Functional and metabolomic analysis of urinary extracellular vesicles from juvenile mice with renal compensatory hypertrophy

Unilateral nephrectomy, a procedure reducing kidney mass, triggers a compensatory response in the remaining kidney, increasing its size and function to maintain a normal glomerular filtration rate (GFR). Recent research has highlighted the role of extracellular vesicles (EVs) in renal physiology and disease, although their involvement in unilateral nephrectomy has been underexplored. In this study, unilateral nephrectomy was performed on young mice, and urinary extracellular vesicles (uEVs) characterization and cargo were analyzed. Kidney volume increased significantly post-nephrectomy, demonstrating compensatory hypertrophy. Serum creatinine, cystatin C, and urinary electrolytes concentrations were similar in both nephrectomized and control groups. Western blot analysis revealed upregulation of sodium-glucose cotransporter 2 (SGLT2) and sodium chloride cotransporter (NCC), and downregulation of sodium‑potassium-chloride co-transporter (NKCC2) and epithelial sodium channel (ENaC) in the nephrectomized group. Metabolomic analysis of uEVs showed an enrichment of certain metabolites, including citrate and stachydrine. Interestingly, uEVs from the nephrectomized group demonstrated a protective effect, downregulating signal transducer and activator of transcription 3 (STAT3) and reducing reactive oxygen species (ROS) in renal proximal cells, compared to uEVs from the control group. This study suggests that uEVs contain bioactive components capable of inducing protective, anti-inflammatory, anti-fibrinolytic, and antioxidative effects in renal cells. These findings contribute to our understanding of uEVs' role in renal compensatory mechanisms after unilateral nephrectomy and may hold promise for future therapeutic interventions in renal diseases.

Metabolomic signatures of carfilzomib-related cardiotoxicity in patients with multiple myeloma

As a treatment for relapsed or refractory multiple myeloma (MM), carfilzomib has been associated with a significant risk of cardiovascular adverse events (CVAE). The goals of our study were to evaluate the metabolomic profile of MM patients to identify those at high risk prior to carfilzomib treatment and to explore the mechanisms of carfilzomib-CVAE to inform potential strategies to protect patients from this cardiotoxicity. Global metabolomic profiling was performed on the baseline and post-baseline plasma samples of 60 MM patients treated with carfilzomib-based therapy, including 31 who experienced CVAE, in a prospective cohort study. Baseline metabolites and post-baseline/baseline metabolite ratios that differ between the CVAE and no-CVAE patients were identified using unadjusted and adjusted methods. A baseline metabolomic risk score was created to stratify patients. We observed a lower abundance of tauroursodeoxycholic acid (T-UDCA) in CVAE patients at baseline (odds ratio [OR] = 0.47, 95% confidence interval [CI] = 0.21-0.94, p = 0.044) compared with the no-CVAE patients. A metabolite risk score was able to stratify patients into three risk groups. The area under the receiver-operating curve of the model with clinical predictors and metabolite risk score was 0.93. Glycochenodeoxycholic acid (OR = 0.56, 95% CI = 0.31-0.87, p = 0.023) was significantly lower in post-baseline/baseline ratios of CVAE patients compared with no-CVAE patients. Following metabolomic analysis, we created a baseline metabolite risk score that can stratify MM patients into different risk groups. The result also provided intriguing clues about the mechanism of carfilzomib-CVAE and potential cardioprotective strategies.

Lipoxin A 4 /FPR2 signaling mitigates ferroptosis of alveolar epithelial cells via NRF2-dependent pathway during lung ischemia-reperfusion injury

BACKGROUND

Post-lung transplantation (LTx) injury can involve sterile inflammation due to ischemia-reperfusion injury (IRI). We investigated the cell-specific role of ferroptosis (excessive iron-mediated cell death) in mediating lung IRI and determined if specialized pro-resolving mediators such as Lipoxin A4 (LxA 4 ) can protect against ferroptosis in lung IRI.

METHODS

Single-cell RNA sequencing of lung tissue from post-LTx patients was analyzed. Lung IRI was evaluated in C57BL/6 (WT), formyl peptide receptor 2 knockout ( Fpr2 -/- ) and nuclear factor erythroid 2-related factor 2 knockout ( Nrf2 -/- ) mice using a hilar-ligation model with or without LxA 4 administration. Furthermore, the protective efficacy of LxA 4 was evaluated employing a murine orthotopic LTx model and in vitro studies using alveolar type II epithelial (ATII) cells.

RESULTS

Differential expression of ferroptosis-related genes was observed in post-LTx patient samples compared to healthy controls. A significant increase in the levels of oxidized lipids and reduction in the levels of intact lipids were observed in mice subjected to IRI compared to shams. Furthermore, pharmacological inhibition of ferroptosis with liproxstatin-1 mitigated lung IRI and lung dysfunction. Importantly, LxA 4 treatment attenuated pulmonary dysfunction, ferroptosis and inflammation in WT mice subjected to lung IRI, but not in Fpr2 -/- or Nrf2 -/- mice, after IRI. In the murine LTx model, LxA 4 treatment increased PaO 2 levels and attenuated lung IRI. Mechanistically, LxA 4 -mediated protection involves increase in NRF2 activation and glutathione concentration as well as decrease in MDA levels in ATII cells.

CONCLUSIONS

LxA 4 /FPR2 signaling on ATII cells mitigates ferroptosis via NRF2 activation and protects against lung IRI.

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.

Association of Tryptophan: Kynurenine Metabolites with Healing in Chronic Venous Leg Ulcers

OBJECTIVE

Chronic wound healing is a complex process that is still not well understood. The tryptophan (TRP)-L-Kynurenine (KYN) pathway has recently been under increased scrutiny in regards to wound healing. The study applied metabolomics to elucidate the TRP-L- KYN pathway associated with wound healing in chronic venous leg ulcers (CVLUs).

APPROACH

This study used a longitudinal comparative design of 60 serum samples collected from 30 older adult patients with CVLUs, receiving weekly sharp debridement at a wound clinic. The serum samples were collected at baseline and week 4 (healed wounds) or week 8 (non-healed wounds). Liquid chromatography-mass spectrometry (LC-MS) metabolomics was used to analyze targeted metabolites. A Bayesian approach was employed to examine robust correlations between changes in metabolite values and linear healing slope and to compare by group.

RESULTS

The mean age was 71.13 (±9.46). Half of the sample were female and the minority (17%) were Black. The mean values of evaluated metabolites for the non-healed group were consistently lower than those for the healed group. The healed group (n=12) had higher KYN values; Those on a healing trajectory (n=23) had lower KYN levels and higher TRP levels at baseline and over time. There was moderate support (Bayes Factor = 3.70) for a negative association between change in Kynurenic Acid and linear healing slope (r = -0.35, CrI = -0.62, -0.04, PD= 98%). Results suggest KYN and TRP may be markers for healing in individuals with CVLUs.

INNOVATION AND CONCLUSION

Gaining a better understanding of the associations between the TRP-L- KYN pathway and the healing of CVLUs may help to clarify the links of inflammation with the rate and success of wound healing. Biomarker development focused on the TRP-L- KYN pathway could be pursued, if the associations are further supported by focused research studies.

Liberation of host heme by Clostridioides difficile-mediated damage enhances Enterococcus faecalis fitness during infection

IMPORTANCE

Clostridioides difficile and Enterococcus faecalis are two pathogens of great public health importance. Both bacteria colonize the human gastrointestinal tract where they are known to interact in ways that worsen disease outcomes. We show that the damage associated with C. difficile infection (CDI) releases nutrients that benefit E. faecalis. One particular nutrient, heme, allows E. faecalis to use oxygen to generate energy and grow better in the gut. Understanding the mechanisms of these interspecies interactions could inform therapeutic strategies for CDI.

Identification of Novel and Early Biomarkers for Cisplatin-induced Nephrotoxicity and the Nephroprotective Role of Cimetidine using a Pharmacometabolomic-based Approach Coupled with In Vitro Toxicodynamic Modeling and Simulation

Cisplatin is widely used for the treatment of various types of cancer. However, cisplatin-induced nephrotoxicity (CIN) is frequently observed in patients receiving cisplatin therapy which poses a challenge in its clinical utility. Currently used clinical biomarkers for CIN are not adequate for early detection of nephrotoxicity, hence there is a need to identify potential early biomarkers in predicting CIN. In the current study, a combination of in vitro toxicodynamic (TD) modeling and untargeted global metabolomics approach was used to identify novel potential metabolite biomarkers for early detection of CIN. In addition, we investigated the protective role of cimetidine (CIM), an inhibitor of the organic cation transporter 2 (OCT2), in suppressing CIN. We first characterized the time-course of nephrotoxic effects of cisplatin (CIS) and the protective effects of CIM in a human pseudo-immortalized renal proximal tubule epithelial cell line (RPTEC), SA7K cell line. Secondly, we used a mathematical cell-level, in vitro TD modeling approach to quantitatively characterize the time-course effects of CIS and CIM as single agents and combination in SA7K cells. Based on the experimental and modeling results, we selected relevant concentrations of CIS and CIM for our metabolomics study. With the help of PCA (Principal Component Analysis) and PLS-DA (Projection to Latent Structure - Discriminate Analysis) analyses, we confirmed global metabolome changes for different groups (CIS, CIM, CIS+CIM vs control) in SA7K cells. Based on the criterion of a p-value ≤ 0.05 and a fold change ≥ 2 or ≤ 0.5, we identified 20 top metabolites that were significantly changed during the early phase i.e. within first 12 h of CIS treatment. Finally, pathway analysis was conducted that revealed the key metabolic pathways that were most impacted in CIN.

Matrix Linear Models for connecting metabolite composition to individual characteristics

High-throughput metabolomics data provide a detailed molecular window into biological processes. We consider the problem of assessing how the association of metabolite levels with individual (sample) characteristics such as sex or treatment may depend on metabolite characteristics such as pathway. Typically this is one in a two-step process: In the first step we assess the association of each metabolite with individual characteristics. In the second step an enrichment analysis is performed by metabolite characteristics among significant associations. We combine the two steps using a bilinear model based on the matrix linear model (MLM) framework we have previously developed for high-throughput genetic screens. Our framework can estimate relationships in metabolites sharing known characteristics, whether categorical (such as type of lipid or pathway) or numerical (such as number of double bonds in triglycerides). We demonstrate how MLM offers flexibility and interpretability by applying our method to three metabolomic studies. We show that our approach can separate the contribution of the overlapping triglycerides characteristics, such as the number of double bonds and the number of carbon atoms. The proposed method have been implemented in the open-source Julia package, MatrixLM. Data analysis scripts with example data analyses are also available.

miRNA-211 maintains metabolic homeostasis in medulloblastoma through its target gene long-chain acyl-CoA synthetase 4

The prognosis of childhood medulloblastoma (MB) is often poor, and it usually requires aggressive therapy that adversely affects quality of life. microRNA-211 (miR-211) was previously identified as an important regulator of cells that descend from neural cells. Since medulloblastomas primarily affect cells with similar ontogeny, we investigated the role and mechanism of miR-211 in MB. Here we showed that miR-211 expression was highly downregulated in cell lines, PDXs, and clinical samples of different MB subgroups (SHH, Group 3, and Group 4) compared to normal cerebellum. miR-211 gene was ectopically expressed in transgenic cells from MB subgroups, and they were subjected to molecular and phenotypic investigations. Monoclonal cells stably expressing miR-211 were injected into the mouse cerebellum. miR-211 forced expression acts as a tumor suppressor in MB both in vitro and in vivo, attenuating growth, promoting apoptosis, and inhibiting invasion. In support of emerging regulatory roles of metabolism in various forms of cancer, we identified the acyl-CoA synthetase long-chain family member (ACSL4) as a direct miR-211 target. Furthermore, lipid nanoparticle-coated, dendrimer-coated, and cerium oxide-coated miR-211 nanoparticles were applied to deliver synthetic miR-211 into MB cell lines and cellular responses were assayed. Synthesizing nanoparticle-miR-211 conjugates can suppress MB cell viability and invasion in vitro. Our findings reveal miR-211 as a tumor suppressor and a potential therapeutic agent in MB. This proof-of-concept paves the way for further pre-clinical and clinical development.

Effect of statin treatment on metabolites, lipids and prostanoids in patients with Statin Associated Muscle Symptoms (SAMS)

BACKGROUND

Between 5-10% of patients discontinue statin therapy due to statin-associated adverse reactions, primarily statin associated muscle symptoms (SAMS). The absence of a clear clinical phenotype or of biomarkers poses a challenge for diagnosis and management of SAMS. Similarly, our incomplete understanding of the pathogenesis of SAMS hinders the identification of treatments for SAMS. Metabolomics, the profiling of metabolites in biofluids, cells and tissues is an important tool for biomarker discovery and provides important insight into the origins of symptomatology. In order to better understand the pathophysiology of this common disorder and to identify biomarkers, we undertook comprehensive metabolomic and lipidomic profiling of plasma samples from patients with SAMS who were undergoing statin rechallenge as part of their clinical care.

METHODS AND FINDINGS

We report our findings in 67 patients, 28 with SAMS (cases) and 39 statin-tolerant controls. SAMS patients were studied during statin rechallenge and statin tolerant controls were studied while on statin. Plasma samples were analyzed using untargeted LC-MS metabolomics and lipidomics to detect differences between cases and controls. Differences in lipid species in plasma were observed between cases and controls. These included higher levels of linoleic acid containing phospholipids and lower ether lipids and sphingolipids. Reduced levels of acylcarnitines and altered amino acid profile (tryptophan, tyrosine, proline, arginine, and taurine) were observed in cases relative to controls. Pathway analysis identified significant increase of urea cycle metabolites and arginine and proline metabolites among cases along with downregulation of pathways mediating oxidation of branched chain fatty acids, carnitine synthesis, and transfer of acetyl groups into mitochondria.

CONCLUSIONS

The plasma metabolome of patients with SAMS exhibited reduced content of long chain fatty acids and increased levels of linoleic acid (18:2) in phospholipids, altered energy production pathways (β-oxidation, citric acid cycle and urea cycles) as well as reduced levels of carnitine, an essential mediator of mitochondrial energy production. Our findings support the hypothesis that alterations in pro-inflammatory lipids (arachidonic acid pathway) and impaired mitochondrial energy metabolism underlie the muscle symptoms of patients with statin associated muscle symptoms (SAMS).

An Automated Workflow Composition System for Liquid Chromatography-Mass Spectrometry Metabolomics Data Processing

Liquid chromatography-mass spectrometry (LC-MS) metabolomics studies produce high-dimensional data that must be processed by a complex network of informatics tools to generate analysis-ready data sets. As the first computational step in metabolomics, data processing is increasingly becoming a challenge for researchers to develop customized computational workflows that are applicable for LC-MS metabolomics analysis. Ontology-based automated workflow composition (AWC) systems provide a feasible approach for developing computational workflows that consume high-dimensional molecular data. We used the Automated Pipeline Explorer (APE) to create an AWC for LC-MS metabolomics data processing across three use cases. Our results show that APE predicted 145 data processing workflows across all the three use cases. We identified six traditional workflows and six novel workflows. Through manual review, we found that one-third of novel workflows were executable whereby the data processing function could be completed without obtaining an error. When selecting the top six workflows from each use case, the computational viable rate of our predicted workflows reached 45%. Collectively, our study demonstrates the feasibility of developing an AWC system for LC-MS metabolomics data processing.

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.

Expanding Per- and Polyfluoroalkyl Substances Coverage in Nontargeted Analysis Using Data-Independent Analysis and IonDecon

Per- and polyfluoroalkyl substances (PFAS) are widespread, persistent environmental contaminants that have been linked to various health issues. Comprehensive PFAS analysis often relies on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC HRMS) and molecular fragmentation (MS/MS). However, the selection and fragmentation of ions for MS/MS analysis using data-dependent analysis results in only the topmost abundant ions being selected. To overcome these limitations, All Ions fragmentation (AIF) can be used alongside data-dependent analysis. In AIF, ions across the entire m/z range are simultaneously fragmented; hence, precursor-fragment relationships are lost, leading to a high false positive rate. We introduce IonDecon, which filters All Ions data to only those fragments correlating with precursor ions. This software can be used to deconvolute any All Ions files and generates an open source DDA formatted file, which can be used in any downstream nontargeted analysis workflow. In a neat solution, annotation of PFAS standards using IonDecon and All Ions had the exact same false positive rate as when using DDA; this suggests accurate annotation using All Ions and IonDecon. Furthermore, deconvoluted All Ions spectra retained the most abundant peaks also observed in DDA, while filtering out much of the artifact peaks. In complex samples, incorporating AIF and IonDecon into workflows can enhance the MS/MS coverage of PFAS (more than tripling the number of annotations in domestic sewage). Deconvolution in complex samples of All Ions data using IonDecon did retain some false fragments (fragments not observed when using ion selection, which were not isotopes or multimers), and therefore DDA and intelligent acquisition methods should still be acquired when possible alongside All Ions to decrease the false positive rate. Increased coverage of PFAS can inform on the development of regulations to address the entire PFAS problem, including both legacy and newly discovered PFAS.

Niclosamide as a chemical probe for analyzing SARS-CoV-2 modulation of host cell lipid metabolism

Introduction

SARS-CoV-2 subverts host cell processes to facilitate rapid replication and dissemination, and this leads to pathological inflammation.

Methods

We used niclosamide (NIC), a poorly soluble anti-helminth drug identified initially for repurposed treatment of COVID-19, which activates the cells' autophagic and lipophagic processes as a chemical probe to determine if it can modulate the host cell's total lipid profile that would otherwise be either amplified or reduced during SARS-CoV-2 infection.

Results

Through parallel lipidomic and transcriptomic analyses we observed massive reorganization of lipid profiles of SARS-CoV-2 infected Vero E6 cells, especially with triglycerides, which were elevated early during virus replication, but decreased thereafter, as well as plasmalogens, which were elevated at later timepoints during virus replication, but were also elevated under normal cell growth. These findings suggested a complex interplay of lipid profile reorganization involving plasmalogen metabolism. We also observed that NIC treatment of both low and high viral loads does not affect virus entry. Instead, NIC treatment reduced the abundance of plasmalogens, diacylglycerides, and ceramides, which we found elevated during virus infection in the absence of NIC, resulting in a significant reduction in the production of infectious virions. Unexpectedly, at higher viral loads, NIC treatment also resulted in elevated triglyceride levels, and induced significant changes in phospholipid metabolism.

Discussion

We posit that future screens of approved or new partner drugs should prioritize compounds that effectively counter SARS-CoV-2 subversion of lipid metabolism, thereby reducing virus replication, egress, and the subsequent regulation of key lipid mediators of pathological inflammation.

Metabolomic and Lipidomic Characterization of Meningioma Grades Using LC-HRMS and Machine Learning

Meningiomas are among the most common brain tumors that arise from the leptomeningeal cover of the brain and spinal cord and account for around 37% of all central nervous system tumors. According to the World Health Organization, meningiomas are classified into three histological subtypes: benign, atypical, and anaplastic. Sometimes, meningiomas with a histological diagnosis of benign tumors show clinical characteristics and behavior of aggressive tumors. In this study, we examined the metabolomic and lipidomic profiles of meningioma tumors, focusing on comparing low-grade and high-grade tumors and identifying potential markers that can discriminate between benign and malignant tumors. High-resolution mass spectrometry coupled to liquid chromatography was used for untargeted metabolomics and lipidomics analyses of 85 tumor biopsy samples with different meningioma grades. We then applied feature selection and machine learning techniques to find the features with the highest information to aid in the diagnosis of meningioma grades. Three biomarkers were identified to differentiate low- and high-grade meningioma brain tumors. The use of mass-spectrometry-based metabolomics and lipidomics combined with machine learning analyses to prospect and characterize biomarkers associated with meningioma grades may pave the way for elucidating potential therapeutic and prognostic targets.

Quantitation of phenylalanine and tyrosine from dried Blood/Plasma spots with impregnated stable isotope internal standards (SIIS) by FIA-SRM

BACKGROUND

Dried Blood Spot (DBS) analysis has been used for identification and quantification of diseases and disorders in large populations. Simply collecting blood or plasma samples on cotton paper, followed with an organic solvent extraction, many small molecules can be detected and quantified. In a typical procedure of DBS analysis in newborn screening, stable isotope internal standards (SIIS) are added to extraction solvent as a reference. However, this way of employing SIIS does not reflect extraction efficiency, or protein binding issues, nor does it reflect potential degradation that could occur. In addition, punched-out discs from larger DBS are known to have imprecision typically ≥ 15%.

METHODS

We developed and tested an approach, internal quantitative DBS (iqDBS), which delivers an exact volume of whole blood or plasma to a paper disc that is impregnated with a dried concentration of SIIS for quantitation. Amino acids were derivatized to make butyl esters and measured using Flow Injection Analysis with Selected Reaction Monitoring (FIA-SRM).

RESULTS

We demonstrated with phenylalanine and tyrosine improved sensitivity and accuracy by applying iqDBS.

CONCLUSIONS

We established a new method for quantitative analysis of small molecules from dried blood spots that incorporates stable isotope internal standard at the time of blood collection.

Untargeted Metabolomic Analysis of Lactation-Stage-Matched Human and Bovine Milk Samples at 2 Weeks Postnatal

Epidemiological data demonstrate that bovine whole milk is often substituted for human milk during the first 12 months of life and may be associated with adverse infant outcomes. The objective of this study is to interrogate the human and bovine milk metabolome at 2 weeks of life to identify unique metabolites that may impact infant health outcomes. Human milk (n = 10) was collected at 2 weeks postpartum from normal-weight mothers (pre-pregnant BMI < 25 kg/m2) that vaginally delivered term infants and were exclusively breastfeeding their infant for at least 2 months. Similarly, bovine milk (n = 10) was collected 2 weeks postpartum from normal-weight primiparous Holstein dairy cows. Untargeted data were acquired on all milk samples using high-resolution liquid chromatography-high-resolution tandem mass spectrometry (HR LC-MS/MS). MS data pre-processing from feature calling to metabolite annotation was performed using MS-DIAL and MS-FLO. Our results revealed that more than 80% of the milk metabolome is shared between human and bovine milk samples during early lactation. Unbiased analysis of identified metabolites revealed that nearly 80% of milk metabolites may contribute to microbial metabolism and microbe-host interactions. Collectively, these results highlight untargeted metabolomics as a potential strategy to identify unique and shared metabolites in bovine and human milk that may relate to and impact infant health outcomes.

Pharmacologic inhibition of glycolysis prevents the development of lupus by altering the gut microbiome in mice

Gut dysbiosis has been associated with lupus pathogenesis, and fecal microbiota transfers (FMT) from lupus-prone mice shown to induce autoimmune activation into healthy mice. The immune cells of lupus patients exhibit an increased glucose metabolism and treatments with 2-deoxy-D-glucose (2DG), a glycolysis inhibitor, are therapeutic in lupus-prone mice. Here, we showed in two models of lupus with different etiologies that 2DG altered the composition of the fecal microbiome and associated metabolites. In both models, FMT from 2DG-treated mice protected lupus-prone mice of the same strain from the development of glomerulonephritis, reduced autoantibody production as well as the activation of CD4+ T cells and myeloid cells as compared to FMT from control mice. Thus, we demonstrated that the protective effect of glucose inhibition in lupus is transferable through the gut microbiota, directly linking alterations in immunometabolism to gut dysbiosis in the hosts.

Sex differences in specialized pro-resolving lipid mediators and their receptors in abdominal aortic aneurysms

Objective

In this study, we tested the hypothesis that endogenous expression of specialized pro-resolving lipid mediators (SPMs) that facilitate the resolution of inflammation, specifically Resolvin D1and -D2, as well as Maresin1 (MaR1), can impact abdominal aortic aneurysm (AAA) formation and progression in a sex-specific manner.

Methods

SPM expression was quantified in aortic tissue from human AAA samples and from a murine in vivo AAA model via liquid chromatography-tandem mass spectrometry. mRNA expression for SPM receptors FPR2, LGR6, and GPR18 were quantified by real-time polymerase chain reaction. A Student t test with nonparametric Mann-Whitney or Wilcoxon test was used for pair-wise comparisons of groups. One-way analysis of variance after post hoc Tukey test was used to determine the differences among multiple comparative groups.

Results

Human aortic tissue analysis revealed a significant decrease in RvD1 levels in male AAAs compared with controls, whereas FPR2 and LGR6 receptor expressions were downregulated in male AAAs compared with male controls. In vivo studies of elastase-treated mice showed higher levels of RvD2 and MaR1 as well as the SPM precursors, omega-3 fatty acids DHA and EPA, in aortic tissue from males compared with females. FPR2 expression was increased in elastase-treated females compared with males.

Conclusions

Our findings demonstrate that specific differences in SPMs and their associated G-protein coupled receptors exist between sexes. These results indicate the relevance of SPM-mediated signaling pathways in sex differences impacting the pathogenesis of AAAs.

DAXX drives de novo lipogenesis and contributes to tumorigenesis

Cancer cells exhibit elevated lipid synthesis. In breast and other cancer types, genes involved in lipid production are highly upregulated, but the mechanisms that control their expression remain poorly understood. Using integrated transcriptomic, lipidomic, and molecular studies, here we report that DAXX is a regulator of oncogenic lipogenesis. DAXX depletion attenuates, while its overexpression enhances, lipogenic gene expression, lipogenesis, and tumor growth. Mechanistically, DAXX interacts with SREBP1 and SREBP2 and activates SREBP-mediated transcription. DAXX associates with lipogenic gene promoters through SREBPs. Underscoring the critical roles for the DAXX-SREBP interaction for lipogenesis, SREBP2 knockdown attenuates tumor growth in cells with DAXX overexpression, and DAXX mutants unable to bind SREBP1/2 have weakened activity in promoting lipogenesis and tumor growth. Remarkably, a DAXX mutant deficient of SUMO-binding fails to activate SREBP1/2 and lipogenesis due to impaired SREBP binding and chromatin recruitment and is defective of stimulating tumorigenesis. Hence, DAXX's SUMO-binding activity is critical to oncogenic lipogenesis. Notably, a peptide corresponding to DAXX's C-terminal SUMO-interacting motif (SIM2) is cell-membrane permeable, disrupts the DAXX-SREBP1/2 interactions, and inhibits lipogenesis and tumor growth. These results establish DAXX as a regulator of lipogenesis and a potential therapeutic target for cancer therapy.

Small molecule biomarker discovery: Proposed workflow for LC-MS-based clinical research projects

Mass spectrometry focusing on small endogenous molecules has become an integral part of biomarker discovery in the pursuit of an in-depth understanding of the pathophysiology of various diseases, ultimately enabling the application of personalized medicine. While LC-MS methods allow researchers to gather vast amounts of data from hundreds or thousands of samples, the successful execution of a study as part of clinical research also requires knowledge transfer with clinicians, involvement of data scientists, and interactions with various stakeholders. The initial planning phase of a clinical research project involves specifying the scope and design, and engaging relevant experts from different fields. Enrolling subjects and designing trials rely largely on the overall objective of the study and epidemiological considerations, while proper pre-analytical sample handling has immediate implications on the quality of analytical data. Subsequent LC-MS measurements may be conducted in a targeted, semi-targeted, or non-targeted manner, resulting in datasets of varying size and accuracy. Data processing further enhances the quality of data and is a prerequisite for in-silico analysis. Nowadays, the evaluation of such complex datasets relies on a mix of classical statistics and machine learning applications, in combination with other tools, such as pathway analysis and gene set enrichment. Finally, results must be validated before biomarkers can be used as prognostic or diagnostic decision-making tools. Throughout the study, quality control measures should be employed to enhance the reliability of data and increase confidence in the results. The aim of this graphical review is to provide an overview of the steps to be taken when conducting an LC-MS-based clinical research project to search for small molecule biomarkers.

Metabolomics in paraganglioma: applications and perspectives from genetics to therapy

Metabolites represent the highest layer of biological information. Their diverse chemical nature enables networks of chemical reactions that are critical for maintaining life by providing energy and building blocks. Quantification by targeted and untargeted analytical methods using either mass spectrometry or nuclear magnetic resonance spectroscopy has been applied to pheochromocytoma/paraganglioma (PPGL) with the long-term goal to improve diagnosis and therapy. PPGLs have unique features that provide useful biomarkers and clues for targeted treatments. Firstly, high production rates of catecholamines and metanephrines allow for specific and sensitive detection of the disease in plasma or urine. Secondly, PPGLs are associated with heritable pathogenic variants (PV) in around 40% of cases, many of which occur in genes encoding enzymes, such as succinate dehydrogenase (SDH) and fumarate hydratase (FH). These genetic aberrations lead to overproduction of oncometabolites succinate or fumarate, respectively, and are detectable in tumors and blood. Such metabolic dysregulation can be exploited diagnostically, with the aim to ensure appropriate interpretation of gene variants, especially those with unknown significance, and facilitate early tumor detection through regular patient follow-up. Furthermore, SDHx and FH PV alter cellular pathways, including DNA hypermethylation, hypoxia signaling, redox homeostasis, DNA repair, calcium signaling, kinase cascades, and central carbon metabolism. Pharmacological interventions targeted towards such features have the potential to uncover treatments against metastatic PPGL, around 50% of which are associated with germline PV in SDHx. With the availability of omics technologies for all layers of biological information personalized diagnostics and treatment is in close reach.

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.

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.

Identification of food and nutrient components as predictors of Lactobacillus colonization

A previous double-blind, randomized clinical trial of 42 healthy individuals conducted with Lactobacillus johnsonii N6.2 found that the probiotic's mechanistic tryptophan pathway was significantly modified when the data was stratified based on the individuals' lactic acid bacteria (LAB) stool content. These results suggest that confounding factors such as dietary intake which impact stool LAB content may affect the response to the probiotic treatment. Using dietary intake, serum metabolite, and stool LAB colony forming unit (CFU) data from a previous clinical trial, the relationships between diet, metabolic response, and fecal LAB were assessed. The diets of subject groups with high vs. low CFUs of LAB/g of wet stool differed in their intakes of monounsaturated fatty acids, vegetables, proteins, and dairy. Individuals with high LAB consumed greater amounts of cheese, fermented meats, soy, nuts and seeds, alcoholic beverages, and oils whereas individuals with low LAB consumed higher amounts of tomatoes, starchy vegetables, and poultry. Several dietary variables correlated with LAB counts; positive correlations were determined for nuts and seeds, fish high in N-3 fatty acids, soy, and processed meats, and negative correlations to consumption of vegetables including tomatoes. Using machine learning, predictors of LAB count included cheese, nuts and seeds, fish high in N-3 fatty acids, and erucic acid. Erucic acid alone accurately predicted LAB categorization, and was shown to be utilized as a sole fatty acid source by several Lactobacillus species regardless of their mode of fermentation. Several metabolites were significantly upregulated in each group based on LAB titers, notably polypropylene glycol, caproic acid, pyrazine, and chondroitin sulfate; however, none were correlated with the dietary intake variables. These findings suggest that dietary variables may drive the presence of LAB in the human gastrointestinal tract and potentially impact response to probiotic interventions.

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-1β (IL-1β) and causes behavioral hypersensitivity. I.th. injection of a IL-1β receptor antagonist blocks SEW2871-induced hypersensitivity, suggesting that IL-1β contributes to S1PR1's actions. Interestingly, previous studies have suggested that IL-1β 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-1β, which in turn activates ADK and leads to mechano-allodynia, then blocking ADK should attenuate IL-1β effects. In support of this idea, recombinant rat (rrIL-1β)-induced allodynia was blocked by at least 90% with ABT702, functionally linking ADK to IL-1β. Moreover, the selective A3AR antagonist, MRS1523, prevents the ability of ABT702 to block SEW2871 and IL-1β-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-β and ADK activation.

Thymidylate synthase accelerates Men1-mediated pancreatic tumor progression and reduces survival

Clinical studies of cancer patients have shown that overexpression or amplification of thymidylate synthase (TS) correlates with a worse clinical outcome. We previously showed that elevated TS exhibits properties of an oncogene and promotes pancreatic neuroendocrine tumors (PanNETs) with a long latency. To study the causal impact of elevated TS levels in PanNETs, we generated a mouse model with elevated human TS (hTS) and conditional inactivation of the Men1 gene in pancreatic islet cells (hTS/Men1^–/–). We demonstrated that increased hTS expression was associated with earlier tumor onset and accelerated PanNET development in comparison with control Men1^–/– and Men1^+/ΔN3-8 mice. We also observed a decrease in overall survival of hTS/Men1^+/– and hTS/Men1^–/– mice as compared with control mice. We showed that elevated hTS in Men1-deleted tumor cells enhanced cell proliferation, deregulated cell cycle kinetics, and was associated with a higher frequency of somatic mutations, DNA damage, and genomic instability. In addition, we analyzed the survival of 88 patients with PanNETs and observed that high TS protein expression independently predicted worse clinical outcomes. In summary, elevated hTS directly participates in promoting PanNET tumorigenesis with reduced survival in Men1-mutant background. This work will refocus attention on new strategies to inhibit TS activity for PanNET treatment.

Sensitization of FOLFOX-resistant colorectal cancer cells via the modulation of a novel pathway involving protein phosphatase 2A

The treatment of colorectal cancer (CRC) with FOLFOX shows some efficacy, but these tumors quickly develop resistance to this treatment. We have observed increased phosphorylation of AKT1/mTOR/4EBP1 and levels of p21 in FOLFOX-resistant CRC cells. We have identified a small molecule, NSC49L, that stimulates protein phosphatase 2A (PP2A) activity, downregulates the AKT1/mTOR/4EBP1-axis, and inhibits p21 translation. We have provided evidence that NSC49L- and TRAIL-mediated sensitization is synergistically induced in p21-knockdown CRC cells, which is reversed in p21-overexpressing cells. p21 binds with procaspase 3 and prevents the activation of caspase 3. We have shown that TRAIL induces apoptosis through the activation of caspase 3 by NSC49L-mediated downregulation of p21 translation, and thereby cleavage of procaspase 3 into caspase 3. NSC49L does not affect global protein synthesis. These studies provide a mechanistic understanding of NSC49L as a PP2A agonist, and how its combination with TRAIL sensitizes FOLFOX-resistant CRC cells.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02091-w.

Lipogenesis mediated by OGR1 regulates metabolic adaptation to acid stress in cancer cells via autophagy

Malignant tumors exhibit altered metabolism resulting in a highly acidic extracellular microenvironment. Here, we show that cytoplasmic lipid droplet (LD) accumulation, indicative of a lipogenic phenotype, is a cellular adaption to extracellular acidity. LD marker PLIN2 is strongly associated with poor overall survival in breast cancer patients. Acid-induced LD accumulation is triggered by activation of the acid-sensing G-protein-coupled receptor (GPCR) OGR1, which is expressed highly in breast tumors. OGR1 depletion inhibits acid-induced lipid accumulation, while activation by a synthetic agonist triggers LD formation. Inhibition of OGR1 downstream signaling abrogates the lipogenic phenotype, which can be rescued with OGR1 ectopic expression. OGR1-depleted cells show growth inhibition under acidic growth conditions in vitro and tumor formation in vivo. Isotope tracing shows that the source of lipid precursors is primarily autophagy-derived ketogenic amino acids. OGR1-depleted cells are defective in endoplasmic reticulum stress response and autophagy and hence fail to accumulate LDs affecting survival under acidic stress.

The gut microbiota transfers the therapeutic effect of inhibiting glucose metabolism in lupus-prone mice

Systemic lupus erythematosus (SLE) is an autoimmune disease in which autoantibodies induce tissue damage including the kidney. Gut microbial dysbiosis contributes to SLE pathogenesis. An abnormal metabolism is a characteristic feature of SLE in which the inflammatory functions of CD4+ T cells rely on glycolysis. We have shown that treatment with 2-deoxy-D-glucose (2DG), a glycolysis inhibitor, reduced the expansion of germinal centers and eliminated the production of autoantibodies, ameliorating disease in lupus-prone mice, including (NZB × NZW)F1 and (NZW x BXSB)F1. Here we show that the 2DG treatment also maintained gut bacterial diversity, reduced the changes in bacterial populations that occurred as disease developed in these mice, and that it altered the distribution of fecal metabolites. We investigated the effect of fecal microbiota transplantation (FMT) from 2DG-treated or control mice into pre-autoimmune lupus-prone mice of the same strain. In both strains, FMT from 2DG-treated mice was highly protective, with a reduction or elimination of anti-dsDNA IgG production, immune cell activation, and renal pathology compared to FMT from control mice. Overall, our results demonstrated for the first time that the therapeutic effect of glucose inhibition in lupus is transferable through the gut microbiota. This implicates either a direct effect of glucose on pathogenic gut bacteria, or an indirect effect through the immune system normalized by glucose inhibition.

Supported b R01 AI143313

Green Chemistry Preservation and Extraction of Biospecimens for Multi-omic Analyses

The Environmental Protection Agency's definition of "Green Chemistry" is "the design of chemical products and processes that reduces or eliminates the use or generation of hazardous substances. Green chemistry applies across the life cycle of a chemical product, including its design, manufacture, use, and ultimate disposal." Conventional omic tissue extraction procedures use solvents that are toxic and carcinogenic, such as chloroform and methyl-tert-butyl ether for lipidomics, or caustic chaotropic solutions for genomics and transcriptomics, such as guanidine or urea. A common preservation solution for pathology is formaldehyde, which is a carcinogen. Use of acetonitrile as a universal biospecimen preservation and extraction solvent will reduce these hazardous wastes, because it is less toxic and more environmentally friendly than the conventional solvents used in biorepository and biospecimen research. A new extraction method never applied to multi-omic, system biology research, called cold-induced phase separation (CIPS), uses freezing point temperatures to induce a phase separation of acetonitrile-water mixtures. Also, the CO₂ exposure during CIPS will acidify the water precipitating DNA out of aqueous phase. The resulting phase separation brings hydrophobic lipids to the top acetonitrile fraction that is easily decanted from the bottom aqueous fraction, especially when the water is frozen. This CIPS acetonitrile extract contains the lipidome (lipids), the bottom aqueous fraction is sampled to obtain the transcriptome (RNA) fraction, and the remaining water and pellet is extracted with 60% acetonitrile to isolate the metabolome (<1 kD polar molecules). Finally, steps 4 and 5 use a TRIzol™ liquid-liquid extraction SOP of the pellet to isolate the genome (DNA) and proteome (proteins). This chapter details the multi-omic sequential extraction SOP and potential problems associated with each of the 5 steps, with steps 2, 4, and 5 still requiring validation. The metabolomic and lipidomic extraction efficiencies using the CIPS SOP is compared to conventional solvent extraction SOPs and is analyzed by nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS), respectively. Acetonitrile biospecimen preservation combined with the CIPS multi-omic extraction SOP is green chemistry technology that will eliminate the generation of the hazardous substances associated with biospecimen processing and permits separation and safe disposal of acetonitrile avoiding environmental contamination.

Lipidomics and Redox Lipidomics Indicate Early Stage Alcohol-Induced Liver Damage

Alcoholic fatty liver disease (AFLD) is characterized by lipid accumulation and inflammation and can progress to cirrhosis and cancer in the liver. AFLD diagnosis currently relies on histological analysis of liver biopsies. Early detection permits interventions that would prevent progression to cirrhosis or later stages of the disease. Herein, we have conducted the first comprehensive time-course study of lipids using novel state-of-the art lipidomics methods in plasma and liver in the early stages of a mouse model of AFLD, i.e., Lieber-DeCarli diet model. In ethanol-treated mice, changes in liver tissue included up-regulation of triglycerides (TGs) and oxidized TGs and down-regulation of phosphatidylcholine, lysophosphatidylcholine, and 20-22-carbon-containing lipid-mediator precursors. An increase in oxidized TGs preceded histological signs of early AFLD, i.e., steatosis, with these changes observed in both the liver and plasma. The major lipid classes dysregulated by ethanol play important roles in hepatic inflammation, steatosis, and oxidative damage. Conclusion: Alcohol consumption alters the liver lipidome before overt histological markers of early AFLD. This introduces the exciting possibility that specific lipids may serve as earlier biomarkers of AFLD than those currently being used.

A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research

Clinical metabolomics emerged as a novel approach for biomarker discovery with the translational potential to guide next-generation therapeutics and precision health interventions. However, reproducibility in clinical research employing metabolomics data is challenging. Checklists are a helpful tool for promoting reproducible research. Existing checklists that promote reproducible metabolomics research primarily focused on metadata and may not be sufficient to ensure reproducible metabolomics data processing. This paper provides a checklist including actions that need to be taken by researchers to make computational steps reproducible for clinical metabolomics studies. We developed an eight-item checklist that includes criteria related to reusable data sharing and reproducible computational workflow development. We also provided recommended tools and resources to complete each item, as well as a GitHub project template to guide the process. The checklist is concise and easy to follow. Studies that follow this checklist and use recommended resources may facilitate other researchers to reproduce metabolomics results easily and efficiently.

Metabolomics Insights into Chemical Convergence in Xanthomonas perforans and Metabolic Changes Following Treatment with the Small Molecule Carvacrol

Microbes are natural chemical factories and their metabolome comprise diverse arrays of chemicals. The genus Xanthomonas comprises some of the most important plant pathogens causing devastating yield losses globally and previous studies suggested that species in the genus are untapped chemical minefields. In this study, we applied an untargeted metabolomics approach to study the metabolome of a globally spread important xanthomonad, X. perforans. The pathogen is difficult to manage, but recent studies suggest that the small molecule carvacrol was efficient in disease control. Bacterial strains were treated with carvacrol, and samples were taken at time intervals (1 and 6 h). An untreated control was also included. There were five replicates for each sample and samples were prepared for metabolomics profiling using the standard procedure. Metabolomics profiling was carried out using a thermo Q-Exactive orbitrap mass spectrometer with Dionex ultra high-performance liquid chromatography (UHPLC) and an autosampler. Annotation of significant metabolites using the Metabolomics Standards Initiative level 2 identified an array of novel metabolites that were previously not reported in Xanthomonas perforans. These metabolites include methoxybrassinin and cyclobrassinone, which are known metabolites of brassicas; sarmentosin, a metabolite of the Passiflora-heliconiine butterfly system; and monatin, a naturally occurring sweetener found in Sclerochiton ilicifolius. To our knowledge, this is the first report of these metabolites in a microbial system. Other significant metabolites previously identified in non-Xanthomonas systems but reported in this study include maculosin; piperidine; β-carboline alkaloids, such as harman and derivatives; and several important medically relevant metabolites, such as valsartan, metharbital, pirbuterol, and ozagrel. This finding is consistent with convergent evolution found in reported biological systems. Analyses of the effect of carvacrol in time-series and associated pathways suggest that carvacrol has a global effect on the metabolome of X. perforans, showing marked changes in metabolites that are critical in energy biosynthesis and degradation pathways, amino acid pathways, nucleic acid pathways, as well as the newly identified metabolites whose pathways are unknown. This study provides the first insight into the X. perforans metabolome and additionally lays a metabolomics-guided foundation for characterization of novel metabolites and pathways in xanthomonad systems.

Targeted metabolomic analysis identifies increased serum levels of GABA and branched chain amino acids in canine diabetes

INTRODUCTION

Dogs with naturally occurring diabetes mellitus represent a potential model for human type 1 diabetes, yet significant knowledge voids exist in terms of the pathogenic mechanisms underlying the canine disorder. Untargeted metabolomic studies from a limited number of diabetic dogs identified similarities to humans with the disease.

OBJECTIVE

To expand and validate earlier metabolomic studies, identify metabolites that differ consistently between diabetic and healthy dogs, and address whether certain metabolites might serve as disease biomarkers.

METHODS

Untargeted metabolomic analysis via liquid chromatography-mass spectrometry was performed on serum from diabetic (n = 15) and control (n = 15) dogs. Results were combined with those of our previously published studies using identical methods (12 diabetic and 12 control dogs) to identify metabolites consistently different between the groups in all 54 dogs. Thirty-two candidate biomarkers were quantified using targeted metabolomics. Biomarker concentrations were compared between the groups using multiple linear regression (corrected P < 0.0051 considered significant).

RESULTS

Untargeted metabolomics identified multiple persistent differences in serum metabolites in diabetic dogs compared with previous studies. Targeted metabolomics showed increases in gamma amino butyric acid, valine, leucine, isoleucine, citramalate, and 2-hydroxyisobutyric acid in diabetic versus control dogs while indoxyl sulfate, N-acetyl-L-aspartic acid, kynurenine, anthranilic acid, tyrosine, glutamine, and tauroursodeoxycholic acid were decreased.

CONCLUSION

Several of these findings parallel metabolomic studies in both human diabetes and other animal models of this disease. Given recent studies on the role of GABA and branched chain amino acids in human diabetes, the increase in serum concentrations in canine diabetes warrants further study of these metabolites as potential biomarkers, and to identify similarity in mechanisms underlying this disease in humans and dogs.

Lactobacillus johnsonii N6.2 and Blueberry Phytophenols Affect Lipidome and Gut Microbiota Composition of Rats Under High-Fat Diet

Obesity is considered a primary contributing factor in the development of many diseases, including cancer, diabetes, and cardiovascular illnesses. Phytochemical-rich foods, associated to healthy gastrointestinal microbiota, have been shown to reduce obesity and associated comorbidities. In the present article, we describe the effects of the probiotic Lactobacillus johnsonii N6.2 and blueberry extracts (BB) on the gut microbiota and lipid profile of rats under a high-fat (HF) or low-calorie (LC) diet. L. johnsonii was found to increase the levels of long chain fatty acids (LCFA) in the serum of all animals under HF diet, while reduced LCFA concentrations were observed in the adipose tissue of animals under HF diet supplemented with BB extracts. All animals under HF diet also showed lower protein levels of SREBP1 and SCAP when treated with L. johnsonii. The gut microbiota diversity, β-diversity was significantly changed by L. johnsonii in the presence of BB. A significant reduction in α-diversity was observed in the ileum of animals under HF diet supplemented with L. johnsonii and BB, while increased α-diversity was observed in the ilium of animals under LC diet supplemented with L. johnsonii or BB. In summary, L. johnsonii and BB supplementation induced significant changes in gut microbiota diversity and lipid metabolism. The phospholipids pool was the lipidome component directly affected by the interventions. The ileum and colon microbiota showed clear differences depending on the diet and the treatments examined.

LC-MS lipidomics of renal biopsies for the diagnosis of Fabry disease

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Fabry is an X-linked lysosomal storage disease with deficiency in α-galactosidase.

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This deficiency results in the accumulation of glycosphinogolipids.

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Diagnosis is often made by analysis of globotriaosylceramide in fluids and tissues.

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Fabry is often misdiagnosed in female patients due to residual enzyme activity.

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Lipidomics by LC-HRMS enables identification of new biomarkers in Fabry.

Introduction

Lipidomics analysis or lipid profiling is a system-based analysis of all lipids in a sample to provide a comprehensive understanding of lipids within a biological system. In the last few years, lipidomics has made it possible to better understand the metabolic processes associated with several rare disorders and proved to be a powerful tool for their clinical investigation. Fabry disease is a rare X-linked lysosomal storage disorder (LSD) caused by a deficiency in α-galactosidase A (α-GAL A). This deficiency results in the progressive accumulation of glycosphingolipids, mostly globotriaosylceramide (Gb₃), globotriaosylsphingosine (lyso-Gb₃), as well as galabiosylceramide (Ga₂) and their isoforms/analogs in the vascular endothelium, nerves, cardiomyocytes, renal glomerular podocytes, and biological fluids.

Objectives

The primary objective of this study was to evaluate lipidomic signatures in renal biopsies to help understand variations in Fabry disease markers that could be used in future diagnostic tests.

Methods

Lipidomic analysis was performed by ultra-high pressure liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) on kidney biopsies that were left over after clinical pathology analysis to diagnose Fabry disease.

Results

We employed UHPLC-HRMS lipidomics analysis on the renal biopsy of a patient suspicious for Fabry disease. Our result confirmed α-GAL A enzyme activity declined in this patient since a Ga2-related lipid biomarker was substantially higher in the patient's renal tissue biopsy compared with two controls. This suggests this patient has a type of LSD that could be non-classical Fabry disease.

Conclusion

This study shows that lipidomics analysis is a valuable tool for rare disorder diagnosis, which can be conducted on leftover tissue samples without disrupting normal patient care.

Normal tissue and tumor microenvironment adaptations to aerobic exercise enhance doxorubicin anti-tumor efficacy and ameliorate its cardiotoxicity in retired breeder mice

Aerobic exercise is receiving increased recognition in oncology for its multiple purported benefits. Exercise is known to induce physiologic adaptations that improve patient quality-of-life parameters as well as all-cause mortality. There also is a growing body of evidence that exercise may directly alter the tumor microenvironment to influence tumor growth, metastasis, and response to anticancer therapies. Furthermore, the physiologic adaptations to exercise in normal tissues may protect against treatment-associated toxicity and allow for greater treatment tolerance. However, the exercise prescription required to induce these beneficial tumor-related outcomes remains unclear. This study characterized the aerobic adaptations to voluntary wheel running in normal tissues and the tumor microenvironment. Female, retired breeder BALB/c mice and syngeneic breast adenocarcinoma cells were utilized in primary tumor and metastasis models. Aerobic exercise was found to induce numerous adaptations across various tissues in these mice, although primary tumor growth and metastasis were largely unaffected. However, intratumoral hypoxia and global metabolism were altered in the tumors of exercising hosts relative to non-wheel running controls. Doxorubicin chemotherapy also was found to be more efficacious at delaying tumor growth with adjuvant aerobic exercise. Additionally, doxorubicin-induced cardiac toxicity was ameliorated in exercising hosts relative to non-wheel running controls. Taken together, these data suggest that the normal tissue and tumor microenvironment adaptations to aerobic exercise can improve doxorubicin efficacy while simultaneously limiting its toxicity.

Germline SUCLG2 Variants in Patients with Pheochromocytoma and Paraganglioma

BACKGROUND

Pheochromocytoma and paraganglioma (PPGL) are neuroendocrine tumors with frequent mutations in genes linked to the tricarboxylic acid cycle. However, no pathogenic variant has been found to date in succinyl-CoA ligase (SUCL), an enzyme that provides substrate for succinate dehydrogenase (SDH; mitochondrial complex II; CII), a known tumor suppressor in PPGL.

METHODS

A cohort of 352 subjects with apparently sporadic PPGL underwent genetic testing using a panel of 54 genes developed at the National Institutes of Health, including the SUCLG2 subunit of SUCL. Gene deletion, succinate levels, and protein levels were assessed in tumors where possible. To confirm the possible mechanism, we used a progenitor cell line, hPheo1, derived from a human pheochromocytoma, and ablated and re-expressed SUCLG2.

RESULTS

We describe eight germline variants in the GTP-binding domain of SUCLG2 in 15 patients (15 of 352, 4.3%) with apparently sporadic PPGL. Analysis of SUCLG2-mutated tumors and SUCLG2-deficient hPheo1 cells revealed absence of SUCLG2 protein, decrease in the level of the SDHB subunit of CII and faulty assembly of the complex, resulting in aberrant respiration and elevated succinate accumulation.

CONCLUSIONS

Our study suggests SUCLG2 as a novel candidate gene in the genetic landscape of PPGL. Large-scale sequencing may uncover additional cases harboring SUCLG2 variants and provide more detailed information about their prevalence and penetrance.

Mitochondrial transcription factor A in RORγt+ lymphocytes regulate small intestine homeostasis and metabolism

RORγt+ lymphocytes, including interleukin 17 (IL-17)-producing gamma delta T (γδT17) cells, T helper 17 (Th17) cells, and group 3 innate lymphoid cells (ILC3s), are important immune regulators. Compared to Th17 cells and ILC3s, γδT17 cell metabolism and its role in tissue homeostasis remains poorly understood. Here, we report that the tissue milieu shapes splenic and intestinal γδT17 cell gene signatures. Conditional deletion of mitochondrial transcription factor A (Tfam) in RORγt+ lymphocytes significantly affects systemic γδT17 cell maintenance and reduces ILC3s without affecting Th17 cells in the gut. In vivo deletion of Tfam in RORγt+ lymphocytes, especially in γδT17 cells, results in small intestine tissue remodeling and increases small intestine length by enhancing the type 2 immune responses in mice. Moreover, these mice show dysregulation of the small intestine transcriptome and metabolism with less body weight but enhanced anti-helminth immunity. IL-22, a cytokine produced by RORγt+ lymphocytes inhibits IL-13-induced tuft cell differentiation in vitro, and suppresses the tuft cell-type 2 immune circuit and small intestine lengthening in vivo, highlighting its key role in gut tissue remodeling.

A Novel Technique for Redox Lipidomics Using Mass Spectrometry: Application on Vegetable Oils Used to Fry Potatoes

Vegetables oils, rich in polyunsaturated fatty acids, are vulnerable to oxidation during manufacturing, processing, and food preparation. Currently, individual oxidation products are not well characterized, and hence, the health impacts of these unique lipid species remain unknown. Here, we introduce an extensive oxidized lipidomics in silico tandem mass spectrometry library and integrate these libraries within a user-friendly software covering a comprehensive redox lipidomics workflow. We apply this workflow to olive, soy, and walnut cooking oil; comparing unheated oil, oil after deep frying potatoes, and oil after oven frying potatoes. We annotated over a thousand oxidized triglycerides across 273 features (many coeluted). This software was validated against traditional chemical assays of oxidation, known oxidized lipids in castor oil, synthesized standards, and an alternate software LPPtiger. Development of these new software programs for redox lipidomics opens the door to characterize health implications of individual oxidation products.