segmented flow. To demonstrate the practicality of this novel platform, it was tested using lipid mixture samples.

Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software.

BACKGROUND: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is a popular approach for metabolomics data acquisition and requires many data processing software tools. The FAIR Principles - Findability, Accessibility, Interoperability, and Reusability - were proposed to promote open science and reusable data management, and to maximize the benefit obtained from contemporary and formal scholarly digital publishing. More recently, the FAIR principles were extended to include Research Software (FAIR4RS). AIM OF REVIEW: This study facilitates open science in metabolomics by providing an implementation solution for adopting FAIR4RS in the LC-HRMS metabolomics data processing software. We believe our evaluation guidelines and results can help improve the FAIRness of research software. KEY SCIENTIFIC CONCEPTS OF REVIEW: We evaluated 124 LC-HRMS metabolomics data processing software obtained from a systematic review and selected 61 software for detailed evaluation using FAIR4RS-related criteria, which were extracted from the literature along with internal discussions. We assigned each criterion one or more FAIR4RS categories through discussion. The minimum, median, and maximum percentages of criteria fulfillment of software were 21.6%, 47.7%, and 71.8%. Statistical analysis revealed no significant improvement in FAIRness over time. We identified four criteria covering multiple FAIR4RS categories but had a low %fulfillment: (1) No software had semantic annotation of key information; (2) only 6.3% of evaluated software were registered to Zenodo and received DOIs; (3) only 14.5% of selected software had official software containerization or virtual machine; (4) only 16.7% of evaluated software had a fully documented functions in code. According to the results, we discussed improvement strategies and future directions.

Strength in Numbers: Density-Dependent Volatile-Induced Antimicrobial Activity by Xanthomonas perforans.

For most of the 20th century, Xanthomonas euvesicatoria was the only known bacterium associated with bacterial spot of tomato in Florida. X. perforans quickly replaced X. euvesicatoria, mainly because of production of three bacteriocins (BCNs) against X. euvesicatoria; however, X. perforans outcompeted X. euvesicatoria even when the three known BCNs were deleted. Surprisingly, we observed antimicrobial activity against X. euvesicatoria in the BCN triple mutant when the triple mutant was grown in Petri plates containing multiple spots but not in Petri plates containing only one spot. We determined that changes in the headspace composition (i.e., volatiles) rather than a diffusible signal in the agar were required for induction of the antimicrobial activity. Other Xanthomonas species also produced volatile-induced antimicrobial compounds against X. euvesicatoria and elicited antimicrobial activity by X. perforans. A wide range of plant pathogenic bacteria, including Clavibacter michiganensis subsp. michiganensis, Pantoea stewartii, and Pseudomonas cichorii, also elicited antimicrobial activity by X. perforans when multiple spots of the species were present. To identify potential antimicrobial compounds, we performed liquid chromatography with high-resolution mass spectrometry of the agar surrounding the spot in the high cell density Petri plates where the antimicrobial activity was present compared with agar surrounding the spot in Petri plates with one spot where antimicrobial activity was not observed. Among the compounds identified in the zone of inhibition were N-butanoyl-L-homoserine lactone and N-(3-hydroxy-butanoyl)-homoserine lactone, which are known quorum-sensing metabolites in other bacteria.

Comparison of serum metabolomics in women with breast Cancer Prior to Chemotherapy and at 1 year: cardiometabolic implications.

OBJECTIVE: Early-stage breast cancer (BC) is the second most common malignancy in women, worldwide. Early-detection and treatment advances have led to 5-year survival rates of 90% for early-stage breast cancer. However, the long-term morbidity of breast cancer remains high, with a majority of survivors facing increased risk of cardiometabolic conditions as well as secondary cancers. In particular, African American women with breast cancer experience higher morbidity and mortality than other women. Metabolomics is the comprehensive study of metabolites in biological samples to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways. Although some studies have found differential metabolites in women with breast cancer compared to normal controls, there has been little study of women with breast cancer across time and the active treatment trajectory. This study examines and compares the serum metabolomic profile of women with BC, prior to initial chemotherapy and at 1 year after inception of chemotherapy. METHODS: This study examined serum metabolites through a secondary analysis of a longitudinal parent study (EPIGEN) of women diagnosed with early-stage BC. Participants were evaluated across 5 time points: prior to their receipt of chemotherapy (T1), at the time of their 4th chemotherapy treatment (T2), 6 months after the initiation of chemotherapy (T3), one year after the initiation of chemotherapy (T4) and two years after the initiation of chemotherapy (T5). This analysis focused on the metabolomic data from 70 participants from T1 to T4. Using ultra high-pressure liquid chromatography high resolution mass spectrometry (UHPLC-HRMS), we performed Friedman Rank Sum Test followed by Nemenyi post-hoc pairwise tests to identify which metabolite levels differed between time points, focusing on metabolites with a Benjamini-Hochberg false discovery rate (FDR) from the overall Friedman test < 0.05 and then specifically examined the p-values from the T1 vs. T4 pairwise comparison. RESULTS: The untargeted serum metabolomics yielded a total of 2,395 metabolites identified on the basis of the accurate mass and MS/MS fragmentation, 1,264 of which were significant after Friedman's test (FDR < 0.05). The analysis then focused on the levels of 124 metabolites from the T1 vs. T4 post-hoc comparison that had a combined FDR < 0.05 and fold change (FC) > 2.0. Metabolite set enrichment analysis (MSEA) as part of Metaboanalyst 3.0 was performed to identify pathways that were significantly altered. The known metabolites identified from the functional analysis were used to evaluate the up and down regulated pathways. The 40metabolites from the Functional Analysis were mainly attributed to amino acids (specifically lysine regulation), fatty acids (particularly unsaturated) and steroid hormone synthesis (lysophosphatidic acid). CONCLUSION: There were multiple significant changes in the serum metabolomic profile of women with breast cancer at one-year post inception of chemotherapy compared to pre-chemotherapy, most notably associated with lysine degradation, branched-chain amino acid synthesis, linoleic acid metabolism, tyrosine metabolism and biosynthesis of unsaturated fatty acids as the top 5 metabolic pathways. Some of these changes could be associated with metabolic perturbations that are consistent with heightened risk of cardiometabolic morbidity. Our results provide new insights into the mechanisms underlying potential heightened cardiovascular health risks in this population.

Metabolomic signatures distinguish extracellular vesicles from osteoclasts and odontoclasts.

AIMS: Pathological dental root resorption and alveolar bone loss are often detected only after irreversible damage. Biomarkers in the gingival crevicular fluid or saliva could provide a means for early detection; however, such biomarkers have proven elusive. We hypothesize that a multiomic approach might yield reliable diagnostic signatures for root resorption and alveolar bone loss. Previously, we showed that extracellular vesicles (EVs) from osteoclasts and odontoclasts differ in their protein composition. In this study, we investigated the metabolome of EVs from osteoclasts, odontoclasts and clasts (non-resorbing clastic cells). MATERIALS AND METHODS: Mouse haematopoietic precursors were cultured on dentine, bone or plastic, in the presence of recombinant RANKL and CSF-1 to trigger differentiation along the clastic line. On Day 7, the cells were fixed and the differentiation state and resorptive status of the clastic cells were confirmed. EVs were isolated from the conditioned media on Day 7 and characterized by nanoparticle tracking and electron microscopy to ensure quality. Global metabolomic profiling was performed using a Thermo Q-Exactive Orbitrap mass spectrometer with a Dionex UHPLC and autosampler. RESULTS: We identified 978 metabolites in clastic EVs. Of those, 79 are potential biomarkers with Variable Interdependent Parameters scores of 2 or greater. Known metabolites cytidine, isocytosine, thymine, succinate and citrulline were found at statistically higher levels in EVs from odontoclasts compared with osteoclasts. CONCLUSION: We conclude that numerous metabolites found in odontoclast EVs differ from those in osteoclast EVs, and thus represent potential biomarkers for root resorption and periodontal tissue destruction.

Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma.

Metabolic reprogramming has been described in rapidly growing tumors, which are thought to mostly contain fast-cycling cells (FCCs) that have impaired mitochondrial function and rely on aerobic glycolysis. Here, we characterize the metabolic landscape of glioblastoma (GBM) and explore metabolic specificities as targetable vulnerabilities. Our studies highlight the metabolic heterogeneity in GBM, in which FCCs harness aerobic glycolysis, and slow-cycling cells (SCCs) preferentially utilize mitochondrial oxidative phosphorylation for their functions. SCCs display enhanced invasion and chemoresistance, suggesting their important role in tumor recurrence. SCCs also demonstrate increased lipid contents that are specifically metabolized under glucose-deprived conditions. Fatty acid transport in SCCs is targetable by pharmacological inhibition or genomic deletion of FABP7, both of which sensitize SCCs to metabolic stress. Furthermore, FABP7 inhibition, whether alone or in combination with glycolysis inhibition, leads to overall increased survival. Our studies reveal the existence of GBM cell subpopulations with distinct metabolic requirements and suggest that FABP7 is central to lipid metabolism in SCCs and that targeting FABP7-related metabolic pathways is a viable therapeutic strategy.

Data-Driven Soft Independent Modeling of Class Analogy in Paper Spray Ionization Mass Spectrometry-Based Metabolomics for Rapid Detection of Prostate Cancer.

Sensitive, rapid, and meaningful diagnostic tools for prostate cancer (PC) screening are urgently needed. Paper spray ionization mass spectrometry (PSI-MS) is an emerging rapid technology for detecting biomarker and disease diagnoses. Due to lack of chromatography and difficulties in employing tandem MS, PSI-MS-based untargeted metabolomics often suffers from increased ion suppression and subsequent feature detection, affecting chemometric methods for disease classification. This study first evaluated the data-driven soft independent modeling of class analogy (DD-SIMCA) model to analyze PSI-MS-based global metabolomics of a urine data matrix to classify PC. The efficiency of DD-SIMCA was analyzed based on the sensitivity and specificity parameters that showed 100% correct classification of the training set, based on only PC and test set samples, based on normal and PC. This analytical methodology is easy to interpret and efficient and does not require any prior information from the healthy individual. This new application of DD-SIMCA in PSI-MS-based metabolomics for PC disease classification could also be extended to other diseases and opens a rapid strategy to discriminate against health problems.

Cereblon harnesses Myc-dependent bioenergetics and activity of CD8+ T lymphocytes.

Immunomodulatory drugs, such as thalidomide and related compounds, potentiate T-cell effector functions. Cereblon (CRBN), a substrate receptor of the DDB1-cullin-RING E3 ubiquitin ligase complex, is the only molecular target for this drug class, where drug-induced, ubiquitin-dependent degradation of known "neosubstrates," such as IKAROS, AIOLOS, and CK1α, accounts for their biological activity. Far less clear is whether these CRBN E3 ligase-modulating compounds disrupt the endogenous functions of CRBN. We report that CRBN functions in a feedback loop that harnesses antigen-specific CD8+ T-cell effector responses. Specifically, Crbn deficiency in murine CD8+ T cells augments their central metabolism manifested as elevated bioenergetics, with supraphysiological levels of polyamines, secondary to enhanced glucose and amino acid transport, and with increased expression of metabolic enzymes, including the polyamine biosynthetic enzyme ornithine decarboxylase. Treatment with CRBN-modulating compounds similarly augments central metabolism of human CD8+ T cells. Notably, the metabolic control of CD8+ T cells by modulating compounds or Crbn deficiency is linked to increased and sustained expression of the master metabolic regulator MYC. Finally, Crbn-deficient T cells have augmented antigen-specific cytolytic activity vs melanoma tumor cells, ex vivo and in vivo, and drive accelerated and highly aggressive graft-versus-host disease. Therefore, CRBN functions to harness the activation of CD8+ T cells, and this phenotype can be exploited by treatment with drugs.

Mass spectrometry imaging in gynecological cancers: the best is yet to come.

Mass spectrometry imaging (MSI) enables obtaining multidimensional results simultaneously in a single run, including regiospecificity and m/z values corresponding with specific proteins, peptides, lipids, etc. The knowledge obtained in this way allows for a multifaceted analysis of the studied issue, e.g., the specificity of the neoplastic process and the search for new therapeutic targets. Despite the enormous possibilities, this relatively new technique in many aspects still requires the development or standardization of analytical protocols (from collecting biological material, through sample preparation, analysis, and data collection, to data processing). The introduction of standardized protocols for MSI studies, with its current potential to extend diagnostic and prognostic capabilities, can revolutionize clinical pathology. As far as identifying ovarian cancer subtypes can be challenging, especially in poorly differentiated tumors, developing MSI-based algorithms may enhance determining prognosis and tumor staging without the need for extensive surgery and optimize the choice of subsequent therapy. MSI might bring new solutions in predicting response to treatment in patients with endometrial cancer. Therefore, MSI may help to revolutionize the future of gynecological oncology in terms of diagnostics, treatment, and predicting the response to therapy. This review will encompass several aspects, e.g., contemporary discoveries in gynecological cancer research utilizing MSI, indicates current challenges, and future perspectives on MSI.

Association between lipid profiles and viral respiratory infections in human sputum samples.

BACKGROUND: Respiratory infections such as influenza account for significant global mortality each year. Generating lipid profiles is a novel and emerging research approach that may provide new insights regarding the development and progression of priority respiratory infections. We hypothesized that select clusters of lipids in human sputum would be associated with specific viral infections (Influenza (H1N1, H3N2) or Rhinovirus). METHODS: Lipid identification and semi-quantitation was determined with liquid chromatography and high-resolution mass spectrometry in induced sputum from individuals with confirmed respiratory infections (influenza (H1N1, H3N2) or rhinovirus). Clusters of lipid species and associations between lipid profiles and the type of respiratory viral agent was determined using Bayesian profile regression and multinomial logistic regression. RESULTS: More than 600 lipid compounds were identified across the sputum samples with the most abundant lipid classes identified as triglycerides (TG), phosphatidylethanolamines (PE), phosphatidylcholines (PC), Sphingomyelins (SM), ether-PC, and ether-PE. A total of 12 lipid species were significantly different when stratified by infection type and included acylcarnitine (AcCar) (10:1, 16:1, 18:2), diacylglycerols (DG) (16:0_18:0, 18:0_18:0), Lysophosphatidylcholine (LPC) (12:0, 20:5), PE (18:0_18:0), and TG (14:1_16:0_18:2, 15:0_17:0_19:0, 16:0_17:0_18:0, 19:0_19:0_19:0). Cluster analysis yielded three clusters of lipid profiles that were driven by just 10 lipid species (TGs and DGs). Cluster 1 had the highest levels of each lipid species and the highest prevalence of influenza A H3 infection (56%, n = 5) whereas cluster 3 had lower levels of each lipid species and the highest prevalence of rhinovirus (60%; n = 6). Using cluster 3 as the reference group, the crude odds of influenza A H3 infection compared to rhinovirus in cluster 1 was significantly (p = 0.047) higher (OR = 15.00 [95% CI: 1.03, 218.29]). After adjustment for confounders (smoking status and pulmonary comorbidities), the odds ratio (OR) became only marginally significant (p = 0.099), but the magnitude of the effect estimate was similar (OR = 16.00 [0.59, 433.03]). CONCLUSIONS: In this study, human sputum lipid profiles were shown to be associated with distinct types of viral infection. Better understanding the relationship between respiratory infections of global importance and lipids contributes to advancing knowledge of pathogenesis of infections including identifying populations with increased susceptibility and developing effective therapeutics and biomarkers of health status.

Role of Adenosine Kinase in Sphingosine-1-Phosphate Receptor 1-Induced Mechano-Hypersensitivities.

Emerging evidence implicates the sphingosine-1-phosphate receptor subtype 1 (S1PR1) in the development of neuropathic pain. Continued investigation of the signaling pathways downstream of S1PR1 are needed to support development of S1PR1 antagonists. In rodents, intrathecal (i.th.) injection of SEW2871, a selective S1PR1 agonist, activates the nod-like receptor family, pyrin domain containing 3 inflammasome, increases interleukin-1ß (IL-1ß) and causes behavioral hypersensitivity. I.th. injection of a IL-1ß receptor antagonist blocks SEW2871-induced hypersensitivity, suggesting that IL-1ß contributes to S1PR1's actions. Interestingly, previous studies have suggested that IL-1ß increases the expression/activity of adenosine kinase (ADK), a key regulator of adenosine signaling at its receptors (ARs). Increased ADK expression reduces adenosine signaling whereas inhibiting ADK restores the action of adenosine. Here, we show that SEW287-induced behavioral hypersensitivity is associated with increased expression of ADK in astrocytes of the dorsal horn of the spinal cord. Moreover, the ADK inhibitor, ABT702, blocks SEW2871-induced hypersensitivity. These findings link ADK activation to S1PR1. If SEW2871-induced pain is mediated by IL-1ß, which in turn activates ADK and leads to mechano-allodynia, then blocking ADK should attenuate IL-1ß effects. In support of this idea, recombinant rat (rrIL-1ß)-induced allodynia was blocked by at least 90% with ABT702, functionally linking ADK to IL-1ß. Moreover, the selective A3AR antagonist, MRS1523, prevents the ability of ABT702 to block SEW2871 and IL-1ß-induced allodynia, implicating A3AR signaling in the beneficial effects exerted by ABT702. Our findings provide novel mechanistic insight into how S1PR1 signaling in the spinal cord produces hypersensitivity through IL1-ß and ADK activation.

Potential and Metabolic Pathways of Eugenol in the Management of Xanthomonas perforans, a Pathogen of Bacterial Spot of Tomato.

Bacterial spot of tomato continues to pose a significant problem to tomato production worldwide. In Florida, bacterial spot of tomato caused by Xanthomonas perforans is one of the most important diseases responsible for tomato yield loss. This disease is difficult to control, and new strategies are continually being investigated to combat the devastating effect of this disease. Recent efforts focusing on essential oils based on small molecules have spurred interests in the utilization of this class of chemicals for disease management. In this study, we evaluated the efficacy of eugenol for the management of bacterial spot of tomato caused by X. perforans. In the greenhouse experiments, eugenol applied as a foliar spray significantly (p < 0.5) reduced bacterial spot disease compared to the untreated control. In the field experiments, the area under the disease progress curve (AUDPC) was significantly (p < 0.5) lower in the plots treated with eugenol or eugenol combined with the surfactant Cohere than in the untreated control plots, and it was comparable to the copper-based treatments. To provide additional insights into the possible pathways of eugenol activities, we applied a liquid chromatography mass spectrometry (LC-MS)-based metabolomic study using a thermo Q-Exactive orbitrap mass spectrometer with Dionex ultra high-performance liquid chromatography (UHPLC) on X. perforans strain 91−118 treated with eugenol. Our results showed that eugenol affected metabolite production in multiple pathways critical to bacterial survival. For example, treatment of cells with eugenol resulted in the downregulation of the glutathione metabolism pathway and associated metabolites, except for 5-oxoproline, which accumulation is known to be toxic to living cells. While the peaks corresponding to the putatively identified sarmentosin showed the most significant impact and reduced in response to eugenol treatment, branched-chain amino acids, such as L-isoleucine, increased in production, suggesting that eugenol may not negatively affect the protein biosynthesis pathways. The results from our study demonstrated the efficacy of eugenol in the management of bacterial spot of tomato under greenhouse and field conditions and identified multiple pathways that are targeted.

Metabolic Changes Are Associated with Melphalan Resistance in Multiple Myeloma.

Multiple myeloma is an incurable hematological malignancy that impacts tens of thousands of people every year in the United States. Treatment for eligible patients involves induction, consolidation with stem cell rescue, and maintenance. High-dose therapy with a DNA alkylating agent, melphalan, remains the primary drug for consolidation therapy in conjunction with autologous stem-cell transplantation; as such, melphalan resistance remains a relevant clinical challenge. Here, we describe a proteometabolomic approach to examine mechanisms of acquired melphalan resistance in two cell line models. Drug metabolism, steady-state metabolomics, activity-based protein profiling (ABPP, data available at PRIDE: PXD019725), acute-treatment metabolomics, and western blot analyses have allowed us to further elucidate metabolic processes associated with melphalan resistance. Proteometabolomic data indicate that drug-resistant cells have higher levels of pentose phosphate pathway metabolites. Purine, pyrimidine, and glutathione metabolisms were commonly altered, and cell-line-specific changes in metabolite levels were observed, which could be linked to the differences in steady-state metabolism of naïve cells. Inhibition of selected enzymes in purine synthesis and pentose phosphate pathways was evaluated to determine their potential to improve melphalan's efficacy. The clinical relevance of these proteometabolomic leads was confirmed by comparison of tumor cell transcriptomes from newly diagnosed MM patients and patients with relapsed disease after treatment with high-dose melphalan and autologous stem-cell transplantation. The observation of common and cell-line-specific changes in metabolite levels suggests that omic approaches will be needed to fully examine melphalan resistance in patient specimens and define personalized strategies to optimize the use of high-dose melphalan.

Rapid Diagnosis of Prostate Cancer Disease Progression Using Paper Spray Ionization Mass Spectrometry.

The limitation of prostate specific antigen (PSA) for prostate cancer (PC) diagnosis is well-recognized. The Gleason score (GS) has been the most widely used grading system for prostate tumor differentiation and represents the best-established prognostic indicator for prostate cancer progression. However, a rapid and sensitive noninvasive diagnostic marker that differentiates GS-based prostate cancer disease progression is needed. As PC is becoming a leading cause of cancer related death for men in the U.S. and worldwide, an immediate need exists for an improved, sensitive, noninvasive, and rapid diagnostic test for PC screening. Here, we employed paper spray ionization-mass spectrometry (PSI MS)-based global metabolomics of urine liquid biopsies to distinguish between healthy (negative for any prostate specific health problems) and progressive PC states (low grade PC such as GS6 and high-grade PC such as GS7, GS8, and GS9). For PSI-MS-based direct untargeted metabolic investigation, a raw urine sample was directly pipetted onto a triangular paper substrate, without any additional sample preparation. Multivariate statistical analysis revealed distinct GS-specific metabolic signatures compared to a healthy control. Variable importance in projection from partial least-squares-discriminant analysis showed distinct metabolic patterns that were correlatively elevated with progressive disease and could serve as biomarkers for diagnosis of prostate cancer risk categorization.